From 03ee67bfd34b9e872b33eb05fef5db83410b16f3 Mon Sep 17 00:00:00 2001 From: WDevelopsWebApps <97454358+WDevelopsWebApps@users.noreply.github.com> Date: Wed, 28 Sep 2022 10:53:40 +0200 Subject: add advanced saving for save button --- modules/ui.py | 37 +++++++++++++++++++++++++++++-------- 1 file changed, 29 insertions(+), 8 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 7db8edbd..87a86a45 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -28,6 +28,7 @@ import modules.gfpgan_model import modules.codeformer_model import modules.styles import modules.generation_parameters_copypaste +from modules.images import apply_filename_pattern, get_next_sequence_number # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI mimetypes.init() @@ -90,13 +91,26 @@ def send_gradio_gallery_to_image(x): def save_files(js_data, images, index): - import csv - - os.makedirs(opts.outdir_save, exist_ok=True) - + import csv filenames = [] + #quick dictionary to class object conversion. Its neccesary due apply_filename_pattern requiring it + class MyObject: + def __init__(self, d=None): + if d is not None: + for key, value in d.items(): + setattr(self, key, value) + data = json.loads(js_data) + p = MyObject(data) + path = opts.outdir_save + save_to_dirs = opts.save_to_dirs + + if save_to_dirs: + dirname = apply_filename_pattern(opts.directories_filename_pattern or "[prompt_words]", p, p.seed, p.prompt) + path = os.path.join(opts.outdir_save, dirname) + + os.makedirs(path, exist_ok=True) if index > -1 and opts.save_selected_only and (index > 0 or not opts.return_grid): # ensures we are looking at a specific non-grid picture, and we have save_selected_only images = [images[index]] @@ -107,11 +121,18 @@ def save_files(js_data, images, index): writer = csv.writer(file) if at_start: writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"]) - - filename_base = str(int(time.time() * 1000)) + file_decoration = opts.samples_filename_pattern or "[seed]-[prompt_spaces]" + if file_decoration != "": + file_decoration = "-" + file_decoration.lower() + file_decoration = apply_filename_pattern(file_decoration, p, p.seed, p.prompt) + truncated = (file_decoration[:240] + '..') if len(file_decoration) > 240 else file_decoration + filename_base = truncated + + basecount = get_next_sequence_number(path, "") for i, filedata in enumerate(images): - filename = filename_base + ("" if len(images) == 1 else "-" + str(i + 1)) + ".png" - filepath = os.path.join(opts.outdir_save, filename) + file_number = f"{basecount+i:05}" + filename = file_number + filename_base + ".png" + filepath = os.path.join(path, filename) if filedata.startswith("data:image/png;base64,"): filedata = filedata[len("data:image/png;base64,"):] -- cgit v1.2.3 From abdbf1de646f007b6d76cfb3f416fdfaadb57903 Mon Sep 17 00:00:00 2001 From: Liam Date: Thu, 29 Sep 2022 14:40:47 -0400 Subject: token counters now update when roll artist and style buttons are pressed https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/1194#issuecomment-1261203893 --- javascript/ui.js | 28 ++++++++++++++++++++++------ modules/ui.py | 6 +++++- 2 files changed, 27 insertions(+), 7 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index bfe02410..88fd45ae 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -199,12 +199,21 @@ let txt2img_textarea, img2img_textarea = undefined; let wait_time = 800 let token_timeout; -function submit_prompt(event, generate_button_id) { - if (event.altKey && event.keyCode === 13) { - event.preventDefault(); - gradioApp().getElementById(generate_button_id).click(); - return; - } +function roll_artist_txt2img(prompt_text) { + update_token_counter("txt2img_token_button") + return prompt_text; +} +function roll_artist_img2img(prompt_text) { + update_token_counter("img2img_token_button") + return prompt_text; +} +function update_style_txt2img(prompt_text, negative_prompt, style1, style2) { + update_token_counter("txt2img_token_button") + return [prompt_text, negative_prompt, style1, style2] +} +function update_style_img2img(prompt_text, negative_prompt, style1, style2) { + update_token_counter("img2img_token_button") + return [prompt_text, negative_prompt, style1, style2] } function update_token_counter(button_id) { @@ -212,3 +221,10 @@ function update_token_counter(button_id) { clearTimeout(token_timeout); token_timeout = setTimeout(() => gradioApp().getElementById(button_id)?.click(), wait_time); } +function submit_prompt(event, generate_button_id) { + if (event.altKey && event.keyCode === 13) { + event.preventDefault(); + gradioApp().getElementById(generate_button_id).click(); + return; + } +} \ No newline at end of file diff --git a/modules/ui.py b/modules/ui.py index 15572bb0..5eea1860 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -539,6 +539,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): roll.click( fn=roll_artist, + _js="roll_artist_txt2img", inputs=[ txt2img_prompt, ], @@ -743,6 +744,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): roll.click( fn=roll_artist, + _js="roll_artist_img2img", inputs=[ img2img_prompt, ], @@ -753,6 +755,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)] style_dropdowns = [(txt2img_prompt_style, txt2img_prompt_style2), (img2img_prompt_style, img2img_prompt_style2)] + style_js_funcs = ["update_style_txt2img", "update_style_img2img"] for button, (prompt, negative_prompt) in zip([txt2img_save_style, img2img_save_style], prompts): button.click( @@ -764,9 +767,10 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): outputs=[txt2img_prompt_style, img2img_prompt_style, txt2img_prompt_style2, img2img_prompt_style2], ) - for button, (prompt, negative_prompt), (style1, style2) in zip([txt2img_prompt_style_apply, img2img_prompt_style_apply], prompts, style_dropdowns): + for button, (prompt, negative_prompt), (style1, style2), js_func in zip([txt2img_prompt_style_apply, img2img_prompt_style_apply], prompts, style_dropdowns, style_js_funcs): button.click( fn=apply_styles, + _js=js_func, inputs=[prompt, negative_prompt, style1, style2], outputs=[prompt, negative_prompt, style1, style2], ) -- cgit v1.2.3 From ff8dc1908af088d0ed43fb85baad662733c5ca9c Mon Sep 17 00:00:00 2001 From: Liam Date: Thu, 29 Sep 2022 15:47:06 -0400 Subject: fixed token counter for prompt editing --- modules/ui.py | 20 +++++++++++++------- 1 file changed, 13 insertions(+), 7 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 5eea1860..6bf28562 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -11,6 +11,7 @@ import time import traceback import platform import subprocess as sp +from functools import reduce import numpy as np import torch @@ -32,6 +33,7 @@ import modules.gfpgan_model import modules.codeformer_model import modules.styles import modules.generation_parameters_copypaste +from modules.prompt_parser import get_learned_conditioning_prompt_schedules # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI mimetypes.init() @@ -345,8 +347,11 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: outputs=[seed, dummy_component] ) -def update_token_counter(text): - tokens, token_count, max_length = model_hijack.tokenize(text) +def update_token_counter(text, steps): + prompt_schedules = get_learned_conditioning_prompt_schedules([text], steps) + flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules) + prompts = [prompt_text for step,prompt_text in flat_prompts] + tokens, token_count, max_length = max([model_hijack.tokenize(prompt) for prompt in prompts], key=lambda args: args[1]) style_class = ' class="red"' if (token_count > max_length) else "" return f"{token_count}/{max_length}" @@ -364,8 +369,7 @@ def create_toprow(is_img2img): roll = gr.Button(value=art_symbol, elem_id="roll", visible=len(shared.artist_db.artists) > 0) paste = gr.Button(value=paste_symbol, elem_id="paste") token_counter = gr.HTML(value="", elem_id=f"{id_part}_token_counter") - hidden_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button") - hidden_button.click(fn=update_token_counter, inputs=[prompt], outputs=[token_counter]) + token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button") with gr.Column(scale=10, elem_id="style_pos_col"): prompt_style = gr.Dropdown(label="Style 1", elem_id=f"{id_part}_style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())), visible=len(shared.prompt_styles.styles) > 1) @@ -396,7 +400,7 @@ def create_toprow(is_img2img): prompt_style_apply = gr.Button('Apply style', elem_id="style_apply") save_style = gr.Button('Create style', elem_id="style_create") - return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, interrogate, prompt_style_apply, save_style, paste + return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, interrogate, prompt_style_apply, save_style, paste, token_counter, token_button def setup_progressbar(progressbar, preview, id_part): @@ -419,7 +423,7 @@ def setup_progressbar(progressbar, preview, id_part): def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): with gr.Blocks(analytics_enabled=False) as txt2img_interface: - txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, txt2img_prompt_style_apply, txt2img_save_style, paste = create_toprow(is_img2img=False) + txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, txt2img_prompt_style_apply, txt2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=False) dummy_component = gr.Label(visible=False) with gr.Row(elem_id='txt2img_progress_row'): @@ -568,9 +572,10 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)), ] modules.generation_parameters_copypaste.connect_paste(paste, txt2img_paste_fields, txt2img_prompt) + token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter]) with gr.Blocks(analytics_enabled=False) as img2img_interface: - img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_prompt_style_apply, img2img_save_style, paste = create_toprow(is_img2img=True) + img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True) with gr.Row(elem_id='img2img_progress_row'): with gr.Column(scale=1): @@ -793,6 +798,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): (denoising_strength, "Denoising strength"), ] modules.generation_parameters_copypaste.connect_paste(paste, img2img_paste_fields, img2img_prompt) + token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter]) with gr.Blocks(analytics_enabled=False) as extras_interface: with gr.Row().style(equal_height=False): -- cgit v1.2.3 From 3c6a049fc3c6b54ada3736710a7e86663ea7f3d9 Mon Sep 17 00:00:00 2001 From: Liam Date: Fri, 30 Sep 2022 12:12:44 -0400 Subject: consolidated token counter functions --- javascript/ui.js | 21 +++++++++------------ modules/ui.py | 6 +++--- 2 files changed, 12 insertions(+), 15 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index 88fd45ae..f94ed081 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -199,21 +199,18 @@ let txt2img_textarea, img2img_textarea = undefined; let wait_time = 800 let token_timeout; -function roll_artist_txt2img(prompt_text) { +function update_txt2img_tokens(...args) { update_token_counter("txt2img_token_button") - return prompt_text; + if (args.length == 2) + return args[0] + return args; } -function roll_artist_img2img(prompt_text) { - update_token_counter("img2img_token_button") - return prompt_text; -} -function update_style_txt2img(prompt_text, negative_prompt, style1, style2) { - update_token_counter("txt2img_token_button") - return [prompt_text, negative_prompt, style1, style2] -} -function update_style_img2img(prompt_text, negative_prompt, style1, style2) { + +function update_img2img_tokens(...args) { update_token_counter("img2img_token_button") - return [prompt_text, negative_prompt, style1, style2] + if (args.length == 2) + return args[0] + return args; } function update_token_counter(button_id) { diff --git a/modules/ui.py b/modules/ui.py index 6bf28562..40c08984 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -543,7 +543,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): roll.click( fn=roll_artist, - _js="roll_artist_txt2img", + _js="update_txt2img_tokens", inputs=[ txt2img_prompt, ], @@ -749,7 +749,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): roll.click( fn=roll_artist, - _js="roll_artist_img2img", + _js="update_img2img_tokens", inputs=[ img2img_prompt, ], @@ -760,7 +760,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)] style_dropdowns = [(txt2img_prompt_style, txt2img_prompt_style2), (img2img_prompt_style, img2img_prompt_style2)] - style_js_funcs = ["update_style_txt2img", "update_style_img2img"] + style_js_funcs = ["update_txt2img_tokens", "update_img2img_tokens"] for button, (prompt, negative_prompt) in zip([txt2img_save_style, img2img_save_style], prompts): button.click( -- cgit v1.2.3 From 4f8490cd5630823ac44de8b5c5e4325bdbbea7fa Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Sat, 1 Oct 2022 18:33:31 +0100 Subject: add restart button --- modules/ui.py | 15 ++++++++++++++- 1 file changed, 14 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 15572bb0..ec6aaa28 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1002,6 +1002,17 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): _js='function(){}' ) + def request_restart(): + settings_interface.gradio_ref.do_restart = True + + restart_gradio = gr.Button(value='Restart Gradio and Refresh Scripts') + restart_gradio.click( + fn=request_restart, + inputs=[], + outputs=[], + _js='function(){document.body.innerHTML=\'

Reloading

\';setTimeout(function(){location.reload()},2000)}' + ) + if column is not None: column.__exit__() @@ -1026,7 +1037,9 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): css += css_hide_progressbar with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo: - + + settings_interface.gradio_ref = demo + with gr.Tabs() as tabs: for interface, label, ifid in interfaces: with gr.TabItem(label, id=ifid): -- cgit v1.2.3 From afaa03c5fd05f48ed9c9f15558ea6f0bc4f61628 Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Sat, 1 Oct 2022 22:43:45 +0100 Subject: add redefinition guard to gradio_routes_templates_response --- modules/ui.py | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index ec6aaa28..fd057916 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1219,12 +1219,13 @@ for filename in sorted(os.listdir(jsdir)): javascript += f"\n" -def template_response(*args, **kwargs): - res = gradio_routes_templates_response(*args, **kwargs) - res.body = res.body.replace(b'', f'{javascript}'.encode("utf8")) - res.init_headers() - return res +if 'gradio_routes_templates_response' not in globals(): + def template_response(*args, **kwargs): + res = gradio_routes_templates_response(*args, **kwargs) + res.body = res.body.replace(b'', f'{javascript}'.encode("utf8")) + res.init_headers() + return res + gradio_routes_templates_response = gradio.routes.templates.TemplateResponse + gradio.routes.templates.TemplateResponse = template_response -gradio_routes_templates_response = gradio.routes.templates.TemplateResponse -gradio.routes.templates.TemplateResponse = template_response -- cgit v1.2.3 From 6048002dade91b82b1ce9fea3c6ff5b5c1f8c990 Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Sat, 1 Oct 2022 23:10:07 +0100 Subject: Add scope warning to refresh button --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index fd057916..72846a12 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1005,7 +1005,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): def request_restart(): settings_interface.gradio_ref.do_restart = True - restart_gradio = gr.Button(value='Restart Gradio and Refresh Scripts') + restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary') restart_gradio.click( fn=request_restart, inputs=[], -- cgit v1.2.3 From 027c5aae5546ff3650347cb3c2b87df4415ab900 Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Sat, 1 Oct 2022 23:29:26 +0100 Subject: update reloading message style --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 72846a12..7b2359c2 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1010,7 +1010,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): fn=request_restart, inputs=[], outputs=[], - _js='function(){document.body.innerHTML=\'

Reloading

\';setTimeout(function(){location.reload()},2000)}' + _js='function(){document.body.innerHTML=\'

Reloading...

\';setTimeout(function(){location.reload()},2000)}' ) if column is not None: -- cgit v1.2.3 From 0aa354bd5e811e2b41b17a3052cf5d4c8190d533 Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Sun, 2 Oct 2022 00:13:47 +0100 Subject: remove styling from python side --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 7b2359c2..cb859ac4 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1010,7 +1010,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): fn=request_restart, inputs=[], outputs=[], - _js='function(){document.body.innerHTML=\'

Reloading...

\';setTimeout(function(){location.reload()},2000)}' + _js='function(){restart_reload()}' ) if column is not None: -- cgit v1.2.3 From 07e40ad7f23472fc1c781fe1cc6c1ee403413918 Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Sun, 2 Oct 2022 01:19:55 +0100 Subject: add custom script body only refresh option --- modules/ui.py | 11 +++++++++++ 1 file changed, 11 insertions(+) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index cb859ac4..eb7c0585 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1012,6 +1012,17 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): outputs=[], _js='function(){restart_reload()}' ) + + def reload_scripts(): + modules.scripts.reload_script_body_only() + + reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='primary') + reload_script_bodies.click( + fn=reload_scripts, + inputs=[], + outputs=[], + _js='function(){}' + ) if column is not None: column.__exit__() -- cgit v1.2.3 From 2deea867814272f1f089b60e9ba8d587c16b2fb1 Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Sun, 2 Oct 2022 01:36:30 +0100 Subject: Put reload buttons in row and add secondary style --- modules/ui.py | 23 +++++++++++++---------- 1 file changed, 13 insertions(+), 10 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index eb7c0585..963a2c61 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1002,27 +1002,30 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): _js='function(){}' ) - def request_restart(): - settings_interface.gradio_ref.do_restart = True + with gr.Row(): + reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary') + restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary') - restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary') - restart_gradio.click( - fn=request_restart, - inputs=[], - outputs=[], - _js='function(){restart_reload()}' - ) def reload_scripts(): modules.scripts.reload_script_body_only() - reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='primary') reload_script_bodies.click( fn=reload_scripts, inputs=[], outputs=[], _js='function(){}' ) + + def request_restart(): + settings_interface.gradio_ref.do_restart = True + + restart_gradio.click( + fn=request_restart, + inputs=[], + outputs=[], + _js='function(){restart_reload()}' + ) if column is not None: column.__exit__() -- cgit v1.2.3 From 820f1dc96b1979d7e92170c161db281ee8bd988b Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 2 Oct 2022 15:03:39 +0300 Subject: initial support for training textual inversion --- .gitignore | 1 + javascript/progressbar.js | 1 + javascript/textualInversion.js | 8 + modules/devices.py | 3 +- modules/processing.py | 13 +- modules/sd_hijack.py | 324 ++++------------------ modules/sd_hijack_optimizations.py | 164 +++++++++++ modules/sd_models.py | 4 +- modules/shared.py | 3 +- modules/textual_inversion/dataset.py | 76 +++++ modules/textual_inversion/textual_inversion.py | 258 +++++++++++++++++ modules/textual_inversion/ui.py | 32 +++ modules/ui.py | 139 ++++++++-- style.css | 10 +- textual_inversion_templates/style.txt | 19 ++ textual_inversion_templates/style_filewords.txt | 19 ++ textual_inversion_templates/subject.txt | 27 ++ textual_inversion_templates/subject_filewords.txt | 27 ++ webui.py | 15 +- 19 files changed, 828 insertions(+), 315 deletions(-) create mode 100644 javascript/textualInversion.js create mode 100644 modules/sd_hijack_optimizations.py create mode 100644 modules/textual_inversion/dataset.py create mode 100644 modules/textual_inversion/textual_inversion.py create mode 100644 modules/textual_inversion/ui.py create mode 100644 textual_inversion_templates/style.txt create mode 100644 textual_inversion_templates/style_filewords.txt create mode 100644 textual_inversion_templates/subject.txt create mode 100644 textual_inversion_templates/subject_filewords.txt (limited to 'modules/ui.py') diff --git a/.gitignore b/.gitignore index 3532dab3..7afc9395 100644 --- a/.gitignore +++ b/.gitignore @@ -25,3 +25,4 @@ __pycache__ /.idea notification.mp3 /SwinIR +/textual_inversion diff --git a/javascript/progressbar.js b/javascript/progressbar.js index 21f25b38..1e297abb 100644 --- a/javascript/progressbar.js +++ b/javascript/progressbar.js @@ -30,6 +30,7 @@ function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_inte onUiUpdate(function(){ check_progressbar('txt2img', 'txt2img_progressbar', 'txt2img_progress_span', 'txt2img_interrupt', 'txt2img_preview', 'txt2img_gallery') check_progressbar('img2img', 'img2img_progressbar', 'img2img_progress_span', 'img2img_interrupt', 'img2img_preview', 'img2img_gallery') + check_progressbar('ti', 'ti_progressbar', 'ti_progress_span', 'ti_interrupt', 'ti_preview', 'ti_gallery') }) function requestMoreProgress(id_part, id_progressbar_span, id_interrupt){ diff --git a/javascript/textualInversion.js b/javascript/textualInversion.js new file mode 100644 index 00000000..8061be08 --- /dev/null +++ b/javascript/textualInversion.js @@ -0,0 +1,8 @@ + + +function start_training_textual_inversion(){ + requestProgress('ti') + gradioApp().querySelector('#ti_error').innerHTML='' + + return args_to_array(arguments) +} diff --git a/modules/devices.py b/modules/devices.py index 07bb2339..ff82f2f6 100644 --- a/modules/devices.py +++ b/modules/devices.py @@ -32,10 +32,9 @@ def enable_tf32(): errors.run(enable_tf32, "Enabling TF32") - device = get_optimal_device() device_codeformer = cpu if has_mps else device - +dtype = torch.float16 def randn(seed, shape): # Pytorch currently doesn't handle setting randomness correctly when the metal backend is used. diff --git a/modules/processing.py b/modules/processing.py index 7eeb5191..8223423a 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -56,7 +56,7 @@ class StableDiffusionProcessing: self.prompt: str = prompt self.prompt_for_display: str = None self.negative_prompt: str = (negative_prompt or "") - self.styles: str = styles + self.styles: list = styles or [] self.seed: int = seed self.subseed: int = subseed self.subseed_strength: float = subseed_strength @@ -271,7 +271,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration "Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength), "Seed resize from": (None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"), "Denoising strength": getattr(p, 'denoising_strength', None), - "Eta": (None if p.sampler.eta == p.sampler.default_eta else p.sampler.eta), + "Eta": (None if p.sampler is None or p.sampler.eta == p.sampler.default_eta else p.sampler.eta), } generation_params.update(p.extra_generation_params) @@ -295,8 +295,11 @@ def process_images(p: StableDiffusionProcessing) -> Processed: fix_seed(p) - os.makedirs(p.outpath_samples, exist_ok=True) - os.makedirs(p.outpath_grids, exist_ok=True) + if p.outpath_samples is not None: + os.makedirs(p.outpath_samples, exist_ok=True) + + if p.outpath_grids is not None: + os.makedirs(p.outpath_grids, exist_ok=True) modules.sd_hijack.model_hijack.apply_circular(p.tiling) @@ -323,7 +326,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed: return create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration, position_in_batch) if os.path.exists(cmd_opts.embeddings_dir): - model_hijack.load_textual_inversion_embeddings(cmd_opts.embeddings_dir, p.sd_model) + model_hijack.embedding_db.load_textual_inversion_embeddings() infotexts = [] output_images = [] diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index fa7eaeb8..fd57e5c5 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -6,244 +6,41 @@ import torch import numpy as np from torch import einsum -from modules import prompt_parser +import modules.textual_inversion.textual_inversion +from modules import prompt_parser, devices, sd_hijack_optimizations, shared from modules.shared import opts, device, cmd_opts -from ldm.util import default -from einops import rearrange import ldm.modules.attention import ldm.modules.diffusionmodules.model +attention_CrossAttention_forward = ldm.modules.attention.CrossAttention.forward +diffusionmodules_model_nonlinearity = ldm.modules.diffusionmodules.model.nonlinearity +diffusionmodules_model_AttnBlock_forward = ldm.modules.diffusionmodules.model.AttnBlock.forward -# see https://github.com/basujindal/stable-diffusion/pull/117 for discussion -def split_cross_attention_forward_v1(self, x, context=None, mask=None): - h = self.heads - q = self.to_q(x) - context = default(context, x) - k = self.to_k(context) - v = self.to_v(context) - del context, x +def apply_optimizations(): + if cmd_opts.opt_split_attention_v1: + ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1 + elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()): + ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward + ldm.modules.diffusionmodules.model.nonlinearity = sd_hijack_optimizations.nonlinearity_hijack + ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward - q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v)) - r1 = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device) - for i in range(0, q.shape[0], 2): - end = i + 2 - s1 = einsum('b i d, b j d -> b i j', q[i:end], k[i:end]) - s1 *= self.scale +def undo_optimizations(): + ldm.modules.attention.CrossAttention.forward = attention_CrossAttention_forward + ldm.modules.diffusionmodules.model.nonlinearity = diffusionmodules_model_nonlinearity + ldm.modules.diffusionmodules.model.AttnBlock.forward = diffusionmodules_model_AttnBlock_forward - s2 = s1.softmax(dim=-1) - del s1 - - r1[i:end] = einsum('b i j, b j d -> b i d', s2, v[i:end]) - del s2 - - r2 = rearrange(r1, '(b h) n d -> b n (h d)', h=h) - del r1 - - return self.to_out(r2) - - -# taken from https://github.com/Doggettx/stable-diffusion -def split_cross_attention_forward(self, x, context=None, mask=None): - h = self.heads - - q_in = self.to_q(x) - context = default(context, x) - k_in = self.to_k(context) * self.scale - v_in = self.to_v(context) - del context, x - - q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q_in, k_in, v_in)) - del q_in, k_in, v_in - - r1 = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device, dtype=q.dtype) - - stats = torch.cuda.memory_stats(q.device) - mem_active = stats['active_bytes.all.current'] - mem_reserved = stats['reserved_bytes.all.current'] - mem_free_cuda, _ = torch.cuda.mem_get_info(torch.cuda.current_device()) - mem_free_torch = mem_reserved - mem_active - mem_free_total = mem_free_cuda + mem_free_torch - - gb = 1024 ** 3 - tensor_size = q.shape[0] * q.shape[1] * k.shape[1] * q.element_size() - modifier = 3 if q.element_size() == 2 else 2.5 - mem_required = tensor_size * modifier - steps = 1 - - if mem_required > mem_free_total: - steps = 2 ** (math.ceil(math.log(mem_required / mem_free_total, 2))) - # print(f"Expected tensor size:{tensor_size/gb:0.1f}GB, cuda free:{mem_free_cuda/gb:0.1f}GB " - # f"torch free:{mem_free_torch/gb:0.1f} total:{mem_free_total/gb:0.1f} steps:{steps}") - - if steps > 64: - max_res = math.floor(math.sqrt(math.sqrt(mem_free_total / 2.5)) / 8) * 64 - raise RuntimeError(f'Not enough memory, use lower resolution (max approx. {max_res}x{max_res}). ' - f'Need: {mem_required / 64 / gb:0.1f}GB free, Have:{mem_free_total / gb:0.1f}GB free') - - slice_size = q.shape[1] // steps if (q.shape[1] % steps) == 0 else q.shape[1] - for i in range(0, q.shape[1], slice_size): - end = i + slice_size - s1 = einsum('b i d, b j d -> b i j', q[:, i:end], k) - - s2 = s1.softmax(dim=-1, dtype=q.dtype) - del s1 - - r1[:, i:end] = einsum('b i j, b j d -> b i d', s2, v) - del s2 - - del q, k, v - - r2 = rearrange(r1, '(b h) n d -> b n (h d)', h=h) - del r1 - - return self.to_out(r2) - -def nonlinearity_hijack(x): - # swish - t = torch.sigmoid(x) - x *= t - del t - - return x - -def cross_attention_attnblock_forward(self, x): - h_ = x - h_ = self.norm(h_) - q1 = self.q(h_) - k1 = self.k(h_) - v = self.v(h_) - - # compute attention - b, c, h, w = q1.shape - - q2 = q1.reshape(b, c, h*w) - del q1 - - q = q2.permute(0, 2, 1) # b,hw,c - del q2 - - k = k1.reshape(b, c, h*w) # b,c,hw - del k1 - - h_ = torch.zeros_like(k, device=q.device) - - stats = torch.cuda.memory_stats(q.device) - mem_active = stats['active_bytes.all.current'] - mem_reserved = stats['reserved_bytes.all.current'] - mem_free_cuda, _ = torch.cuda.mem_get_info(torch.cuda.current_device()) - mem_free_torch = mem_reserved - mem_active - mem_free_total = mem_free_cuda + mem_free_torch - - tensor_size = q.shape[0] * q.shape[1] * k.shape[2] * q.element_size() - mem_required = tensor_size * 2.5 - steps = 1 - - if mem_required > mem_free_total: - steps = 2**(math.ceil(math.log(mem_required / mem_free_total, 2))) - - slice_size = q.shape[1] // steps if (q.shape[1] % steps) == 0 else q.shape[1] - for i in range(0, q.shape[1], slice_size): - end = i + slice_size - - w1 = torch.bmm(q[:, i:end], k) # b,hw,hw w[b,i,j]=sum_c q[b,i,c]k[b,c,j] - w2 = w1 * (int(c)**(-0.5)) - del w1 - w3 = torch.nn.functional.softmax(w2, dim=2, dtype=q.dtype) - del w2 - - # attend to values - v1 = v.reshape(b, c, h*w) - w4 = w3.permute(0, 2, 1) # b,hw,hw (first hw of k, second of q) - del w3 - - h_[:, :, i:end] = torch.bmm(v1, w4) # b, c,hw (hw of q) h_[b,c,j] = sum_i v[b,c,i] w_[b,i,j] - del v1, w4 - - h2 = h_.reshape(b, c, h, w) - del h_ - - h3 = self.proj_out(h2) - del h2 - - h3 += x - - return h3 class StableDiffusionModelHijack: - ids_lookup = {} - word_embeddings = {} - word_embeddings_checksums = {} fixes = None comments = [] - dir_mtime = None layers = None circular_enabled = False clip = None - def load_textual_inversion_embeddings(self, dirname, model): - mt = os.path.getmtime(dirname) - if self.dir_mtime is not None and mt <= self.dir_mtime: - return - - self.dir_mtime = mt - self.ids_lookup.clear() - self.word_embeddings.clear() - - tokenizer = model.cond_stage_model.tokenizer - - def const_hash(a): - r = 0 - for v in a: - r = (r * 281 ^ int(v) * 997) & 0xFFFFFFFF - return r - - def process_file(path, filename): - name = os.path.splitext(filename)[0] - - data = torch.load(path, map_location="cpu") - - # textual inversion embeddings - if 'string_to_param' in data: - param_dict = data['string_to_param'] - if hasattr(param_dict, '_parameters'): - param_dict = getattr(param_dict, '_parameters') # fix for torch 1.12.1 loading saved file from torch 1.11 - assert len(param_dict) == 1, 'embedding file has multiple terms in it' - emb = next(iter(param_dict.items()))[1] - # diffuser concepts - elif type(data) == dict and type(next(iter(data.values()))) == torch.Tensor: - assert len(data.keys()) == 1, 'embedding file has multiple terms in it' - - emb = next(iter(data.values())) - if len(emb.shape) == 1: - emb = emb.unsqueeze(0) - - self.word_embeddings[name] = emb.detach().to(device) - self.word_embeddings_checksums[name] = f'{const_hash(emb.reshape(-1)*100)&0xffff:04x}' - - ids = tokenizer([name], add_special_tokens=False)['input_ids'][0] - - first_id = ids[0] - if first_id not in self.ids_lookup: - self.ids_lookup[first_id] = [] - self.ids_lookup[first_id].append((ids, name)) - - for fn in os.listdir(dirname): - try: - fullfn = os.path.join(dirname, fn) - - if os.stat(fullfn).st_size == 0: - continue - - process_file(fullfn, fn) - except Exception: - print(f"Error loading emedding {fn}:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) - continue - - print(f"Loaded a total of {len(self.word_embeddings)} textual inversion embeddings.") + embedding_db = modules.textual_inversion.textual_inversion.EmbeddingDatabase(cmd_opts.embeddings_dir) def hijack(self, m): model_embeddings = m.cond_stage_model.transformer.text_model.embeddings @@ -253,12 +50,7 @@ class StableDiffusionModelHijack: self.clip = m.cond_stage_model - if cmd_opts.opt_split_attention_v1: - ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward_v1 - elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()): - ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward - ldm.modules.diffusionmodules.model.nonlinearity = nonlinearity_hijack - ldm.modules.diffusionmodules.model.AttnBlock.forward = cross_attention_attnblock_forward + apply_optimizations() def flatten(el): flattened = [flatten(children) for children in el.children()] @@ -296,7 +88,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): def __init__(self, wrapped, hijack): super().__init__() self.wrapped = wrapped - self.hijack = hijack + self.hijack: StableDiffusionModelHijack = hijack self.tokenizer = wrapped.tokenizer self.max_length = wrapped.max_length self.token_mults = {} @@ -317,7 +109,6 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): if mult != 1.0: self.token_mults[ident] = mult - def tokenize_line(self, line, used_custom_terms, hijack_comments): id_start = self.wrapped.tokenizer.bos_token_id id_end = self.wrapped.tokenizer.eos_token_id @@ -339,28 +130,19 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): while i < len(tokens): token = tokens[i] - possible_matches = self.hijack.ids_lookup.get(token, None) + embedding = self.hijack.embedding_db.find_embedding_at_position(tokens, i) - if possible_matches is None: + if embedding is None: remade_tokens.append(token) multipliers.append(weight) + i += 1 else: - found = False - for ids, word in possible_matches: - if tokens[i:i + len(ids)] == ids: - emb_len = int(self.hijack.word_embeddings[word].shape[0]) - fixes.append((len(remade_tokens), word)) - remade_tokens += [0] * emb_len - multipliers += [weight] * emb_len - i += len(ids) - 1 - found = True - used_custom_terms.append((word, self.hijack.word_embeddings_checksums[word])) - break - - if not found: - remade_tokens.append(token) - multipliers.append(weight) - i += 1 + emb_len = int(embedding.vec.shape[0]) + fixes.append((len(remade_tokens), embedding)) + remade_tokens += [0] * emb_len + multipliers += [weight] * emb_len + used_custom_terms.append((embedding.name, embedding.checksum())) + i += emb_len if len(remade_tokens) > maxlen - 2: vocab = {v: k for k, v in self.wrapped.tokenizer.get_vocab().items()} @@ -431,32 +213,23 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): while i < len(tokens): token = tokens[i] - possible_matches = self.hijack.ids_lookup.get(token, None) + embedding = self.hijack.embedding_db.find_embedding_at_position(tokens, i) mult_change = self.token_mults.get(token) if opts.enable_emphasis else None if mult_change is not None: mult *= mult_change - elif possible_matches is None: + i += 1 + elif embedding is None: remade_tokens.append(token) multipliers.append(mult) + i += 1 else: - found = False - for ids, word in possible_matches: - if tokens[i:i+len(ids)] == ids: - emb_len = int(self.hijack.word_embeddings[word].shape[0]) - fixes.append((len(remade_tokens), word)) - remade_tokens += [0] * emb_len - multipliers += [mult] * emb_len - i += len(ids) - 1 - found = True - used_custom_terms.append((word, self.hijack.word_embeddings_checksums[word])) - break - - if not found: - remade_tokens.append(token) - multipliers.append(mult) - - i += 1 + emb_len = int(embedding.vec.shape[0]) + fixes.append((len(remade_tokens), embedding)) + remade_tokens += [0] * emb_len + multipliers += [mult] * emb_len + used_custom_terms.append((embedding.name, embedding.checksum())) + i += emb_len if len(remade_tokens) > maxlen - 2: vocab = {v: k for k, v in self.wrapped.tokenizer.get_vocab().items()} @@ -464,6 +237,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): overflowing_words = [vocab.get(int(x), "") for x in ovf] overflowing_text = self.wrapped.tokenizer.convert_tokens_to_string(''.join(overflowing_words)) hijack_comments.append(f"Warning: too many input tokens; some ({len(overflowing_words)}) have been truncated:\n{overflowing_text}\n") + token_count = len(remade_tokens) remade_tokens = remade_tokens + [id_end] * (maxlen - 2 - len(remade_tokens)) remade_tokens = [id_start] + remade_tokens[0:maxlen-2] + [id_end] @@ -484,7 +258,6 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): else: batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text(text) - self.hijack.fixes = hijack_fixes self.hijack.comments = hijack_comments @@ -517,14 +290,19 @@ class EmbeddingsWithFixes(torch.nn.Module): inputs_embeds = self.wrapped(input_ids) - if batch_fixes is not None: - for fixes, tensor in zip(batch_fixes, inputs_embeds): - for offset, word in fixes: - emb = self.embeddings.word_embeddings[word] - emb_len = min(tensor.shape[0]-offset-1, emb.shape[0]) - tensor[offset+1:offset+1+emb_len] = self.embeddings.word_embeddings[word][0:emb_len] + if batch_fixes is None or len(batch_fixes) == 0 or max([len(x) for x in batch_fixes]) == 0: + return inputs_embeds + + vecs = [] + for fixes, tensor in zip(batch_fixes, inputs_embeds): + for offset, embedding in fixes: + emb = embedding.vec + emb_len = min(tensor.shape[0]-offset-1, emb.shape[0]) + tensor = torch.cat([tensor[0:offset+1], emb[0:emb_len], tensor[offset+1+emb_len:]]) + + vecs.append(tensor) - return inputs_embeds + return torch.stack(vecs) def add_circular_option_to_conv_2d(): diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py new file mode 100644 index 00000000..9c079e57 --- /dev/null +++ b/modules/sd_hijack_optimizations.py @@ -0,0 +1,164 @@ +import math +import torch +from torch import einsum + +from ldm.util import default +from einops import rearrange + + +# see https://github.com/basujindal/stable-diffusion/pull/117 for discussion +def split_cross_attention_forward_v1(self, x, context=None, mask=None): + h = self.heads + + q = self.to_q(x) + context = default(context, x) + k = self.to_k(context) + v = self.to_v(context) + del context, x + + q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v)) + + r1 = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device) + for i in range(0, q.shape[0], 2): + end = i + 2 + s1 = einsum('b i d, b j d -> b i j', q[i:end], k[i:end]) + s1 *= self.scale + + s2 = s1.softmax(dim=-1) + del s1 + + r1[i:end] = einsum('b i j, b j d -> b i d', s2, v[i:end]) + del s2 + + r2 = rearrange(r1, '(b h) n d -> b n (h d)', h=h) + del r1 + + return self.to_out(r2) + + +# taken from https://github.com/Doggettx/stable-diffusion +def split_cross_attention_forward(self, x, context=None, mask=None): + h = self.heads + + q_in = self.to_q(x) + context = default(context, x) + k_in = self.to_k(context) * self.scale + v_in = self.to_v(context) + del context, x + + q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q_in, k_in, v_in)) + del q_in, k_in, v_in + + r1 = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device, dtype=q.dtype) + + stats = torch.cuda.memory_stats(q.device) + mem_active = stats['active_bytes.all.current'] + mem_reserved = stats['reserved_bytes.all.current'] + mem_free_cuda, _ = torch.cuda.mem_get_info(torch.cuda.current_device()) + mem_free_torch = mem_reserved - mem_active + mem_free_total = mem_free_cuda + mem_free_torch + + gb = 1024 ** 3 + tensor_size = q.shape[0] * q.shape[1] * k.shape[1] * q.element_size() + modifier = 3 if q.element_size() == 2 else 2.5 + mem_required = tensor_size * modifier + steps = 1 + + if mem_required > mem_free_total: + steps = 2 ** (math.ceil(math.log(mem_required / mem_free_total, 2))) + # print(f"Expected tensor size:{tensor_size/gb:0.1f}GB, cuda free:{mem_free_cuda/gb:0.1f}GB " + # f"torch free:{mem_free_torch/gb:0.1f} total:{mem_free_total/gb:0.1f} steps:{steps}") + + if steps > 64: + max_res = math.floor(math.sqrt(math.sqrt(mem_free_total / 2.5)) / 8) * 64 + raise RuntimeError(f'Not enough memory, use lower resolution (max approx. {max_res}x{max_res}). ' + f'Need: {mem_required / 64 / gb:0.1f}GB free, Have:{mem_free_total / gb:0.1f}GB free') + + slice_size = q.shape[1] // steps if (q.shape[1] % steps) == 0 else q.shape[1] + for i in range(0, q.shape[1], slice_size): + end = i + slice_size + s1 = einsum('b i d, b j d -> b i j', q[:, i:end], k) + + s2 = s1.softmax(dim=-1, dtype=q.dtype) + del s1 + + r1[:, i:end] = einsum('b i j, b j d -> b i d', s2, v) + del s2 + + del q, k, v + + r2 = rearrange(r1, '(b h) n d -> b n (h d)', h=h) + del r1 + + return self.to_out(r2) + +def nonlinearity_hijack(x): + # swish + t = torch.sigmoid(x) + x *= t + del t + + return x + +def cross_attention_attnblock_forward(self, x): + h_ = x + h_ = self.norm(h_) + q1 = self.q(h_) + k1 = self.k(h_) + v = self.v(h_) + + # compute attention + b, c, h, w = q1.shape + + q2 = q1.reshape(b, c, h*w) + del q1 + + q = q2.permute(0, 2, 1) # b,hw,c + del q2 + + k = k1.reshape(b, c, h*w) # b,c,hw + del k1 + + h_ = torch.zeros_like(k, device=q.device) + + stats = torch.cuda.memory_stats(q.device) + mem_active = stats['active_bytes.all.current'] + mem_reserved = stats['reserved_bytes.all.current'] + mem_free_cuda, _ = torch.cuda.mem_get_info(torch.cuda.current_device()) + mem_free_torch = mem_reserved - mem_active + mem_free_total = mem_free_cuda + mem_free_torch + + tensor_size = q.shape[0] * q.shape[1] * k.shape[2] * q.element_size() + mem_required = tensor_size * 2.5 + steps = 1 + + if mem_required > mem_free_total: + steps = 2**(math.ceil(math.log(mem_required / mem_free_total, 2))) + + slice_size = q.shape[1] // steps if (q.shape[1] % steps) == 0 else q.shape[1] + for i in range(0, q.shape[1], slice_size): + end = i + slice_size + + w1 = torch.bmm(q[:, i:end], k) # b,hw,hw w[b,i,j]=sum_c q[b,i,c]k[b,c,j] + w2 = w1 * (int(c)**(-0.5)) + del w1 + w3 = torch.nn.functional.softmax(w2, dim=2, dtype=q.dtype) + del w2 + + # attend to values + v1 = v.reshape(b, c, h*w) + w4 = w3.permute(0, 2, 1) # b,hw,hw (first hw of k, second of q) + del w3 + + h_[:, :, i:end] = torch.bmm(v1, w4) # b, c,hw (hw of q) h_[b,c,j] = sum_i v[b,c,i] w_[b,i,j] + del v1, w4 + + h2 = h_.reshape(b, c, h, w) + del h_ + + h3 = self.proj_out(h2) + del h2 + + h3 += x + + return h3 diff --git a/modules/sd_models.py b/modules/sd_models.py index 2539f14c..5b3dbdc7 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -8,7 +8,7 @@ from omegaconf import OmegaConf from ldm.util import instantiate_from_config -from modules import shared, modelloader +from modules import shared, modelloader, devices from modules.paths import models_path model_dir = "Stable-diffusion" @@ -134,6 +134,8 @@ def load_model_weights(model, checkpoint_file, sd_model_hash): if not shared.cmd_opts.no_half: model.half() + devices.dtype = torch.float32 if shared.cmd_opts.no_half else torch.float16 + model.sd_model_hash = sd_model_hash model.sd_model_checkpint = checkpoint_file diff --git a/modules/shared.py b/modules/shared.py index ac968b2d..ac0bc480 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -78,6 +78,7 @@ class State: current_latent = None current_image = None current_image_sampling_step = 0 + textinfo = None def interrupt(self): self.interrupted = True @@ -88,7 +89,7 @@ class State: self.current_image_sampling_step = 0 def get_job_timestamp(self): - return datetime.datetime.now().strftime("%Y%m%d%H%M%S") + return datetime.datetime.now().strftime("%Y%m%d%H%M%S") # shouldn't this return job_timestamp? state = State() diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py new file mode 100644 index 00000000..7e134a08 --- /dev/null +++ b/modules/textual_inversion/dataset.py @@ -0,0 +1,76 @@ +import os +import numpy as np +import PIL +import torch +from PIL import Image +from torch.utils.data import Dataset +from torchvision import transforms + +import random +import tqdm + + +class PersonalizedBase(Dataset): + def __init__(self, data_root, size=None, repeats=100, flip_p=0.5, placeholder_token="*", width=512, height=512, model=None, device=None, template_file=None): + + self.placeholder_token = placeholder_token + + self.size = size + self.width = width + self.height = height + self.flip = transforms.RandomHorizontalFlip(p=flip_p) + + self.dataset = [] + + with open(template_file, "r") as file: + lines = [x.strip() for x in file.readlines()] + + self.lines = lines + + assert data_root, 'dataset directory not specified' + + self.image_paths = [os.path.join(data_root, file_path) for file_path in os.listdir(data_root)] + print("Preparing dataset...") + for path in tqdm.tqdm(self.image_paths): + image = Image.open(path) + image = image.convert('RGB') + image = image.resize((self.width, self.height), PIL.Image.BICUBIC) + + filename = os.path.basename(path) + filename_tokens = os.path.splitext(filename)[0].replace('_', '-').replace(' ', '-').split('-') + filename_tokens = [token for token in filename_tokens if token.isalpha()] + + npimage = np.array(image).astype(np.uint8) + npimage = (npimage / 127.5 - 1.0).astype(np.float32) + + torchdata = torch.from_numpy(npimage).to(device=device, dtype=torch.float32) + torchdata = torch.moveaxis(torchdata, 2, 0) + + init_latent = model.get_first_stage_encoding(model.encode_first_stage(torchdata.unsqueeze(dim=0))).squeeze() + + self.dataset.append((init_latent, filename_tokens)) + + self.length = len(self.dataset) * repeats + + self.initial_indexes = np.arange(self.length) % len(self.dataset) + self.indexes = None + self.shuffle() + + def shuffle(self): + self.indexes = self.initial_indexes[torch.randperm(self.initial_indexes.shape[0])] + + def __len__(self): + return self.length + + def __getitem__(self, i): + if i % len(self.dataset) == 0: + self.shuffle() + + index = self.indexes[i % len(self.indexes)] + x, filename_tokens = self.dataset[index] + + text = random.choice(self.lines) + text = text.replace("[name]", self.placeholder_token) + text = text.replace("[filewords]", ' '.join(filename_tokens)) + + return x, text diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py new file mode 100644 index 00000000..c0baaace --- /dev/null +++ b/modules/textual_inversion/textual_inversion.py @@ -0,0 +1,258 @@ +import os +import sys +import traceback + +import torch +import tqdm +import html +import datetime + +from modules import shared, devices, sd_hijack, processing +import modules.textual_inversion.dataset + + +class Embedding: + def __init__(self, vec, name, step=None): + self.vec = vec + self.name = name + self.step = step + self.cached_checksum = None + + def save(self, filename): + embedding_data = { + "string_to_token": {"*": 265}, + "string_to_param": {"*": self.vec}, + "name": self.name, + "step": self.step, + } + + torch.save(embedding_data, filename) + + def checksum(self): + if self.cached_checksum is not None: + return self.cached_checksum + + def const_hash(a): + r = 0 + for v in a: + r = (r * 281 ^ int(v) * 997) & 0xFFFFFFFF + return r + + self.cached_checksum = f'{const_hash(self.vec.reshape(-1) * 100) & 0xffff:04x}' + return self.cached_checksum + +class EmbeddingDatabase: + def __init__(self, embeddings_dir): + self.ids_lookup = {} + self.word_embeddings = {} + self.dir_mtime = None + self.embeddings_dir = embeddings_dir + + def register_embedding(self, embedding, model): + + self.word_embeddings[embedding.name] = embedding + + ids = model.cond_stage_model.tokenizer([embedding.name], add_special_tokens=False)['input_ids'][0] + + first_id = ids[0] + if first_id not in self.ids_lookup: + self.ids_lookup[first_id] = [] + self.ids_lookup[first_id].append((ids, embedding)) + + return embedding + + def load_textual_inversion_embeddings(self): + mt = os.path.getmtime(self.embeddings_dir) + if self.dir_mtime is not None and mt <= self.dir_mtime: + return + + self.dir_mtime = mt + self.ids_lookup.clear() + self.word_embeddings.clear() + + def process_file(path, filename): + name = os.path.splitext(filename)[0] + + data = torch.load(path, map_location="cpu") + + # textual inversion embeddings + if 'string_to_param' in data: + param_dict = data['string_to_param'] + if hasattr(param_dict, '_parameters'): + param_dict = getattr(param_dict, '_parameters') # fix for torch 1.12.1 loading saved file from torch 1.11 + assert len(param_dict) == 1, 'embedding file has multiple terms in it' + emb = next(iter(param_dict.items()))[1] + # diffuser concepts + elif type(data) == dict and type(next(iter(data.values()))) == torch.Tensor: + assert len(data.keys()) == 1, 'embedding file has multiple terms in it' + + emb = next(iter(data.values())) + if len(emb.shape) == 1: + emb = emb.unsqueeze(0) + else: + raise Exception(f"Couldn't identify {filename} as neither textual inversion embedding nor diffuser concept.") + + vec = emb.detach().to(devices.device, dtype=torch.float32) + embedding = Embedding(vec, name) + embedding.step = data.get('step', None) + self.register_embedding(embedding, shared.sd_model) + + for fn in os.listdir(self.embeddings_dir): + try: + fullfn = os.path.join(self.embeddings_dir, fn) + + if os.stat(fullfn).st_size == 0: + continue + + process_file(fullfn, fn) + except Exception: + print(f"Error loading emedding {fn}:", file=sys.stderr) + print(traceback.format_exc(), file=sys.stderr) + continue + + print(f"Loaded a total of {len(self.word_embeddings)} textual inversion embeddings.") + + def find_embedding_at_position(self, tokens, offset): + token = tokens[offset] + possible_matches = self.ids_lookup.get(token, None) + + if possible_matches is None: + return None + + for ids, embedding in possible_matches: + if tokens[offset:offset + len(ids)] == ids: + return embedding + + return None + + + +def create_embedding(name, num_vectors_per_token): + init_text = '*' + + cond_model = shared.sd_model.cond_stage_model + embedding_layer = cond_model.wrapped.transformer.text_model.embeddings + + ids = cond_model.tokenizer(init_text, max_length=num_vectors_per_token, return_tensors="pt", add_special_tokens=False)["input_ids"] + embedded = embedding_layer(ids.to(devices.device)).squeeze(0) + vec = torch.zeros((num_vectors_per_token, embedded.shape[1]), device=devices.device) + + for i in range(num_vectors_per_token): + vec[i] = embedded[i * int(embedded.shape[0]) // num_vectors_per_token] + + fn = os.path.join(shared.cmd_opts.embeddings_dir, f"{name}.pt") + assert not os.path.exists(fn), f"file {fn} already exists" + + embedding = Embedding(vec, name) + embedding.step = 0 + embedding.save(fn) + + return fn + + +def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps, create_image_every, save_embedding_every, template_file): + assert embedding_name, 'embedding not selected' + + shared.state.textinfo = "Initializing textual inversion training..." + shared.state.job_count = steps + + filename = os.path.join(shared.cmd_opts.embeddings_dir, f'{embedding_name}.pt') + + log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%d-%m"), embedding_name) + + if save_embedding_every > 0: + embedding_dir = os.path.join(log_directory, "embeddings") + os.makedirs(embedding_dir, exist_ok=True) + else: + embedding_dir = None + + if create_image_every > 0: + images_dir = os.path.join(log_directory, "images") + os.makedirs(images_dir, exist_ok=True) + else: + images_dir = None + + cond_model = shared.sd_model.cond_stage_model + + shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..." + with torch.autocast("cuda"): + ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=512, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file) + + hijack = sd_hijack.model_hijack + + embedding = hijack.embedding_db.word_embeddings[embedding_name] + embedding.vec.requires_grad = True + + optimizer = torch.optim.AdamW([embedding.vec], lr=learn_rate) + + losses = torch.zeros((32,)) + + last_saved_file = "" + last_saved_image = "" + + ititial_step = embedding.step or 0 + if ititial_step > steps: + return embedding, filename + + pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step) + for i, (x, text) in pbar: + embedding.step = i + ititial_step + + if embedding.step > steps: + break + + if shared.state.interrupted: + break + + with torch.autocast("cuda"): + c = cond_model([text]) + loss = shared.sd_model(x.unsqueeze(0), c)[0] + + losses[embedding.step % losses.shape[0]] = loss.item() + + optimizer.zero_grad() + loss.backward() + optimizer.step() + + pbar.set_description(f"loss: {losses.mean():.7f}") + + if embedding.step > 0 and embedding_dir is not None and embedding.step % save_embedding_every == 0: + last_saved_file = os.path.join(embedding_dir, f'{embedding_name}-{embedding.step}.pt') + embedding.save(last_saved_file) + + if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0: + last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png') + + p = processing.StableDiffusionProcessingTxt2Img( + sd_model=shared.sd_model, + prompt=text, + steps=20, + do_not_save_grid=True, + do_not_save_samples=True, + ) + + processed = processing.process_images(p) + image = processed.images[0] + + shared.state.current_image = image + image.save(last_saved_image) + + last_saved_image += f", prompt: {text}" + + shared.state.job_no = embedding.step + + shared.state.textinfo = f""" +

+Loss: {losses.mean():.7f}
+Step: {embedding.step}
+Last prompt: {html.escape(text)}
+Last saved embedding: {html.escape(last_saved_file)}
+Last saved image: {html.escape(last_saved_image)}
+

+""" + + embedding.cached_checksum = None + embedding.save(filename) + + return embedding, filename + diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py new file mode 100644 index 00000000..ce3677a9 --- /dev/null +++ b/modules/textual_inversion/ui.py @@ -0,0 +1,32 @@ +import html + +import gradio as gr + +import modules.textual_inversion.textual_inversion as ti +from modules import sd_hijack, shared + + +def create_embedding(name, nvpt): + filename = ti.create_embedding(name, nvpt) + + sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings() + + return gr.Dropdown.update(choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())), f"Created: {filename}", "" + + +def train_embedding(*args): + + try: + sd_hijack.undo_optimizations() + + embedding, filename = ti.train_embedding(*args) + + res = f""" +Training {'interrupted' if shared.state.interrupted else 'finished'} after {embedding.step} steps. +Embedding saved to {html.escape(filename)} +""" + return res, "" + except Exception: + raise + finally: + sd_hijack.apply_optimizations() diff --git a/modules/ui.py b/modules/ui.py index 15572bb0..57aef6ff 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -21,6 +21,7 @@ import gradio as gr import gradio.utils import gradio.routes +from modules import sd_hijack from modules.paths import script_path from modules.shared import opts, cmd_opts import modules.shared as shared @@ -32,6 +33,7 @@ import modules.gfpgan_model import modules.codeformer_model import modules.styles import modules.generation_parameters_copypaste +import modules.textual_inversion.ui # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI mimetypes.init() @@ -142,8 +144,8 @@ def save_files(js_data, images, index): return '', '', plaintext_to_html(f"Saved: {filenames[0]}") -def wrap_gradio_call(func): - def f(*args, **kwargs): +def wrap_gradio_call(func, extra_outputs=None): + def f(*args, extra_outputs_array=extra_outputs, **kwargs): run_memmon = opts.memmon_poll_rate > 0 and not shared.mem_mon.disabled if run_memmon: shared.mem_mon.monitor() @@ -159,7 +161,10 @@ def wrap_gradio_call(func): shared.state.job = "" shared.state.job_count = 0 - res = [None, '', f"
{plaintext_to_html(type(e).__name__+': '+str(e))}
"] + if extra_outputs_array is None: + extra_outputs_array = [None, ''] + + res = extra_outputs_array + [f"
{plaintext_to_html(type(e).__name__+': '+str(e))}
"] elapsed = time.perf_counter() - t @@ -179,6 +184,7 @@ def wrap_gradio_call(func): res[-1] += f"

Time taken: {elapsed:.2f}s

{vram_html}
" shared.state.interrupted = False + shared.state.job_count = 0 return tuple(res) @@ -187,7 +193,7 @@ def wrap_gradio_call(func): def check_progress_call(id_part): if shared.state.job_count == 0: - return "", gr_show(False), gr_show(False) + return "", gr_show(False), gr_show(False), gr_show(False) progress = 0 @@ -219,13 +225,19 @@ def check_progress_call(id_part): else: preview_visibility = gr_show(True) - return f"

{progressbar}

", preview_visibility, image + if shared.state.textinfo is not None: + textinfo_result = gr.HTML.update(value=shared.state.textinfo, visible=True) + else: + textinfo_result = gr_show(False) + + return f"

{progressbar}

", preview_visibility, image, textinfo_result def check_progress_call_initial(id_part): shared.state.job_count = -1 shared.state.current_latent = None shared.state.current_image = None + shared.state.textinfo = None return check_progress_call(id_part) @@ -399,13 +411,16 @@ def create_toprow(is_img2img): return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, interrogate, prompt_style_apply, save_style, paste -def setup_progressbar(progressbar, preview, id_part): +def setup_progressbar(progressbar, preview, id_part, textinfo=None): + if textinfo is None: + textinfo = gr.HTML(visible=False) + check_progress = gr.Button('Check progress', elem_id=f"{id_part}_check_progress", visible=False) check_progress.click( fn=lambda: check_progress_call(id_part), show_progress=False, inputs=[], - outputs=[progressbar, preview, preview], + outputs=[progressbar, preview, preview, textinfo], ) check_progress_initial = gr.Button('Check progress (first)', elem_id=f"{id_part}_check_progress_initial", visible=False) @@ -413,11 +428,14 @@ def setup_progressbar(progressbar, preview, id_part): fn=lambda: check_progress_call_initial(id_part), show_progress=False, inputs=[], - outputs=[progressbar, preview, preview], + outputs=[progressbar, preview, preview, textinfo], ) -def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): +def create_ui(wrap_gradio_gpu_call): + import modules.img2img + import modules.txt2img + with gr.Blocks(analytics_enabled=False) as txt2img_interface: txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, txt2img_prompt_style_apply, txt2img_save_style, paste = create_toprow(is_img2img=False) dummy_component = gr.Label(visible=False) @@ -483,7 +501,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) txt2img_args = dict( - fn=txt2img, + fn=wrap_gradio_gpu_call(modules.txt2img.txt2img), _js="submit", inputs=[ txt2img_prompt, @@ -675,7 +693,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): ) img2img_args = dict( - fn=img2img, + fn=wrap_gradio_gpu_call(modules.img2img.img2img), _js="submit_img2img", inputs=[ dummy_component, @@ -828,7 +846,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): open_extras_folder = gr.Button('Open output directory', elem_id=button_id) submit.click( - fn=run_extras, + fn=wrap_gradio_gpu_call(modules.extras.run_extras), _js="get_extras_tab_index", inputs=[ dummy_component, @@ -878,7 +896,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): pnginfo_send_to_img2img = gr.Button('Send to img2img') image.change( - fn=wrap_gradio_call(run_pnginfo), + fn=wrap_gradio_call(modules.extras.run_pnginfo), inputs=[image], outputs=[html, generation_info, html2], ) @@ -887,7 +905,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): with gr.Row().style(equal_height=False): with gr.Column(variant='panel'): gr.HTML(value="

A merger of the two checkpoints will be generated in your checkpoint directory.

") - + with gr.Row(): primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary Model Name") secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary Model Name") @@ -896,10 +914,96 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid", "Inverse Sigmoid"], value="Weighted Sum", label="Interpolation Method") save_as_half = gr.Checkbox(value=False, label="Safe as float16") modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary') - + with gr.Column(variant='panel'): submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False) + sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings() + + with gr.Blocks() as textual_inversion_interface: + with gr.Row().style(equal_height=False): + with gr.Column(): + with gr.Group(): + gr.HTML(value="

Create a new embedding

") + + new_embedding_name = gr.Textbox(label="Name") + nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1) + + with gr.Row(): + with gr.Column(scale=3): + gr.HTML(value="") + + with gr.Column(): + create_embedding = gr.Button(value="Create", variant='primary') + + with gr.Group(): + gr.HTML(value="

Train an embedding; must specify a directory with a set of 512x512 images

") + train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) + learn_rate = gr.Number(label='Learning rate', value=5.0e-03) + dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images") + log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion") + template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt")) + steps = gr.Number(label='Max steps', value=100000, precision=0) + create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=1000, precision=0) + save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=1000, precision=0) + + with gr.Row(): + with gr.Column(scale=2): + gr.HTML(value="") + + with gr.Column(): + with gr.Row(): + interrupt_training = gr.Button(value="Interrupt") + train_embedding = gr.Button(value="Train", variant='primary') + + with gr.Column(): + progressbar = gr.HTML(elem_id="ti_progressbar") + ti_output = gr.Text(elem_id="ti_output", value="", show_label=False) + + ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(grid=4) + ti_preview = gr.Image(elem_id='ti_preview', visible=False) + ti_progress = gr.HTML(elem_id="ti_progress", value="") + ti_outcome = gr.HTML(elem_id="ti_error", value="") + setup_progressbar(progressbar, ti_preview, 'ti', textinfo=ti_progress) + + create_embedding.click( + fn=modules.textual_inversion.ui.create_embedding, + inputs=[ + new_embedding_name, + nvpt, + ], + outputs=[ + train_embedding_name, + ti_output, + ti_outcome, + ] + ) + + train_embedding.click( + fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]), + _js="start_training_textual_inversion", + inputs=[ + train_embedding_name, + learn_rate, + dataset_directory, + log_directory, + steps, + create_image_every, + save_embedding_every, + template_file, + ], + outputs=[ + ti_output, + ti_outcome, + ] + ) + + interrupt_training.click( + fn=lambda: shared.state.interrupt(), + inputs=[], + outputs=[], + ) + def create_setting_component(key): def fun(): return opts.data[key] if key in opts.data else opts.data_labels[key].default @@ -1011,6 +1115,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): (extras_interface, "Extras", "extras"), (pnginfo_interface, "PNG Info", "pnginfo"), (modelmerger_interface, "Checkpoint Merger", "modelmerger"), + (textual_inversion_interface, "Textual inversion", "ti"), (settings_interface, "Settings", "settings"), ] @@ -1044,11 +1149,11 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): def modelmerger(*args): try: - results = run_modelmerger(*args) + results = modules.extras.run_modelmerger(*args) except Exception as e: print("Error loading/saving model file:", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) - modules.sd_models.list_models() #To remove the potentially missing models from the list + modules.sd_models.list_models() # to remove the potentially missing models from the list return ["Error loading/saving model file. It doesn't exist or the name contains illegal characters"] + [gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(3)] return results diff --git a/style.css b/style.css index 79d6bb0d..39586bf1 100644 --- a/style.css +++ b/style.css @@ -157,7 +157,7 @@ button{ max-width: 10em; } -#txt2img_preview, #img2img_preview{ +#txt2img_preview, #img2img_preview, #ti_preview{ position: absolute; width: 320px; left: 0; @@ -172,18 +172,18 @@ button{ } @media screen and (min-width: 768px) { - #txt2img_preview, #img2img_preview { + #txt2img_preview, #img2img_preview, #ti_preview { position: absolute; } } @media screen and (max-width: 767px) { - #txt2img_preview, #img2img_preview { + #txt2img_preview, #img2img_preview, #ti_preview { position: relative; } } -#txt2img_preview div.left-0.top-0, #img2img_preview div.left-0.top-0{ +#txt2img_preview div.left-0.top-0, #img2img_preview div.left-0.top-0, #ti_preview div.left-0.top-0{ display: none; } @@ -247,7 +247,7 @@ input[type="range"]{ #txt2img_negative_prompt, #img2img_negative_prompt{ } -#txt2img_progressbar, #img2img_progressbar{ +#txt2img_progressbar, #img2img_progressbar, #ti_progressbar{ position: absolute; z-index: 1000; right: 0; diff --git a/textual_inversion_templates/style.txt b/textual_inversion_templates/style.txt new file mode 100644 index 00000000..15af2d6b --- /dev/null +++ b/textual_inversion_templates/style.txt @@ -0,0 +1,19 @@ +a painting, art by [name] +a rendering, art by [name] +a cropped painting, art by [name] +the painting, art by [name] +a clean painting, art by [name] +a dirty painting, art by [name] +a dark painting, art by [name] +a picture, art by [name] +a cool painting, art by [name] +a close-up painting, art by [name] +a bright painting, art by [name] +a cropped painting, art by [name] +a good painting, art by [name] +a close-up painting, art by [name] +a rendition, art by [name] +a nice painting, art by [name] +a small painting, art by [name] +a weird painting, art by [name] +a large painting, art by [name] diff --git a/textual_inversion_templates/style_filewords.txt b/textual_inversion_templates/style_filewords.txt new file mode 100644 index 00000000..b3a8159a --- /dev/null +++ b/textual_inversion_templates/style_filewords.txt @@ -0,0 +1,19 @@ +a painting of [filewords], art by [name] +a rendering of [filewords], art by [name] +a cropped painting of [filewords], art by [name] +the painting of [filewords], art by [name] +a clean painting of [filewords], art by [name] +a dirty painting of [filewords], art by [name] +a dark painting of [filewords], art by [name] +a picture of [filewords], art by [name] +a cool painting of [filewords], art by [name] +a close-up painting of [filewords], art by [name] +a bright painting of [filewords], art by [name] +a cropped painting of [filewords], art by [name] +a good painting of [filewords], art by [name] +a close-up painting of [filewords], art by [name] +a rendition of [filewords], art by [name] +a nice painting of [filewords], art by [name] +a small painting of [filewords], art by [name] +a weird painting of [filewords], art by [name] +a large painting of [filewords], art by [name] diff --git a/textual_inversion_templates/subject.txt b/textual_inversion_templates/subject.txt new file mode 100644 index 00000000..79f36aa0 --- /dev/null +++ b/textual_inversion_templates/subject.txt @@ -0,0 +1,27 @@ +a photo of a [name] +a rendering of a [name] +a cropped photo of the [name] +the photo of a [name] +a photo of a clean [name] +a photo of a dirty [name] +a dark photo of the [name] +a photo of my [name] +a photo of the cool [name] +a close-up photo of a [name] +a bright photo of the [name] +a cropped photo of a [name] +a photo of the [name] +a good photo of the [name] +a photo of one [name] +a close-up photo of the [name] +a rendition of the [name] +a photo of the clean [name] +a rendition of a [name] +a photo of a nice [name] +a good photo of a [name] +a photo of the nice [name] +a photo of the small [name] +a photo of the weird [name] +a photo of the large [name] +a photo of a cool [name] +a photo of a small [name] diff --git a/textual_inversion_templates/subject_filewords.txt b/textual_inversion_templates/subject_filewords.txt new file mode 100644 index 00000000..008652a6 --- /dev/null +++ b/textual_inversion_templates/subject_filewords.txt @@ -0,0 +1,27 @@ +a photo of a [name], [filewords] +a rendering of a [name], [filewords] +a cropped photo of the [name], [filewords] +the photo of a [name], [filewords] +a photo of a clean [name], [filewords] +a photo of a dirty [name], [filewords] +a dark photo of the [name], [filewords] +a photo of my [name], [filewords] +a photo of the cool [name], [filewords] +a close-up photo of a [name], [filewords] +a bright photo of the [name], [filewords] +a cropped photo of a [name], [filewords] +a photo of the [name], [filewords] +a good photo of the [name], [filewords] +a photo of one [name], [filewords] +a close-up photo of the [name], [filewords] +a rendition of the [name], [filewords] +a photo of the clean [name], [filewords] +a rendition of a [name], [filewords] +a photo of a nice [name], [filewords] +a good photo of a [name], [filewords] +a photo of the nice [name], [filewords] +a photo of the small [name], [filewords] +a photo of the weird [name], [filewords] +a photo of the large [name], [filewords] +a photo of a cool [name], [filewords] +a photo of a small [name], [filewords] diff --git a/webui.py b/webui.py index b8cccd54..19fdcdd4 100644 --- a/webui.py +++ b/webui.py @@ -12,7 +12,6 @@ import modules.bsrgan_model as bsrgan import modules.extras import modules.face_restoration import modules.gfpgan_model as gfpgan -import modules.img2img import modules.ldsr_model as ldsr import modules.lowvram import modules.realesrgan_model as realesrgan @@ -21,7 +20,6 @@ import modules.sd_hijack import modules.sd_models import modules.shared as shared import modules.swinir_model as swinir -import modules.txt2img import modules.ui from modules import modelloader from modules.paths import script_path @@ -46,7 +44,7 @@ def wrap_queued_call(func): return f -def wrap_gradio_gpu_call(func): +def wrap_gradio_gpu_call(func, extra_outputs=None): def f(*args, **kwargs): devices.torch_gc() @@ -58,6 +56,7 @@ def wrap_gradio_gpu_call(func): shared.state.current_image = None shared.state.current_image_sampling_step = 0 shared.state.interrupted = False + shared.state.textinfo = None with queue_lock: res = func(*args, **kwargs) @@ -69,7 +68,7 @@ def wrap_gradio_gpu_call(func): return res - return modules.ui.wrap_gradio_call(f) + return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs) modules.scripts.load_scripts(os.path.join(script_path, "scripts")) @@ -86,13 +85,7 @@ def webui(): signal.signal(signal.SIGINT, sigint_handler) - demo = modules.ui.create_ui( - txt2img=wrap_gradio_gpu_call(modules.txt2img.txt2img), - img2img=wrap_gradio_gpu_call(modules.img2img.img2img), - run_extras=wrap_gradio_gpu_call(modules.extras.run_extras), - run_pnginfo=modules.extras.run_pnginfo, - run_modelmerger=modules.extras.run_modelmerger - ) + demo = modules.ui.create_ui(wrap_gradio_gpu_call=wrap_gradio_gpu_call) demo.launch( share=cmd_opts.share, -- cgit v1.2.3 From 88ec0cf5571883d84abd09196652b3679e359f2e Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 2 Oct 2022 19:40:51 +0300 Subject: fix for incorrect embedding token length calculation (will break seeds that use embeddings, you're welcome!) add option to input initialization text for embeddings --- modules/sd_hijack.py | 8 ++++---- modules/textual_inversion/textual_inversion.py | 13 +++++-------- modules/textual_inversion/ui.py | 4 ++-- modules/ui.py | 2 ++ 4 files changed, 13 insertions(+), 14 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index fd57e5c5..3fa06242 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -130,7 +130,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): while i < len(tokens): token = tokens[i] - embedding = self.hijack.embedding_db.find_embedding_at_position(tokens, i) + embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i) if embedding is None: remade_tokens.append(token) @@ -142,7 +142,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): remade_tokens += [0] * emb_len multipliers += [weight] * emb_len used_custom_terms.append((embedding.name, embedding.checksum())) - i += emb_len + i += embedding_length_in_tokens if len(remade_tokens) > maxlen - 2: vocab = {v: k for k, v in self.wrapped.tokenizer.get_vocab().items()} @@ -213,7 +213,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): while i < len(tokens): token = tokens[i] - embedding = self.hijack.embedding_db.find_embedding_at_position(tokens, i) + embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i) mult_change = self.token_mults.get(token) if opts.enable_emphasis else None if mult_change is not None: @@ -229,7 +229,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): remade_tokens += [0] * emb_len multipliers += [mult] * emb_len used_custom_terms.append((embedding.name, embedding.checksum())) - i += emb_len + i += embedding_length_in_tokens if len(remade_tokens) > maxlen - 2: vocab = {v: k for k, v in self.wrapped.tokenizer.get_vocab().items()} diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index c0baaace..0c50161d 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -117,24 +117,21 @@ class EmbeddingDatabase: possible_matches = self.ids_lookup.get(token, None) if possible_matches is None: - return None + return None, None for ids, embedding in possible_matches: if tokens[offset:offset + len(ids)] == ids: - return embedding + return embedding, len(ids) - return None + return None, None - -def create_embedding(name, num_vectors_per_token): - init_text = '*' - +def create_embedding(name, num_vectors_per_token, init_text='*'): cond_model = shared.sd_model.cond_stage_model embedding_layer = cond_model.wrapped.transformer.text_model.embeddings ids = cond_model.tokenizer(init_text, max_length=num_vectors_per_token, return_tensors="pt", add_special_tokens=False)["input_ids"] - embedded = embedding_layer(ids.to(devices.device)).squeeze(0) + embedded = embedding_layer.token_embedding.wrapped(ids.to(devices.device)).squeeze(0) vec = torch.zeros((num_vectors_per_token, embedded.shape[1]), device=devices.device) for i in range(num_vectors_per_token): diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py index ce3677a9..66c43ffb 100644 --- a/modules/textual_inversion/ui.py +++ b/modules/textual_inversion/ui.py @@ -6,8 +6,8 @@ import modules.textual_inversion.textual_inversion as ti from modules import sd_hijack, shared -def create_embedding(name, nvpt): - filename = ti.create_embedding(name, nvpt) +def create_embedding(name, initialization_text, nvpt): + filename = ti.create_embedding(name, nvpt, init_text=initialization_text) sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings() diff --git a/modules/ui.py b/modules/ui.py index 3b81a4f7..eca50df0 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -954,6 +954,7 @@ def create_ui(wrap_gradio_gpu_call): gr.HTML(value="

Create a new embedding

") new_embedding_name = gr.Textbox(label="Name") + initialization_text = gr.Textbox(label="Initialization text", value="*") nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1) with gr.Row(): @@ -997,6 +998,7 @@ def create_ui(wrap_gradio_gpu_call): fn=modules.textual_inversion.ui.create_embedding, inputs=[ new_embedding_name, + initialization_text, nvpt, ], outputs=[ -- cgit v1.2.3 From e808096cf641d868f88465515d70d40fc46125d4 Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Sun, 2 Oct 2022 19:26:06 +0100 Subject: correct indent --- modules/scripts.py | 48 +++++++++++++++++++++++++----------------------- modules/ui.py | 25 ++++++++++++------------- 2 files changed, 37 insertions(+), 36 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/scripts.py b/modules/scripts.py index 788397f5..45230f9a 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -163,37 +163,39 @@ class ScriptRunner: return processed def reload_sources(self): - for si,script in list(enumerate(self.scripts)): - with open(script.filename, "r", encoding="utf8") as file: - args_from = script.args_from - args_to = script.args_to - filename = script.filename - text = file.read() + for si, script in list(enumerate(self.scripts)): + with open(script.filename, "r", encoding="utf8") as file: + args_from = script.args_from + args_to = script.args_to + filename = script.filename + text = file.read() - from types import ModuleType - compiled = compile(text, filename, 'exec') - module = ModuleType(script.filename) - exec(compiled, module.__dict__) + from types import ModuleType - for key, script_class in module.__dict__.items(): - if type(script_class) == type and issubclass(script_class, Script): - self.scripts[si] = script_class() - self.scripts[si].filename = filename - self.scripts[si].args_from = args_from - self.scripts[si].args_to = args_to + compiled = compile(text, filename, 'exec') + module = ModuleType(script.filename) + exec(compiled, module.__dict__) + + for key, script_class in module.__dict__.items(): + if type(script_class) == type and issubclass(script_class, Script): + self.scripts[si] = script_class() + self.scripts[si].filename = filename + self.scripts[si].args_from = args_from + self.scripts[si].args_to = args_to scripts_txt2img = ScriptRunner() scripts_img2img = ScriptRunner() def reload_script_body_only(): - scripts_txt2img.reload_sources() - scripts_img2img.reload_sources() + scripts_txt2img.reload_sources() + scripts_img2img.reload_sources() + def reload_scripts(basedir): - global scripts_txt2img,scripts_img2img + global scripts_txt2img, scripts_img2img - scripts_data.clear() - load_scripts(basedir) + scripts_data.clear() + load_scripts(basedir) - scripts_txt2img = ScriptRunner() - scripts_img2img = ScriptRunner() + scripts_txt2img = ScriptRunner() + scripts_img2img = ScriptRunner() diff --git a/modules/ui.py b/modules/ui.py index 963a2c61..6b30f84b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1003,12 +1003,12 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): ) with gr.Row(): - reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary') - restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary') + reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary') + restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary') def reload_scripts(): - modules.scripts.reload_script_body_only() + modules.scripts.reload_script_body_only() reload_script_bodies.click( fn=reload_scripts, @@ -1018,7 +1018,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): ) def request_restart(): - settings_interface.gradio_ref.do_restart = True + settings_interface.gradio_ref.do_restart = True restart_gradio.click( fn=request_restart, @@ -1234,12 +1234,11 @@ for filename in sorted(os.listdir(jsdir)): if 'gradio_routes_templates_response' not in globals(): - def template_response(*args, **kwargs): - res = gradio_routes_templates_response(*args, **kwargs) - res.body = res.body.replace(b'', f'{javascript}'.encode("utf8")) - res.init_headers() - return res - - gradio_routes_templates_response = gradio.routes.templates.TemplateResponse - gradio.routes.templates.TemplateResponse = template_response - + def template_response(*args, **kwargs): + res = gradio_routes_templates_response(*args, **kwargs) + res.body = res.body.replace(b'', f'{javascript}'.encode("utf8")) + res.init_headers() + return res + + gradio_routes_templates_response = gradio.routes.templates.TemplateResponse + gradio.routes.templates.TemplateResponse = template_response -- cgit v1.2.3 From 91f327f22bb2feb780c424c74723cc0629dc34a1 Mon Sep 17 00:00:00 2001 From: Lopyter Date: Sun, 2 Oct 2022 18:15:31 +0200 Subject: make save to dirs optional for imgs saved from ui --- modules/shared.py | 1 + modules/ui.py | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/shared.py b/modules/shared.py index 1bf7a6c1..785e7af6 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -173,6 +173,7 @@ options_templates.update(options_section(('saving-to-dirs', "Saving to a directo "grid_save_to_dirs": OptionInfo(False, "Save grids to subdirectory"), "directories_filename_pattern": OptionInfo("", "Directory name pattern"), "directories_max_prompt_words": OptionInfo(8, "Max prompt words", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1}), + "use_save_to_dirs_for_ui": OptionInfo(False, "Use \"Save images to a subdirectory\" option for images saved from UI"), })) options_templates.update(options_section(('upscaling', "Upscaling"), { diff --git a/modules/ui.py b/modules/ui.py index 78a15d83..8912deff 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -113,7 +113,7 @@ def save_files(js_data, images, index): p = MyObject(data) path = opts.outdir_save - save_to_dirs = opts.save_to_dirs + save_to_dirs = opts.use_save_to_dirs_for_ui if save_to_dirs: dirname = apply_filename_pattern(opts.directories_filename_pattern or "[prompt_words]", p, p.seed, p.prompt) -- cgit v1.2.3 From c7543d4940da672d970124ae8f2fec9de7bdc1da Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 2 Oct 2022 22:41:21 +0300 Subject: preprocessing for textual inversion added --- modules/interrogate.py | 1 + modules/textual_inversion/preprocess.py | 75 ++++++++++++++++++++++++++ modules/textual_inversion/textual_inversion.py | 1 + modules/textual_inversion/ui.py | 14 +++-- modules/ui.py | 36 +++++++++++++ 5 files changed, 124 insertions(+), 3 deletions(-) create mode 100644 modules/textual_inversion/preprocess.py (limited to 'modules/ui.py') diff --git a/modules/interrogate.py b/modules/interrogate.py index f62a4745..eed87144 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -21,6 +21,7 @@ Category = namedtuple("Category", ["name", "topn", "items"]) re_topn = re.compile(r"\.top(\d+)\.") + class InterrogateModels: blip_model = None clip_model = None diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py new file mode 100644 index 00000000..209e928f --- /dev/null +++ b/modules/textual_inversion/preprocess.py @@ -0,0 +1,75 @@ +import os +from PIL import Image, ImageOps +import tqdm + +from modules import shared, images + + +def preprocess(process_src, process_dst, process_flip, process_split, process_caption): + size = 512 + src = os.path.abspath(process_src) + dst = os.path.abspath(process_dst) + + assert src != dst, 'same directory specified as source and desitnation' + + os.makedirs(dst, exist_ok=True) + + files = os.listdir(src) + + shared.state.textinfo = "Preprocessing..." + shared.state.job_count = len(files) + + if process_caption: + shared.interrogator.load() + + def save_pic_with_caption(image, index): + if process_caption: + caption = "-" + shared.interrogator.generate_caption(image) + else: + caption = "" + + image.save(os.path.join(dst, f"{index:05}-{subindex[0]}{caption}.png")) + subindex[0] += 1 + + def save_pic(image, index): + save_pic_with_caption(image, index) + + if process_flip: + save_pic_with_caption(ImageOps.mirror(image), index) + + for index, imagefile in enumerate(tqdm.tqdm(files)): + subindex = [0] + filename = os.path.join(src, imagefile) + img = Image.open(filename).convert("RGB") + + if shared.state.interrupted: + break + + ratio = img.height / img.width + is_tall = ratio > 1.35 + is_wide = ratio < 1 / 1.35 + + if process_split and is_tall: + img = img.resize((size, size * img.height // img.width)) + + top = img.crop((0, 0, size, size)) + save_pic(top, index) + + bot = img.crop((0, img.height - size, size, img.height)) + save_pic(bot, index) + elif process_split and is_wide: + img = img.resize((size * img.width // img.height, size)) + + left = img.crop((0, 0, size, size)) + save_pic(left, index) + + right = img.crop((img.width - size, 0, img.width, size)) + save_pic(right, index) + else: + img = images.resize_image(1, img, size, size) + save_pic(img, index) + + shared.state.nextjob() + + if process_caption: + shared.interrogator.send_blip_to_ram() diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 1183aab7..d4e250d8 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -7,6 +7,7 @@ import tqdm import html import datetime + from modules import shared, devices, sd_hijack, processing, sd_models import modules.textual_inversion.dataset diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py index 633037d8..f19ac5e0 100644 --- a/modules/textual_inversion/ui.py +++ b/modules/textual_inversion/ui.py @@ -2,24 +2,31 @@ import html import gradio as gr -import modules.textual_inversion.textual_inversion as ti +import modules.textual_inversion.textual_inversion +import modules.textual_inversion.preprocess from modules import sd_hijack, shared def create_embedding(name, initialization_text, nvpt): - filename = ti.create_embedding(name, nvpt, init_text=initialization_text) + filename = modules.textual_inversion.textual_inversion.create_embedding(name, nvpt, init_text=initialization_text) sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings() return gr.Dropdown.update(choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())), f"Created: {filename}", "" +def preprocess(*args): + modules.textual_inversion.preprocess.preprocess(*args) + + return "Preprocessing finished.", "" + + def train_embedding(*args): try: sd_hijack.undo_optimizations() - embedding, filename = ti.train_embedding(*args) + embedding, filename = modules.textual_inversion.textual_inversion.train_embedding(*args) res = f""" Training {'interrupted' if shared.state.interrupted else 'finished'} at {embedding.step} steps. @@ -30,3 +37,4 @@ Embedding saved to {html.escape(filename)} raise finally: sd_hijack.apply_optimizations() + diff --git a/modules/ui.py b/modules/ui.py index 8912deff..e7bde53b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -961,6 +961,8 @@ def create_ui(wrap_gradio_gpu_call): with gr.Row().style(equal_height=False): with gr.Column(): with gr.Group(): + gr.HTML(value="

See wiki for detailed explanation.

") + gr.HTML(value="

Create a new embedding

") new_embedding_name = gr.Textbox(label="Name") @@ -974,6 +976,24 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column(): create_embedding = gr.Button(value="Create", variant='primary') + with gr.Group(): + gr.HTML(value="

Preprocess images

") + + process_src = gr.Textbox(label='Source directory') + process_dst = gr.Textbox(label='Destination directory') + + with gr.Row(): + process_flip = gr.Checkbox(label='Flip') + process_split = gr.Checkbox(label='Split into two') + process_caption = gr.Checkbox(label='Add caption') + + with gr.Row(): + with gr.Column(scale=3): + gr.HTML(value="") + + with gr.Column(): + run_preprocess = gr.Button(value="Preprocess", variant='primary') + with gr.Group(): gr.HTML(value="

Train an embedding; must specify a directory with a set of 512x512 images

") train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) @@ -1018,6 +1038,22 @@ def create_ui(wrap_gradio_gpu_call): ] ) + run_preprocess.click( + fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), + _js="start_training_textual_inversion", + inputs=[ + process_src, + process_dst, + process_flip, + process_split, + process_caption, + ], + outputs=[ + ti_output, + ti_outcome, + ], + ) + train_embedding.click( fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]), _js="start_training_textual_inversion", -- cgit v1.2.3 From 6785331e22d6a488fbf5905fab56d7fec867e038 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 2 Oct 2022 22:59:01 +0300 Subject: keep textual inversion dataset latents in CPU memory to save a bit of VRAM --- modules/textual_inversion/dataset.py | 2 ++ modules/textual_inversion/textual_inversion.py | 3 +++ modules/ui.py | 4 ++-- 3 files changed, 7 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py index 7e134a08..e8394ff6 100644 --- a/modules/textual_inversion/dataset.py +++ b/modules/textual_inversion/dataset.py @@ -8,6 +8,7 @@ from torchvision import transforms import random import tqdm +from modules import devices class PersonalizedBase(Dataset): @@ -47,6 +48,7 @@ class PersonalizedBase(Dataset): torchdata = torch.moveaxis(torchdata, 2, 0) init_latent = model.get_first_stage_encoding(model.encode_first_stage(torchdata.unsqueeze(dim=0))).squeeze() + init_latent = init_latent.to(devices.cpu) self.dataset.append((init_latent, filename_tokens)) diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index d4e250d8..8686f534 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -212,7 +212,10 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps, with torch.autocast("cuda"): c = cond_model([text]) + + x = x.to(devices.device) loss = shared.sd_model(x.unsqueeze(0), c)[0] + del x losses[embedding.step % losses.shape[0]] = loss.item() diff --git a/modules/ui.py b/modules/ui.py index e7bde53b..d9d02ece 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1002,8 +1002,8 @@ def create_ui(wrap_gradio_gpu_call): log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion") template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt")) steps = gr.Number(label='Max steps', value=100000, precision=0) - create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=1000, precision=0) - save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=1000, precision=0) + create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0) + save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0) with gr.Row(): with gr.Column(scale=2): -- cgit v1.2.3 From e615d4f9d101e2712c7c2d0e3e8feb19cb430c74 Mon Sep 17 00:00:00 2001 From: Hanusz Leszek Date: Sun, 2 Oct 2022 21:08:23 +0200 Subject: Convert folder icon surrogate pair to valid utf8 --- javascript/hints.js | 2 +- modules/ui.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/hints.js b/javascript/hints.js index 84694eeb..e72e9338 100644 --- a/javascript/hints.js +++ b/javascript/hints.js @@ -15,7 +15,7 @@ titles = { "\u267b\ufe0f": "Reuse seed from last generation, mostly useful if it was randomed", "\u{1f3a8}": "Add a random artist to the prompt.", "\u2199\ufe0f": "Read generation parameters from prompt into user interface.", - "\uD83D\uDCC2": "Open images output directory", + "\u{1f4c2}": "Open images output directory", "Inpaint a part of image": "Draw a mask over an image, and the script will regenerate the masked area with content according to prompt", "SD upscale": "Upscale image normally, split result into tiles, improve each tile using img2img, merge whole image back", diff --git a/modules/ui.py b/modules/ui.py index d9d02ece..16432151 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -69,7 +69,7 @@ random_symbol = '\U0001f3b2\ufe0f' # 🎲️ reuse_symbol = '\u267b\ufe0f' # ♻️ art_symbol = '\U0001f3a8' # 🎨 paste_symbol = '\u2199\ufe0f' # ↙ -folder_symbol = '\uD83D\uDCC2' +folder_symbol = '\U0001f4c2' # 📂 def plaintext_to_html(text): text = "

" + "
\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "

" -- cgit v1.2.3 From 43a74fa595003321200a40bd2431e56c245e75ed Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Mon, 3 Oct 2022 11:48:19 +0300 Subject: batch processing for img2img with an empty output directory, by request --- modules/img2img.py | 7 +++++-- modules/ui.py | 2 +- 2 files changed, 6 insertions(+), 3 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/img2img.py b/modules/img2img.py index f4455c90..2ff8e261 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -23,8 +23,10 @@ def process_batch(p, input_dir, output_dir, args): print(f"Will process {len(images)} images, creating {p.n_iter * p.batch_size} new images for each.") + save_normally = output_dir == '' + p.do_not_save_grid = True - p.do_not_save_samples = True + p.do_not_save_samples = not save_normally state.job_count = len(images) * p.n_iter @@ -48,7 +50,8 @@ def process_batch(p, input_dir, output_dir, args): left, right = os.path.splitext(filename) filename = f"{left}-{n}{right}" - processed_image.save(os.path.join(output_dir, filename)) + if not save_normally: + processed_image.save(os.path.join(output_dir, filename)) def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, init_img_with_mask, init_img_inpaint, init_mask_inpaint, mask_mode, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args): diff --git a/modules/ui.py b/modules/ui.py index 16432151..55f7aa95 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -658,7 +658,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.TabItem('Batch img2img', id='batch'): hidden = '
Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else '' - gr.HTML(f"

Process images in a directory on the same machine where the server is running.{hidden}

") + gr.HTML(f"

Process images in a directory on the same machine where the server is running.
Use an empty output directory to save pictures normally instead of writing to the output directory.{hidden}

") img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs) img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs) -- cgit v1.2.3 From d5bba20a58f43a9f984bb67b4e17f48661f6b818 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 4 Oct 2022 14:35:12 +0300 Subject: ignore errors in parse for purposes of token counting for #1564 --- modules/ui.py | 12 ++++++++++-- 1 file changed, 10 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 55f7aa95..20dc8c37 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -386,14 +386,22 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: outputs=[seed, dummy_component] ) + def update_token_counter(text, steps): - prompt_schedules = get_learned_conditioning_prompt_schedules([text], steps) + try: + prompt_schedules = get_learned_conditioning_prompt_schedules([text], steps) + except Exception: + # a parsing error can happen here during typing, and we don't want to bother the user with + # messages related to it in console + prompt_schedules = [[[steps, text]]] + flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules) - prompts = [prompt_text for step,prompt_text in flat_prompts] + prompts = [prompt_text for step, prompt_text in flat_prompts] tokens, token_count, max_length = max([model_hijack.tokenize(prompt) for prompt in prompts], key=lambda args: args[1]) style_class = ' class="red"' if (token_count > max_length) else "" return f"{token_count}/{max_length}" + def create_toprow(is_img2img): id_part = "img2img" if is_img2img else "txt2img" -- cgit v1.2.3 From b32852ef037251eb3d846af76e2965594e1ac7a5 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 4 Oct 2022 20:49:54 +0300 Subject: add editor to img2img --- modules/shared.py | 1 + modules/ui.py | 2 +- style.css | 4 ++++ 3 files changed, 6 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/shared.py b/modules/shared.py index ff4e5fa3..e52c9b1d 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -55,6 +55,7 @@ parser.add_argument("--hide-ui-dir-config", action='store_true', help="hide dire parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(script_path, 'config.json')) parser.add_argument("--gradio-debug", action='store_true', help="launch gradio with --debug option") parser.add_argument("--gradio-auth", type=str, help='set gradio authentication like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3"', default=None) +parser.add_argument("--gradio-img2img-tool", type=str, help='gradio image uploader tool: can be either editor for ctopping, or color-sketch for drawing', choices=["color-sketch", "editor"], default="color-sketch") parser.add_argument("--opt-channelslast", action='store_true', help="change memory type for stable diffusion to channels last") parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(script_path, 'styles.csv')) parser.add_argument("--autolaunch", action='store_true', help="open the webui URL in the system's default browser upon launch", default=False) diff --git a/modules/ui.py b/modules/ui.py index 20dc8c37..6cd6761b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -644,7 +644,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Tabs(elem_id="mode_img2img") as tabs_img2img_mode: with gr.TabItem('img2img', id='img2img'): - init_img = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil") + init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_img2img_tool) with gr.TabItem('Inpaint', id='inpaint'): init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA") diff --git a/style.css b/style.css index 39586bf1..e8f4cb75 100644 --- a/style.css +++ b/style.css @@ -403,3 +403,7 @@ input[type="range"]{ .red { color: red; } + +#img2img_image div.h-60{ + height: 480px; +} \ No newline at end of file -- cgit v1.2.3 From ef40e4cd4d383a3405e03f1da3f5b5a1820a8f53 Mon Sep 17 00:00:00 2001 From: xpscyho Date: Tue, 4 Oct 2022 15:12:38 -0400 Subject: Display time taken in mins, secs when relevant Fixes #1656 --- modules/ui.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 6cd6761b..de6342a4 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -196,6 +196,11 @@ def wrap_gradio_call(func, extra_outputs=None): res = extra_outputs_array + [f"
{plaintext_to_html(type(e).__name__+': '+str(e))}
"] elapsed = time.perf_counter() - t + elapsed_m = int(elapsed // 60) + elapsed_s = elapsed % 60 + elapsed_text = f"{elapsed_s:.2f}s" + if (elapsed_m > 0): + elapsed_text = f"{elapsed_m}m "+elapsed_text if run_memmon: mem_stats = {k: -(v//-(1024*1024)) for k, v in shared.mem_mon.stop().items()} @@ -210,7 +215,7 @@ def wrap_gradio_call(func, extra_outputs=None): vram_html = '' # last item is always HTML - res[-1] += f"

Time taken: {elapsed:.2f}s

{vram_html}
" + res[-1] += f"

Time taken: {elapsed_text}

{vram_html}
" shared.state.interrupted = False shared.state.job_count = 0 -- cgit v1.2.3 From bbdbbd36eda870cf0bd49fdf28476c78919a123e Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Wed, 5 Oct 2022 04:43:05 +0100 Subject: shared.state.interrupt when restart is requested --- modules/ui.py | 1 + 1 file changed, 1 insertion(+) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index de6342a4..523ab25b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1210,6 +1210,7 @@ def create_ui(wrap_gradio_gpu_call): ) def request_restart(): + shared.state.interrupt() settings_interface.gradio_ref.do_restart = True restart_gradio.click( -- cgit v1.2.3 From 59a2b9e5afc27d2fda72069ca0635070535d18fe Mon Sep 17 00:00:00 2001 From: Greendayle Date: Wed, 5 Oct 2022 20:50:10 +0200 Subject: deepdanbooru interrogator --- ... your deepbooru release project folder here.txt | 0 modules/deepbooru.py | 60 ++++++++++++++++++++++ modules/ui.py | 24 +++++++-- requirements.txt | 3 ++ requirements_versions.txt | 3 ++ style.css | 7 ++- 6 files changed, 91 insertions(+), 6 deletions(-) create mode 100644 models/deepbooru/Put your deepbooru release project folder here.txt create mode 100644 modules/deepbooru.py (limited to 'modules/ui.py') diff --git a/models/deepbooru/Put your deepbooru release project folder here.txt b/models/deepbooru/Put your deepbooru release project folder here.txt new file mode 100644 index 00000000..e69de29b diff --git a/modules/deepbooru.py b/modules/deepbooru.py new file mode 100644 index 00000000..958b1c3d --- /dev/null +++ b/modules/deepbooru.py @@ -0,0 +1,60 @@ +import os.path +from concurrent.futures import ProcessPoolExecutor + +import numpy as np +import deepdanbooru as dd +import tensorflow as tf + + +def _load_tf_and_return_tags(pil_image, threshold): + this_folder = os.path.dirname(__file__) + model_path = os.path.join(this_folder, '..', 'models', 'deepbooru', 'deepdanbooru-v3-20211112-sgd-e28') + if not os.path.exists(model_path): + return "Download https://github.com/KichangKim/DeepDanbooru/releases/download/v3-20211112-sgd-e28/deepdanbooru-v3-20211112-sgd-e28.zip unpack and put into models/deepbooru" + + tags = dd.project.load_tags_from_project(model_path) + model = dd.project.load_model_from_project( + model_path, compile_model=True + ) + + width = model.input_shape[2] + height = model.input_shape[1] + image = np.array(pil_image) + image = tf.image.resize( + image, + size=(height, width), + method=tf.image.ResizeMethod.AREA, + preserve_aspect_ratio=True, + ) + image = image.numpy() # EagerTensor to np.array + image = dd.image.transform_and_pad_image(image, width, height) + image = image / 255.0 + image_shape = image.shape + image = image.reshape((1, image_shape[0], image_shape[1], image_shape[2])) + + y = model.predict(image)[0] + + result_dict = {} + + for i, tag in enumerate(tags): + result_dict[tag] = y[i] + + + + result_tags_out = [] + result_tags_print = [] + for tag in tags: + if result_dict[tag] >= threshold: + result_tags_out.append(tag) + result_tags_print.append(f'{result_dict[tag]} {tag}') + + print('\n'.join(sorted(result_tags_print, reverse=True))) + + return ', '.join(result_tags_out) + + +def get_deepbooru_tags(pil_image, threshold=0.5): + with ProcessPoolExecutor() as executor: + f = executor.submit(_load_tf_and_return_tags, pil_image, threshold) + ret = f.result() # will rethrow any exceptions + return ret \ No newline at end of file diff --git a/modules/ui.py b/modules/ui.py index 20dc8c37..ae98219a 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -23,6 +23,7 @@ import gradio.utils import gradio.routes from modules import sd_hijack +from modules.deepbooru import get_deepbooru_tags from modules.paths import script_path from modules.shared import opts, cmd_opts import modules.shared as shared @@ -312,6 +313,11 @@ def interrogate(image): return gr_show(True) if prompt is None else prompt +def interrogate_deepbooru(image): + prompt = get_deepbooru_tags(image) + return gr_show(True) if prompt is None else prompt + + def create_seed_inputs(): with gr.Row(): with gr.Box(): @@ -439,15 +445,17 @@ def create_toprow(is_img2img): outputs=[], ) - with gr.Row(): + with gr.Row(scale=1): if is_img2img: - interrogate = gr.Button('Interrogate', elem_id="interrogate") + interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate") + deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru") else: interrogate = None + deepbooru = None prompt_style_apply = gr.Button('Apply style', elem_id="style_apply") save_style = gr.Button('Create style', elem_id="style_create") - return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, interrogate, prompt_style_apply, save_style, paste, token_counter, token_button + return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, interrogate, deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button def setup_progressbar(progressbar, preview, id_part, textinfo=None): @@ -476,7 +484,7 @@ def create_ui(wrap_gradio_gpu_call): import modules.txt2img with gr.Blocks(analytics_enabled=False) as txt2img_interface: - txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, txt2img_prompt_style_apply, txt2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=False) + txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=False) dummy_component = gr.Label(visible=False) with gr.Row(elem_id='txt2img_progress_row'): @@ -628,7 +636,7 @@ def create_ui(wrap_gradio_gpu_call): token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter]) with gr.Blocks(analytics_enabled=False) as img2img_interface: - img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True) + img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True) with gr.Row(elem_id='img2img_progress_row'): with gr.Column(scale=1): @@ -785,6 +793,12 @@ def create_ui(wrap_gradio_gpu_call): outputs=[img2img_prompt], ) + img2img_deepbooru.click( + fn=interrogate_deepbooru, + inputs=[init_img], + outputs=[img2img_prompt], + ) + save.click( fn=wrap_gradio_call(save_files), _js="(x, y, z) => [x, y, selected_gallery_index()]", diff --git a/requirements.txt b/requirements.txt index 631fe616..cab101f8 100644 --- a/requirements.txt +++ b/requirements.txt @@ -23,3 +23,6 @@ resize-right torchdiffeq kornia lark +deepdanbooru +tensorflow +tensorflow-io diff --git a/requirements_versions.txt b/requirements_versions.txt index fdff2687..811953c6 100644 --- a/requirements_versions.txt +++ b/requirements_versions.txt @@ -22,3 +22,6 @@ resize-right==0.0.2 torchdiffeq==0.2.3 kornia==0.6.7 lark==1.1.2 +git+https://github.com/KichangKim/DeepDanbooru.git@edf73df4cdaeea2cf00e9ac08bd8a9026b7a7b26#egg=deepdanbooru[tensorflow] +tensorflow==2.10.0 +tensorflow-io==0.27.0 diff --git a/style.css b/style.css index 39586bf1..2fd351f9 100644 --- a/style.css +++ b/style.css @@ -103,7 +103,12 @@ #style_apply, #style_create, #interrogate{ margin: 0.75em 0.25em 0.25em 0.25em; - min-width: 3em; + min-width: 5em; +} + +#style_apply, #style_create, #deepbooru{ + margin: 0.75em 0.25em 0.25em 0.25em; + min-width: 5em; } #style_pos_col, #style_neg_col{ -- cgit v1.2.3 From c26732fbee2a57e621ac22bf70decf7496daa4cd Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 5 Oct 2022 23:16:27 +0300 Subject: added support for AND from https://energy-based-model.github.io/Compositional-Visual-Generation-with-Composable-Diffusion-Models/ --- modules/processing.py | 2 +- modules/prompt_parser.py | 114 ++++++++++++++++++++++++++++++++++++++++++++--- modules/sd_samplers.py | 35 ++++++++++----- modules/ui.py | 6 ++- 4 files changed, 138 insertions(+), 19 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/processing.py b/modules/processing.py index bb94033b..d8c6b8d5 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -360,7 +360,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed: #c = p.sd_model.get_learned_conditioning(prompts) with devices.autocast(): uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], p.steps) - c = prompt_parser.get_learned_conditioning(shared.sd_model, prompts, p.steps) + c = prompt_parser.get_multicond_learned_conditioning(shared.sd_model, prompts, p.steps) if len(model_hijack.comments) > 0: for comment in model_hijack.comments: diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py index a3b12421..f7420daf 100644 --- a/modules/prompt_parser.py +++ b/modules/prompt_parser.py @@ -97,10 +97,26 @@ def get_learned_conditioning_prompt_schedules(prompts, steps): ScheduledPromptConditioning = namedtuple("ScheduledPromptConditioning", ["end_at_step", "cond"]) -ScheduledPromptBatch = namedtuple("ScheduledPromptBatch", ["shape", "schedules"]) def get_learned_conditioning(model, prompts, steps): + """converts a list of prompts into a list of prompt schedules - each schedule is a list of ScheduledPromptConditioning, specifying the comdition (cond), + and the sampling step at which this condition is to be replaced by the next one. + + Input: + (model, ['a red crown', 'a [blue:green:5] jeweled crown'], 20) + + Output: + [ + [ + ScheduledPromptConditioning(end_at_step=20, cond=tensor([[-0.3886, 0.0229, -0.0523, ..., -0.4901, -0.3066, 0.0674], ..., [ 0.3317, -0.5102, -0.4066, ..., 0.4119, -0.7647, -1.0160]], device='cuda:0')) + ], + [ + ScheduledPromptConditioning(end_at_step=5, cond=tensor([[-0.3886, 0.0229, -0.0522, ..., -0.4901, -0.3067, 0.0673], ..., [-0.0192, 0.3867, -0.4644, ..., 0.1135, -0.3696, -0.4625]], device='cuda:0')), + ScheduledPromptConditioning(end_at_step=20, cond=tensor([[-0.3886, 0.0229, -0.0522, ..., -0.4901, -0.3067, 0.0673], ..., [-0.7352, -0.4356, -0.7888, ..., 0.6994, -0.4312, -1.2593]], device='cuda:0')) + ] + ] + """ res = [] prompt_schedules = get_learned_conditioning_prompt_schedules(prompts, steps) @@ -123,13 +139,75 @@ def get_learned_conditioning(model, prompts, steps): cache[prompt] = cond_schedule res.append(cond_schedule) - return ScheduledPromptBatch((len(prompts),) + res[0][0].cond.shape, res) + return res + + +re_AND = re.compile(r"\bAND\b") +re_weight = re.compile(r"^(.*?)(?:\s*:\s*([-+]?\s*(?:\d+|\d*\.\d+)?))?\s*$") + + +def get_multicond_prompt_list(prompts): + res_indexes = [] + + prompt_flat_list = [] + prompt_indexes = {} + + for prompt in prompts: + subprompts = re_AND.split(prompt) + + indexes = [] + for subprompt in subprompts: + text, weight = re_weight.search(subprompt).groups() + + weight = float(weight) if weight is not None else 1.0 + + index = prompt_indexes.get(text, None) + if index is None: + index = len(prompt_flat_list) + prompt_flat_list.append(text) + prompt_indexes[text] = index + + indexes.append((index, weight)) + + res_indexes.append(indexes) + + return res_indexes, prompt_flat_list, prompt_indexes + + +class ComposableScheduledPromptConditioning: + def __init__(self, schedules, weight=1.0): + self.schedules: list[ScheduledPromptConditioning] = schedules + self.weight: float = weight + + +class MulticondLearnedConditioning: + def __init__(self, shape, batch): + self.shape: tuple = shape # the shape field is needed to send this object to DDIM/PLMS + self.batch: list[list[ComposableScheduledPromptConditioning]] = batch -def reconstruct_cond_batch(c: ScheduledPromptBatch, current_step): - param = c.schedules[0][0].cond - res = torch.zeros(c.shape, device=param.device, dtype=param.dtype) - for i, cond_schedule in enumerate(c.schedules): +def get_multicond_learned_conditioning(model, prompts, steps) -> MulticondLearnedConditioning: + """same as get_learned_conditioning, but returns a list of ScheduledPromptConditioning along with the weight objects for each prompt. + For each prompt, the list is obtained by splitting the prompt using the AND separator. + + https://energy-based-model.github.io/Compositional-Visual-Generation-with-Composable-Diffusion-Models/ + """ + + res_indexes, prompt_flat_list, prompt_indexes = get_multicond_prompt_list(prompts) + + learned_conditioning = get_learned_conditioning(model, prompt_flat_list, steps) + + res = [] + for indexes in res_indexes: + res.append([ComposableScheduledPromptConditioning(learned_conditioning[i], weight) for i, weight in indexes]) + + return MulticondLearnedConditioning(shape=(len(prompts),), batch=res) + + +def reconstruct_cond_batch(c: list[list[ScheduledPromptConditioning]], current_step): + param = c[0][0].cond + res = torch.zeros((len(c),) + param.shape, device=param.device, dtype=param.dtype) + for i, cond_schedule in enumerate(c): target_index = 0 for current, (end_at, cond) in enumerate(cond_schedule): if current_step <= end_at: @@ -140,6 +218,30 @@ def reconstruct_cond_batch(c: ScheduledPromptBatch, current_step): return res +def reconstruct_multicond_batch(c: MulticondLearnedConditioning, current_step): + param = c.batch[0][0].schedules[0].cond + + tensors = [] + conds_list = [] + + for batch_no, composable_prompts in enumerate(c.batch): + conds_for_batch = [] + + for cond_index, composable_prompt in enumerate(composable_prompts): + target_index = 0 + for current, (end_at, cond) in enumerate(composable_prompt.schedules): + if current_step <= end_at: + target_index = current + break + + conds_for_batch.append((len(tensors), composable_prompt.weight)) + tensors.append(composable_prompt.schedules[target_index].cond) + + conds_list.append(conds_for_batch) + + return conds_list, torch.stack(tensors).to(device=param.device, dtype=param.dtype) + + re_attention = re.compile(r""" \\\(| \\\)| diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index dbf570d2..d27c547b 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -109,9 +109,12 @@ class VanillaStableDiffusionSampler: return 0 def p_sample_ddim_hook(self, x_dec, cond, ts, unconditional_conditioning, *args, **kwargs): - cond = prompt_parser.reconstruct_cond_batch(cond, self.step) + conds_list, tensor = prompt_parser.reconstruct_multicond_batch(cond, self.step) unconditional_conditioning = prompt_parser.reconstruct_cond_batch(unconditional_conditioning, self.step) + assert all([len(conds) == 1 for conds in conds_list]), 'composition via AND is not supported for DDIM/PLMS samplers' + cond = tensor + if self.mask is not None: img_orig = self.sampler.model.q_sample(self.init_latent, ts) x_dec = img_orig * self.mask + self.nmask * x_dec @@ -183,19 +186,31 @@ class CFGDenoiser(torch.nn.Module): self.step = 0 def forward(self, x, sigma, uncond, cond, cond_scale): - cond = prompt_parser.reconstruct_cond_batch(cond, self.step) + conds_list, tensor = prompt_parser.reconstruct_multicond_batch(cond, self.step) uncond = prompt_parser.reconstruct_cond_batch(uncond, self.step) + batch_size = len(conds_list) + repeats = [len(conds_list[i]) for i in range(batch_size)] + + x_in = torch.cat([torch.stack([x[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [x]) + sigma_in = torch.cat([torch.stack([sigma[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [sigma]) + cond_in = torch.cat([tensor, uncond]) + if shared.batch_cond_uncond: - x_in = torch.cat([x] * 2) - sigma_in = torch.cat([sigma] * 2) - cond_in = torch.cat([uncond, cond]) - uncond, cond = self.inner_model(x_in, sigma_in, cond=cond_in).chunk(2) - denoised = uncond + (cond - uncond) * cond_scale + x_out = self.inner_model(x_in, sigma_in, cond=cond_in) else: - uncond = self.inner_model(x, sigma, cond=uncond) - cond = self.inner_model(x, sigma, cond=cond) - denoised = uncond + (cond - uncond) * cond_scale + x_out = torch.zeros_like(x_in) + for batch_offset in range(0, x_out.shape[0], batch_size): + a = batch_offset + b = a + batch_size + x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=cond_in[a:b]) + + denoised_uncond = x_out[-batch_size:] + denoised = torch.clone(denoised_uncond) + + for i, conds in enumerate(conds_list): + for cond_index, weight in conds: + denoised[i] += (x_out[cond_index] - denoised_uncond[i]) * (weight * cond_scale) if self.mask is not None: denoised = self.init_latent * self.mask + self.nmask * denoised diff --git a/modules/ui.py b/modules/ui.py index 523ab25b..9620350f 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -34,7 +34,7 @@ import modules.gfpgan_model import modules.codeformer_model import modules.styles import modules.generation_parameters_copypaste -from modules.prompt_parser import get_learned_conditioning_prompt_schedules +from modules import prompt_parser from modules.images import apply_filename_pattern, get_next_sequence_number import modules.textual_inversion.ui @@ -394,7 +394,9 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: def update_token_counter(text, steps): try: - prompt_schedules = get_learned_conditioning_prompt_schedules([text], steps) + _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text]) + prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps) + except Exception: # a parsing error can happen here during typing, and we don't want to bother the user with # messages related to it in console -- cgit v1.2.3 From 0bb458f0ca06a7be27cf1a1003c536d1f06a5bd3 Mon Sep 17 00:00:00 2001 From: Milly Date: Wed, 5 Oct 2022 01:19:50 +0900 Subject: Removed duplicate image saving codes Use `modules.images.save_image()` instead. --- modules/images.py | 7 ++++--- modules/ui.py | 46 ++++++++++------------------------------------ 2 files changed, 14 insertions(+), 39 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/images.py b/modules/images.py index c2fadab9..810f1446 100644 --- a/modules/images.py +++ b/modules/images.py @@ -353,7 +353,7 @@ def get_next_sequence_number(path, basename): return result + 1 -def save_image(image, path, basename, seed=None, prompt=None, extension='png', info=None, short_filename=False, no_prompt=False, grid=False, pnginfo_section_name='parameters', p=None, existing_info=None, forced_filename=None, suffix=""): +def save_image(image, path, basename, seed=None, prompt=None, extension='png', info=None, short_filename=False, no_prompt=False, grid=False, pnginfo_section_name='parameters', p=None, existing_info=None, forced_filename=None, suffix="", save_to_dirs=None): if short_filename or prompt is None or seed is None: file_decoration = "" elif opts.save_to_dirs: @@ -377,7 +377,8 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i else: pnginfo = None - save_to_dirs = (grid and opts.grid_save_to_dirs) or (not grid and opts.save_to_dirs and not no_prompt) + if save_to_dirs is None: + save_to_dirs = (grid and opts.grid_save_to_dirs) or (not grid and opts.save_to_dirs and not no_prompt) if save_to_dirs: dirname = apply_filename_pattern(opts.directories_filename_pattern or "[prompt_words]", p, seed, prompt).strip('\\ /') @@ -431,4 +432,4 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i with open(f"{fullfn_without_extension}.txt", "w", encoding="utf8") as file: file.write(info + "\n") - + return fullfn diff --git a/modules/ui.py b/modules/ui.py index 9620350f..4f18126f 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -35,7 +35,7 @@ import modules.codeformer_model import modules.styles import modules.generation_parameters_copypaste from modules import prompt_parser -from modules.images import apply_filename_pattern, get_next_sequence_number +from modules.images import save_image import modules.textual_inversion.ui # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI @@ -114,20 +114,13 @@ def save_files(js_data, images, index): p = MyObject(data) path = opts.outdir_save save_to_dirs = opts.use_save_to_dirs_for_ui - - if save_to_dirs: - dirname = apply_filename_pattern(opts.directories_filename_pattern or "[prompt_words]", p, p.seed, p.prompt) - path = os.path.join(opts.outdir_save, dirname) - - os.makedirs(path, exist_ok=True) - + extension: str = opts.samples_format + start_index = 0 if index > -1 and opts.save_selected_only and (index >= data["index_of_first_image"]): # ensures we are looking at a specific non-grid picture, and we have save_selected_only images = [images[index]] - infotexts = [data["infotexts"][index]] - else: - infotexts = data["infotexts"] + start_index = index with open(os.path.join(opts.outdir_save, "log.csv"), "a", encoding="utf8", newline='') as file: at_start = file.tell() == 0 @@ -135,37 +128,18 @@ def save_files(js_data, images, index): if at_start: writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"]) - file_decoration = opts.samples_filename_pattern or "[seed]-[prompt_spaces]" - if file_decoration != "": - file_decoration = "-" + file_decoration.lower() - file_decoration = apply_filename_pattern(file_decoration, p, p.seed, p.prompt) - truncated = (file_decoration[:240] + '..') if len(file_decoration) > 240 else file_decoration - filename_base = truncated - extension = opts.samples_format.lower() - - basecount = get_next_sequence_number(path, "") - for i, filedata in enumerate(images): - file_number = f"{basecount+i:05}" - filename = file_number + filename_base + f".{extension}" - filepath = os.path.join(path, filename) - - + for image_index, filedata in enumerate(images, start_index): if filedata.startswith("data:image/png;base64,"): filedata = filedata[len("data:image/png;base64,"):] image = Image.open(io.BytesIO(base64.decodebytes(filedata.encode('utf-8')))) - if opts.enable_pnginfo and extension == 'png': - pnginfo = PngImagePlugin.PngInfo() - pnginfo.add_text('parameters', infotexts[i]) - image.save(filepath, pnginfo=pnginfo) - else: - image.save(filepath, quality=opts.jpeg_quality) - if opts.enable_pnginfo and extension in ("jpg", "jpeg", "webp"): - piexif.insert(piexif.dump({"Exif": { - piexif.ExifIFD.UserComment: piexif.helper.UserComment.dump(infotexts[i], encoding="unicode") - }}), filepath) + is_grid = image_index < p.index_of_first_image + i = 0 if is_grid else (image_index - p.index_of_first_image) + + fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs) + filename = os.path.relpath(fullfn, path) filenames.append(filename) writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]]) -- cgit v1.2.3 From 12c4d5c6b5bf9dd50d0601c36af4f99b65316d58 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 7 Oct 2022 23:22:22 +0300 Subject: hypernetwork training mk1 --- modules/hypernetwork.py | 88 --------- modules/hypernetwork/hypernetwork.py | 267 +++++++++++++++++++++++++++ modules/hypernetwork/ui.py | 43 +++++ modules/sd_hijack.py | 4 +- modules/sd_hijack_optimizations.py | 3 +- modules/shared.py | 13 +- modules/textual_inversion/ui.py | 1 - modules/ui.py | 58 +++++- scripts/xy_grid.py | 7 +- textual_inversion_templates/hypernetwork.txt | 27 +++ textual_inversion_templates/none.txt | 1 + webui.py | 9 + 12 files changed, 414 insertions(+), 107 deletions(-) delete mode 100644 modules/hypernetwork.py create mode 100644 modules/hypernetwork/hypernetwork.py create mode 100644 modules/hypernetwork/ui.py create mode 100644 textual_inversion_templates/hypernetwork.txt create mode 100644 textual_inversion_templates/none.txt (limited to 'modules/ui.py') diff --git a/modules/hypernetwork.py b/modules/hypernetwork.py deleted file mode 100644 index c7b86682..00000000 --- a/modules/hypernetwork.py +++ /dev/null @@ -1,88 +0,0 @@ -import glob -import os -import sys -import traceback - -import torch - -from ldm.util import default -from modules import devices, shared -import torch -from torch import einsum -from einops import rearrange, repeat - - -class HypernetworkModule(torch.nn.Module): - def __init__(self, dim, state_dict): - super().__init__() - - self.linear1 = torch.nn.Linear(dim, dim * 2) - self.linear2 = torch.nn.Linear(dim * 2, dim) - - self.load_state_dict(state_dict, strict=True) - self.to(devices.device) - - def forward(self, x): - return x + (self.linear2(self.linear1(x))) - - -class Hypernetwork: - filename = None - name = None - - def __init__(self, filename): - self.filename = filename - self.name = os.path.splitext(os.path.basename(filename))[0] - self.layers = {} - - state_dict = torch.load(filename, map_location='cpu') - for size, sd in state_dict.items(): - self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1])) - - -def load_hypernetworks(path): - res = {} - - for filename in glob.iglob(path + '**/*.pt', recursive=True): - try: - hn = Hypernetwork(filename) - res[hn.name] = hn - except Exception: - print(f"Error loading hypernetwork {filename}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) - - return res - - -def attention_CrossAttention_forward(self, x, context=None, mask=None): - h = self.heads - - q = self.to_q(x) - context = default(context, x) - - hypernetwork = shared.selected_hypernetwork() - hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None) - - if hypernetwork_layers is not None: - k = self.to_k(hypernetwork_layers[0](context)) - v = self.to_v(hypernetwork_layers[1](context)) - else: - k = self.to_k(context) - v = self.to_v(context) - - q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v)) - - sim = einsum('b i d, b j d -> b i j', q, k) * self.scale - - if mask is not None: - mask = rearrange(mask, 'b ... -> b (...)') - max_neg_value = -torch.finfo(sim.dtype).max - mask = repeat(mask, 'b j -> (b h) () j', h=h) - sim.masked_fill_(~mask, max_neg_value) - - # attention, what we cannot get enough of - attn = sim.softmax(dim=-1) - - out = einsum('b i j, b j d -> b i d', attn, v) - out = rearrange(out, '(b h) n d -> b n (h d)', h=h) - return self.to_out(out) diff --git a/modules/hypernetwork/hypernetwork.py b/modules/hypernetwork/hypernetwork.py new file mode 100644 index 00000000..a3d6a47e --- /dev/null +++ b/modules/hypernetwork/hypernetwork.py @@ -0,0 +1,267 @@ +import datetime +import glob +import html +import os +import sys +import traceback +import tqdm + +import torch + +from ldm.util import default +from modules import devices, shared, processing, sd_models +import torch +from torch import einsum +from einops import rearrange, repeat +import modules.textual_inversion.dataset + + +class HypernetworkModule(torch.nn.Module): + def __init__(self, dim, state_dict=None): + super().__init__() + + self.linear1 = torch.nn.Linear(dim, dim * 2) + self.linear2 = torch.nn.Linear(dim * 2, dim) + + if state_dict is not None: + self.load_state_dict(state_dict, strict=True) + else: + self.linear1.weight.data.fill_(0.0001) + self.linear1.bias.data.fill_(0.0001) + self.linear2.weight.data.fill_(0.0001) + self.linear2.bias.data.fill_(0.0001) + + self.to(devices.device) + + def forward(self, x): + return x + (self.linear2(self.linear1(x))) + + +class Hypernetwork: + filename = None + name = None + + def __init__(self, name=None): + self.filename = None + self.name = name + self.layers = {} + self.step = 0 + self.sd_checkpoint = None + self.sd_checkpoint_name = None + + for size in [320, 640, 768, 1280]: + self.layers[size] = (HypernetworkModule(size), HypernetworkModule(size)) + + def weights(self): + res = [] + + for k, layers in self.layers.items(): + for layer in layers: + layer.train() + res += [layer.linear1.weight, layer.linear1.bias, layer.linear2.weight, layer.linear2.bias] + + return res + + def save(self, filename): + state_dict = {} + + for k, v in self.layers.items(): + state_dict[k] = (v[0].state_dict(), v[1].state_dict()) + + state_dict['step'] = self.step + state_dict['name'] = self.name + state_dict['sd_checkpoint'] = self.sd_checkpoint + state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name + + torch.save(state_dict, filename) + + def load(self, filename): + self.filename = filename + if self.name is None: + self.name = os.path.splitext(os.path.basename(filename))[0] + + state_dict = torch.load(filename, map_location='cpu') + + for size, sd in state_dict.items(): + if type(size) == int: + self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1])) + + self.name = state_dict.get('name', self.name) + self.step = state_dict.get('step', 0) + self.sd_checkpoint = state_dict.get('sd_checkpoint', None) + self.sd_checkpoint_name = state_dict.get('sd_checkpoint_name', None) + + +def load_hypernetworks(path): + res = {} + + for filename in glob.iglob(path + '**/*.pt', recursive=True): + try: + hn = Hypernetwork() + hn.load(filename) + res[hn.name] = hn + except Exception: + print(f"Error loading hypernetwork {filename}", file=sys.stderr) + print(traceback.format_exc(), file=sys.stderr) + + return res + + +def attention_CrossAttention_forward(self, x, context=None, mask=None): + h = self.heads + + q = self.to_q(x) + context = default(context, x) + + hypernetwork_layers = (shared.hypernetwork.layers if shared.hypernetwork is not None else {}).get(context.shape[2], None) + + if hypernetwork_layers is not None: + hypernetwork_k, hypernetwork_v = hypernetwork_layers + + self.hypernetwork_k = hypernetwork_k + self.hypernetwork_v = hypernetwork_v + + context_k = hypernetwork_k(context) + context_v = hypernetwork_v(context) + else: + context_k = context + context_v = context + + k = self.to_k(context_k) + v = self.to_v(context_v) + + q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v)) + + sim = einsum('b i d, b j d -> b i j', q, k) * self.scale + + if mask is not None: + mask = rearrange(mask, 'b ... -> b (...)') + max_neg_value = -torch.finfo(sim.dtype).max + mask = repeat(mask, 'b j -> (b h) () j', h=h) + sim.masked_fill_(~mask, max_neg_value) + + # attention, what we cannot get enough of + attn = sim.softmax(dim=-1) + + out = einsum('b i j, b j d -> b i d', attn, v) + out = rearrange(out, '(b h) n d -> b n (h d)', h=h) + return self.to_out(out) + + +def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt): + assert hypernetwork_name, 'embedding not selected' + + shared.hypernetwork = shared.hypernetworks[hypernetwork_name] + + shared.state.textinfo = "Initializing hypernetwork training..." + shared.state.job_count = steps + + filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt') + + log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%m-%d"), hypernetwork_name) + + if save_hypernetwork_every > 0: + hypernetwork_dir = os.path.join(log_directory, "hypernetworks") + os.makedirs(hypernetwork_dir, exist_ok=True) + else: + hypernetwork_dir = None + + if create_image_every > 0: + images_dir = os.path.join(log_directory, "images") + os.makedirs(images_dir, exist_ok=True) + else: + images_dir = None + + cond_model = shared.sd_model.cond_stage_model + + shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..." + with torch.autocast("cuda"): + ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=512, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file) + + hypernetwork = shared.hypernetworks[hypernetwork_name] + weights = hypernetwork.weights() + for weight in weights: + weight.requires_grad = True + + optimizer = torch.optim.AdamW(weights, lr=learn_rate) + + losses = torch.zeros((32,)) + + last_saved_file = "" + last_saved_image = "" + + ititial_step = hypernetwork.step or 0 + if ititial_step > steps: + return hypernetwork, filename + + pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step) + for i, (x, text) in pbar: + hypernetwork.step = i + ititial_step + + if hypernetwork.step > steps: + break + + if shared.state.interrupted: + break + + with torch.autocast("cuda"): + c = cond_model([text]) + + x = x.to(devices.device) + loss = shared.sd_model(x.unsqueeze(0), c)[0] + del x + + losses[hypernetwork.step % losses.shape[0]] = loss.item() + + optimizer.zero_grad() + loss.backward() + optimizer.step() + + pbar.set_description(f"loss: {losses.mean():.7f}") + + if hypernetwork.step > 0 and hypernetwork_dir is not None and hypernetwork.step % save_hypernetwork_every == 0: + last_saved_file = os.path.join(hypernetwork_dir, f'{hypernetwork_name}-{hypernetwork.step}.pt') + hypernetwork.save(last_saved_file) + + if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0: + last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png') + + preview_text = text if preview_image_prompt == "" else preview_image_prompt + + p = processing.StableDiffusionProcessingTxt2Img( + sd_model=shared.sd_model, + prompt=preview_text, + steps=20, + do_not_save_grid=True, + do_not_save_samples=True, + ) + + processed = processing.process_images(p) + image = processed.images[0] + + shared.state.current_image = image + image.save(last_saved_image) + + last_saved_image += f", prompt: {preview_text}" + + shared.state.job_no = hypernetwork.step + + shared.state.textinfo = f""" +

+Loss: {losses.mean():.7f}
+Step: {hypernetwork.step}
+Last prompt: {html.escape(text)}
+Last saved embedding: {html.escape(last_saved_file)}
+Last saved image: {html.escape(last_saved_image)}
+

+""" + + checkpoint = sd_models.select_checkpoint() + + hypernetwork.sd_checkpoint = checkpoint.hash + hypernetwork.sd_checkpoint_name = checkpoint.model_name + hypernetwork.save(filename) + + return hypernetwork, filename + + diff --git a/modules/hypernetwork/ui.py b/modules/hypernetwork/ui.py new file mode 100644 index 00000000..525f978c --- /dev/null +++ b/modules/hypernetwork/ui.py @@ -0,0 +1,43 @@ +import html +import os + +import gradio as gr + +import modules.textual_inversion.textual_inversion +import modules.textual_inversion.preprocess +from modules import sd_hijack, shared + + +def create_hypernetwork(name): + fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt") + assert not os.path.exists(fn), f"file {fn} already exists" + + hypernetwork = modules.hypernetwork.hypernetwork.Hypernetwork(name=name) + hypernetwork.save(fn) + + shared.reload_hypernetworks() + shared.hypernetwork = shared.hypernetworks.get(shared.opts.sd_hypernetwork, None) + + return gr.Dropdown.update(choices=sorted([x for x in shared.hypernetworks.keys()])), f"Created: {fn}", "" + + +def train_hypernetwork(*args): + + initial_hypernetwork = shared.hypernetwork + + try: + sd_hijack.undo_optimizations() + + hypernetwork, filename = modules.hypernetwork.hypernetwork.train_hypernetwork(*args) + + res = f""" +Training {'interrupted' if shared.state.interrupted else 'finished'} at {hypernetwork.step} steps. +Hypernetwork saved to {html.escape(filename)} +""" + return res, "" + except Exception: + raise + finally: + shared.hypernetwork = initial_hypernetwork + sd_hijack.apply_optimizations() + diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index d68f89cc..ec8c9d4b 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -8,7 +8,7 @@ from torch import einsum from torch.nn.functional import silu import modules.textual_inversion.textual_inversion -from modules import prompt_parser, devices, sd_hijack_optimizations, shared, hypernetwork +from modules import prompt_parser, devices, sd_hijack_optimizations, shared from modules.shared import opts, device, cmd_opts import ldm.modules.attention @@ -32,6 +32,8 @@ def apply_optimizations(): def undo_optimizations(): + from modules.hypernetwork import hypernetwork + ldm.modules.attention.CrossAttention.forward = hypernetwork.attention_CrossAttention_forward ldm.modules.diffusionmodules.model.nonlinearity = diffusionmodules_model_nonlinearity ldm.modules.diffusionmodules.model.AttnBlock.forward = diffusionmodules_model_AttnBlock_forward diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py index d9cca485..3f32e020 100644 --- a/modules/sd_hijack_optimizations.py +++ b/modules/sd_hijack_optimizations.py @@ -45,8 +45,7 @@ def split_cross_attention_forward(self, x, context=None, mask=None): q_in = self.to_q(x) context = default(context, x) - hypernetwork = shared.selected_hypernetwork() - hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None) + hypernetwork_layers = (shared.hypernetwork.layers if shared.hypernetwork is not None else {}).get(context.shape[2], None) if hypernetwork_layers is not None: k_in = self.to_k(hypernetwork_layers[0](context)) diff --git a/modules/shared.py b/modules/shared.py index 879d8424..c5a893e8 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -13,7 +13,7 @@ import modules.memmon import modules.sd_models import modules.styles import modules.devices as devices -from modules import sd_samplers, hypernetwork +from modules import sd_samplers from modules.paths import models_path, script_path, sd_path sd_model_file = os.path.join(script_path, 'model.ckpt') @@ -28,6 +28,7 @@ parser.add_argument("--no-half", action='store_true', help="do not switch the mo parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)") parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI") parser.add_argument("--embeddings-dir", type=str, default=os.path.join(script_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)") +parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory") parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui") parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage") parser.add_argument("--lowvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a lot of speed for very low VRM usage") @@ -76,11 +77,15 @@ parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram config_filename = cmd_opts.ui_settings_file -hypernetworks = hypernetwork.load_hypernetworks(os.path.join(models_path, 'hypernetworks')) +def reload_hypernetworks(): + from modules.hypernetwork import hypernetwork + hypernetworks.clear() + hypernetworks.update(hypernetwork.load_hypernetworks(cmd_opts.hypernetwork_dir)) -def selected_hypernetwork(): - return hypernetworks.get(opts.sd_hypernetwork, None) + +hypernetworks = {} +hypernetwork = None class State: diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py index f19ac5e0..c57de1f9 100644 --- a/modules/textual_inversion/ui.py +++ b/modules/textual_inversion/ui.py @@ -22,7 +22,6 @@ def preprocess(*args): def train_embedding(*args): - try: sd_hijack.undo_optimizations() diff --git a/modules/ui.py b/modules/ui.py index 4f18126f..051908c1 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -37,6 +37,7 @@ import modules.generation_parameters_copypaste from modules import prompt_parser from modules.images import save_image import modules.textual_inversion.ui +import modules.hypernetwork.ui # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI mimetypes.init() @@ -965,6 +966,18 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column(): create_embedding = gr.Button(value="Create", variant='primary') + with gr.Group(): + gr.HTML(value="

Create a new hypernetwork

") + + new_hypernetwork_name = gr.Textbox(label="Name") + + with gr.Row(): + with gr.Column(scale=3): + gr.HTML(value="") + + with gr.Column(): + create_hypernetwork = gr.Button(value="Create", variant='primary') + with gr.Group(): gr.HTML(value="

Preprocess images

") @@ -986,6 +999,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Group(): gr.HTML(value="

Train an embedding; must specify a directory with a set of 512x512 images

") train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) + train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()]) learn_rate = gr.Number(label='Learning rate', value=5.0e-03) dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images") log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion") @@ -993,15 +1007,12 @@ def create_ui(wrap_gradio_gpu_call): steps = gr.Number(label='Max steps', value=100000, precision=0) create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0) save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0) + preview_image_prompt = gr.Textbox(label='Preview prompt', value="") with gr.Row(): - with gr.Column(scale=2): - gr.HTML(value="") - - with gr.Column(): - with gr.Row(): - interrupt_training = gr.Button(value="Interrupt") - train_embedding = gr.Button(value="Train", variant='primary') + interrupt_training = gr.Button(value="Interrupt") + train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary') + train_embedding = gr.Button(value="Train Embedding", variant='primary') with gr.Column(): progressbar = gr.HTML(elem_id="ti_progressbar") @@ -1027,6 +1038,18 @@ def create_ui(wrap_gradio_gpu_call): ] ) + create_hypernetwork.click( + fn=modules.hypernetwork.ui.create_hypernetwork, + inputs=[ + new_hypernetwork_name, + ], + outputs=[ + train_hypernetwork_name, + ti_output, + ti_outcome, + ] + ) + run_preprocess.click( fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), _js="start_training_textual_inversion", @@ -1062,12 +1085,33 @@ def create_ui(wrap_gradio_gpu_call): ] ) + train_hypernetwork.click( + fn=wrap_gradio_gpu_call(modules.hypernetwork.ui.train_hypernetwork, extra_outputs=[gr.update()]), + _js="start_training_textual_inversion", + inputs=[ + train_hypernetwork_name, + learn_rate, + dataset_directory, + log_directory, + steps, + create_image_every, + save_embedding_every, + template_file, + preview_image_prompt, + ], + outputs=[ + ti_output, + ti_outcome, + ] + ) + interrupt_training.click( fn=lambda: shared.state.interrupt(), inputs=[], outputs=[], ) + def create_setting_component(key): def fun(): return opts.data[key] if key in opts.data else opts.data_labels[key].default diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py index c0c364df..5b504de6 100644 --- a/scripts/xy_grid.py +++ b/scripts/xy_grid.py @@ -78,8 +78,7 @@ def apply_checkpoint(p, x, xs): def apply_hypernetwork(p, x, xs): - hn = shared.hypernetworks.get(x, None) - opts.data["sd_hypernetwork"] = hn.name if hn is not None else 'None' + shared.hypernetwork = shared.hypernetworks.get(x, None) def format_value_add_label(p, opt, x): @@ -199,7 +198,7 @@ class Script(scripts.Script): modules.processing.fix_seed(p) p.batch_size = 1 - initial_hn = opts.sd_hypernetwork + initial_hn = shared.hypernetwork def process_axis(opt, vals): if opt.label == 'Nothing': @@ -308,6 +307,6 @@ class Script(scripts.Script): # restore checkpoint in case it was changed by axes modules.sd_models.reload_model_weights(shared.sd_model) - opts.data["sd_hypernetwork"] = initial_hn + shared.hypernetwork = initial_hn return processed diff --git a/textual_inversion_templates/hypernetwork.txt b/textual_inversion_templates/hypernetwork.txt new file mode 100644 index 00000000..91e06890 --- /dev/null +++ b/textual_inversion_templates/hypernetwork.txt @@ -0,0 +1,27 @@ +a photo of a [filewords] +a rendering of a [filewords] +a cropped photo of the [filewords] +the photo of a [filewords] +a photo of a clean [filewords] +a photo of a dirty [filewords] +a dark photo of the [filewords] +a photo of my [filewords] +a photo of the cool [filewords] +a close-up photo of a [filewords] +a bright photo of the [filewords] +a cropped photo of a [filewords] +a photo of the [filewords] +a good photo of the [filewords] +a photo of one [filewords] +a close-up photo of the [filewords] +a rendition of the [filewords] +a photo of the clean [filewords] +a rendition of a [filewords] +a photo of a nice [filewords] +a good photo of a [filewords] +a photo of the nice [filewords] +a photo of the small [filewords] +a photo of the weird [filewords] +a photo of the large [filewords] +a photo of a cool [filewords] +a photo of a small [filewords] diff --git a/textual_inversion_templates/none.txt b/textual_inversion_templates/none.txt new file mode 100644 index 00000000..f77af461 --- /dev/null +++ b/textual_inversion_templates/none.txt @@ -0,0 +1 @@ +picture diff --git a/webui.py b/webui.py index 480360fe..60f9061f 100644 --- a/webui.py +++ b/webui.py @@ -74,6 +74,15 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs) +def set_hypernetwork(): + shared.hypernetwork = shared.hypernetworks.get(shared.opts.sd_hypernetwork, None) + + +shared.reload_hypernetworks() +shared.opts.onchange("sd_hypernetwork", set_hypernetwork) +set_hypernetwork() + + modules.scripts.load_scripts(os.path.join(script_path, "scripts")) shared.sd_model = modules.sd_models.load_model() -- cgit v1.2.3 From 786d9f63aaa4515df82eb2cf357ea92f3dae1e29 Mon Sep 17 00:00:00 2001 From: Trung Ngo Date: Tue, 4 Oct 2022 22:56:30 -0500 Subject: Add button to skip the current iteration --- javascript/hints.js | 1 + javascript/progressbar.js | 20 ++++++++++++++------ modules/img2img.py | 4 ++++ modules/processing.py | 4 ++++ modules/shared.py | 5 +++++ modules/ui.py | 8 ++++++++ style.css | 14 ++++++++++++-- webui.py | 1 + 8 files changed, 49 insertions(+), 8 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/hints.js b/javascript/hints.js index 8adcd983..8e352e94 100644 --- a/javascript/hints.js +++ b/javascript/hints.js @@ -35,6 +35,7 @@ titles = { "Denoising strength": "Determines how little respect the algorithm should have for image's content. At 0, nothing will change, and at 1 you'll get an unrelated image. With values below 1.0, processing will take less steps than the Sampling Steps slider specifies.", "Denoising strength change factor": "In loopback mode, on each loop the denoising strength is multiplied by this value. <1 means decreasing variety so your sequence will converge on a fixed picture. >1 means increasing variety so your sequence will become more and more chaotic.", + "Skip": "Stop processing current image and continue processing.", "Interrupt": "Stop processing images and return any results accumulated so far.", "Save": "Write image to a directory (default - log/images) and generation parameters into csv file.", diff --git a/javascript/progressbar.js b/javascript/progressbar.js index f9e9290e..4395a215 100644 --- a/javascript/progressbar.js +++ b/javascript/progressbar.js @@ -1,8 +1,9 @@ // code related to showing and updating progressbar shown as the image is being made global_progressbars = {} -function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_interrupt, id_preview, id_gallery){ +function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_skip, id_interrupt, id_preview, id_gallery){ var progressbar = gradioApp().getElementById(id_progressbar) + var skip = id_skip ? gradioApp().getElementById(id_skip) : null var interrupt = gradioApp().getElementById(id_interrupt) if(opts.show_progress_in_title && progressbar && progressbar.offsetParent){ @@ -32,30 +33,37 @@ function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_inte var progressDiv = gradioApp().querySelectorAll('#' + id_progressbar_span).length > 0; if(!progressDiv){ + if (skip) { + skip.style.display = "none" + } interrupt.style.display = "none" } } - window.setTimeout(function(){ requestMoreProgress(id_part, id_progressbar_span, id_interrupt) }, 500) + window.setTimeout(function() { requestMoreProgress(id_part, id_progressbar_span, id_skip, id_interrupt) }, 500) }); mutationObserver.observe( progressbar, { childList:true, subtree:true }) } } onUiUpdate(function(){ - check_progressbar('txt2img', 'txt2img_progressbar', 'txt2img_progress_span', 'txt2img_interrupt', 'txt2img_preview', 'txt2img_gallery') - check_progressbar('img2img', 'img2img_progressbar', 'img2img_progress_span', 'img2img_interrupt', 'img2img_preview', 'img2img_gallery') - check_progressbar('ti', 'ti_progressbar', 'ti_progress_span', 'ti_interrupt', 'ti_preview', 'ti_gallery') + check_progressbar('txt2img', 'txt2img_progressbar', 'txt2img_progress_span', 'txt2img_skip', 'txt2img_interrupt', 'txt2img_preview', 'txt2img_gallery') + check_progressbar('img2img', 'img2img_progressbar', 'img2img_progress_span', 'img2img_skip', 'img2img_interrupt', 'img2img_preview', 'img2img_gallery') + check_progressbar('ti', 'ti_progressbar', 'ti_progress_span', '', 'ti_interrupt', 'ti_preview', 'ti_gallery') }) -function requestMoreProgress(id_part, id_progressbar_span, id_interrupt){ +function requestMoreProgress(id_part, id_progressbar_span, id_skip, id_interrupt){ btn = gradioApp().getElementById(id_part+"_check_progress"); if(btn==null) return; btn.click(); var progressDiv = gradioApp().querySelectorAll('#' + id_progressbar_span).length > 0; + var skip = id_skip ? gradioApp().getElementById(id_skip) : null var interrupt = gradioApp().getElementById(id_interrupt) if(progressDiv && interrupt){ + if (skip) { + skip.style.display = "block" + } interrupt.style.display = "block" } } diff --git a/modules/img2img.py b/modules/img2img.py index da212d72..e60b7e0f 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -32,6 +32,10 @@ def process_batch(p, input_dir, output_dir, args): for i, image in enumerate(images): state.job = f"{i+1} out of {len(images)}" + if state.skipped: + state.skipped = False + state.interrupted = False + continue if state.interrupted: break diff --git a/modules/processing.py b/modules/processing.py index d814d5ac..6805039c 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -355,6 +355,10 @@ def process_images(p: StableDiffusionProcessing) -> Processed: state.job_count = p.n_iter for n in range(p.n_iter): + if state.skipped: + state.skipped = False + state.interrupted = False + if state.interrupted: break diff --git a/modules/shared.py b/modules/shared.py index 864e772c..7f802bd9 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -84,6 +84,7 @@ def selected_hypernetwork(): class State: + skipped = False interrupted = False job = "" job_no = 0 @@ -96,6 +97,10 @@ class State: current_image_sampling_step = 0 textinfo = None + def skip(self): + self.skipped = True + self.interrupted = True + def interrupt(self): self.interrupted = True diff --git a/modules/ui.py b/modules/ui.py index 4f18126f..e3e62fdd 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -191,6 +191,7 @@ def wrap_gradio_call(func, extra_outputs=None): # last item is always HTML res[-1] += f"

Time taken: {elapsed_text}

{vram_html}
" + shared.state.skipped = False shared.state.interrupted = False shared.state.job_count = 0 @@ -411,9 +412,16 @@ def create_toprow(is_img2img): with gr.Column(scale=1): with gr.Row(): + skip = gr.Button('Skip', elem_id=f"{id_part}_skip") interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt") submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary') + skip.click( + fn=lambda: shared.state.skip(), + inputs=[], + outputs=[], + ) + interrupt.click( fn=lambda: shared.state.interrupt(), inputs=[], diff --git a/style.css b/style.css index 50c5e557..6904fc50 100644 --- a/style.css +++ b/style.css @@ -393,10 +393,20 @@ input[type="range"]{ #txt2img_interrupt, #img2img_interrupt{ position: absolute; - width: 100%; + width: 50%; height: 72px; background: #b4c0cc; - border-radius: 8px; + border-radius: 0px; + display: none; +} + +#txt2img_skip, #img2img_skip{ + position: absolute; + width: 50%; + right: 0px; + height: 72px; + background: #b4c0cc; + border-radius: 0px; display: none; } diff --git a/webui.py b/webui.py index 480360fe..3b4cf5e9 100644 --- a/webui.py +++ b/webui.py @@ -58,6 +58,7 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): shared.state.current_latent = None shared.state.current_image = None shared.state.current_image_sampling_step = 0 + shared.state.skipped = False shared.state.interrupted = False shared.state.textinfo = None -- cgit v1.2.3 From 4f33289d0fc5aa3a197f4a4c926d03d44f0d597e Mon Sep 17 00:00:00 2001 From: Milly Date: Sat, 8 Oct 2022 22:48:15 +0900 Subject: Fixed typo --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index e3e62fdd..ffd75f6a 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -946,7 +946,7 @@ def create_ui(wrap_gradio_gpu_call): custom_name = gr.Textbox(label="Custom Name (Optional)") interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Interpolation Amount', value=0.3) interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid", "Inverse Sigmoid"], value="Weighted Sum", label="Interpolation Method") - save_as_half = gr.Checkbox(value=False, label="Safe as float16") + save_as_half = gr.Checkbox(value=False, label="Save as float16") modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary') with gr.Column(variant='panel'): -- cgit v1.2.3 From 01f8cb44474e454903c11718e6a4f33dbde34bb8 Mon Sep 17 00:00:00 2001 From: Greendayle Date: Sat, 8 Oct 2022 18:02:56 +0200 Subject: made deepdanbooru optional, added to readme, automatic download of deepbooru model --- README.md | 2 ++ launch.py | 4 ++++ modules/deepbooru.py | 20 ++++++++++---------- modules/shared.py | 1 + modules/ui.py | 19 ++++++++++++------- requirements.txt | 3 --- requirements_versions.txt | 3 --- 7 files changed, 29 insertions(+), 23 deletions(-) (limited to 'modules/ui.py') diff --git a/README.md b/README.md index ef9b5e31..6cd7a1f9 100644 --- a/README.md +++ b/README.md @@ -66,6 +66,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web - separate prompts using uppercase `AND` - also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2` - No token limit for prompts (original stable diffusion lets you use up to 75 tokens) +- DeepDanbooru integration, creates danbooru style tags for anime prompts (add --deepdanbooru to commandline args) ## Installation and Running Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs. @@ -123,4 +124,5 @@ The documentation was moved from this README over to the project's [wiki](https: - Noise generation for outpainting mk2 - https://github.com/parlance-zz/g-diffuser-bot - CLIP interrogator idea and borrowing some code - https://github.com/pharmapsychotic/clip-interrogator - Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user. +- DeepDanbooru - interrogator for anime diffusors https://github.com/KichangKim/DeepDanbooru - (You) diff --git a/launch.py b/launch.py index 61f62096..d46426eb 100644 --- a/launch.py +++ b/launch.py @@ -33,6 +33,7 @@ def extract_arg(args, name): args, skip_torch_cuda_test = extract_arg(args, '--skip-torch-cuda-test') xformers = '--xformers' in args +deepdanbooru = '--deepdanbooru' in args def repo_dir(name): @@ -132,6 +133,9 @@ if not is_installed("xformers") and xformers: elif platform.system() == "Linux": run_pip("install xformers", "xformers") +if not is_installed("deepdanbooru") and deepdanbooru: + run_pip("install git+https://github.com/KichangKim/DeepDanbooru.git@edf73df4cdaeea2cf00e9ac08bd8a9026b7a7b26#egg=deepdanbooru[tensorflow] tensorflow==2.10.0 tensorflow-io==0.27.0", "deepdanbooru") + os.makedirs(dir_repos, exist_ok=True) git_clone("https://github.com/CompVis/stable-diffusion.git", repo_dir('stable-diffusion'), "Stable Diffusion", stable_diffusion_commit_hash) diff --git a/modules/deepbooru.py b/modules/deepbooru.py index 781b2249..7e3c0618 100644 --- a/modules/deepbooru.py +++ b/modules/deepbooru.py @@ -9,16 +9,16 @@ def _load_tf_and_return_tags(pil_image, threshold): import numpy as np this_folder = os.path.dirname(__file__) - model_path = os.path.join(this_folder, '..', 'models', 'deepbooru', 'deepdanbooru-v3-20211112-sgd-e28') - - model_good = False - for path_candidate in [model_path, os.path.dirname(model_path)]: - if os.path.exists(os.path.join(path_candidate, 'project.json')): - model_path = path_candidate - model_good = True - if not model_good: - return ("Download https://github.com/KichangKim/DeepDanbooru/releases/download/v3-20211112-sgd-e28/" - "deepdanbooru-v3-20211112-sgd-e28.zip unpack and put into models/deepbooru") + model_path = os.path.abspath(os.path.join(this_folder, '..', 'models', 'deepbooru')) + if not os.path.exists(os.path.join(model_path, 'project.json')): + # there is no point importing these every time + import zipfile + from basicsr.utils.download_util import load_file_from_url + load_file_from_url(r"https://github.com/KichangKim/DeepDanbooru/releases/download/v3-20211112-sgd-e28/deepdanbooru-v3-20211112-sgd-e28.zip", + model_path) + with zipfile.ZipFile(os.path.join(model_path, "deepdanbooru-v3-20211112-sgd-e28.zip"), "r") as zip_ref: + zip_ref.extractall(model_path) + os.remove(os.path.join(model_path, "deepdanbooru-v3-20211112-sgd-e28.zip")) tags = dd.project.load_tags_from_project(model_path) model = dd.project.load_model_from_project( diff --git a/modules/shared.py b/modules/shared.py index 02cb2722..c87b726e 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -44,6 +44,7 @@ parser.add_argument("--scunet-models-path", type=str, help="Path to directory wi parser.add_argument("--swinir-models-path", type=str, help="Path to directory with SwinIR model file(s).", default=os.path.join(models_path, 'SwinIR')) parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with LDSR model file(s).", default=os.path.join(models_path, 'LDSR')) parser.add_argument("--xformers", action='store_true', help="enable xformers for cross attention layers") +parser.add_argument("--deepdanbooru", action='store_true', help="enable deepdanbooru interrogator") parser.add_argument("--opt-split-attention", action='store_true', help="force-enables cross-attention layer optimization. By default, it's on for torch.cuda and off for other torch devices.") parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization") parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find") diff --git a/modules/ui.py b/modules/ui.py index 30583fe9..c5c11c3c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -23,9 +23,10 @@ import gradio.utils import gradio.routes from modules import sd_hijack -from modules.deepbooru import get_deepbooru_tags from modules.paths import script_path from modules.shared import opts, cmd_opts +if cmd_opts.deepdanbooru: + from modules.deepbooru import get_deepbooru_tags import modules.shared as shared from modules.sd_samplers import samplers, samplers_for_img2img from modules.sd_hijack import model_hijack @@ -437,7 +438,10 @@ def create_toprow(is_img2img): with gr.Row(scale=1): if is_img2img: interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate") - deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru") + if cmd_opts.deepdanbooru: + deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru") + else: + deepbooru = None else: interrogate = None deepbooru = None @@ -782,11 +786,12 @@ def create_ui(wrap_gradio_gpu_call): outputs=[img2img_prompt], ) - img2img_deepbooru.click( - fn=interrogate_deepbooru, - inputs=[init_img], - outputs=[img2img_prompt], - ) + if cmd_opts.deepdanbooru: + img2img_deepbooru.click( + fn=interrogate_deepbooru, + inputs=[init_img], + outputs=[img2img_prompt], + ) save.click( fn=wrap_gradio_call(save_files), diff --git a/requirements.txt b/requirements.txt index cd3953c6..81641d68 100644 --- a/requirements.txt +++ b/requirements.txt @@ -23,7 +23,4 @@ resize-right torchdiffeq kornia lark -deepdanbooru -tensorflow -tensorflow-io functorch diff --git a/requirements_versions.txt b/requirements_versions.txt index 2d256a54..fec3e9d5 100644 --- a/requirements_versions.txt +++ b/requirements_versions.txt @@ -22,7 +22,4 @@ resize-right==0.0.2 torchdiffeq==0.2.3 kornia==0.6.7 lark==1.1.2 -git+https://github.com/KichangKim/DeepDanbooru.git@edf73df4cdaeea2cf00e9ac08bd8a9026b7a7b26#egg=deepdanbooru[tensorflow] -tensorflow==2.10.0 -tensorflow-io==0.27.0 functorch==0.2.1 -- cgit v1.2.3 From 15c4278f1a18b8104e135dd82690d10cff39a2e7 Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Sat, 8 Oct 2022 17:50:01 +0100 Subject: TI preprocess wording MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit I had to check the code to work out what splitting was 🤷🏿 --- modules/ui.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index ffd75f6a..d52d74c6 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -980,9 +980,9 @@ def create_ui(wrap_gradio_gpu_call): process_dst = gr.Textbox(label='Destination directory') with gr.Row(): - process_flip = gr.Checkbox(label='Flip') - process_split = gr.Checkbox(label='Split into two') - process_caption = gr.Checkbox(label='Add caption') + process_flip = gr.Checkbox(label='Create flipped copies') + process_split = gr.Checkbox(label='Split oversized images into two') + process_caption = gr.Checkbox(label='Use CLIP caption as filename') with gr.Row(): with gr.Column(scale=3): -- cgit v1.2.3 From b458fa48fe5734a872bca83061d702609cb52940 Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Sat, 8 Oct 2022 17:56:28 +0100 Subject: Update ui.py --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index d52d74c6..b09359aa 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -982,7 +982,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Row(): process_flip = gr.Checkbox(label='Create flipped copies') process_split = gr.Checkbox(label='Split oversized images into two') - process_caption = gr.Checkbox(label='Use CLIP caption as filename') + process_caption = gr.Checkbox(label='Use BLIP caption as filename') with gr.Row(): with gr.Column(scale=3): -- cgit v1.2.3 From 432782163ae53e605470bcefc9a6f796c4556912 Mon Sep 17 00:00:00 2001 From: Aidan Holland Date: Sat, 8 Oct 2022 15:12:24 -0400 Subject: chore: Fix typos --- README.md | 2 +- javascript/imageviewer.js | 2 +- modules/interrogate.py | 4 ++-- modules/processing.py | 2 +- modules/scunet_model_arch.py | 4 ++-- modules/sd_models.py | 4 ++-- modules/sd_samplers.py | 4 ++-- modules/shared.py | 6 +++--- modules/swinir_model_arch.py | 2 +- modules/ui.py | 4 ++-- 10 files changed, 17 insertions(+), 17 deletions(-) (limited to 'modules/ui.py') diff --git a/README.md b/README.md index ef9b5e31..63dd0c18 100644 --- a/README.md +++ b/README.md @@ -34,7 +34,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web - Sampling method selection - Interrupt processing at any time - 4GB video card support (also reports of 2GB working) -- Correct seeds for batches +- Correct seeds for batches - Prompt length validation - get length of prompt in tokens as you type - get a warning after generation if some text was truncated diff --git a/javascript/imageviewer.js b/javascript/imageviewer.js index 4c0e8f4b..6a00c0da 100644 --- a/javascript/imageviewer.js +++ b/javascript/imageviewer.js @@ -95,7 +95,7 @@ function showGalleryImage(){ e.addEventListener('click', function (evt) { if(!opts.js_modal_lightbox) return; - modalZoomSet(gradioApp().getElementById('modalImage'), opts.js_modal_lightbox_initialy_zoomed) + modalZoomSet(gradioApp().getElementById('modalImage'), opts.js_modal_lightbox_initially_zoomed) showModal(evt) },true); } diff --git a/modules/interrogate.py b/modules/interrogate.py index eed87144..635e266e 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -140,11 +140,11 @@ class InterrogateModels: res = caption - cilp_image = self.clip_preprocess(pil_image).unsqueeze(0).type(self.dtype).to(shared.device) + clip_image = self.clip_preprocess(pil_image).unsqueeze(0).type(self.dtype).to(shared.device) precision_scope = torch.autocast if shared.cmd_opts.precision == "autocast" else contextlib.nullcontext with torch.no_grad(), precision_scope("cuda"): - image_features = self.clip_model.encode_image(cilp_image).type(self.dtype) + image_features = self.clip_model.encode_image(clip_image).type(self.dtype) image_features /= image_features.norm(dim=-1, keepdim=True) diff --git a/modules/processing.py b/modules/processing.py index 515fc91a..31220881 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -386,7 +386,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed: if state.interrupted or state.skipped: - # if we are interruped, sample returns just noise + # if we are interrupted, sample returns just noise # use the image collected previously in sampler loop samples_ddim = shared.state.current_latent diff --git a/modules/scunet_model_arch.py b/modules/scunet_model_arch.py index 972a2639..43ca8d36 100644 --- a/modules/scunet_model_arch.py +++ b/modules/scunet_model_arch.py @@ -40,7 +40,7 @@ class WMSA(nn.Module): Returns: attn_mask: should be (1 1 w p p), """ - # supporting sqaure. + # supporting square. attn_mask = torch.zeros(h, w, p, p, p, p, dtype=torch.bool, device=self.relative_position_params.device) if self.type == 'W': return attn_mask @@ -65,7 +65,7 @@ class WMSA(nn.Module): x = rearrange(x, 'b (w1 p1) (w2 p2) c -> b w1 w2 p1 p2 c', p1=self.window_size, p2=self.window_size) h_windows = x.size(1) w_windows = x.size(2) - # sqaure validation + # square validation # assert h_windows == w_windows x = rearrange(x, 'b w1 w2 p1 p2 c -> b (w1 w2) (p1 p2) c', p1=self.window_size, p2=self.window_size) diff --git a/modules/sd_models.py b/modules/sd_models.py index 9409d070..a09866ce 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -147,7 +147,7 @@ def load_model_weights(model, checkpoint_file, sd_model_hash): model.first_stage_model.load_state_dict(vae_dict) model.sd_model_hash = sd_model_hash - model.sd_model_checkpint = checkpoint_file + model.sd_model_checkpoint = checkpoint_file def load_model(): @@ -175,7 +175,7 @@ def reload_model_weights(sd_model, info=None): from modules import lowvram, devices, sd_hijack checkpoint_info = info or select_checkpoint() - if sd_model.sd_model_checkpint == checkpoint_info.filename: + if sd_model.sd_model_checkpoint == checkpoint_info.filename: return if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index eade0dbb..6e743f7e 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -181,7 +181,7 @@ class VanillaStableDiffusionSampler: self.initialize(p) - # existing code fails with cetain step counts, like 9 + # existing code fails with certain step counts, like 9 try: self.sampler.make_schedule(ddim_num_steps=steps, ddim_eta=self.eta, ddim_discretize=p.ddim_discretize, verbose=False) except Exception: @@ -204,7 +204,7 @@ class VanillaStableDiffusionSampler: steps = steps or p.steps - # existing code fails with cetin step counts, like 9 + # existing code fails with certain step counts, like 9 try: samples_ddim, _ = self.sampler.sample(S=steps, conditioning=conditioning, batch_size=int(x.shape[0]), shape=x[0].shape, verbose=False, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning, x_T=x, eta=self.eta) except Exception: diff --git a/modules/shared.py b/modules/shared.py index af8dc744..2dc092d6 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -141,9 +141,9 @@ class OptionInfo: self.section = None -def options_section(section_identifer, options_dict): +def options_section(section_identifier, options_dict): for k, v in options_dict.items(): - v.section = section_identifer + v.section = section_identifier return options_dict @@ -246,7 +246,7 @@ options_templates.update(options_section(('ui', "User interface"), { "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"), "font": OptionInfo("", "Font for image grids that have text"), "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"), - "js_modal_lightbox_initialy_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"), + "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"), "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."), })) diff --git a/modules/swinir_model_arch.py b/modules/swinir_model_arch.py index 461fb354..863f42db 100644 --- a/modules/swinir_model_arch.py +++ b/modules/swinir_model_arch.py @@ -166,7 +166,7 @@ class SwinTransformerBlock(nn.Module): Args: dim (int): Number of input channels. - input_resolution (tuple[int]): Input resulotion. + input_resolution (tuple[int]): Input resolution. num_heads (int): Number of attention heads. window_size (int): Window size. shift_size (int): Shift size for SW-MSA. diff --git a/modules/ui.py b/modules/ui.py index b09359aa..b51af121 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -38,7 +38,7 @@ from modules import prompt_parser from modules.images import save_image import modules.textual_inversion.ui -# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI +# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() mimetypes.add_type('application/javascript', '.js') @@ -102,7 +102,7 @@ def save_files(js_data, images, index): import csv filenames = [] - #quick dictionary to class object conversion. Its neccesary due apply_filename_pattern requiring it + #quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it class MyObject: def __init__(self, d=None): if d is not None: -- cgit v1.2.3 From cd8673bd9b2e59bddefee8d307340d643695fe11 Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Sun, 9 Oct 2022 05:40:57 +0100 Subject: add embed embedding to ui --- modules/ui.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index b51af121..a5983204 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1001,7 +1001,8 @@ def create_ui(wrap_gradio_gpu_call): steps = gr.Number(label='Max steps', value=100000, precision=0) create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0) save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0) - + save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True) + with gr.Row(): with gr.Column(scale=2): gr.HTML(value="") @@ -1063,6 +1064,7 @@ def create_ui(wrap_gradio_gpu_call): create_image_every, save_embedding_every, template_file, + save_image_with_stored_embedding, ], outputs=[ ti_output, -- cgit v1.2.3 From 5ab7e88d9b0bb0125af9f7237242a00a93360ce5 Mon Sep 17 00:00:00 2001 From: aoirusann <82883326+aoirusann@users.noreply.github.com> Date: Sat, 8 Oct 2022 13:09:29 +0800 Subject: Add `Download` & `Download as zip` --- modules/ui.py | 39 ++++++++++++++++++++++++++++++++++----- 1 file changed, 34 insertions(+), 5 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index b51af121..fe7f10a7 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -98,9 +98,10 @@ def send_gradio_gallery_to_image(x): return image_from_url_text(x[0]) -def save_files(js_data, images, index): +def save_files(js_data, images, do_make_zip, index): import csv filenames = [] + fullfns = [] #quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it class MyObject: @@ -141,10 +142,22 @@ def save_files(js_data, images, index): filename = os.path.relpath(fullfn, path) filenames.append(filename) + fullfns.append(fullfn) writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]]) - return '', '', plaintext_to_html(f"Saved: {filenames[0]}") + # Make Zip + if do_make_zip: + zip_filepath = os.path.join(path, "images.zip") + + from zipfile import ZipFile + with ZipFile(zip_filepath, "w") as zip_file: + for i in range(len(fullfns)): + with open(fullfns[i], mode="rb") as f: + zip_file.writestr(filenames[i], f.read()) + fullfns.insert(0, zip_filepath) + + return fullfns, '', '', plaintext_to_html(f"Saved: {filenames[0]}") def wrap_gradio_call(func, extra_outputs=None): @@ -521,6 +534,12 @@ def create_ui(wrap_gradio_gpu_call): button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder' open_txt2img_folder = gr.Button(folder_symbol, elem_id=button_id) + with gr.Row(): + do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False) + + with gr.Row(): + download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False) + with gr.Group(): html_info = gr.HTML() generation_info = gr.Textbox(visible=False) @@ -570,13 +589,15 @@ def create_ui(wrap_gradio_gpu_call): save.click( fn=wrap_gradio_call(save_files), - _js="(x, y, z) => [x, y, selected_gallery_index()]", + _js="(x, y, z, w) => [x, y, z, selected_gallery_index()]", inputs=[ generation_info, txt2img_gallery, + do_make_zip, html_info, ], outputs=[ + download_files, html_info, html_info, html_info, @@ -701,6 +722,12 @@ def create_ui(wrap_gradio_gpu_call): button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder' open_img2img_folder = gr.Button(folder_symbol, elem_id=button_id) + with gr.Row(): + do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False) + + with gr.Row(): + download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False) + with gr.Group(): html_info = gr.HTML() generation_info = gr.Textbox(visible=False) @@ -776,13 +803,15 @@ def create_ui(wrap_gradio_gpu_call): save.click( fn=wrap_gradio_call(save_files), - _js="(x, y, z) => [x, y, selected_gallery_index()]", + _js="(x, y, z, w) => [x, y, z, selected_gallery_index()]", inputs=[ generation_info, img2img_gallery, - html_info + do_make_zip, + html_info, ], outputs=[ + download_files, html_info, html_info, html_info, -- cgit v1.2.3 From 14192c5b207b16b1ec7a4c9c4ea538d1a6811a4d Mon Sep 17 00:00:00 2001 From: aoirusann Date: Sun, 9 Oct 2022 13:01:10 +0800 Subject: Support `Download` for txt files. --- modules/images.py | 39 +++++++++++++++++++++++++++++++++++++-- modules/ui.py | 5 ++++- 2 files changed, 41 insertions(+), 3 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/images.py b/modules/images.py index 29c5ee24..c0a90676 100644 --- a/modules/images.py +++ b/modules/images.py @@ -349,6 +349,38 @@ def get_next_sequence_number(path, basename): def save_image(image, path, basename, seed=None, prompt=None, extension='png', info=None, short_filename=False, no_prompt=False, grid=False, pnginfo_section_name='parameters', p=None, existing_info=None, forced_filename=None, suffix="", save_to_dirs=None): + '''Save an image. + + Args: + image (`PIL.Image`): + The image to be saved. + path (`str`): + The directory to save the image. Note, the option `save_to_dirs` will make the image to be saved into a sub directory. + basename (`str`): + The base filename which will be applied to `filename pattern`. + seed, prompt, short_filename, + extension (`str`): + Image file extension, default is `png`. + pngsectionname (`str`): + Specify the name of the section which `info` will be saved in. + info (`str` or `PngImagePlugin.iTXt`): + PNG info chunks. + existing_info (`dict`): + Additional PNG info. `existing_info == {pngsectionname: info, ...}` + no_prompt: + TODO I don't know its meaning. + p (`StableDiffusionProcessing`) + forced_filename (`str`): + If specified, `basename` and filename pattern will be ignored. + save_to_dirs (bool): + If true, the image will be saved into a subdirectory of `path`. + + Returns: (fullfn, txt_fullfn) + fullfn (`str`): + The full path of the saved imaged. + txt_fullfn (`str` or None): + If a text file is saved for this image, this will be its full path. Otherwise None. + ''' if short_filename or prompt is None or seed is None: file_decoration = "" elif opts.save_to_dirs: @@ -424,7 +456,10 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i piexif.insert(exif_bytes(), fullfn_without_extension + ".jpg") if opts.save_txt and info is not None: - with open(f"{fullfn_without_extension}.txt", "w", encoding="utf8") as file: + txt_fullfn = f"{fullfn_without_extension}.txt" + with open(txt_fullfn, "w", encoding="utf8") as file: file.write(info + "\n") + else: + txt_fullfn = None - return fullfn + return fullfn, txt_fullfn diff --git a/modules/ui.py b/modules/ui.py index fe7f10a7..debd8873 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -138,11 +138,14 @@ def save_files(js_data, images, do_make_zip, index): is_grid = image_index < p.index_of_first_image i = 0 if is_grid else (image_index - p.index_of_first_image) - fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs) + fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs) filename = os.path.relpath(fullfn, path) filenames.append(filename) fullfns.append(fullfn) + if txt_fullfn: + filenames.append(os.path.basename(txt_fullfn)) + fullfns.append(txt_fullfn) writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]]) -- cgit v1.2.3 From ab4fe4f44c3d2675a351269fe2ff1ddeac557aa6 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 9 Oct 2022 11:59:41 +0300 Subject: hide filenames for save button by default --- modules/ui.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 8071b1cb..e1ab2665 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -162,7 +162,7 @@ def save_files(js_data, images, do_make_zip, index): zip_file.writestr(filenames[i], f.read()) fullfns.insert(0, zip_filepath) - return fullfns, '', '', plaintext_to_html(f"Saved: {filenames[0]}") + return gr.File.update(value=fullfns, visible=True), '', '', plaintext_to_html(f"Saved: {filenames[0]}") def wrap_gradio_call(func, extra_outputs=None): @@ -553,7 +553,7 @@ def create_ui(wrap_gradio_gpu_call): do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False) with gr.Row(): - download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False) + download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False) with gr.Group(): html_info = gr.HTML() @@ -741,7 +741,7 @@ def create_ui(wrap_gradio_gpu_call): do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False) with gr.Row(): - download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False) + download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False) with gr.Group(): html_info = gr.HTML() -- cgit v1.2.3 From 6f6798ddabe10d320fe8ea05edf0fdcef0c51a8e Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 9 Oct 2022 12:33:37 +0300 Subject: prevent a possible code execution error (thanks, RyotaK) --- modules/ui.py | 9 +++++++++ 1 file changed, 9 insertions(+) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index e1ab2665..dad509f3 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1153,6 +1153,15 @@ def create_ui(wrap_gradio_gpu_call): component_dict = {} def open_folder(f): + if not os.path.isdir(f): + print(f""" +WARNING +An open_folder request was made with an argument that is not a folder. +This could be an error or a malicious attempt to run code on your computer. +Requested path was: {f} +""", file=sys.stderr) + return + if not shared.cmd_opts.hide_ui_dir_config: path = os.path.normpath(f) if platform.system() == "Windows": -- cgit v1.2.3 From 6c383d2e82045fc4475d665f83bdeeac8fd844d9 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 9 Oct 2022 22:24:07 +0300 Subject: show model selection setting on top of page --- modules/shared.py | 5 +++-- modules/ui.py | 54 +++++++++++++++++++++++++++++++++++++++++++++--------- style.css | 9 +++++++++ 3 files changed, 57 insertions(+), 11 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/shared.py b/modules/shared.py index 3d7f08e1..270fa402 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -131,13 +131,14 @@ def realesrgan_models_names(): class OptionInfo: - def __init__(self, default=None, label="", component=None, component_args=None, onchange=None): + def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, show_on_main_page=False): self.default = default self.label = label self.component = component self.component_args = component_args self.onchange = onchange self.section = None + self.show_on_main_page = show_on_main_page def options_section(section_identifier, options_dict): @@ -214,7 +215,7 @@ options_templates.update(options_section(('system', "System"), { })) options_templates.update(options_section(('sd', "Stable Diffusion"), { - "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}), + "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, show_on_main_page=True), "sd_hypernetwork": OptionInfo("None", "Stable Diffusion finetune hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}), "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."), "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"), diff --git a/modules/ui.py b/modules/ui.py index dad509f3..2231a8ed 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1175,10 +1175,13 @@ Requested path was: {f} changed = 0 for key, value, comp in zip(opts.data_labels.keys(), args, components): - if not opts.same_type(value, opts.data_labels[key].default): - return f"Bad value for setting {key}: {value}; expecting {type(opts.data_labels[key].default).__name__}" + if comp != dummy_component and not opts.same_type(value, opts.data_labels[key].default): + return f"Bad value for setting {key}: {value}; expecting {type(opts.data_labels[key].default).__name__}", opts.dumpjson() for key, value, comp in zip(opts.data_labels.keys(), args, components): + if comp == dummy_component: + continue + comp_args = opts.data_labels[key].component_args if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False: continue @@ -1196,6 +1199,21 @@ Requested path was: {f} return f'{changed} settings changed.', opts.dumpjson() + def run_settings_single(value, key): + if not opts.same_type(value, opts.data_labels[key].default): + return gr.update(visible=True), opts.dumpjson() + + oldval = opts.data.get(key, None) + opts.data[key] = value + + if oldval != value: + if opts.data_labels[key].onchange is not None: + opts.data_labels[key].onchange() + + opts.save(shared.config_filename) + + return gr.update(value=value), opts.dumpjson() + with gr.Blocks(analytics_enabled=False) as settings_interface: settings_submit = gr.Button(value="Apply settings", variant='primary') result = gr.HTML() @@ -1203,6 +1221,8 @@ Requested path was: {f} settings_cols = 3 items_per_col = int(len(opts.data_labels) * 0.9 / settings_cols) + quicksettings_list = [] + cols_displayed = 0 items_displayed = 0 previous_section = None @@ -1225,10 +1245,14 @@ Requested path was: {f} gr.HTML(elem_id="settings_header_text_{}".format(item.section[0]), value='

{}

'.format(item.section[1])) - component = create_setting_component(k) - component_dict[k] = component - components.append(component) - items_displayed += 1 + if item.show_on_main_page: + quicksettings_list.append((i, k, item)) + components.append(dummy_component) + else: + component = create_setting_component(k) + component_dict[k] = component + components.append(component) + items_displayed += 1 request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications") request_notifications.click( @@ -1242,7 +1266,6 @@ Requested path was: {f} reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary') restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary') - def reload_scripts(): modules.scripts.reload_script_body_only() @@ -1289,7 +1312,11 @@ Requested path was: {f} css += css_hide_progressbar with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo: - + with gr.Row(elem_id="quicksettings"): + for i, k, item in quicksettings_list: + component = create_setting_component(k) + component_dict[k] = component + settings_interface.gradio_ref = demo with gr.Tabs() as tabs: @@ -1306,7 +1333,16 @@ Requested path was: {f} inputs=components, outputs=[result, text_settings], ) - + + for i, k, item in quicksettings_list: + component = component_dict[k] + + component.change( + fn=lambda value, k=k: run_settings_single(value, key=k), + inputs=[component], + outputs=[component, text_settings], + ) + def modelmerger(*args): try: results = modules.extras.run_modelmerger(*args) diff --git a/style.css b/style.css index 101d2052..28160bdf 100644 --- a/style.css +++ b/style.css @@ -453,3 +453,12 @@ input[type="range"]{ .context-menu-items a:hover{ background: #a55000; } + +#quicksettings > div{ + border: none; +} + +#quicksettings > div > div{ + max-width: 32em; + padding: 0; +} -- cgit v1.2.3 From 6435691bb11c5a35703720bfd2a875f24c066f86 Mon Sep 17 00:00:00 2001 From: Justin Maier Date: Sun, 9 Oct 2022 19:26:52 -0600 Subject: Add "Scale to" option to Extras --- javascript/ui.js | 3 ++- modules/extras.py | 28 +++++++++++++++++++++++----- modules/ui.py | 38 +++++++++++++++++++++++++------------- 3 files changed, 50 insertions(+), 19 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index b1053201..4100944e 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -101,7 +101,8 @@ function create_tab_index_args(tabId, args){ } function get_extras_tab_index(){ - return create_tab_index_args('mode_extras', arguments) + const [,,...args] = [...arguments] + return [get_tab_index('mode_extras'), get_tab_index('extras_resize_mode'), ...args] } function create_submit_args(args){ diff --git a/modules/extras.py b/modules/extras.py index 41e8612c..83ca7049 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -1,3 +1,4 @@ +import math import os import numpy as np @@ -19,7 +20,7 @@ import gradio as gr cached_images = {} -def run_extras(extras_mode, image, image_folder, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility): +def run_extras(extras_mode, resize_mode, image, image_folder, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility): devices.torch_gc() imageArr = [] @@ -67,8 +68,23 @@ def run_extras(extras_mode, image, image_folder, gfpgan_visibility, codeformer_v info += f"CodeFormer w: {round(codeformer_weight, 2)}, CodeFormer visibility:{round(codeformer_visibility, 2)}\n" image = res + if resize_mode == 1: + upscaling_resize = max(upscaling_resize_w/image.width, upscaling_resize_h/image.height) + crop_info = " (crop)" if upscaling_crop else "" + info += f"Resize to: {upscaling_resize_w:g}x{upscaling_resize_h:g}{crop_info}\n" + + def crop_upscaled_center(image, resize_w, resize_h): + left = int(math.ceil((image.width - resize_w) / 2)) + right = image.width - int(math.floor((image.width - resize_w) / 2)) + top = int(math.ceil((image.height - resize_h) / 2)) + bottom = image.height - int(math.floor((image.height - resize_h) / 2)) + + image = image.crop((left, top, right, bottom)) + return image + + if upscaling_resize != 1.0: - def upscale(image, scaler_index, resize): + def upscale(image, scaler_index, resize, mode, resize_w, resize_h, crop): small = image.crop((image.width // 2, image.height // 2, image.width // 2 + 10, image.height // 2 + 10)) pixels = tuple(np.array(small).flatten().tolist()) key = (resize, scaler_index, image.width, image.height, gfpgan_visibility, codeformer_visibility, codeformer_weight) + pixels @@ -77,15 +93,17 @@ def run_extras(extras_mode, image, image_folder, gfpgan_visibility, codeformer_v if c is None: upscaler = shared.sd_upscalers[scaler_index] c = upscaler.scaler.upscale(image, resize, upscaler.data_path) + if mode == 1 and crop: + c = crop_upscaled_center(c, resize_w, resize_h) cached_images[key] = c return c info += f"Upscale: {round(upscaling_resize, 3)}, model:{shared.sd_upscalers[extras_upscaler_1].name}\n" - res = upscale(image, extras_upscaler_1, upscaling_resize) + res = upscale(image, extras_upscaler_1, upscaling_resize, resize_mode, upscaling_resize_w, upscaling_resize_h, upscaling_crop) if extras_upscaler_2 != 0 and extras_upscaler_2_visibility > 0: - res2 = upscale(image, extras_upscaler_2, upscaling_resize) + res2 = upscale(image, extras_upscaler_2, upscaling_resize, resize_mode, upscaling_resize_w, upscaling_resize_h, upscaling_crop) info += f"Upscale: {round(upscaling_resize, 3)}, visibility: {round(extras_upscaler_2_visibility, 3)}, model:{shared.sd_upscalers[extras_upscaler_2].name}\n" res = Image.blend(res, res2, extras_upscaler_2_visibility) @@ -190,7 +208,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int theta_0[key] = theta_func(theta_0[key], theta_1[key], (float(1.0) - interp_amount)) # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint if save_as_half: theta_0[key] = theta_0[key].half() - + for key in theta_1.keys(): if 'model' in key and key not in theta_0: theta_0[key] = theta_1[key] diff --git a/modules/ui.py b/modules/ui.py index 2231a8ed..4bb2892b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -101,7 +101,7 @@ def send_gradio_gallery_to_image(x): def save_files(js_data, images, do_make_zip, index): - import csv + import csv filenames = [] fullfns = [] @@ -551,7 +551,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Row(): do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False) - + with gr.Row(): download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False) @@ -739,7 +739,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Row(): do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False) - + with gr.Row(): download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False) @@ -903,7 +903,15 @@ def create_ui(wrap_gradio_gpu_call): with gr.TabItem('Batch Process'): image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file") - upscaling_resize = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Resize", value=2) + with gr.Tabs(elem_id="extras_resize_mode"): + with gr.TabItem('Scale by'): + upscaling_resize = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Resize", value=2) + with gr.TabItem('Scale to'): + with gr.Group(): + with gr.Row(): + upscaling_resize_w = gr.Number(label="Width", value=512) + upscaling_resize_h = gr.Number(label="Height", value=512) + upscaling_crop = gr.Checkbox(label='Crop to fit', value=True) with gr.Group(): extras_upscaler_1 = gr.Radio(label='Upscaler 1', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") @@ -934,6 +942,7 @@ def create_ui(wrap_gradio_gpu_call): fn=wrap_gradio_gpu_call(modules.extras.run_extras), _js="get_extras_tab_index", inputs=[ + dummy_component, dummy_component, extras_image, image_batch, @@ -941,6 +950,9 @@ def create_ui(wrap_gradio_gpu_call): codeformer_visibility, codeformer_weight, upscaling_resize, + upscaling_resize_w, + upscaling_resize_h, + upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, @@ -951,14 +963,14 @@ def create_ui(wrap_gradio_gpu_call): html_info, ] ) - + extras_send_to_img2img.click( fn=lambda x: image_from_url_text(x), _js="extract_image_from_gallery_img2img", inputs=[result_images], outputs=[init_img], ) - + extras_send_to_inpaint.click( fn=lambda x: image_from_url_text(x), _js="extract_image_from_gallery_img2img", @@ -1286,7 +1298,7 @@ Requested path was: {f} outputs=[], _js='function(){restart_reload()}' ) - + if column is not None: column.__exit__() @@ -1318,12 +1330,12 @@ Requested path was: {f} component_dict[k] = component settings_interface.gradio_ref = demo - + with gr.Tabs() as tabs: for interface, label, ifid in interfaces: with gr.TabItem(label, id=ifid): interface.render() - + if os.path.exists(os.path.join(script_path, "notification.mp3")): audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False) @@ -1456,10 +1468,10 @@ Requested path was: {f} if getattr(obj,'custom_script_source',None) is not None: key = 'customscript/' + obj.custom_script_source + '/' + key - + if getattr(obj, 'do_not_save_to_config', False): return - + saved_value = ui_settings.get(key, None) if saved_value is None: ui_settings[key] = getattr(obj, field) @@ -1483,10 +1495,10 @@ Requested path was: {f} if type(x) == gr.Textbox: apply_field(x, 'value') - + if type(x) == gr.Number: apply_field(x, 'value') - + visit(txt2img_interface, loadsave, "txt2img") visit(img2img_interface, loadsave, "img2img") visit(extras_interface, loadsave, "extras") -- cgit v1.2.3 From 1f92336be768d235c18a82acb2195b7135101ae7 Mon Sep 17 00:00:00 2001 From: JC_Array Date: Sun, 9 Oct 2022 23:58:18 -0500 Subject: refactored the deepbooru module to improve speed on running multiple interogations in a row. Added the option to generate deepbooru tags for textual inversion preproccessing. --- modules/deepbooru.py | 84 +++++++++++++++++++++++++-------- modules/textual_inversion/preprocess.py | 22 ++++++++- modules/ui.py | 52 ++++++++++++++------ 3 files changed, 122 insertions(+), 36 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/deepbooru.py b/modules/deepbooru.py index 7e3c0618..cee4a3b4 100644 --- a/modules/deepbooru.py +++ b/modules/deepbooru.py @@ -1,21 +1,74 @@ import os.path from concurrent.futures import ProcessPoolExecutor -from multiprocessing import get_context +import multiprocessing -def _load_tf_and_return_tags(pil_image, threshold): +def get_deepbooru_tags(pil_image, threshold=0.5): + """ + This method is for running only one image at a time for simple use. Used to the img2img interrogate. + """ + from modules import shared # prevents circular reference + create_deepbooru_process(threshold) + shared.deepbooru_process_return["value"] = -1 + shared.deepbooru_process_queue.put(pil_image) + while shared.deepbooru_process_return["value"] == -1: + time.sleep(0.2) + release_process() + return ret + + +def deepbooru_process(queue, deepbooru_process_return, threshold): + model, tags = get_deepbooru_tags_model() + while True: # while process is running, keep monitoring queue for new image + pil_image = queue.get() + if pil_image == "QUIT": + break + else: + deepbooru_process_return["value"] = get_deepbooru_tags_from_model(model, tags, pil_image, threshold) + + +def create_deepbooru_process(threshold=0.5): + """ + Creates deepbooru process. A queue is created to send images into the process. This enables multiple images + to be processed in a row without reloading the model or creating a new process. To return the data, a shared + dictionary is created to hold the tags created. To wait for tags to be returned, a value of -1 is assigned + to the dictionary and the method adding the image to the queue should wait for this value to be updated with + the tags. + """ + from modules import shared # prevents circular reference + shared.deepbooru_process_manager = multiprocessing.Manager() + shared.deepbooru_process_queue = shared.deepbooru_process_manager.Queue() + shared.deepbooru_process_return = shared.deepbooru_process_manager.dict() + shared.deepbooru_process_return["value"] = -1 + shared.deepbooru_process = multiprocessing.Process(target=deepbooru_process, args=(shared.deepbooru_process_queue, shared.deepbooru_process_return, threshold)) + shared.deepbooru_process.start() + + +def release_process(): + """ + Stops the deepbooru process to return used memory + """ + from modules import shared # prevents circular reference + shared.deepbooru_process_queue.put("QUIT") + shared.deepbooru_process.join() + shared.deepbooru_process_queue = None + shared.deepbooru_process = None + shared.deepbooru_process_return = None + shared.deepbooru_process_manager = None + +def get_deepbooru_tags_model(): import deepdanbooru as dd import tensorflow as tf import numpy as np - this_folder = os.path.dirname(__file__) model_path = os.path.abspath(os.path.join(this_folder, '..', 'models', 'deepbooru')) if not os.path.exists(os.path.join(model_path, 'project.json')): # there is no point importing these every time import zipfile from basicsr.utils.download_util import load_file_from_url - load_file_from_url(r"https://github.com/KichangKim/DeepDanbooru/releases/download/v3-20211112-sgd-e28/deepdanbooru-v3-20211112-sgd-e28.zip", - model_path) + load_file_from_url( + r"https://github.com/KichangKim/DeepDanbooru/releases/download/v3-20211112-sgd-e28/deepdanbooru-v3-20211112-sgd-e28.zip", + model_path) with zipfile.ZipFile(os.path.join(model_path, "deepdanbooru-v3-20211112-sgd-e28.zip"), "r") as zip_ref: zip_ref.extractall(model_path) os.remove(os.path.join(model_path, "deepdanbooru-v3-20211112-sgd-e28.zip")) @@ -24,7 +77,13 @@ def _load_tf_and_return_tags(pil_image, threshold): model = dd.project.load_model_from_project( model_path, compile_model=True ) + return model, tags + +def get_deepbooru_tags_from_model(model, tags, pil_image, threshold=0.5): + import deepdanbooru as dd + import tensorflow as tf + import numpy as np width = model.input_shape[2] height = model.input_shape[1] image = np.array(pil_image) @@ -57,17 +116,4 @@ def _load_tf_and_return_tags(pil_image, threshold): print('\n'.join(sorted(result_tags_print, reverse=True))) - return ', '.join(result_tags_out).replace('_', ' ').replace(':', ' ') - - -def subprocess_init_no_cuda(): - import os - os.environ["CUDA_VISIBLE_DEVICES"] = "-1" - - -def get_deepbooru_tags(pil_image, threshold=0.5): - context = get_context('spawn') - with ProcessPoolExecutor(initializer=subprocess_init_no_cuda, mp_context=context) as executor: - f = executor.submit(_load_tf_and_return_tags, pil_image, threshold, ) - ret = f.result() # will rethrow any exceptions - return ret \ No newline at end of file + return ', '.join(result_tags_out).replace('_', ' ').replace(':', ' ') \ No newline at end of file diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index f1c002a2..9f63c9a4 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -3,11 +3,14 @@ from PIL import Image, ImageOps import platform import sys import tqdm +import time from modules import shared, images +from modules.shared import opts, cmd_opts +if cmd_opts.deepdanbooru: + import modules.deepbooru as deepbooru - -def preprocess(process_src, process_dst, process_flip, process_split, process_caption): +def preprocess(process_src, process_dst, process_flip, process_split, process_caption, process_caption_deepbooru=False): size = 512 src = os.path.abspath(process_src) dst = os.path.abspath(process_dst) @@ -24,10 +27,21 @@ def preprocess(process_src, process_dst, process_flip, process_split, process_ca if process_caption: shared.interrogator.load() + if process_caption_deepbooru: + deepbooru.create_deepbooru_process() + def save_pic_with_caption(image, index): if process_caption: caption = "-" + shared.interrogator.generate_caption(image) caption = sanitize_caption(os.path.join(dst, f"{index:05}-{subindex[0]}"), caption, ".png") + elif process_caption_deepbooru: + shared.deepbooru_process_return["value"] = -1 + shared.deepbooru_process_queue.put(image) + while shared.deepbooru_process_return["value"] == -1: + time.sleep(0.2) + caption = "-" + shared.deepbooru_process_return["value"] + caption = sanitize_caption(os.path.join(dst, f"{index:05}-{subindex[0]}"), caption, ".png") + shared.deepbooru_process_return["value"] = -1 else: caption = filename caption = os.path.splitext(caption)[0] @@ -79,6 +93,10 @@ def preprocess(process_src, process_dst, process_flip, process_split, process_ca if process_caption: shared.interrogator.send_blip_to_ram() + if process_caption_deepbooru: + deepbooru.release_process() + + def sanitize_caption(base_path, original_caption, suffix): operating_system = platform.system().lower() if (operating_system == "windows"): diff --git a/modules/ui.py b/modules/ui.py index 2231a8ed..179e3a83 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1034,6 +1034,9 @@ def create_ui(wrap_gradio_gpu_call): process_flip = gr.Checkbox(label='Create flipped copies') process_split = gr.Checkbox(label='Split oversized images into two') process_caption = gr.Checkbox(label='Use BLIP caption as filename') + if cmd_opts.deepdanbooru: + process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename') + with gr.Row(): with gr.Column(scale=3): @@ -1086,21 +1089,40 @@ def create_ui(wrap_gradio_gpu_call): ] ) - run_preprocess.click( - fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), - _js="start_training_textual_inversion", - inputs=[ - process_src, - process_dst, - process_flip, - process_split, - process_caption, - ], - outputs=[ - ti_output, - ti_outcome, - ], - ) + if cmd_opts.deepdanbooru: + # if process_caption_deepbooru is None, it will cause an error, as a result only include it if it is enabled + run_preprocess.click( + fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), + _js="start_training_textual_inversion", + inputs=[ + process_src, + process_dst, + process_flip, + process_split, + process_caption, + process_caption_deepbooru, + ], + outputs=[ + ti_output, + ti_outcome, + ], + ) + else: + run_preprocess.click( + fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), + _js="start_training_textual_inversion", + inputs=[ + process_src, + process_dst, + process_flip, + process_split, + process_caption, + ], + outputs=[ + ti_output, + ti_outcome, + ], + ) train_embedding.click( fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]), -- cgit v1.2.3 From 8a7c07a2140c98bceca858087525d77fd0352fda Mon Sep 17 00:00:00 2001 From: yfszzx Date: Mon, 10 Oct 2022 15:39:39 +0800 Subject: show image history --- javascript/images_history.js | 66 ++++++++++++++++++++++ javascript/jquery-3.6.0.min.js | 2 + modules/images_history.py | 90 ++++++++++++++++++++++++++++++ modules/ui.py | 11 +++- repositorieslatent-diffusion | 1 + testui.py | 124 +++++++++++++++++++++++++++++++++++++++++ 6 files changed, 292 insertions(+), 2 deletions(-) create mode 100644 javascript/images_history.js create mode 100644 javascript/jquery-3.6.0.min.js create mode 100644 modules/images_history.py create mode 160000 repositorieslatent-diffusion create mode 100644 testui.py (limited to 'modules/ui.py') diff --git a/javascript/images_history.js b/javascript/images_history.js new file mode 100644 index 00000000..f30b7eff --- /dev/null +++ b/javascript/images_history.js @@ -0,0 +1,66 @@ +function init_images_history(){ + if (gradioApp().getElementById('txt2img_images_history_first_page') == null) { + setTimeout(init_images_history, 1000) + } else { + tab_list = ["txt2img", "img2img"] + for (i in tab_list){ + tab = tab_list[i] + gradioApp().getElementById(tab + "_images_history_first_page").click() + $(gradioApp().getElementById(tab + '_images_history')).addClass("images_history_gallery") + item = $(gradioApp().getElementById(tab + '_images_history_set_index')) + item.addClass("images_history_set_index") + item.hide() + } + } + +} +setTimeout(init_images_history, 1000) +onUiUpdate(function(){ + fullImg_preview = gradioApp().querySelectorAll('#txt2img_images_history img.w-full') + if(fullImg_preview.length > 0){ + fullImg_preview.forEach(set_history_index_from_img); + } + fullImg_preview = gradioApp().querySelectorAll('#img2img_images_history img.w-full') + if(fullImg_preview.length > 0){ + fullImg_preview.forEach(set_history_index_from_img); + } +}) + +function set_history_gallery_index(item){ + buttons = item.find(".gallery-item") + // alert(item.attr("id") + " " + buttons.length) + index = -1 + i = 0 + buttons.each(function(){ + if($(this).hasClass("!ring-2")){ index = i } + i += 1 + }) + if (index == -1){ + setTimeout(set_history_gallery_index, 10, item) + } else { + item = item.find(".images_history_set_index").first() + item.attr("img_index", index) + item.click() + } +} +function set_history_index_from_img(e){ + if(e && e.parentElement.tagName == 'BUTTON'){ + bnt = $(e).parent() + if (bnt.hasClass("transform")){ + bnt.off("click").on("click",function(){ + set_history_gallery_index($(this).parents(".images_history_gallery").first()) + }) + } else { + bnt.off("mousedown").on("mousedown", function(){ + set_history_gallery_index($(this).parents(".images_history_gallery").first()) + }) + + } + } +} +function images_history_get_current_img(is_image2image){ + head = is_image2image?"img2img":"txt2img" + s = $(gradioApp().getElementById(head + '_images_history_set_index')).attr("img_index") + return s +} + diff --git a/javascript/jquery-3.6.0.min.js b/javascript/jquery-3.6.0.min.js new file mode 100644 index 00000000..c4c6022f --- /dev/null +++ b/javascript/jquery-3.6.0.min.js @@ -0,0 +1,2 @@ +/*! jQuery v3.6.0 | (c) OpenJS Foundation and other contributors | jquery.org/license */ +!function(e,t){"use strict";"object"==typeof module&&"object"==typeof module.exports?module.exports=e.document?t(e,!0):function(e){if(!e.document)throw new Error("jQuery requires a window with a document");return t(e)}:t(e)}("undefined"!=typeof window?window:this,function(C,e){"use strict";var t=[],r=Object.getPrototypeOf,s=t.slice,g=t.flat?function(e){return t.flat.call(e)}:function(e){return t.concat.apply([],e)},u=t.push,i=t.indexOf,n={},o=n.toString,v=n.hasOwnProperty,a=v.toString,l=a.call(Object),y={},m=function(e){return"function"==typeof e&&"number"!=typeof 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1) * num + file_list = file_list[idx_frm:idx_frm + num] + print(f"Loading history page {page_index}") + return [os.path.join(dir_name, file) for file in file_list], page_index, file_list +def first_page_click(is_img2img, dir_name): + return get_recent_images(is_img2img, dir_name, 1, 0) +def end_page_click(is_img2img, dir_name): + return get_recent_images(is_img2img, dir_name, -1, 0) +def prev_page_click(is_img2img, dir_name, page_index): + return get_recent_images(is_img2img, dir_name, page_index, -1) +def next_page_click(is_img2img, dir_name, page_index): + return get_recent_images(is_img2img, dir_name, page_index, 1) +def page_index_change(is_img2img, dir_name, page_index): + return get_recent_images(is_img2img, dir_name, page_index, 0) +def show_image_info(num, filenames): + return filenames[int(num)] +def delete_image(is_img2img, dir_name, name, page_index, filenames): + path = os.path.join(dir_name, name) + if os.path.exists(path): + print(f"Delete file {path}") + os.remove(path) + i = 0 + for f in filenames: + if f == name: + break + i += 1 + images, page_index, file_list = get_recent_images(is_img2img, dir_name, page_index, 0) + current_file = file_list[i] if i < len(file_list) else None + return images, page_index, file_list, current_file + + +def show_images_history(gr, opts, is_img2img): + def id_name(is_img2img, name): + return ("img2img" if is_img2img else "txt2img") + "_" + name + with gr.Row(): + if is_img2img: + dir_name = opts.outdir_img2img_samples + else: + dir_name = opts.outdir_txt2img_samples + first_page = gr.Button('First Page', elem_id=id_name(is_img2img,"images_history_first_page")) + prev_page = gr.Button('Prev Page') + page_index = gr.Number(value=1) + next_page = gr.Button('Next Page') + end_page = gr.Button('End Page') + with gr.Row(): + delete = gr.Button('Delete') + Send = gr.Button('Send') + with gr.Row(): + with gr.Column(elem_id=id_name(is_img2img,"images_history")): + history_gallery = gr.Gallery(label="Images history").style(grid=6) + img_file_name = gr.Textbox() + img_file_info = gr.Textbox(dir_name) + img_path = gr.Textbox(dir_name, visible=False) + set_index = gr.Button('set_index', elem_id=id_name(is_img2img,"images_history_set_index")) + is_img2img_flag = gr.Checkbox(is_img2img, visible=False) + filenames = gr.State() + first_page.click(first_page_click, inputs=[is_img2img_flag, img_path], outputs=[history_gallery, page_index, filenames]) + next_page.click(next_page_click, inputs=[is_img2img_flag, img_path, page_index], outputs=[history_gallery, page_index, filenames]) + prev_page.click(prev_page_click, inputs=[is_img2img_flag, img_path, page_index], outputs=[history_gallery, page_index, filenames]) + end_page.click(end_page_click, inputs=[is_img2img_flag, img_path], outputs=[history_gallery, page_index, filenames]) + page_index.submit(page_index_change, inputs=[is_img2img_flag, img_path, page_index], outputs=[history_gallery, page_index, filenames]) + set_index.click(show_image_info, _js="images_history_get_current_img",inputs=[is_img2img_flag, filenames], outputs=img_file_name) + delete.click(delete_image, inputs=[is_img2img_flag, img_path, img_file_name, page_index, filenames], outputs=[history_gallery, page_index, filenames,img_file_name]) + #page_index.change(page_index_change, inputs=[is_img2img_flag, img_path, page_index], outputs=[history_gallery, page_index]) + +def create_history_tabs(gr, opts): + with gr.Blocks(analytics_enabled=False) as images_history: + with gr.Tabs() as tabs: + with gr.Tab("txt2img history", id="images_history_txt2img"): + with gr.Blocks(analytics_enabled=False) as images_history_txt2img: + show_images_history(gr, opts, is_img2img=False) + with gr.Tab("img2img history", id="images_history_img2img"): + with gr.Blocks(analytics_enabled=False) as images_history_img2img: + show_images_history(gr, opts, is_img2img=True) + return images_history diff --git a/modules/ui.py b/modules/ui.py index 4f18126f..8762fcf5 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -37,6 +37,7 @@ import modules.generation_parameters_copypaste from modules import prompt_parser from modules.images import save_image import modules.textual_inversion.ui +import modules.images_history as img_his # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI mimetypes.init() @@ -499,7 +500,6 @@ def create_ui(wrap_gradio_gpu_call): custom_inputs = modules.scripts.scripts_txt2img.setup_ui(is_img2img=False) with gr.Column(variant='panel'): - with gr.Group(): txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False) txt2img_gallery = gr.Gallery(label='Output', show_label=False, elem_id='txt2img_gallery').style(grid=4) @@ -516,6 +516,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Group(): html_info = gr.HTML() generation_info = gr.Textbox(visible=False) + connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) @@ -607,6 +608,7 @@ def create_ui(wrap_gradio_gpu_call): ] modules.generation_parameters_copypaste.connect_paste(paste, txt2img_paste_fields, txt2img_prompt) token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter]) + with gr.Blocks(analytics_enabled=False) as img2img_interface: img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True) @@ -696,6 +698,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Group(): html_info = gr.HTML() generation_info = gr.Textbox(visible=False) + connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) @@ -1126,8 +1129,10 @@ def create_ui(wrap_gradio_gpu_call): opts.save(shared.config_filename) - return f'{changed} settings changed.', opts.dumpjson() + return f'{changed} settings changed.', opts.dumpjson() + + images_history = img_his.create_history_tabs(gr, opts) with gr.Blocks(analytics_enabled=False) as settings_interface: settings_submit = gr.Button(value="Apply settings", variant='primary') result = gr.HTML() @@ -1206,7 +1211,9 @@ def create_ui(wrap_gradio_gpu_call): (pnginfo_interface, "PNG Info", "pnginfo"), (modelmerger_interface, "Checkpoint Merger", "modelmerger"), (textual_inversion_interface, "Textual inversion", "ti"), + (images_history, "History", "images_history"), (settings_interface, "Settings", "settings"), + ] with open(os.path.join(script_path, "style.css"), "r", encoding="utf8") as file: diff --git a/repositorieslatent-diffusion b/repositorieslatent-diffusion new file mode 160000 index 00000000..abf33e70 --- /dev/null +++ b/repositorieslatent-diffusion @@ -0,0 +1 @@ +Subproject commit abf33e7002d59d9085081bce93ec798dcabd49af diff --git a/testui.py b/testui.py new file mode 100644 index 00000000..f54e4a62 --- /dev/null +++ b/testui.py @@ -0,0 +1,124 @@ +import os +import threading +import time +import importlib +import signal +import threading + +from modules.paths import script_path + +from modules import devices, sd_samplers +import modules.codeformer_model as codeformer +import modules.extras +import modules.face_restoration +import modules.gfpgan_model as gfpgan +import modules.img2img + +import modules.lowvram +import modules.paths +import modules.scripts +import modules.sd_hijack +import modules.sd_models +import modules.shared as shared +import modules.txt2img + +import modules.ui +from modules import devices +from modules import modelloader +from modules.paths import script_path +from modules.shared import cmd_opts + +modelloader.cleanup_models() +modules.sd_models.setup_model() +codeformer.setup_model(cmd_opts.codeformer_models_path) +gfpgan.setup_model(cmd_opts.gfpgan_models_path) +shared.face_restorers.append(modules.face_restoration.FaceRestoration()) +modelloader.load_upscalers() +queue_lock = threading.Lock() + + +def wrap_queued_call(func): + def f(*args, **kwargs): + with queue_lock: + res = func(*args, **kwargs) + + return res + + return f + + +def wrap_gradio_gpu_call(func, extra_outputs=None): + def f(*args, **kwargs): + devices.torch_gc() + + shared.state.sampling_step = 0 + shared.state.job_count = -1 + shared.state.job_no = 0 + shared.state.job_timestamp = shared.state.get_job_timestamp() + shared.state.current_latent = None + shared.state.current_image = None + shared.state.current_image_sampling_step = 0 + shared.state.interrupted = False + shared.state.textinfo = None + + with queue_lock: + res = func(*args, **kwargs) + + shared.state.job = "" + shared.state.job_count = 0 + + devices.torch_gc() + + return res + + return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs) + + +modules.scripts.load_scripts(os.path.join(script_path, "scripts")) + +shared.sd_model = None #modules.sd_models.load_model() +#shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model))) + + +def webui(): + # make the program just exit at ctrl+c without waiting for anything + def sigint_handler(sig, frame): + print(f'Interrupted with signal {sig} in {frame}') + os._exit(0) + + signal.signal(signal.SIGINT, sigint_handler) + + while 1: + + demo = modules.ui.create_ui(wrap_gradio_gpu_call=wrap_gradio_gpu_call) + + demo.launch( + share=cmd_opts.share, + server_name="0.0.0.0" if cmd_opts.listen else None, + server_port=cmd_opts.port, + debug=cmd_opts.gradio_debug, + auth=[tuple(cred.split(':')) for cred in cmd_opts.gradio_auth.strip('"').split(',')] if cmd_opts.gradio_auth else None, + inbrowser=cmd_opts.autolaunch, + prevent_thread_lock=True + ) + + while 1: + time.sleep(0.5) + if getattr(demo, 'do_restart', False): + time.sleep(0.5) + demo.close() + time.sleep(0.5) + break + + sd_samplers.set_samplers() + + print('Reloading Custom Scripts') + modules.scripts.reload_scripts(os.path.join(script_path, "scripts")) + print('Reloading modules: modules.ui') + importlib.reload(modules.ui) + print('Restarting Gradio') + + + +if __name__ == "__main__": + webui() -- cgit v1.2.3 From 8ec069e64df48f8f202f8b93a08e91b69448eb39 Mon Sep 17 00:00:00 2001 From: JC_Array Date: Mon, 10 Oct 2022 03:23:24 -0500 Subject: removed duplicate run_preprocess.click by creating run_preprocess_inputs list and appending deepbooru variable to input list if in scope --- modules/ui.py | 49 +++++++++++++++++-------------------------------- 1 file changed, 17 insertions(+), 32 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 179e3a83..22ca74c2 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1089,40 +1089,25 @@ def create_ui(wrap_gradio_gpu_call): ] ) + run_preprocess_inputs = [ + process_src, + process_dst, + process_flip, + process_split, + process_caption, + ] if cmd_opts.deepdanbooru: # if process_caption_deepbooru is None, it will cause an error, as a result only include it if it is enabled - run_preprocess.click( - fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), - _js="start_training_textual_inversion", - inputs=[ - process_src, - process_dst, - process_flip, - process_split, - process_caption, - process_caption_deepbooru, - ], - outputs=[ - ti_output, - ti_outcome, - ], - ) - else: - run_preprocess.click( - fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), - _js="start_training_textual_inversion", - inputs=[ - process_src, - process_dst, - process_flip, - process_split, - process_caption, - ], - outputs=[ - ti_output, - ti_outcome, - ], - ) + run_preprocess_inputs.append(process_caption_deepbooru) + run_preprocess.click( + fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), + _js="start_training_textual_inversion", + inputs=run_preprocess_inputs, + outputs=[ + ti_output, + ti_outcome, + ], + ) train_embedding.click( fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]), -- cgit v1.2.3 From 2f94331df2cb1181439adecc28cfd758049f6501 Mon Sep 17 00:00:00 2001 From: JC_Array Date: Mon, 10 Oct 2022 03:34:00 -0500 Subject: removed change in last commit, simplified to adding the visible argument to process_caption_deepbooru and it set to False if deepdanbooru argument is not set --- modules/ui.py | 22 ++++++++++------------ 1 file changed, 10 insertions(+), 12 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 22ca74c2..f8adafb3 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1036,7 +1036,8 @@ def create_ui(wrap_gradio_gpu_call): process_caption = gr.Checkbox(label='Use BLIP caption as filename') if cmd_opts.deepdanbooru: process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename') - + else: + process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename', visible=False) with gr.Row(): with gr.Column(scale=3): @@ -1089,20 +1090,17 @@ def create_ui(wrap_gradio_gpu_call): ] ) - run_preprocess_inputs = [ - process_src, - process_dst, - process_flip, - process_split, - process_caption, - ] - if cmd_opts.deepdanbooru: - # if process_caption_deepbooru is None, it will cause an error, as a result only include it if it is enabled - run_preprocess_inputs.append(process_caption_deepbooru) run_preprocess.click( fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), _js="start_training_textual_inversion", - inputs=run_preprocess_inputs, + inputs=[ + process_src, + process_dst, + process_flip, + process_split, + process_caption, + process_caption_deepbooru + ], outputs=[ ti_output, ti_outcome, -- cgit v1.2.3 From 23f2989799ee3911d2959cfceb74b921f20c9a51 Mon Sep 17 00:00:00 2001 From: yfszzx Date: Mon, 10 Oct 2022 18:33:49 +0800 Subject: images history over --- javascript/images_history.js | 4 +- modules/images_history.py | 141 ++++++++++++++++++++++++++----------------- modules/ui.py | 9 ++- testui.py | 124 ------------------------------------- 4 files changed, 94 insertions(+), 184 deletions(-) delete mode 100644 testui.py (limited to 'modules/ui.py') diff --git a/javascript/images_history.js b/javascript/images_history.js index f30b7eff..93d2b89a 100644 --- a/javascript/images_history.js +++ b/javascript/images_history.js @@ -58,9 +58,9 @@ function set_history_index_from_img(e){ } } } -function images_history_get_current_img(is_image2image){ +function images_history_get_current_img(is_image2image, image_path, files){ head = is_image2image?"img2img":"txt2img" s = $(gradioApp().getElementById(head + '_images_history_set_index')).attr("img_index") - return s + return [s, image_path, files] } diff --git a/modules/images_history.py b/modules/images_history.py index 23d83557..0e0a48f3 100644 --- a/modules/images_history.py +++ b/modules/images_history.py @@ -1,5 +1,6 @@ import os -def get_recent_images(is_img2img, dir_name, page_index, step): +def get_recent_images(dir_name, page_index, step, image_index): + print(image_index) page_index = int(page_index) f_list = os.listdir(dir_name) file_list = [] @@ -8,7 +9,7 @@ def get_recent_images(is_img2img, dir_name, page_index, step): continue file_list.append(file) file_list = sorted(file_list, key=lambda file: -os.path.getctime(os.path.join(dir_name, file))) - num = 24 + num = 48 max_page_index = len(file_list) // num + 1 page_index = max_page_index if page_index == -1 else page_index + step page_index = 1 if page_index < 1 else page_index @@ -16,75 +17,101 @@ def get_recent_images(is_img2img, dir_name, page_index, step): idx_frm = (page_index - 1) * num file_list = file_list[idx_frm:idx_frm + num] print(f"Loading history page {page_index}") - return [os.path.join(dir_name, file) for file in file_list], page_index, file_list -def first_page_click(is_img2img, dir_name): - return get_recent_images(is_img2img, dir_name, 1, 0) -def end_page_click(is_img2img, dir_name): - return get_recent_images(is_img2img, dir_name, -1, 0) -def prev_page_click(is_img2img, dir_name, page_index): - return get_recent_images(is_img2img, dir_name, page_index, -1) -def next_page_click(is_img2img, dir_name, page_index): - return get_recent_images(is_img2img, dir_name, page_index, 1) -def page_index_change(is_img2img, dir_name, page_index): - return get_recent_images(is_img2img, dir_name, page_index, 0) -def show_image_info(num, filenames): - return filenames[int(num)] -def delete_image(is_img2img, dir_name, name, page_index, filenames): + image_index = int(image_index) + if image_index < 0 or image_index > len(file_list) - 1: + current_file = None + hide_image = None + else: + current_file = file_list[int(image_index)] + hide_image = os.path.join(dir_name, current_file) + return [os.path.join(dir_name, file) for file in file_list], page_index, file_list, current_file, hide_image +def first_page_click(dir_name, page_index, image_index): + return get_recent_images(dir_name, 1, 0, image_index) +def end_page_click(dir_name, page_index, image_index): + return get_recent_images(dir_name, -1, 0, image_index) +def prev_page_click(dir_name, page_index, image_index): + return get_recent_images(dir_name, page_index, -1, image_index) +def next_page_click(dir_name, page_index, image_index): + return get_recent_images(dir_name, page_index, 1, image_index) +def page_index_change(dir_name, page_index, image_index): + return get_recent_images(dir_name, page_index, 0, image_index) + +def show_image_info(num, image_path, filenames): + file = filenames[int(num)] + return file, num, os.path.join(image_path, file) +def delete_image(is_img2img, dir_name, name, page_index, filenames, image_index): + print("filename", name) path = os.path.join(dir_name, name) if os.path.exists(path): print(f"Delete file {path}") os.remove(path) - i = 0 - for f in filenames: - if f == name: - break - i += 1 - images, page_index, file_list = get_recent_images(is_img2img, dir_name, page_index, 0) - current_file = file_list[i] if i < len(file_list) else None - return images, page_index, file_list, current_file + images, page_index, file_list, current_file, hide_image = get_recent_images(dir_name, page_index, 0, image_index) + return images, page_index, file_list, current_file, hide_image -def show_images_history(gr, opts, is_img2img): +def show_images_history(gr, opts, is_img2img, run_pnginfo, switch_dict): def id_name(is_img2img, name): return ("img2img" if is_img2img else "txt2img") + "_" + name - with gr.Row(): - if is_img2img: - dir_name = opts.outdir_img2img_samples - else: - dir_name = opts.outdir_txt2img_samples - first_page = gr.Button('First Page', elem_id=id_name(is_img2img,"images_history_first_page")) - prev_page = gr.Button('Prev Page') - page_index = gr.Number(value=1) - next_page = gr.Button('Next Page') - end_page = gr.Button('End Page') - with gr.Row(): - delete = gr.Button('Delete') - Send = gr.Button('Send') - with gr.Row(): - with gr.Column(elem_id=id_name(is_img2img,"images_history")): - history_gallery = gr.Gallery(label="Images history").style(grid=6) - img_file_name = gr.Textbox() - img_file_info = gr.Textbox(dir_name) - img_path = gr.Textbox(dir_name, visible=False) - set_index = gr.Button('set_index', elem_id=id_name(is_img2img,"images_history_set_index")) - is_img2img_flag = gr.Checkbox(is_img2img, visible=False) - filenames = gr.State() - first_page.click(first_page_click, inputs=[is_img2img_flag, img_path], outputs=[history_gallery, page_index, filenames]) - next_page.click(next_page_click, inputs=[is_img2img_flag, img_path, page_index], outputs=[history_gallery, page_index, filenames]) - prev_page.click(prev_page_click, inputs=[is_img2img_flag, img_path, page_index], outputs=[history_gallery, page_index, filenames]) - end_page.click(end_page_click, inputs=[is_img2img_flag, img_path], outputs=[history_gallery, page_index, filenames]) - page_index.submit(page_index_change, inputs=[is_img2img_flag, img_path, page_index], outputs=[history_gallery, page_index, filenames]) - set_index.click(show_image_info, _js="images_history_get_current_img",inputs=[is_img2img_flag, filenames], outputs=img_file_name) - delete.click(delete_image, inputs=[is_img2img_flag, img_path, img_file_name, page_index, filenames], outputs=[history_gallery, page_index, filenames,img_file_name]) + if is_img2img: + dir_name = opts.outdir_img2img_samples + else: + dir_name = opts.outdir_txt2img_samples + with gr.Row(): + first_page = gr.Button('First', elem_id=id_name(is_img2img,"images_history_first_page")) + prev_page = gr.Button('Prev') + page_index = gr.Number(value=1, label="Page Index") + next_page = gr.Button('Next') + end_page = gr.Button('End') + with gr.Row(elem_id=id_name(is_img2img,"images_history")): + with gr.Row(): + with gr.Column(): + history_gallery = gr.Gallery(show_label=False).style(grid=6) + with gr.Column(): + with gr.Row(): + delete = gr.Button('Delete') + pnginfo_send_to_txt2img = gr.Button('Send to txt2img') + pnginfo_send_to_img2img = gr.Button('Send to img2img') + with gr.Row(): + with gr.Column(): + img_file_info = gr.Textbox(dir_name, label="Generate Info") + img_file_name = gr.Textbox(label="File Name") + with gr.Row(): + # hiden items + img_path = gr.Textbox(dir_name, visible=False) + is_img2img_flag = gr.Checkbox(is_img2img, visible=False) + image_index = gr.Textbox(value=-1, visible=False) + set_index = gr.Button('set_index', elem_id=id_name(is_img2img,"images_history_set_index")) + filenames = gr.State() + hide_image = gr.Image(visible=False, type="pil") + info1 = gr.Textbox(visible=False) + info2 = gr.Textbox(visible=False) + + + # turn pages + gallery_inputs = [img_path, page_index, image_index] + gallery_outputs = [history_gallery, page_index, filenames, img_file_name, hide_image] + first_page.click(first_page_click, inputs=gallery_inputs, outputs=gallery_outputs) + next_page.click(next_page_click, inputs=gallery_inputs, outputs=gallery_outputs) + prev_page.click(prev_page_click, inputs=gallery_inputs, outputs=gallery_outputs) + end_page.click(end_page_click, inputs=gallery_inputs, outputs=gallery_outputs) + page_index.submit(page_index_change, inputs=gallery_inputs, outputs=gallery_outputs) #page_index.change(page_index_change, inputs=[is_img2img_flag, img_path, page_index], outputs=[history_gallery, page_index]) + + #other funcitons + set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[is_img2img_flag, img_path, filenames], outputs=[img_file_name, image_index, hide_image]) + delete.click(delete_image, inputs=[is_img2img_flag, img_path, img_file_name, page_index, filenames, image_index], outputs=gallery_outputs) + hide_image.change(fn=run_pnginfo, inputs=[hide_image], outputs=[info1, img_file_info, info2]) + switch_dict["fn"](pnginfo_send_to_txt2img, switch_dict["t2i"], img_file_info, 'switch_to_txt2img') + switch_dict["fn"](pnginfo_send_to_img2img, switch_dict["i2i"], img_file_info, 'switch_to_img2img_img2img') + -def create_history_tabs(gr, opts): +def create_history_tabs(gr, opts, run_pnginfo, switch_dict): with gr.Blocks(analytics_enabled=False) as images_history: with gr.Tabs() as tabs: with gr.Tab("txt2img history", id="images_history_txt2img"): with gr.Blocks(analytics_enabled=False) as images_history_txt2img: - show_images_history(gr, opts, is_img2img=False) + show_images_history(gr, opts, False, run_pnginfo, switch_dict) with gr.Tab("img2img history", id="images_history_img2img"): with gr.Blocks(analytics_enabled=False) as images_history_img2img: - show_images_history(gr, opts, is_img2img=True) + show_images_history(gr, opts, True, run_pnginfo, switch_dict) return images_history diff --git a/modules/ui.py b/modules/ui.py index 8762fcf5..21c9236b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1131,8 +1131,15 @@ def create_ui(wrap_gradio_gpu_call): return f'{changed} settings changed.', opts.dumpjson() + #images history + images_history_switch_dict = { + "fn":modules.generation_parameters_copypaste.connect_paste, + "t2i":txt2img_paste_fields, + "i2i":img2img_paste_fields + } + images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) - images_history = img_his.create_history_tabs(gr, opts) + with gr.Blocks(analytics_enabled=False) as settings_interface: settings_submit = gr.Button(value="Apply settings", variant='primary') result = gr.HTML() diff --git a/testui.py b/testui.py deleted file mode 100644 index f54e4a62..00000000 --- a/testui.py +++ /dev/null @@ -1,124 +0,0 @@ -import os -import threading -import time -import importlib -import signal -import threading - -from modules.paths import script_path - -from modules import devices, sd_samplers -import modules.codeformer_model as codeformer -import modules.extras -import modules.face_restoration -import modules.gfpgan_model as gfpgan -import modules.img2img - -import modules.lowvram -import modules.paths -import modules.scripts -import modules.sd_hijack -import modules.sd_models -import modules.shared as shared -import modules.txt2img - -import modules.ui -from modules import devices -from modules import modelloader -from modules.paths import script_path -from modules.shared import cmd_opts - -modelloader.cleanup_models() -modules.sd_models.setup_model() -codeformer.setup_model(cmd_opts.codeformer_models_path) -gfpgan.setup_model(cmd_opts.gfpgan_models_path) -shared.face_restorers.append(modules.face_restoration.FaceRestoration()) -modelloader.load_upscalers() -queue_lock = threading.Lock() - - -def wrap_queued_call(func): - def f(*args, **kwargs): - with queue_lock: - res = func(*args, **kwargs) - - return res - - return f - - -def wrap_gradio_gpu_call(func, extra_outputs=None): - def f(*args, **kwargs): - devices.torch_gc() - - shared.state.sampling_step = 0 - shared.state.job_count = -1 - shared.state.job_no = 0 - shared.state.job_timestamp = shared.state.get_job_timestamp() - shared.state.current_latent = None - shared.state.current_image = None - shared.state.current_image_sampling_step = 0 - shared.state.interrupted = False - shared.state.textinfo = None - - with queue_lock: - res = func(*args, **kwargs) - - shared.state.job = "" - shared.state.job_count = 0 - - devices.torch_gc() - - return res - - return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs) - - -modules.scripts.load_scripts(os.path.join(script_path, "scripts")) - -shared.sd_model = None #modules.sd_models.load_model() -#shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model))) - - -def webui(): - # make the program just exit at ctrl+c without waiting for anything - def sigint_handler(sig, frame): - print(f'Interrupted with signal {sig} in {frame}') - os._exit(0) - - signal.signal(signal.SIGINT, sigint_handler) - - while 1: - - demo = modules.ui.create_ui(wrap_gradio_gpu_call=wrap_gradio_gpu_call) - - demo.launch( - share=cmd_opts.share, - server_name="0.0.0.0" if cmd_opts.listen else None, - server_port=cmd_opts.port, - debug=cmd_opts.gradio_debug, - auth=[tuple(cred.split(':')) for cred in cmd_opts.gradio_auth.strip('"').split(',')] if cmd_opts.gradio_auth else None, - inbrowser=cmd_opts.autolaunch, - prevent_thread_lock=True - ) - - while 1: - time.sleep(0.5) - if getattr(demo, 'do_restart', False): - time.sleep(0.5) - demo.close() - time.sleep(0.5) - break - - sd_samplers.set_samplers() - - print('Reloading Custom Scripts') - modules.scripts.reload_scripts(os.path.join(script_path, "scripts")) - print('Reloading modules: modules.ui') - importlib.reload(modules.ui) - print('Restarting Gradio') - - - -if __name__ == "__main__": - webui() -- cgit v1.2.3 From ea00c1624bbb0dcb5be07f59c9509061baddf5b1 Mon Sep 17 00:00:00 2001 From: alg-wiki Date: Mon, 10 Oct 2022 17:07:46 +0900 Subject: Textual Inversion: Added custom training image size and number of repeats per input image in a single epoch --- modules/textual_inversion/dataset.py | 6 +++--- modules/textual_inversion/preprocess.py | 4 ++-- modules/textual_inversion/textual_inversion.py | 15 ++++++++++++--- modules/ui.py | 8 +++++++- 4 files changed, 24 insertions(+), 9 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py index 7c44ea5b..acc4ce59 100644 --- a/modules/textual_inversion/dataset.py +++ b/modules/textual_inversion/dataset.py @@ -15,13 +15,13 @@ re_tag = re.compile(r"[a-zA-Z][_\w\d()]+") class PersonalizedBase(Dataset): - def __init__(self, data_root, size=None, repeats=100, flip_p=0.5, placeholder_token="*", width=512, height=512, model=None, device=None, template_file=None): + def __init__(self, data_root, size, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None): self.placeholder_token = placeholder_token self.size = size - self.width = width - self.height = height + self.width = size + self.height = size self.flip = transforms.RandomHorizontalFlip(p=flip_p) self.dataset = [] diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index f1c002a2..b3de6fd7 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -7,8 +7,8 @@ import tqdm from modules import shared, images -def preprocess(process_src, process_dst, process_flip, process_split, process_caption): - size = 512 +def preprocess(process_src, process_dst, process_size, process_flip, process_split, process_caption): + size = process_size src = os.path.abspath(process_src) dst = os.path.abspath(process_dst) diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index cd9f3498..e34dc2e8 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -6,6 +6,7 @@ import torch import tqdm import html import datetime +import math from modules import shared, devices, sd_hijack, processing, sd_models @@ -156,7 +157,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'): return fn -def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps, create_image_every, save_embedding_every, template_file): +def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_size, steps, num_repeats, create_image_every, save_embedding_every, template_file): assert embedding_name, 'embedding not selected' shared.state.textinfo = "Initializing textual inversion training..." @@ -182,7 +183,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps, shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..." with torch.autocast("cuda"): - ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=512, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file) + ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=training_size, repeats=num_repeats, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file) hijack = sd_hijack.model_hijack @@ -200,6 +201,9 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps, if ititial_step > steps: return embedding, filename + tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root)]) + epoch_len = (tr_img_len * num_repeats) + tr_img_len + pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step) for i, (x, text) in pbar: embedding.step = i + ititial_step @@ -223,7 +227,10 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps, loss.backward() optimizer.step() - pbar.set_description(f"loss: {losses.mean():.7f}") + epoch_num = math.floor(embedding.step / epoch_len) + epoch_step = embedding.step - (epoch_num * epoch_len) + + pbar.set_description(f"[Epoch {epoch_num}: {epoch_step}/{epoch_len}]loss: {losses.mean():.7f}") if embedding.step > 0 and embedding_dir is not None and embedding.step % save_embedding_every == 0: last_saved_file = os.path.join(embedding_dir, f'{embedding_name}-{embedding.step}.pt') @@ -236,6 +243,8 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps, sd_model=shared.sd_model, prompt=text, steps=20, + height=training_size, + width=training_size, do_not_save_grid=True, do_not_save_samples=True, ) diff --git a/modules/ui.py b/modules/ui.py index 2231a8ed..f821fd8d 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1029,6 +1029,7 @@ def create_ui(wrap_gradio_gpu_call): process_src = gr.Textbox(label='Source directory') process_dst = gr.Textbox(label='Destination directory') + process_size = gr.Slider(minimum=64, maximum=2048, step=64, label="Size (width and height)", value=512) with gr.Row(): process_flip = gr.Checkbox(label='Create flipped copies') @@ -1043,13 +1044,15 @@ def create_ui(wrap_gradio_gpu_call): run_preprocess = gr.Button(value="Preprocess", variant='primary') with gr.Group(): - gr.HTML(value="

Train an embedding; must specify a directory with a set of 512x512 images

") + gr.HTML(value="

Train an embedding; must specify a directory with a set of 1:1 ratio images

") train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) learn_rate = gr.Number(label='Learning rate', value=5.0e-03) dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images") log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion") template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt")) + training_size = gr.Slider(minimum=64, maximum=2048, step=64, label="Size (width and height)", value=512) steps = gr.Number(label='Max steps', value=100000, precision=0) + num_repeats = gr.Number(label='Number of repeats for a single input image per epoch', value=100, precision=0) create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0) save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0) @@ -1092,6 +1095,7 @@ def create_ui(wrap_gradio_gpu_call): inputs=[ process_src, process_dst, + process_size, process_flip, process_split, process_caption, @@ -1110,7 +1114,9 @@ def create_ui(wrap_gradio_gpu_call): learn_rate, dataset_directory, log_directory, + training_size, steps, + num_repeats, create_image_every, save_embedding_every, template_file, -- cgit v1.2.3 From 7a20f914eddfdf09c0ccced157ec108205bc3d0f Mon Sep 17 00:00:00 2001 From: alg-wiki Date: Mon, 10 Oct 2022 22:35:35 +0900 Subject: Custom Width and Height --- modules/textual_inversion/dataset.py | 7 +++---- modules/textual_inversion/preprocess.py | 19 ++++++++++--------- modules/textual_inversion/textual_inversion.py | 11 +++++------ modules/ui.py | 12 ++++++++---- 4 files changed, 26 insertions(+), 23 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py index acc4ce59..bcf772d2 100644 --- a/modules/textual_inversion/dataset.py +++ b/modules/textual_inversion/dataset.py @@ -15,13 +15,12 @@ re_tag = re.compile(r"[a-zA-Z][_\w\d()]+") class PersonalizedBase(Dataset): - def __init__(self, data_root, size, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None): + def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None): self.placeholder_token = placeholder_token - self.size = size - self.width = size - self.height = size + self.width = width + self.height = height self.flip = transforms.RandomHorizontalFlip(p=flip_p) self.dataset = [] diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index b3de6fd7..d7efdef2 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -7,8 +7,9 @@ import tqdm from modules import shared, images -def preprocess(process_src, process_dst, process_size, process_flip, process_split, process_caption): - size = process_size +def preprocess(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption): + width = process_width + height = process_height src = os.path.abspath(process_src) dst = os.path.abspath(process_dst) @@ -55,23 +56,23 @@ def preprocess(process_src, process_dst, process_size, process_flip, process_spl is_wide = ratio < 1 / 1.35 if process_split and is_tall: - img = img.resize((size, size * img.height // img.width)) + img = img.resize((width, height * img.height // img.width)) - top = img.crop((0, 0, size, size)) + top = img.crop((0, 0, width, height)) save_pic(top, index) - bot = img.crop((0, img.height - size, size, img.height)) + bot = img.crop((0, img.height - height, width, img.height)) save_pic(bot, index) elif process_split and is_wide: - img = img.resize((size * img.width // img.height, size)) + img = img.resize((width * img.width // img.height, height)) - left = img.crop((0, 0, size, size)) + left = img.crop((0, 0, width, height)) save_pic(left, index) - right = img.crop((img.width - size, 0, img.width, size)) + right = img.crop((img.width - width, 0, img.width, height)) save_pic(right, index) else: - img = images.resize_image(1, img, size, size) + img = images.resize_image(1, img, width, height) save_pic(img, index) shared.state.nextjob() diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 769682ea..5965c5a0 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -6,7 +6,6 @@ import torch import tqdm import html import datetime -import math from modules import shared, devices, sd_hijack, processing, sd_models @@ -157,7 +156,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'): return fn -def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_size, steps, num_repeats, create_image_every, save_embedding_every, template_file): +def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, num_repeats, create_image_every, save_embedding_every, template_file): assert embedding_name, 'embedding not selected' shared.state.textinfo = "Initializing textual inversion training..." @@ -183,7 +182,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..." with torch.autocast("cuda"): - ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=training_size, repeats=num_repeats, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file) + ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=num_repeats, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file) hijack = sd_hijack.model_hijack @@ -227,7 +226,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini loss.backward() optimizer.step() - epoch_num = math.floor(embedding.step / epoch_len) + epoch_num = embedding.step // epoch_len epoch_step = embedding.step - (epoch_num * epoch_len) + 1 pbar.set_description(f"[Epoch {epoch_num}: {epoch_step}/{epoch_len}]loss: {losses.mean():.7f}") @@ -243,8 +242,8 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini sd_model=shared.sd_model, prompt=text, steps=20, - height=training_size, - width=training_size, + height=training_height, + width=training_width, do_not_save_grid=True, do_not_save_samples=True, ) diff --git a/modules/ui.py b/modules/ui.py index f821fd8d..8c06ad7c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1029,7 +1029,8 @@ def create_ui(wrap_gradio_gpu_call): process_src = gr.Textbox(label='Source directory') process_dst = gr.Textbox(label='Destination directory') - process_size = gr.Slider(minimum=64, maximum=2048, step=64, label="Size (width and height)", value=512) + process_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512) + process_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) with gr.Row(): process_flip = gr.Checkbox(label='Create flipped copies') @@ -1050,7 +1051,8 @@ def create_ui(wrap_gradio_gpu_call): dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images") log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion") template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt")) - training_size = gr.Slider(minimum=64, maximum=2048, step=64, label="Size (width and height)", value=512) + training_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512) + training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) steps = gr.Number(label='Max steps', value=100000, precision=0) num_repeats = gr.Number(label='Number of repeats for a single input image per epoch', value=100, precision=0) create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0) @@ -1095,7 +1097,8 @@ def create_ui(wrap_gradio_gpu_call): inputs=[ process_src, process_dst, - process_size, + process_width, + process_height, process_flip, process_split, process_caption, @@ -1114,7 +1117,8 @@ def create_ui(wrap_gradio_gpu_call): learn_rate, dataset_directory, log_directory, - training_size, + training_width, + training_height, steps, num_repeats, create_image_every, -- cgit v1.2.3 From f347ddfd808c56bb1bacdec0c4bedf826ff85cd8 Mon Sep 17 00:00:00 2001 From: RW21 Date: Mon, 10 Oct 2022 10:44:11 +0900 Subject: Remove max_batch_count from ui.py --- modules/ui.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 8c06ad7c..8ba84911 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -524,7 +524,7 @@ def create_ui(wrap_gradio_gpu_call): denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7) with gr.Row(): - batch_count = gr.Slider(minimum=1, maximum=cmd_opts.max_batch_count, step=1, label='Batch count', value=1) + batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1) batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1) cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0) @@ -710,7 +710,7 @@ def create_ui(wrap_gradio_gpu_call): tiling = gr.Checkbox(label='Tiling', value=False) with gr.Row(): - batch_count = gr.Slider(minimum=1, maximum=cmd_opts.max_batch_count, step=1, label='Batch count', value=1) + batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1) batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1) with gr.Group(): -- cgit v1.2.3 From 9d33baba587637815d818e5e641d8f8b74c4900d Mon Sep 17 00:00:00 2001 From: Vladimir Repin <32306715+mezotaken@users.noreply.github.com> Date: Mon, 10 Oct 2022 18:46:48 +0300 Subject: Always show previous mask and fix extras_send dest --- modules/ui.py | 2 +- style.css | 7 +++++++ 2 files changed, 8 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 8ba84911..e8039d76 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -961,7 +961,7 @@ def create_ui(wrap_gradio_gpu_call): extras_send_to_inpaint.click( fn=lambda x: image_from_url_text(x), - _js="extract_image_from_gallery_img2img", + _js="extract_image_from_gallery_inpaint", inputs=[result_images], outputs=[init_img_with_mask], ) diff --git a/style.css b/style.css index 04bb9576..00a3d07f 100644 --- a/style.css +++ b/style.css @@ -467,3 +467,10 @@ input[type="range"]{ max-width: 32em; padding: 0; } + +canvas[key="mask"] { + z-index: 12 !important; + filter: invert(); + mix-blend-mode: multiply; + pointer-events: none; +} -- cgit v1.2.3 From 1d64976dbc5a0f3124567b91fadd5014a9d93c5f Mon Sep 17 00:00:00 2001 From: Justin Maier Date: Mon, 10 Oct 2022 12:04:21 -0600 Subject: Simplify crop logic --- modules/extras.py | 14 +++----------- modules/ui.py | 4 ++-- 2 files changed, 5 insertions(+), 13 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/extras.py b/modules/extras.py index 83ca7049..b24d7de3 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -73,16 +73,6 @@ def run_extras(extras_mode, resize_mode, image, image_folder, gfpgan_visibility, crop_info = " (crop)" if upscaling_crop else "" info += f"Resize to: {upscaling_resize_w:g}x{upscaling_resize_h:g}{crop_info}\n" - def crop_upscaled_center(image, resize_w, resize_h): - left = int(math.ceil((image.width - resize_w) / 2)) - right = image.width - int(math.floor((image.width - resize_w) / 2)) - top = int(math.ceil((image.height - resize_h) / 2)) - bottom = image.height - int(math.floor((image.height - resize_h) / 2)) - - image = image.crop((left, top, right, bottom)) - return image - - if upscaling_resize != 1.0: def upscale(image, scaler_index, resize, mode, resize_w, resize_h, crop): small = image.crop((image.width // 2, image.height // 2, image.width // 2 + 10, image.height // 2 + 10)) @@ -94,7 +84,9 @@ def run_extras(extras_mode, resize_mode, image, image_folder, gfpgan_visibility, upscaler = shared.sd_upscalers[scaler_index] c = upscaler.scaler.upscale(image, resize, upscaler.data_path) if mode == 1 and crop: - c = crop_upscaled_center(c, resize_w, resize_h) + cropped = Image.new("RGB", (resize_w, resize_h)) + cropped.paste(c, box=(resize_w // 2 - c.width // 2, resize_h // 2 - c.height // 2)) + c = cropped cached_images[key] = c return c diff --git a/modules/ui.py b/modules/ui.py index 4bb2892b..1aabe18d 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -909,8 +909,8 @@ def create_ui(wrap_gradio_gpu_call): with gr.TabItem('Scale to'): with gr.Group(): with gr.Row(): - upscaling_resize_w = gr.Number(label="Width", value=512) - upscaling_resize_h = gr.Number(label="Height", value=512) + upscaling_resize_w = gr.Number(label="Width", value=512, precision=0) + upscaling_resize_h = gr.Number(label="Height", value=512, precision=0) upscaling_crop = gr.Checkbox(label='Crop to fit', value=True) with gr.Group(): -- cgit v1.2.3 From 2536ecbb1790da2af0d61b6a26f38732cba665cd Mon Sep 17 00:00:00 2001 From: Fampai <> Date: Mon, 10 Oct 2022 17:10:29 -0400 Subject: Refactored learning rate code --- modules/textual_inversion/textual_inversion.py | 51 ++++++++++++++++++++++++-- modules/ui.py | 2 +- 2 files changed, 48 insertions(+), 5 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 5965c5a0..c64a4598 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -189,8 +189,6 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini embedding = hijack.embedding_db.word_embeddings[embedding_name] embedding.vec.requires_grad = True - optimizer = torch.optim.AdamW([embedding.vec], lr=learn_rate) - losses = torch.zeros((32,)) last_saved_file = "" @@ -203,12 +201,24 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root)]) epoch_len = (tr_img_len * num_repeats) + tr_img_len + scheduleIter = iter(LearnSchedule(learn_rate, steps, ititial_step)) + (learn_rate, end_step) = next(scheduleIter) + print(f'Training at rate of {learn_rate} until step {end_step}') + + optimizer = torch.optim.AdamW([embedding.vec], lr=learn_rate) + pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step) for i, (x, text) in pbar: embedding.step = i + ititial_step - if embedding.step > steps: - break + if embedding.step > end_step: + try: + (learn_rate, end_step) = next(scheduleIter) + except: + break + tqdm.tqdm.write(f'Training at rate of {learn_rate} until step {end_step}') + for pg in optimizer.param_groups: + pg['lr'] = learn_rate if shared.state.interrupted: break @@ -277,3 +287,36 @@ Last saved image: {html.escape(last_saved_image)}
return embedding, filename +class LearnSchedule: + def __init__(self, learn_rate, max_steps, cur_step=0): + pairs = learn_rate.split(',') + self.rates = [] + self.it = 0 + self.maxit = 0 + for i, pair in enumerate(pairs): + tmp = pair.split(':') + if len(tmp) == 2: + step = int(tmp[1]) + if step > cur_step: + self.rates.append((float(tmp[0]), min(step, max_steps))) + self.maxit += 1 + if step > max_steps: + return + elif step == -1: + self.rates.append((float(tmp[0]), max_steps)) + self.maxit += 1 + return + else: + self.rates.append((float(tmp[0]), max_steps)) + self.maxit += 1 + return + + def __iter__(self): + return self + + def __next__(self): + if self.it < self.maxit: + self.it += 1 + return self.rates[self.it - 1] + else: + raise StopIteration diff --git a/modules/ui.py b/modules/ui.py index 8c06ad7c..c9e8355b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1047,7 +1047,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Group(): gr.HTML(value="

Train an embedding; must specify a directory with a set of 1:1 ratio images

") train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) - learn_rate = gr.Number(label='Learning rate', value=5.0e-03) + learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value = "5.0e-03") dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images") log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion") template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt")) -- cgit v1.2.3 From 1add3cff84b7e2436d69b1e97ae689281e4a7c33 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Mon, 10 Oct 2022 19:57:43 -0500 Subject: Refresh list of models/ckpts upon hitting restart gradio in the settings pane --- modules/ui.py | 4 ++++ 1 file changed, 4 insertions(+) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index e8039d76..06ff118f 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -39,6 +39,7 @@ import modules.generation_parameters_copypaste from modules import prompt_parser from modules.images import save_image import modules.textual_inversion.ui +from modules.sd_models import list_models # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() @@ -1290,6 +1291,9 @@ Requested path was: {f} shared.state.interrupt() settings_interface.gradio_ref.do_restart = True + # refresh models so that new models/.ckpt's show up on reload + list_models() + restart_gradio.click( fn=request_restart, inputs=[], -- cgit v1.2.3 From 8b7d3f1bef47bbe048f644ed0d8dd3ad46554045 Mon Sep 17 00:00:00 2001 From: Jairo Correa Date: Tue, 11 Oct 2022 02:22:46 -0300 Subject: Make the ctrl+enter shortcut use the generate button on the current tab --- modules/ui.py | 2 +- script.js | 11 +++++++++-- 2 files changed, 10 insertions(+), 3 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index e8039d76..cafda884 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1331,7 +1331,7 @@ Requested path was: {f} with gr.Tabs() as tabs: for interface, label, ifid in interfaces: - with gr.TabItem(label, id=ifid): + with gr.TabItem(label, id=ifid, elem_id='tab_' + ifid): interface.render() if os.path.exists(os.path.join(script_path, "notification.mp3")): diff --git a/script.js b/script.js index a92c0f77..9543cbe6 100644 --- a/script.js +++ b/script.js @@ -6,6 +6,10 @@ function get_uiCurrentTab() { return gradioApp().querySelector('.tabs button:not(.border-transparent)') } +function get_uiCurrentTabContent() { + return gradioApp().querySelector('.tabitem[id^=tab_]:not([style*="display: none"])') +} + uiUpdateCallbacks = [] uiTabChangeCallbacks = [] let uiCurrentTab = null @@ -50,8 +54,11 @@ document.addEventListener("DOMContentLoaded", function() { } else if (e.keyCode !== undefined) { if((e.keyCode == 13 && (e.metaKey || e.ctrlKey))) handled = true; } - if (handled) { - gradioApp().querySelector("#txt2img_generate").click(); + if (handled) { + button = get_uiCurrentTabContent().querySelector('button[id$=_generate]'); + if (button) { + button.click(); + } e.preventDefault(); } }) -- cgit v1.2.3 From 8617396c6df71074c7fd3d39419802026874712a Mon Sep 17 00:00:00 2001 From: Kenneth Date: Mon, 10 Oct 2022 17:23:07 -0600 Subject: Added slider for deepbooru score threshold in settings --- modules/shared.py | 1 + modules/ui.py | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/shared.py b/modules/shared.py index ecd15ef5..e0830e28 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -239,6 +239,7 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"), "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}), "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}), "interrogate_clip_dict_limit": OptionInfo(1500, "Interrogate: maximum number of lines in text file (0 = No limit)"), + "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), })) options_templates.update(options_section(('ui', "User interface"), { diff --git a/modules/ui.py b/modules/ui.py index cafda884..ca3151c4 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -311,7 +311,7 @@ def interrogate(image): def interrogate_deepbooru(image): - prompt = get_deepbooru_tags(image) + prompt = get_deepbooru_tags(image, opts.interrogate_deepbooru_score_threshold) return gr_show(True) if prompt is None else prompt -- cgit v1.2.3 From 530103b586109c11fd068eb70ef09503ec6a4caf Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 11 Oct 2022 14:53:02 +0300 Subject: fixes related to merge --- modules/hypernetwork.py | 103 ------------------------- modules/hypernetwork/hypernetwork.py | 74 +++++++++++------- modules/hypernetwork/ui.py | 10 +-- modules/sd_hijack_optimizations.py | 3 +- modules/shared.py | 13 +++- modules/textual_inversion/textual_inversion.py | 12 +-- modules/ui.py | 5 +- scripts/xy_grid.py | 3 +- webui.py | 15 +--- 9 files changed, 78 insertions(+), 160 deletions(-) delete mode 100644 modules/hypernetwork.py (limited to 'modules/ui.py') diff --git a/modules/hypernetwork.py b/modules/hypernetwork.py deleted file mode 100644 index 7bbc443e..00000000 --- a/modules/hypernetwork.py +++ /dev/null @@ -1,103 +0,0 @@ -import glob -import os -import sys -import traceback - -import torch - -from ldm.util import default -from modules import devices, shared -import torch -from torch import einsum -from einops import rearrange, repeat - - -class HypernetworkModule(torch.nn.Module): - def __init__(self, dim, state_dict): - super().__init__() - - self.linear1 = torch.nn.Linear(dim, dim * 2) - self.linear2 = torch.nn.Linear(dim * 2, dim) - - self.load_state_dict(state_dict, strict=True) - self.to(devices.device) - - def forward(self, x): - return x + (self.linear2(self.linear1(x))) - - -class Hypernetwork: - filename = None - name = None - - def __init__(self, filename): - self.filename = filename - self.name = os.path.splitext(os.path.basename(filename))[0] - self.layers = {} - - state_dict = torch.load(filename, map_location='cpu') - for size, sd in state_dict.items(): - self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1])) - - -def list_hypernetworks(path): - res = {} - for filename in glob.iglob(os.path.join(path, '**/*.pt'), recursive=True): - name = os.path.splitext(os.path.basename(filename))[0] - res[name] = filename - return res - - -def load_hypernetwork(filename): - path = shared.hypernetworks.get(filename, None) - if path is not None: - print(f"Loading hypernetwork {filename}") - try: - shared.loaded_hypernetwork = Hypernetwork(path) - except Exception: - print(f"Error loading hypernetwork {path}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) - else: - if shared.loaded_hypernetwork is not None: - print(f"Unloading hypernetwork") - - shared.loaded_hypernetwork = None - - -def apply_hypernetwork(hypernetwork, context): - hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None) - - if hypernetwork_layers is None: - return context, context - - context_k = hypernetwork_layers[0](context) - context_v = hypernetwork_layers[1](context) - return context_k, context_v - - -def attention_CrossAttention_forward(self, x, context=None, mask=None): - h = self.heads - - q = self.to_q(x) - context = default(context, x) - - context_k, context_v = apply_hypernetwork(shared.loaded_hypernetwork, context) - k = self.to_k(context_k) - v = self.to_v(context_v) - - q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v)) - - sim = einsum('b i d, b j d -> b i j', q, k) * self.scale - - if mask is not None: - mask = rearrange(mask, 'b ... -> b (...)') - max_neg_value = -torch.finfo(sim.dtype).max - mask = repeat(mask, 'b j -> (b h) () j', h=h) - sim.masked_fill_(~mask, max_neg_value) - - # attention, what we cannot get enough of - attn = sim.softmax(dim=-1) - - out = einsum('b i j, b j d -> b i d', attn, v) - out = rearrange(out, '(b h) n d -> b n (h d)', h=h) - return self.to_out(out) diff --git a/modules/hypernetwork/hypernetwork.py b/modules/hypernetwork/hypernetwork.py index a3d6a47e..aa701bda 100644 --- a/modules/hypernetwork/hypernetwork.py +++ b/modules/hypernetwork/hypernetwork.py @@ -26,10 +26,11 @@ class HypernetworkModule(torch.nn.Module): if state_dict is not None: self.load_state_dict(state_dict, strict=True) else: - self.linear1.weight.data.fill_(0.0001) - self.linear1.bias.data.fill_(0.0001) - self.linear2.weight.data.fill_(0.0001) - self.linear2.bias.data.fill_(0.0001) + + self.linear1.weight.data.normal_(mean=0.0, std=0.01) + self.linear1.bias.data.zero_() + self.linear2.weight.data.normal_(mean=0.0, std=0.01) + self.linear2.bias.data.zero_() self.to(devices.device) @@ -92,41 +93,54 @@ class Hypernetwork: self.sd_checkpoint_name = state_dict.get('sd_checkpoint_name', None) -def load_hypernetworks(path): +def list_hypernetworks(path): res = {} + for filename in glob.iglob(os.path.join(path, '**/*.pt'), recursive=True): + name = os.path.splitext(os.path.basename(filename))[0] + res[name] = filename + return res - for filename in glob.iglob(path + '**/*.pt', recursive=True): + +def load_hypernetwork(filename): + path = shared.hypernetworks.get(filename, None) + if path is not None: + print(f"Loading hypernetwork {filename}") try: - hn = Hypernetwork() - hn.load(filename) - res[hn.name] = hn + shared.loaded_hypernetwork = Hypernetwork() + shared.loaded_hypernetwork.load(path) + except Exception: - print(f"Error loading hypernetwork {filename}", file=sys.stderr) + print(f"Error loading hypernetwork {path}", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) + else: + if shared.loaded_hypernetwork is not None: + print(f"Unloading hypernetwork") - return res + shared.loaded_hypernetwork = None -def attention_CrossAttention_forward(self, x, context=None, mask=None): - h = self.heads +def apply_hypernetwork(hypernetwork, context, layer=None): + hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None) - q = self.to_q(x) - context = default(context, x) + if hypernetwork_layers is None: + return context, context - hypernetwork_layers = (shared.hypernetwork.layers if shared.hypernetwork is not None else {}).get(context.shape[2], None) + if layer is not None: + layer.hyper_k = hypernetwork_layers[0] + layer.hyper_v = hypernetwork_layers[1] - if hypernetwork_layers is not None: - hypernetwork_k, hypernetwork_v = hypernetwork_layers + context_k = hypernetwork_layers[0](context) + context_v = hypernetwork_layers[1](context) + return context_k, context_v - self.hypernetwork_k = hypernetwork_k - self.hypernetwork_v = hypernetwork_v - context_k = hypernetwork_k(context) - context_v = hypernetwork_v(context) - else: - context_k = context - context_v = context +def attention_CrossAttention_forward(self, x, context=None, mask=None): + h = self.heads + + q = self.to_q(x) + context = default(context, x) + context_k, context_v = apply_hypernetwork(shared.loaded_hypernetwork, context, self) k = self.to_k(context_k) v = self.to_v(context_v) @@ -151,7 +165,9 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None): def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt): assert hypernetwork_name, 'embedding not selected' - shared.hypernetwork = shared.hypernetworks[hypernetwork_name] + path = shared.hypernetworks.get(hypernetwork_name, None) + shared.loaded_hypernetwork = Hypernetwork() + shared.loaded_hypernetwork.load(path) shared.state.textinfo = "Initializing hypernetwork training..." shared.state.job_count = steps @@ -176,9 +192,9 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..." with torch.autocast("cuda"): - ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=512, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file) + ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=1, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file) - hypernetwork = shared.hypernetworks[hypernetwork_name] + hypernetwork = shared.loaded_hypernetwork weights = hypernetwork.weights() for weight in weights: weight.requires_grad = True @@ -194,7 +210,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, if ititial_step > steps: return hypernetwork, filename - pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step) + pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step) for i, (x, text) in pbar: hypernetwork.step = i + ititial_step diff --git a/modules/hypernetwork/ui.py b/modules/hypernetwork/ui.py index 525f978c..f6d1d0a3 100644 --- a/modules/hypernetwork/ui.py +++ b/modules/hypernetwork/ui.py @@ -6,24 +6,24 @@ import gradio as gr import modules.textual_inversion.textual_inversion import modules.textual_inversion.preprocess from modules import sd_hijack, shared +from modules.hypernetwork import hypernetwork def create_hypernetwork(name): fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt") assert not os.path.exists(fn), f"file {fn} already exists" - hypernetwork = modules.hypernetwork.hypernetwork.Hypernetwork(name=name) - hypernetwork.save(fn) + hypernet = modules.hypernetwork.hypernetwork.Hypernetwork(name=name) + hypernet.save(fn) shared.reload_hypernetworks() - shared.hypernetwork = shared.hypernetworks.get(shared.opts.sd_hypernetwork, None) return gr.Dropdown.update(choices=sorted([x for x in shared.hypernetworks.keys()])), f"Created: {fn}", "" def train_hypernetwork(*args): - initial_hypernetwork = shared.hypernetwork + initial_hypernetwork = shared.loaded_hypernetwork try: sd_hijack.undo_optimizations() @@ -38,6 +38,6 @@ Hypernetwork saved to {html.escape(filename)} except Exception: raise finally: - shared.hypernetwork = initial_hypernetwork + shared.loaded_hypernetwork = initial_hypernetwork sd_hijack.apply_optimizations() diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py index 25cb67a4..27e571fc 100644 --- a/modules/sd_hijack_optimizations.py +++ b/modules/sd_hijack_optimizations.py @@ -8,7 +8,8 @@ from torch import einsum from ldm.util import default from einops import rearrange -from modules import shared, hypernetwork +from modules import shared +from modules.hypernetwork import hypernetwork if shared.cmd_opts.xformers or shared.cmd_opts.force_enable_xformers: diff --git a/modules/shared.py b/modules/shared.py index 14b40d70..8753015e 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -13,7 +13,8 @@ import modules.memmon import modules.sd_models import modules.styles import modules.devices as devices -from modules import sd_samplers, hypernetwork +from modules import sd_samplers +from modules.hypernetwork import hypernetwork from modules.paths import models_path, script_path, sd_path sd_model_file = os.path.join(script_path, 'model.ckpt') @@ -29,6 +30,7 @@ parser.add_argument("--no-half-vae", action='store_true', help="do not switch th parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)") parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI") parser.add_argument("--embeddings-dir", type=str, default=os.path.join(script_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)") +parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory") parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui") parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage") parser.add_argument("--lowvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a lot of speed for very low VRM usage") @@ -82,10 +84,17 @@ parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram xformers_available = False config_filename = cmd_opts.ui_settings_file -hypernetworks = hypernetwork.list_hypernetworks(os.path.join(models_path, 'hypernetworks')) +hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) loaded_hypernetwork = None +def reload_hypernetworks(): + global hypernetworks + + hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) + hypernetwork.load_hypernetwork(opts.sd_hypernetwork) + + class State: skipped = False interrupted = False diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 5965c5a0..d6977950 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -156,7 +156,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'): return fn -def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, num_repeats, create_image_every, save_embedding_every, template_file): +def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, num_repeats, create_image_every, save_embedding_every, template_file, preview_image_prompt): assert embedding_name, 'embedding not selected' shared.state.textinfo = "Initializing textual inversion training..." @@ -238,12 +238,14 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0: last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png') + preview_text = text if preview_image_prompt == "" else preview_image_prompt + p = processing.StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, - prompt=text, + prompt=preview_text, steps=20, - height=training_height, - width=training_width, + height=training_height, + width=training_width, do_not_save_grid=True, do_not_save_samples=True, ) @@ -254,7 +256,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini shared.state.current_image = image image.save(last_saved_image) - last_saved_image += f", prompt: {text}" + last_saved_image += f", prompt: {preview_text}" shared.state.job_no = embedding.step diff --git a/modules/ui.py b/modules/ui.py index 10b1ee3a..df653059 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1023,7 +1023,7 @@ def create_ui(wrap_gradio_gpu_call): gr.HTML(value="") with gr.Column(): - create_embedding = gr.Button(value="Create", variant='primary') + create_embedding = gr.Button(value="Create embedding", variant='primary') with gr.Group(): gr.HTML(value="

Create a new hypernetwork

") @@ -1035,7 +1035,7 @@ def create_ui(wrap_gradio_gpu_call): gr.HTML(value="") with gr.Column(): - create_hypernetwork = gr.Button(value="Create", variant='primary') + create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary') with gr.Group(): gr.HTML(value="

Preprocess images

") @@ -1147,6 +1147,7 @@ def create_ui(wrap_gradio_gpu_call): create_image_every, save_embedding_every, template_file, + preview_image_prompt, ], outputs=[ ti_output, diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py index 42e1489c..0af5993c 100644 --- a/scripts/xy_grid.py +++ b/scripts/xy_grid.py @@ -10,7 +10,8 @@ import numpy as np import modules.scripts as scripts import gradio as gr -from modules import images, hypernetwork +from modules import images +from modules.hypernetwork import hypernetwork from modules.processing import process_images, Processed, get_correct_sampler from modules.shared import opts, cmd_opts, state import modules.shared as shared diff --git a/webui.py b/webui.py index 7c200551..ba2156c8 100644 --- a/webui.py +++ b/webui.py @@ -29,6 +29,7 @@ from modules import devices from modules import modelloader from modules.paths import script_path from modules.shared import cmd_opts +import modules.hypernetwork.hypernetwork modelloader.cleanup_models() modules.sd_models.setup_model() @@ -77,22 +78,12 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs) -def set_hypernetwork(): - shared.hypernetwork = shared.hypernetworks.get(shared.opts.sd_hypernetwork, None) - - -shared.reload_hypernetworks() -shared.opts.onchange("sd_hypernetwork", set_hypernetwork) -set_hypernetwork() - - modules.scripts.load_scripts(os.path.join(script_path, "scripts")) shared.sd_model = modules.sd_models.load_model() shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model))) -loaded_hypernetwork = modules.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork) -shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork))) +shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetwork.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork))) def webui(): @@ -117,7 +108,7 @@ def webui(): prevent_thread_lock=True ) - app.add_middleware(GZipMiddleware,minimum_size=1000) + app.add_middleware(GZipMiddleware, minimum_size=1000) while 1: time.sleep(0.5) -- cgit v1.2.3 From 87b77cad5f3017c952a7dfec0e7904a9df5b72fd Mon Sep 17 00:00:00 2001 From: Ben <110583491+TheLastBen@users.noreply.github.com> Date: Mon, 10 Oct 2022 19:37:16 +0100 Subject: Layout fix --- modules/ui.py | 28 ++++++++++++++-------------- 1 file changed, 14 insertions(+), 14 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index df653059..de4cd7f2 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -550,15 +550,15 @@ def create_ui(wrap_gradio_gpu_call): button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder' open_txt2img_folder = gr.Button(folder_symbol, elem_id=button_id) - with gr.Row(): - do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False) + with gr.Row(): + do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False) - with gr.Row(): - download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False) + with gr.Row(): + download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False) - with gr.Group(): - html_info = gr.HTML() - generation_info = gr.Textbox(visible=False) + with gr.Group(): + html_info = gr.HTML() + generation_info = gr.Textbox(visible=False) connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) @@ -738,15 +738,15 @@ def create_ui(wrap_gradio_gpu_call): button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder' open_img2img_folder = gr.Button(folder_symbol, elem_id=button_id) - with gr.Row(): - do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False) + with gr.Row(): + do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False) - with gr.Row(): - download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False) + with gr.Row(): + download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False) - with gr.Group(): - html_info = gr.HTML() - generation_info = gr.Textbox(visible=False) + with gr.Group(): + html_info = gr.HTML() + generation_info = gr.Textbox(visible=False) connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) -- cgit v1.2.3 From 861297cefe2bb663f4e09dd4778a4cb93ebe8ff1 Mon Sep 17 00:00:00 2001 From: Ben <110583491+TheLastBen@users.noreply.github.com> Date: Tue, 11 Oct 2022 08:08:45 +0100 Subject: add a space holder --- modules/ui.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index de4cd7f2..fc0f3d3c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -429,7 +429,10 @@ def create_toprow(is_img2img): with gr.Row(): with gr.Column(scale=8): - negative_prompt = gr.Textbox(label="Negative prompt", elem_id="negative_prompt", show_label=False, placeholder="Negative prompt", lines=2) + with gr.Row(): + negative_prompt = gr.Textbox(label="Negative prompt", elem_id="negative_prompt", show_label=False, placeholder="Negative prompt", lines=2) + with gr.Column(scale=1, elem_id="roll_col"): + sh = gr.Button(elem_id="sh", visible=True) with gr.Column(scale=1, elem_id="style_neg_col"): prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())), visible=len(shared.prompt_styles.styles) > 1) -- cgit v1.2.3 From 59925644480b6fd84f6bb84b4df7d4fbc6a0cce8 Mon Sep 17 00:00:00 2001 From: JamnedZ Date: Tue, 11 Oct 2022 16:40:27 +0700 Subject: Cleaned ngrok integration --- modules/ngrok.py | 15 +++++++++++++++ modules/shared.py | 1 + modules/ui.py | 5 +++++ 3 files changed, 21 insertions(+) create mode 100644 modules/ngrok.py (limited to 'modules/ui.py') diff --git a/modules/ngrok.py b/modules/ngrok.py new file mode 100644 index 00000000..17e6976f --- /dev/null +++ b/modules/ngrok.py @@ -0,0 +1,15 @@ +from pyngrok import ngrok, conf, exception + + +def connect(token, port): + if token == None: + token = 'None' + conf.get_default().auth_token = token + try: + public_url = ngrok.connect(port).public_url + except exception.PyngrokNgrokError: + print(f'Invalid ngrok authtoken, ngrok connection aborted.\n' + f'Your token: {token}, get the right one on https://dashboard.ngrok.com/get-started/your-authtoken') + else: + print(f'ngrok connected to localhost:{port}! URL: {public_url}\n' + 'You can use this link after the launch is complete.') \ No newline at end of file diff --git a/modules/shared.py b/modules/shared.py index 8753015e..375e3afb 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -38,6 +38,7 @@ parser.add_argument("--always-batch-cond-uncond", action='store_true', help="dis parser.add_argument("--unload-gfpgan", action='store_true', help="does not do anything.") parser.add_argument("--precision", type=str, help="evaluate at this precision", choices=["full", "autocast"], default="autocast") parser.add_argument("--share", action='store_true', help="use share=True for gradio and make the UI accessible through their site (doesn't work for me but you might have better luck)") +parser.add_argument("--ngrok", type=str, help="ngrok authtoken, alternative to gradio --share", default=None) parser.add_argument("--codeformer-models-path", type=str, help="Path to directory with codeformer model file(s).", default=os.path.join(models_path, 'Codeformer')) parser.add_argument("--gfpgan-models-path", type=str, help="Path to directory with GFPGAN model file(s).", default=os.path.join(models_path, 'GFPGAN')) parser.add_argument("--esrgan-models-path", type=str, help="Path to directory with ESRGAN model file(s).", default=os.path.join(models_path, 'ESRGAN')) diff --git a/modules/ui.py b/modules/ui.py index fc0f3d3c..f57f32db 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -51,6 +51,11 @@ if not cmd_opts.share and not cmd_opts.listen: gradio.utils.version_check = lambda: None gradio.utils.get_local_ip_address = lambda: '127.0.0.1' +if cmd_opts.ngrok != None: + import modules.ngrok as ngrok + print('ngrok authtoken detected, trying to connect...') + ngrok.connect(cmd_opts.ngrok, cmd_opts.port if cmd_opts.port != None else 7860) + def gr_show(visible=True): return {"visible": visible, "__type__": "update"} -- cgit v1.2.3 From 873efeed49bb5197a42da18272115b326c5d68f3 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 11 Oct 2022 15:51:22 +0300 Subject: rename hypernetwork dir to hypernetworks to prevent clash with an old filename that people who use zip instead of git clone will have --- modules/hypernetwork/hypernetwork.py | 283 ---------------------------------- modules/hypernetwork/ui.py | 43 ------ modules/hypernetworks/hypernetwork.py | 283 ++++++++++++++++++++++++++++++++++ modules/hypernetworks/ui.py | 43 ++++++ modules/sd_hijack.py | 2 +- modules/sd_hijack_optimizations.py | 2 +- modules/shared.py | 2 +- modules/ui.py | 2 +- scripts/xy_grid.py | 2 +- webui.py | 2 +- 10 files changed, 332 insertions(+), 332 deletions(-) delete mode 100644 modules/hypernetwork/hypernetwork.py delete mode 100644 modules/hypernetwork/ui.py create mode 100644 modules/hypernetworks/hypernetwork.py create mode 100644 modules/hypernetworks/ui.py (limited to 'modules/ui.py') diff --git a/modules/hypernetwork/hypernetwork.py b/modules/hypernetwork/hypernetwork.py deleted file mode 100644 index aa701bda..00000000 --- a/modules/hypernetwork/hypernetwork.py +++ /dev/null @@ -1,283 +0,0 @@ -import datetime -import glob -import html -import os -import sys -import traceback -import tqdm - -import torch - -from ldm.util import default -from modules import devices, shared, processing, sd_models -import torch -from torch import einsum -from einops import rearrange, repeat -import modules.textual_inversion.dataset - - -class HypernetworkModule(torch.nn.Module): - def __init__(self, dim, state_dict=None): - super().__init__() - - self.linear1 = torch.nn.Linear(dim, dim * 2) - self.linear2 = torch.nn.Linear(dim * 2, dim) - - if state_dict is not None: - self.load_state_dict(state_dict, strict=True) - else: - - self.linear1.weight.data.normal_(mean=0.0, std=0.01) - self.linear1.bias.data.zero_() - self.linear2.weight.data.normal_(mean=0.0, std=0.01) - self.linear2.bias.data.zero_() - - self.to(devices.device) - - def forward(self, x): - return x + (self.linear2(self.linear1(x))) - - -class Hypernetwork: - filename = None - name = None - - def __init__(self, name=None): - self.filename = None - self.name = name - self.layers = {} - self.step = 0 - self.sd_checkpoint = None - self.sd_checkpoint_name = None - - for size in [320, 640, 768, 1280]: - self.layers[size] = (HypernetworkModule(size), HypernetworkModule(size)) - - def weights(self): - res = [] - - for k, layers in self.layers.items(): - for layer in layers: - layer.train() - res += [layer.linear1.weight, layer.linear1.bias, layer.linear2.weight, layer.linear2.bias] - - return res - - def save(self, filename): - state_dict = {} - - for k, v in self.layers.items(): - state_dict[k] = (v[0].state_dict(), v[1].state_dict()) - - state_dict['step'] = self.step - state_dict['name'] = self.name - state_dict['sd_checkpoint'] = self.sd_checkpoint - state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name - - torch.save(state_dict, filename) - - def load(self, filename): - self.filename = filename - if self.name is None: - self.name = os.path.splitext(os.path.basename(filename))[0] - - state_dict = torch.load(filename, map_location='cpu') - - for size, sd in state_dict.items(): - if type(size) == int: - self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1])) - - self.name = state_dict.get('name', self.name) - self.step = state_dict.get('step', 0) - self.sd_checkpoint = state_dict.get('sd_checkpoint', None) - self.sd_checkpoint_name = state_dict.get('sd_checkpoint_name', None) - - -def list_hypernetworks(path): - res = {} - for filename in glob.iglob(os.path.join(path, '**/*.pt'), recursive=True): - name = os.path.splitext(os.path.basename(filename))[0] - res[name] = filename - return res - - -def load_hypernetwork(filename): - path = shared.hypernetworks.get(filename, None) - if path is not None: - print(f"Loading hypernetwork {filename}") - try: - shared.loaded_hypernetwork = Hypernetwork() - shared.loaded_hypernetwork.load(path) - - except Exception: - print(f"Error loading hypernetwork {path}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) - else: - if shared.loaded_hypernetwork is not None: - print(f"Unloading hypernetwork") - - shared.loaded_hypernetwork = None - - -def apply_hypernetwork(hypernetwork, context, layer=None): - hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None) - - if hypernetwork_layers is None: - return context, context - - if layer is not None: - layer.hyper_k = hypernetwork_layers[0] - layer.hyper_v = hypernetwork_layers[1] - - context_k = hypernetwork_layers[0](context) - context_v = hypernetwork_layers[1](context) - return context_k, context_v - - -def attention_CrossAttention_forward(self, x, context=None, mask=None): - h = self.heads - - q = self.to_q(x) - context = default(context, x) - - context_k, context_v = apply_hypernetwork(shared.loaded_hypernetwork, context, self) - k = self.to_k(context_k) - v = self.to_v(context_v) - - q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v)) - - sim = einsum('b i d, b j d -> b i j', q, k) * self.scale - - if mask is not None: - mask = rearrange(mask, 'b ... -> b (...)') - max_neg_value = -torch.finfo(sim.dtype).max - mask = repeat(mask, 'b j -> (b h) () j', h=h) - sim.masked_fill_(~mask, max_neg_value) - - # attention, what we cannot get enough of - attn = sim.softmax(dim=-1) - - out = einsum('b i j, b j d -> b i d', attn, v) - out = rearrange(out, '(b h) n d -> b n (h d)', h=h) - return self.to_out(out) - - -def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt): - assert hypernetwork_name, 'embedding not selected' - - path = shared.hypernetworks.get(hypernetwork_name, None) - shared.loaded_hypernetwork = Hypernetwork() - shared.loaded_hypernetwork.load(path) - - shared.state.textinfo = "Initializing hypernetwork training..." - shared.state.job_count = steps - - filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt') - - log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%m-%d"), hypernetwork_name) - - if save_hypernetwork_every > 0: - hypernetwork_dir = os.path.join(log_directory, "hypernetworks") - os.makedirs(hypernetwork_dir, exist_ok=True) - else: - hypernetwork_dir = None - - if create_image_every > 0: - images_dir = os.path.join(log_directory, "images") - os.makedirs(images_dir, exist_ok=True) - else: - images_dir = None - - cond_model = shared.sd_model.cond_stage_model - - shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..." - with torch.autocast("cuda"): - ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=1, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file) - - hypernetwork = shared.loaded_hypernetwork - weights = hypernetwork.weights() - for weight in weights: - weight.requires_grad = True - - optimizer = torch.optim.AdamW(weights, lr=learn_rate) - - losses = torch.zeros((32,)) - - last_saved_file = "" - last_saved_image = "" - - ititial_step = hypernetwork.step or 0 - if ititial_step > steps: - return hypernetwork, filename - - pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step) - for i, (x, text) in pbar: - hypernetwork.step = i + ititial_step - - if hypernetwork.step > steps: - break - - if shared.state.interrupted: - break - - with torch.autocast("cuda"): - c = cond_model([text]) - - x = x.to(devices.device) - loss = shared.sd_model(x.unsqueeze(0), c)[0] - del x - - losses[hypernetwork.step % losses.shape[0]] = loss.item() - - optimizer.zero_grad() - loss.backward() - optimizer.step() - - pbar.set_description(f"loss: {losses.mean():.7f}") - - if hypernetwork.step > 0 and hypernetwork_dir is not None and hypernetwork.step % save_hypernetwork_every == 0: - last_saved_file = os.path.join(hypernetwork_dir, f'{hypernetwork_name}-{hypernetwork.step}.pt') - hypernetwork.save(last_saved_file) - - if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0: - last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png') - - preview_text = text if preview_image_prompt == "" else preview_image_prompt - - p = processing.StableDiffusionProcessingTxt2Img( - sd_model=shared.sd_model, - prompt=preview_text, - steps=20, - do_not_save_grid=True, - do_not_save_samples=True, - ) - - processed = processing.process_images(p) - image = processed.images[0] - - shared.state.current_image = image - image.save(last_saved_image) - - last_saved_image += f", prompt: {preview_text}" - - shared.state.job_no = hypernetwork.step - - shared.state.textinfo = f""" -

-Loss: {losses.mean():.7f}
-Step: {hypernetwork.step}
-Last prompt: {html.escape(text)}
-Last saved embedding: {html.escape(last_saved_file)}
-Last saved image: {html.escape(last_saved_image)}
-

-""" - - checkpoint = sd_models.select_checkpoint() - - hypernetwork.sd_checkpoint = checkpoint.hash - hypernetwork.sd_checkpoint_name = checkpoint.model_name - hypernetwork.save(filename) - - return hypernetwork, filename - - diff --git a/modules/hypernetwork/ui.py b/modules/hypernetwork/ui.py deleted file mode 100644 index f6d1d0a3..00000000 --- a/modules/hypernetwork/ui.py +++ /dev/null @@ -1,43 +0,0 @@ -import html -import os - -import gradio as gr - -import modules.textual_inversion.textual_inversion -import modules.textual_inversion.preprocess -from modules import sd_hijack, shared -from modules.hypernetwork import hypernetwork - - -def create_hypernetwork(name): - fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt") - assert not os.path.exists(fn), f"file {fn} already exists" - - hypernet = modules.hypernetwork.hypernetwork.Hypernetwork(name=name) - hypernet.save(fn) - - shared.reload_hypernetworks() - - return gr.Dropdown.update(choices=sorted([x for x in shared.hypernetworks.keys()])), f"Created: {fn}", "" - - -def train_hypernetwork(*args): - - initial_hypernetwork = shared.loaded_hypernetwork - - try: - sd_hijack.undo_optimizations() - - hypernetwork, filename = modules.hypernetwork.hypernetwork.train_hypernetwork(*args) - - res = f""" -Training {'interrupted' if shared.state.interrupted else 'finished'} at {hypernetwork.step} steps. -Hypernetwork saved to {html.escape(filename)} -""" - return res, "" - except Exception: - raise - finally: - shared.loaded_hypernetwork = initial_hypernetwork - sd_hijack.apply_optimizations() - diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py new file mode 100644 index 00000000..aa701bda --- /dev/null +++ b/modules/hypernetworks/hypernetwork.py @@ -0,0 +1,283 @@ +import datetime +import glob +import html +import os +import sys +import traceback +import tqdm + +import torch + +from ldm.util import default +from modules import devices, shared, processing, sd_models +import torch +from torch import einsum +from einops import rearrange, repeat +import modules.textual_inversion.dataset + + +class HypernetworkModule(torch.nn.Module): + def __init__(self, dim, state_dict=None): + super().__init__() + + self.linear1 = torch.nn.Linear(dim, dim * 2) + self.linear2 = torch.nn.Linear(dim * 2, dim) + + if state_dict is not None: + self.load_state_dict(state_dict, strict=True) + else: + + self.linear1.weight.data.normal_(mean=0.0, std=0.01) + self.linear1.bias.data.zero_() + self.linear2.weight.data.normal_(mean=0.0, std=0.01) + self.linear2.bias.data.zero_() + + self.to(devices.device) + + def forward(self, x): + return x + (self.linear2(self.linear1(x))) + + +class Hypernetwork: + filename = None + name = None + + def __init__(self, name=None): + self.filename = None + self.name = name + self.layers = {} + self.step = 0 + self.sd_checkpoint = None + self.sd_checkpoint_name = None + + for size in [320, 640, 768, 1280]: + self.layers[size] = (HypernetworkModule(size), HypernetworkModule(size)) + + def weights(self): + res = [] + + for k, layers in self.layers.items(): + for layer in layers: + layer.train() + res += [layer.linear1.weight, layer.linear1.bias, layer.linear2.weight, layer.linear2.bias] + + return res + + def save(self, filename): + state_dict = {} + + for k, v in self.layers.items(): + state_dict[k] = (v[0].state_dict(), v[1].state_dict()) + + state_dict['step'] = self.step + state_dict['name'] = self.name + state_dict['sd_checkpoint'] = self.sd_checkpoint + state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name + + torch.save(state_dict, filename) + + def load(self, filename): + self.filename = filename + if self.name is None: + self.name = os.path.splitext(os.path.basename(filename))[0] + + state_dict = torch.load(filename, map_location='cpu') + + for size, sd in state_dict.items(): + if type(size) == int: + self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1])) + + self.name = state_dict.get('name', self.name) + self.step = state_dict.get('step', 0) + self.sd_checkpoint = state_dict.get('sd_checkpoint', None) + self.sd_checkpoint_name = state_dict.get('sd_checkpoint_name', None) + + +def list_hypernetworks(path): + res = {} + for filename in glob.iglob(os.path.join(path, '**/*.pt'), recursive=True): + name = os.path.splitext(os.path.basename(filename))[0] + res[name] = filename + return res + + +def load_hypernetwork(filename): + path = shared.hypernetworks.get(filename, None) + if path is not None: + print(f"Loading hypernetwork {filename}") + try: + shared.loaded_hypernetwork = Hypernetwork() + shared.loaded_hypernetwork.load(path) + + except Exception: + print(f"Error loading hypernetwork {path}", file=sys.stderr) + print(traceback.format_exc(), file=sys.stderr) + else: + if shared.loaded_hypernetwork is not None: + print(f"Unloading hypernetwork") + + shared.loaded_hypernetwork = None + + +def apply_hypernetwork(hypernetwork, context, layer=None): + hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None) + + if hypernetwork_layers is None: + return context, context + + if layer is not None: + layer.hyper_k = hypernetwork_layers[0] + layer.hyper_v = hypernetwork_layers[1] + + context_k = hypernetwork_layers[0](context) + context_v = hypernetwork_layers[1](context) + return context_k, context_v + + +def attention_CrossAttention_forward(self, x, context=None, mask=None): + h = self.heads + + q = self.to_q(x) + context = default(context, x) + + context_k, context_v = apply_hypernetwork(shared.loaded_hypernetwork, context, self) + k = self.to_k(context_k) + v = self.to_v(context_v) + + q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v)) + + sim = einsum('b i d, b j d -> b i j', q, k) * self.scale + + if mask is not None: + mask = rearrange(mask, 'b ... -> b (...)') + max_neg_value = -torch.finfo(sim.dtype).max + mask = repeat(mask, 'b j -> (b h) () j', h=h) + sim.masked_fill_(~mask, max_neg_value) + + # attention, what we cannot get enough of + attn = sim.softmax(dim=-1) + + out = einsum('b i j, b j d -> b i d', attn, v) + out = rearrange(out, '(b h) n d -> b n (h d)', h=h) + return self.to_out(out) + + +def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt): + assert hypernetwork_name, 'embedding not selected' + + path = shared.hypernetworks.get(hypernetwork_name, None) + shared.loaded_hypernetwork = Hypernetwork() + shared.loaded_hypernetwork.load(path) + + shared.state.textinfo = "Initializing hypernetwork training..." + shared.state.job_count = steps + + filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt') + + log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%m-%d"), hypernetwork_name) + + if save_hypernetwork_every > 0: + hypernetwork_dir = os.path.join(log_directory, "hypernetworks") + os.makedirs(hypernetwork_dir, exist_ok=True) + else: + hypernetwork_dir = None + + if create_image_every > 0: + images_dir = os.path.join(log_directory, "images") + os.makedirs(images_dir, exist_ok=True) + else: + images_dir = None + + cond_model = shared.sd_model.cond_stage_model + + shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..." + with torch.autocast("cuda"): + ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=1, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file) + + hypernetwork = shared.loaded_hypernetwork + weights = hypernetwork.weights() + for weight in weights: + weight.requires_grad = True + + optimizer = torch.optim.AdamW(weights, lr=learn_rate) + + losses = torch.zeros((32,)) + + last_saved_file = "" + last_saved_image = "" + + ititial_step = hypernetwork.step or 0 + if ititial_step > steps: + return hypernetwork, filename + + pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step) + for i, (x, text) in pbar: + hypernetwork.step = i + ititial_step + + if hypernetwork.step > steps: + break + + if shared.state.interrupted: + break + + with torch.autocast("cuda"): + c = cond_model([text]) + + x = x.to(devices.device) + loss = shared.sd_model(x.unsqueeze(0), c)[0] + del x + + losses[hypernetwork.step % losses.shape[0]] = loss.item() + + optimizer.zero_grad() + loss.backward() + optimizer.step() + + pbar.set_description(f"loss: {losses.mean():.7f}") + + if hypernetwork.step > 0 and hypernetwork_dir is not None and hypernetwork.step % save_hypernetwork_every == 0: + last_saved_file = os.path.join(hypernetwork_dir, f'{hypernetwork_name}-{hypernetwork.step}.pt') + hypernetwork.save(last_saved_file) + + if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0: + last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png') + + preview_text = text if preview_image_prompt == "" else preview_image_prompt + + p = processing.StableDiffusionProcessingTxt2Img( + sd_model=shared.sd_model, + prompt=preview_text, + steps=20, + do_not_save_grid=True, + do_not_save_samples=True, + ) + + processed = processing.process_images(p) + image = processed.images[0] + + shared.state.current_image = image + image.save(last_saved_image) + + last_saved_image += f", prompt: {preview_text}" + + shared.state.job_no = hypernetwork.step + + shared.state.textinfo = f""" +

+Loss: {losses.mean():.7f}
+Step: {hypernetwork.step}
+Last prompt: {html.escape(text)}
+Last saved embedding: {html.escape(last_saved_file)}
+Last saved image: {html.escape(last_saved_image)}
+

+""" + + checkpoint = sd_models.select_checkpoint() + + hypernetwork.sd_checkpoint = checkpoint.hash + hypernetwork.sd_checkpoint_name = checkpoint.model_name + hypernetwork.save(filename) + + return hypernetwork, filename + + diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py new file mode 100644 index 00000000..811bc31e --- /dev/null +++ b/modules/hypernetworks/ui.py @@ -0,0 +1,43 @@ +import html +import os + +import gradio as gr + +import modules.textual_inversion.textual_inversion +import modules.textual_inversion.preprocess +from modules import sd_hijack, shared +from modules.hypernetworks import hypernetwork + + +def create_hypernetwork(name): + fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt") + assert not os.path.exists(fn), f"file {fn} already exists" + + hypernet = modules.hypernetwork.hypernetwork.Hypernetwork(name=name) + hypernet.save(fn) + + shared.reload_hypernetworks() + + return gr.Dropdown.update(choices=sorted([x for x in shared.hypernetworks.keys()])), f"Created: {fn}", "" + + +def train_hypernetwork(*args): + + initial_hypernetwork = shared.loaded_hypernetwork + + try: + sd_hijack.undo_optimizations() + + hypernetwork, filename = modules.hypernetwork.hypernetwork.train_hypernetwork(*args) + + res = f""" +Training {'interrupted' if shared.state.interrupted else 'finished'} at {hypernetwork.step} steps. +Hypernetwork saved to {html.escape(filename)} +""" + return res, "" + except Exception: + raise + finally: + shared.loaded_hypernetwork = initial_hypernetwork + sd_hijack.apply_optimizations() + diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index f873049a..f07ec041 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -37,7 +37,7 @@ def apply_optimizations(): def undo_optimizations(): - from modules.hypernetwork import hypernetwork + from modules.hypernetworks import hypernetwork ldm.modules.attention.CrossAttention.forward = hypernetwork.attention_CrossAttention_forward ldm.modules.diffusionmodules.model.nonlinearity = diffusionmodules_model_nonlinearity diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py index 27e571fc..3349b9c3 100644 --- a/modules/sd_hijack_optimizations.py +++ b/modules/sd_hijack_optimizations.py @@ -9,7 +9,7 @@ from ldm.util import default from einops import rearrange from modules import shared -from modules.hypernetwork import hypernetwork +from modules.hypernetworks import hypernetwork if shared.cmd_opts.xformers or shared.cmd_opts.force_enable_xformers: diff --git a/modules/shared.py b/modules/shared.py index 375e3afb..1dc2ccf2 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -14,7 +14,7 @@ import modules.sd_models import modules.styles import modules.devices as devices from modules import sd_samplers -from modules.hypernetwork import hypernetwork +from modules.hypernetworks import hypernetwork from modules.paths import models_path, script_path, sd_path sd_model_file = os.path.join(script_path, 'model.ckpt') diff --git a/modules/ui.py b/modules/ui.py index f57f32db..42e5d866 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -39,7 +39,7 @@ import modules.generation_parameters_copypaste from modules import prompt_parser from modules.images import save_image import modules.textual_inversion.ui -import modules.hypernetwork.ui +import modules.hypernetworks.ui # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py index 16918c99..cddb192a 100644 --- a/scripts/xy_grid.py +++ b/scripts/xy_grid.py @@ -11,7 +11,7 @@ import modules.scripts as scripts import gradio as gr from modules import images -from modules.hypernetwork import hypernetwork +from modules.hypernetworks import hypernetwork from modules.processing import process_images, Processed, get_correct_sampler from modules.shared import opts, cmd_opts, state import modules.shared as shared diff --git a/webui.py b/webui.py index ba2156c8..faa38a0d 100644 --- a/webui.py +++ b/webui.py @@ -29,7 +29,7 @@ from modules import devices from modules import modelloader from modules.paths import script_path from modules.shared import cmd_opts -import modules.hypernetwork.hypernetwork +import modules.hypernetworks.hypernetwork modelloader.cleanup_models() modules.sd_models.setup_model() -- cgit v1.2.3 From b0583be0884cd17dafb408fd79b52b2a0a972563 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 11 Oct 2022 15:54:34 +0300 Subject: more renames --- modules/hypernetworks/ui.py | 4 ++-- modules/ui.py | 4 ++-- webui.py | 2 +- 3 files changed, 5 insertions(+), 5 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py index 811bc31e..e7540f41 100644 --- a/modules/hypernetworks/ui.py +++ b/modules/hypernetworks/ui.py @@ -13,7 +13,7 @@ def create_hypernetwork(name): fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt") assert not os.path.exists(fn), f"file {fn} already exists" - hypernet = modules.hypernetwork.hypernetwork.Hypernetwork(name=name) + hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(name=name) hypernet.save(fn) shared.reload_hypernetworks() @@ -28,7 +28,7 @@ def train_hypernetwork(*args): try: sd_hijack.undo_optimizations() - hypernetwork, filename = modules.hypernetwork.hypernetwork.train_hypernetwork(*args) + hypernetwork, filename = modules.hypernetworks.hypernetwork.train_hypernetwork(*args) res = f""" Training {'interrupted' if shared.state.interrupted else 'finished'} at {hypernetwork.step} steps. diff --git a/modules/ui.py b/modules/ui.py index 42e5d866..ee333c3b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1111,7 +1111,7 @@ def create_ui(wrap_gradio_gpu_call): ) create_hypernetwork.click( - fn=modules.hypernetwork.ui.create_hypernetwork, + fn=modules.hypernetworks.ui.create_hypernetwork, inputs=[ new_hypernetwork_name, ], @@ -1164,7 +1164,7 @@ def create_ui(wrap_gradio_gpu_call): ) train_hypernetwork.click( - fn=wrap_gradio_gpu_call(modules.hypernetwork.ui.train_hypernetwork, extra_outputs=[gr.update()]), + fn=wrap_gradio_gpu_call(modules.hypernetworks.ui.train_hypernetwork, extra_outputs=[gr.update()]), _js="start_training_textual_inversion", inputs=[ train_hypernetwork_name, diff --git a/webui.py b/webui.py index faa38a0d..338f58e1 100644 --- a/webui.py +++ b/webui.py @@ -83,7 +83,7 @@ modules.scripts.load_scripts(os.path.join(script_path, "scripts")) shared.sd_model = modules.sd_models.load_model() shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model))) -shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetwork.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork))) +shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork))) def webui(): -- cgit v1.2.3 From d01a2d01560b31937df1f3433d210c18f97d32fa Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Tue, 11 Oct 2022 08:03:31 -0500 Subject: move list refresh to webui.py and add stdout indicating it's doing so --- modules/ui.py | 3 --- webui.py | 2 ++ 2 files changed, 2 insertions(+), 3 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 06ff118f..ae9317a3 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -39,7 +39,6 @@ import modules.generation_parameters_copypaste from modules import prompt_parser from modules.images import save_image import modules.textual_inversion.ui -from modules.sd_models import list_models # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() @@ -1291,8 +1290,6 @@ Requested path was: {f} shared.state.interrupt() settings_interface.gradio_ref.do_restart = True - # refresh models so that new models/.ckpt's show up on reload - list_models() restart_gradio.click( fn=request_restart, diff --git a/webui.py b/webui.py index 270584f7..94098c4c 100644 --- a/webui.py +++ b/webui.py @@ -124,6 +124,8 @@ def webui(): modules.scripts.reload_scripts(os.path.join(script_path, "scripts")) print('Reloading modules: modules.ui') importlib.reload(modules.ui) + print('Refreshing Model List') + modules.sd_models.list_models() print('Restarting Gradio') -- cgit v1.2.3 From d682444ecc99319fbd2b142a12727501e2884ba7 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 11 Oct 2022 18:04:47 +0300 Subject: add option to select hypernetwork modules when creating --- modules/hypernetworks/hypernetwork.py | 4 ++-- modules/hypernetworks/ui.py | 4 ++-- modules/ui.py | 2 ++ 3 files changed, 6 insertions(+), 4 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index aa701bda..b081f14e 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -42,7 +42,7 @@ class Hypernetwork: filename = None name = None - def __init__(self, name=None): + def __init__(self, name=None, enable_sizes=None): self.filename = None self.name = name self.layers = {} @@ -50,7 +50,7 @@ class Hypernetwork: self.sd_checkpoint = None self.sd_checkpoint_name = None - for size in [320, 640, 768, 1280]: + for size in enable_sizes or [320, 640, 768, 1280]: self.layers[size] = (HypernetworkModule(size), HypernetworkModule(size)) def weights(self): diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py index e7540f41..cdddcce1 100644 --- a/modules/hypernetworks/ui.py +++ b/modules/hypernetworks/ui.py @@ -9,11 +9,11 @@ from modules import sd_hijack, shared from modules.hypernetworks import hypernetwork -def create_hypernetwork(name): +def create_hypernetwork(name, enable_sizes): fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt") assert not os.path.exists(fn), f"file {fn} already exists" - hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(name=name) + hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(name=name, enable_sizes=[int(x) for x in enable_sizes]) hypernet.save(fn) shared.reload_hypernetworks() diff --git a/modules/ui.py b/modules/ui.py index f2d16b12..14b87b92 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1037,6 +1037,7 @@ def create_ui(wrap_gradio_gpu_call): gr.HTML(value="

Create a new hypernetwork

") new_hypernetwork_name = gr.Textbox(label="Name") + new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) with gr.Row(): with gr.Column(scale=3): @@ -1114,6 +1115,7 @@ def create_ui(wrap_gradio_gpu_call): fn=modules.hypernetworks.ui.create_hypernetwork, inputs=[ new_hypernetwork_name, + new_hypernetwork_sizes, ], outputs=[ train_hypernetwork_name, -- cgit v1.2.3 From d6fcc6b87bc00fcdecea276fe5b7c7945f7a8b14 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 11 Oct 2022 22:03:05 +0300 Subject: apply lr schedule to hypernets --- modules/hypernetworks/hypernetwork.py | 19 ++++++++--- modules/textual_inversion/learn_schedule.py | 34 ++++++++++++++++++++ modules/textual_inversion/textual_inversion.py | 44 +++----------------------- modules/ui.py | 2 +- 4 files changed, 54 insertions(+), 45 deletions(-) create mode 100644 modules/textual_inversion/learn_schedule.py (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 5608e799..470659df 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -14,6 +14,7 @@ import torch from torch import einsum from einops import rearrange, repeat import modules.textual_inversion.dataset +from modules.textual_inversion.learn_schedule import LearnSchedule class HypernetworkModule(torch.nn.Module): @@ -202,8 +203,6 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, for weight in weights: weight.requires_grad = True - optimizer = torch.optim.AdamW(weights, lr=learn_rate) - losses = torch.zeros((32,)) last_saved_file = "" @@ -213,12 +212,24 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, if ititial_step > steps: return hypernetwork, filename + schedules = iter(LearnSchedule(learn_rate, steps, ititial_step)) + (learn_rate, end_step) = next(schedules) + print(f'Training at rate of {learn_rate} until step {end_step}') + + optimizer = torch.optim.AdamW(weights, lr=learn_rate) + pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step) for i, (x, text, cond) in pbar: hypernetwork.step = i + ititial_step - if hypernetwork.step > steps: - break + if hypernetwork.step > end_step: + try: + (learn_rate, end_step) = next(schedules) + except Exception: + break + tqdm.tqdm.write(f'Training at rate of {learn_rate} until step {end_step}') + for pg in optimizer.param_groups: + pg['lr'] = learn_rate if shared.state.interrupted: break diff --git a/modules/textual_inversion/learn_schedule.py b/modules/textual_inversion/learn_schedule.py new file mode 100644 index 00000000..db720271 --- /dev/null +++ b/modules/textual_inversion/learn_schedule.py @@ -0,0 +1,34 @@ + +class LearnSchedule: + def __init__(self, learn_rate, max_steps, cur_step=0): + pairs = learn_rate.split(',') + self.rates = [] + self.it = 0 + self.maxit = 0 + for i, pair in enumerate(pairs): + tmp = pair.split(':') + if len(tmp) == 2: + step = int(tmp[1]) + if step > cur_step: + self.rates.append((float(tmp[0]), min(step, max_steps))) + self.maxit += 1 + if step > max_steps: + return + elif step == -1: + self.rates.append((float(tmp[0]), max_steps)) + self.maxit += 1 + return + else: + self.rates.append((float(tmp[0]), max_steps)) + self.maxit += 1 + return + + def __iter__(self): + return self + + def __next__(self): + if self.it < self.maxit: + self.it += 1 + return self.rates[self.it - 1] + else: + raise StopIteration diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 47a27faf..7717837d 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -10,6 +10,7 @@ import datetime from modules import shared, devices, sd_hijack, processing, sd_models import modules.textual_inversion.dataset +from modules.textual_inversion.learn_schedule import LearnSchedule class Embedding: @@ -198,11 +199,8 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini if ititial_step > steps: return embedding, filename - tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root)]) - epoch_len = (tr_img_len * num_repeats) + tr_img_len - - scheduleIter = iter(LearnSchedule(learn_rate, steps, ititial_step)) - (learn_rate, end_step) = next(scheduleIter) + schedules = iter(LearnSchedule(learn_rate, steps, ititial_step)) + (learn_rate, end_step) = next(schedules) print(f'Training at rate of {learn_rate} until step {end_step}') optimizer = torch.optim.AdamW([embedding.vec], lr=learn_rate) @@ -213,7 +211,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini if embedding.step > end_step: try: - (learn_rate, end_step) = next(scheduleIter) + (learn_rate, end_step) = next(schedules) except: break tqdm.tqdm.write(f'Training at rate of {learn_rate} until step {end_step}') @@ -288,37 +286,3 @@ Last saved image: {html.escape(last_saved_image)}
embedding.save(filename) return embedding, filename - -class LearnSchedule: - def __init__(self, learn_rate, max_steps, cur_step=0): - pairs = learn_rate.split(',') - self.rates = [] - self.it = 0 - self.maxit = 0 - for i, pair in enumerate(pairs): - tmp = pair.split(':') - if len(tmp) == 2: - step = int(tmp[1]) - if step > cur_step: - self.rates.append((float(tmp[0]), min(step, max_steps))) - self.maxit += 1 - if step > max_steps: - return - elif step == -1: - self.rates.append((float(tmp[0]), max_steps)) - self.maxit += 1 - return - else: - self.rates.append((float(tmp[0]), max_steps)) - self.maxit += 1 - return - - def __iter__(self): - return self - - def __next__(self): - if self.it < self.maxit: - self.it += 1 - return self.rates[self.it - 1] - else: - raise StopIteration diff --git a/modules/ui.py b/modules/ui.py index 2b688e32..1204eef7 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1070,7 +1070,7 @@ def create_ui(wrap_gradio_gpu_call): gr.HTML(value="

Train an embedding; must specify a directory with a set of 1:1 ratio images

") train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()]) - learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value = "5.0e-03") + learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.005") dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images") log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion") template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt")) -- cgit v1.2.3 From f53f703aebc801c4204182d52bb1e0bef9808e1f Mon Sep 17 00:00:00 2001 From: JC_Array Date: Tue, 11 Oct 2022 18:12:12 -0500 Subject: resolved conflicts, moved settings under interrogate section, settings only show if deepbooru flag is enabled --- modules/deepbooru.py | 2 +- modules/shared.py | 19 +++++++++---------- modules/textual_inversion/preprocess.py | 2 +- modules/ui.py | 2 +- 4 files changed, 12 insertions(+), 13 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/deepbooru.py b/modules/deepbooru.py index 89dcac3c..29529949 100644 --- a/modules/deepbooru.py +++ b/modules/deepbooru.py @@ -8,7 +8,7 @@ def get_deepbooru_tags(pil_image): This method is for running only one image at a time for simple use. Used to the img2img interrogate. """ from modules import shared # prevents circular reference - create_deepbooru_process(shared.opts.deepbooru_threshold, shared.opts.deepbooru_sort_alpha) + create_deepbooru_process(shared.opts.interrogate_deepbooru_score_threshold, shared.opts.deepbooru_sort_alpha) shared.deepbooru_process_return["value"] = -1 shared.deepbooru_process_queue.put(pil_image) while shared.deepbooru_process_return["value"] == -1: diff --git a/modules/shared.py b/modules/shared.py index 817203f8..5456c477 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -248,15 +248,20 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}), })) -options_templates.update(options_section(('interrogate', "Interrogate Options"), { +interrogate_option_dictionary = { "interrogate_keep_models_in_memory": OptionInfo(False, "Interrogate: keep models in VRAM"), "interrogate_use_builtin_artists": OptionInfo(True, "Interrogate: use artists from artists.csv"), "interrogate_clip_num_beams": OptionInfo(1, "Interrogate: num_beams for BLIP", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}), "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}), "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}), - "interrogate_clip_dict_limit": OptionInfo(1500, "Interrogate: maximum number of lines in text file (0 = No limit)"), - "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), -})) + "interrogate_clip_dict_limit": OptionInfo(1500, "Interrogate: maximum number of lines in text file (0 = No limit)") +} + +if cmd_opts.deepdanbooru: + interrogate_option_dictionary["interrogate_deepbooru_score_threshold"] = OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}) + interrogate_option_dictionary["deepbooru_sort_alpha"] = OptionInfo(True, "Interrogate: deepbooru sort alphabetically", gr.Checkbox) + +options_templates.update(options_section(('interrogate', "Interrogate Options"), interrogate_option_dictionary)) options_templates.update(options_section(('ui', "User interface"), { "show_progressbar": OptionInfo(True, "Show progressbar"), @@ -282,12 +287,6 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}), })) -if cmd_opts.deepdanbooru: - options_templates.update(options_section(('deepbooru-params', "DeepBooru parameters"), { - "deepbooru_sort_alpha": OptionInfo(True, "Sort Alphabetical", gr.Checkbox), - 'deepbooru_threshold': OptionInfo(0.5, "Threshold", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - })) - class Options: data = None diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index a96388d6..113cecf1 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -29,7 +29,7 @@ def preprocess(process_src, process_dst, process_width, process_height, process_ shared.interrogator.load() if process_caption_deepbooru: - deepbooru.create_deepbooru_process(opts.deepbooru_threshold, opts.deepbooru_sort_alpha) + deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, opts.deepbooru_sort_alpha) def save_pic_with_caption(image, index): if process_caption: diff --git a/modules/ui.py b/modules/ui.py index 2891fc8c..fa45edca 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -317,7 +317,7 @@ def interrogate(image): def interrogate_deepbooru(image): - prompt = get_deepbooru_tags(image, opts.interrogate_deepbooru_score_threshold) + prompt = get_deepbooru_tags(image) return gr_show(True) if prompt is None else prompt -- cgit v1.2.3 From fec2221eeaafb50afd26ba3e109bf6f928011e69 Mon Sep 17 00:00:00 2001 From: Greg Fuller Date: Tue, 11 Oct 2022 19:29:38 -0700 Subject: Truncate error text to fix service lockup / stall What: * Update wrap_gradio_call to add a limit to the maximum amount of text output Why: * wrap_gradio_call currently prints out a list of the arguments provided to the failing function. * if that function is save_image, this causes the entire image to be printed to stderr * If the image is large, this can cause the service to lock up while attempting to print all the text * It is easy to generate large images using the x/y plot script * it is easy to encounter image save exceptions, including if the output directory does not exist / cannot be written to, or if the file is too big * The huge amount of log spam is confusing and not particularly helpful --- modules/ui.py | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 1204eef7..33a49d3b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -181,8 +181,15 @@ def wrap_gradio_call(func, extra_outputs=None): try: res = list(func(*args, **kwargs)) except Exception as e: + # When printing out our debug argument list, do not print out more than a MB of text + max_debug_str_len = 131072 # (1024*1024)/8 + print("Error completing request", file=sys.stderr) - print("Arguments:", args, kwargs, file=sys.stderr) + argStr = f"Arguments: {str(args)} {str(kwargs)}" + print(argStr[:max_debug_str_len], file=sys.stderr) + if len(argStr) > max_debug_str_len: + print(f"(Argument list truncated at {max_debug_str_len}/{len(argStr)} characters)", file=sys.stderr) + print(traceback.format_exc(), file=sys.stderr) shared.state.job = "" -- cgit v1.2.3 From 57e03cdd244eee4e33ccab7554b3594563a3d0cd Mon Sep 17 00:00:00 2001 From: brkirch Date: Wed, 12 Oct 2022 00:54:24 -0400 Subject: Ensure the directory exists before saving to it The directory for the images saved with the Save button may still not exist, so it needs to be created prior to opening the log.csv file. --- modules/ui.py | 2 ++ 1 file changed, 2 insertions(+) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 00bf09ae..cd67b84b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -131,6 +131,8 @@ def save_files(js_data, images, do_make_zip, index): images = [images[index]] start_index = index + os.makedirs(opts.outdir_save, exist_ok=True) + with open(os.path.join(opts.outdir_save, "log.csv"), "a", encoding="utf8", newline='') as file: at_start = file.tell() == 0 writer = csv.writer(file) -- cgit v1.2.3 From ee015a1af66a94a75c914659fa0d321e702a0a87 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 12 Oct 2022 11:05:57 +0300 Subject: change textual inversion tab to train remake train interface to use tabs --- modules/hypernetworks/hypernetwork.py | 2 +- modules/ui.py | 22 +++++++++------------- 2 files changed, 10 insertions(+), 14 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 8f2192e2..8314450a 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -175,7 +175,7 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None): def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt): - assert hypernetwork_name, 'embedding not selected' + assert hypernetwork_name, 'hypernetwork not selected' path = shared.hypernetworks.get(hypernetwork_name, None) shared.loaded_hypernetwork = Hypernetwork() diff --git a/modules/ui.py b/modules/ui.py index 4bfdd275..86a2da6c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1035,14 +1035,14 @@ def create_ui(wrap_gradio_gpu_call): sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings() - with gr.Blocks() as textual_inversion_interface: + with gr.Blocks() as train_interface: with gr.Row().style(equal_height=False): - with gr.Column(): - with gr.Group(): - gr.HTML(value="

See wiki for detailed explanation.

") + gr.HTML(value="

See wiki for detailed explanation.

") - gr.HTML(value="

Create a new embedding

") + with gr.Row().style(equal_height=False): + with gr.Tabs(elem_id="train_tabs"): + with gr.Tab(label="Create embedding"): new_embedding_name = gr.Textbox(label="Name") initialization_text = gr.Textbox(label="Initialization text", value="*") nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1) @@ -1054,9 +1054,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column(): create_embedding = gr.Button(value="Create embedding", variant='primary') - with gr.Group(): - gr.HTML(value="

Create a new hypernetwork

") - + with gr.Tab(label="Create hypernetwork"): new_hypernetwork_name = gr.Textbox(label="Name") new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) @@ -1067,9 +1065,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column(): create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary') - with gr.Group(): - gr.HTML(value="

Preprocess images

") - + with gr.Tab(label="Preprocess images"): process_src = gr.Textbox(label='Source directory') process_dst = gr.Textbox(label='Destination directory') process_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512) @@ -1091,7 +1087,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column(): run_preprocess = gr.Button(value="Preprocess", variant='primary') - with gr.Group(): + with gr.Tab(label="Train"): gr.HTML(value="

Train an embedding; must specify a directory with a set of 1:1 ratio images

") train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()]) @@ -1388,7 +1384,7 @@ Requested path was: {f} (extras_interface, "Extras", "extras"), (pnginfo_interface, "PNG Info", "pnginfo"), (modelmerger_interface, "Checkpoint Merger", "modelmerger"), - (textual_inversion_interface, "Textual inversion", "ti"), + (train_interface, "Train", "ti"), (settings_interface, "Settings", "settings"), ] -- cgit v1.2.3 From a1a94b8b5f342f467aecc53b21b80ed0227ee76a Mon Sep 17 00:00:00 2001 From: yfszzx Date: Thu, 13 Oct 2022 00:19:34 +0800 Subject: images history improvement --- javascript/images_history.js | 125 ++++++++++++++++++++++--------------------- modules/images_history.py | 7 +-- modules/ui.py | 40 +++++++------- 3 files changed, 88 insertions(+), 84 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/images_history.js b/javascript/images_history.js index c9a63166..620f242c 100644 --- a/javascript/images_history.js +++ b/javascript/images_history.js @@ -18,20 +18,26 @@ var images_history_click_image = function(){ } var images_history_click_tab = function(){ - var tabs_box = gradioApp().getElementById("images_history_tab"); - if (!tabs_box.classList.contains(this.getAttribute("tabname"))) { - gradioApp().getElementById(this.getAttribute("tabname") + "_images_history_renew_page").click(); - tabs_box.classList.add(this.getAttribute("tabname")) - } + var tabs_box = gradioApp().getElementById("images_history_tab"); + if (!tabs_box.classList.contains(this.getAttribute("tabname"))) { + gradioApp().getElementById(this.getAttribute("tabname") + "_images_history_renew_page").click(); + tabs_box.classList.add(this.getAttribute("tabname")) + } } var images_history_close_full_view = function(){ - var box = images_history_get_parent_by_class(this, "images_history_cantainor"); - box.querySelector(".images_history_del_button").setAttribute("disabled", "disabled"); + var box = images_history_get_parent_by_class(this, "images_history_cantainor"); + box.querySelector(".images_history_del_button").setAttribute("disabled", "disabled"); +} + +function images_history_disabled_del(){ + gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){ + btn.setAttribute('disabled','disabled'); + }); } function images_history_get_parent_by_class(item, class_name){ - var parent = item.parentElement; + var parent = item.parentElement; while(!parent.classList.contains(class_name)){ parent = parent.parentElement; } @@ -39,14 +45,15 @@ function images_history_get_parent_by_class(item, class_name){ } function images_history_get_parent_by_tagname(item, tagname){ - var parent = item.parentElement; - tagname = tagname.toUpperCase() + var parent = item.parentElement; + tagname = tagname.toUpperCase() while(parent.tagName != tagname){ - console.log(parent.tagName, tagname) + console.log(parent.tagName, tagname) parent = parent.parentElement; } return parent; } + function images_history_hide_buttons(hidden_list, gallery){ var buttons = gallery.querySelectorAll(".gallery-item"); var num = 0; @@ -54,7 +61,7 @@ function images_history_hide_buttons(hidden_list, gallery){ if (e.style.display == "none"){ num += 1; } - }) + }); if (num == hidden_list.length){ setTimeout(images_history_hide_buttons, 10, hidden_list, gallery); } @@ -74,14 +81,15 @@ function images_history_set_image_info(button){ if(e.style.display != "none"){ i += 1; } - }) + }); var gallery = images_history_get_parent_by_class(button, "images_history_cantainor"); var set_btn = gallery.querySelector(".images_history_set_index"); - set_btn.setAttribute("img_index", index); + var curr_idx = set_btn.getAttribute("img_index", index); + if (curr_idx != index) { + set_btn.setAttribute("img_index", index); + images_history_disabled_del(); + } set_btn.click(); - gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){ - btn.setAttribute('disabled','disabled'); - }) } @@ -102,24 +110,24 @@ function images_history_delete(tabname, img_path, img_file_name, page_index, fil if (e.style.display != 'none'){ buttons.push(e); } - }); - + }); var img_num = buttons.length / 2; if (img_num === 1){ setTimeout(function(tabname){ gradioApp().getElementById(tabname + '_images_history_renew_page').click(); }, 30, tabname); - } else { + } else { buttons[image_index].style.display = 'none'; buttons[image_index + img_num].style.display = 'none'; var bnt; if (image_index >= img_num - 1){ btn = buttons[img_num - 2]; - } else { + } else { btn = buttons[image_index + 1] ; - } + } setTimeout(function(btn){btn.click()}, 30, btn); - } + } + images_history_disabled_del(); return [tabname, img_path, img_file_name, page_index, filenames, image_index]; } @@ -132,61 +140,58 @@ function images_history_turnpage(img_path, page_index, image_index, tabname){ } function images_history_enable_del_buttons(){ - gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){ - btn.removeAttribute('disabled'); + gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){ + btn.removeAttribute('disabled'); }) } function images_history_init(){ - if (gradioApp().getElementById('txt2img_images_history_renew_page') == null) { - setTimeout(images_history_init, 500); - } else { + var load_txt2img_button = gradioApp().getElementById('txt2img_images_history_renew_page') + if (load_txt2img_button){ for (var i in images_history_tab_list ){ tab = images_history_tab_list[i]; gradioApp().getElementById(tab + '_images_history').classList.add("images_history_cantainor"); gradioApp().getElementById(tab + '_images_history_set_index').classList.add("images_history_set_index"); gradioApp().getElementById(tab + '_images_history_del_button').classList.add("images_history_del_button"); - gradioApp().getElementById(tab + '_images_history_gallery').classList.add("images_history_gallery"); - - + gradioApp().getElementById(tab + '_images_history_gallery').classList.add("images_history_gallery"); + } var tabs_box = gradioApp().getElementById("tab_images_history").querySelector("div").querySelector("div").querySelector("div"); - tabs_box.setAttribute("id", "images_history_tab"); - tabs_box.classList.add(images_history_tab_list[0]); - gradioApp().getElementById("txt2img_images_history_renew_page").click(); - } + tabs_box.setAttribute("id", "images_history_tab"); + var tab_btns = tabs_box.querySelectorAll("button"); + for (var i in images_history_tab_list){ + var tabname = images_history_tab_list[i] + tab_btns[i].setAttribute("tabname", tabname); + tab_btns[i].addEventListener('click', images_history_click_tab); + } + tabs_box.classList.add(images_history_tab_list[0]); + load_txt2img_button.click(); + } else { + setTimeout(images_history_init, 500); + } } var images_history_tab_list = ["txt2img", "img2img", "extras"]; -var images_history_start_flag = false; - -onUiUpdate(function(){ - var tab = gradioApp().getElementById("images_history_tab"); - if (tab) { - if (!images_history_start_flag){ - images_history_init(); - images_history_start_flag = true; - } - var tab_btns = gradioApp().getElementById("images_history_tab").querySelectorAll("button"); - for (var i in images_history_tab_list ){ - var buttons = gradioApp().querySelectorAll('#' + images_history_tab_list[i] + '_images_history .gallery-item'); - buttons.forEach(function(bnt){ - bnt.addEventListener('click', images_history_click_image, true); - }); - var tabname = images_history_tab_list[i] - tab_btns[i].setAttribute("tabname", tabname); - tab_btns[i].addEventListener('click', images_history_click_tab, true); +setTimeout(images_history_init, 500) +document.addEventListener("DOMContentLoaded", function() { + var mutationObserver = new MutationObserver(function(m){ + for (var i in images_history_tab_list ){ + var buttons = gradioApp().querySelectorAll('#' + images_history_tab_list[i] + '_images_history .gallery-item'); + buttons.forEach(function(bnt){ + bnt.addEventListener('click', images_history_click_image, true); + }); // var cls_btn = gradioApp().getElementById(tabname + '_images_history_gallery').querySelector("svg"); // if (cls_btn){ - // cls_btn.addEventListener('click', images_history_close_full_view, false); + // cls_btn.addEventListener('click', images_history_close_full_view, false); // } // console.log(cls_btn, cls_btn.parentElement.parentElement) // if (cls_btn) { - // cls_btn = images_history_get_parent_by_tagname(cls_btn, "BUTTON"); - // cls_btn.addEventListener('click', images_history_close_full_view, true); - // } - } + // cls_btn = images_history_get_parent_by_tagname(cls_btn, "BUTTON"); + // cls_btn.addEventListener('click', images_history_close_full_view, true); + } + }); + mutationObserver.observe( gradioApp(), { childList:true, subtree:true }); + +}); - } -}); diff --git a/modules/images_history.py b/modules/images_history.py index 2bc4b7ee..1bca0ad9 100644 --- a/modules/images_history.py +++ b/modules/images_history.py @@ -61,7 +61,7 @@ def delete_image(tabname, dir_name, name, page_index, filenames, image_index): os.remove(path) txt_file = os.path.splitext(path)[0] + ".txt" if os.path.exists(txt_file): - os.remove(txt_file) + os.remove(txt_file) new_file_list = [] for f in filenames: if f == name: @@ -88,7 +88,7 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): end_page = gr.Button('End Page') with gr.Row(elem_id=tabname + "_images_history"): with gr.Row(): - with gr.Column(scale=2): + with gr.Column(scale=2): history_gallery = gr.Gallery(show_label=False, elem_id=tabname + "_images_history_gallery").style(grid=6) delete = gr.Button('Delete', elem_id=tabname + "_images_history_del_button") with gr.Column(): @@ -126,9 +126,10 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): #other funcitons set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[tabname_box, img_path, filenames], outputs=[img_file_name, image_index, hide_image]) + img_file_name.change(fn=None, _js="images_history_enable_del_buttons", inputs=None, outputs=None) delete.click(delete_image,_js="images_history_delete", inputs=[tabname_box, img_path, img_file_name, page_index, filenames, image_index], outputs=[page_index, filenames]) hide_image.change(fn=run_pnginfo, inputs=[hide_image], outputs=[info1, img_file_info, info2]) - hide_image.change(fn=None, _js="images_history_enable_del_buttons", inputs=None, outputs=None) + #pnginfo.click(fn=run_pnginfo, inputs=[hide_image], outputs=[info1, img_file_info, info2]) switch_dict["fn"](pnginfo_send_to_txt2img, switch_dict["t2i"], img_file_info, 'switch_to_txt2img') switch_dict["fn"](pnginfo_send_to_img2img, switch_dict["i2i"], img_file_info, 'switch_to_img2img_img2img') diff --git a/modules/ui.py b/modules/ui.py index 94297ba6..8cd12b51 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -39,7 +39,7 @@ import modules.generation_parameters_copypaste from modules import prompt_parser from modules.images import save_image import modules.textual_inversion.ui -import modules.hypernetwork.ui +import modules.hypernetworks.ui import modules.images_history as img_his # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI @@ -554,6 +554,7 @@ def create_ui(wrap_gradio_gpu_call): custom_inputs = modules.scripts.scripts_txt2img.setup_ui(is_img2img=False) with gr.Column(variant='panel'): + with gr.Group(): txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False) txt2img_gallery = gr.Gallery(label='Output', show_label=False, elem_id='txt2img_gallery').style(grid=4) @@ -573,9 +574,9 @@ def create_ui(wrap_gradio_gpu_call): with gr.Row(): download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False) - with gr.Group(): - html_info = gr.HTML() - generation_info = gr.Textbox(visible=False) + with gr.Group(): + html_info = gr.HTML() + generation_info = gr.Textbox(visible=False) connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) @@ -669,7 +670,6 @@ def create_ui(wrap_gradio_gpu_call): ] modules.generation_parameters_copypaste.connect_paste(paste, txt2img_paste_fields, txt2img_prompt) token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter]) - with gr.Blocks(analytics_enabled=False) as img2img_interface: img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True) @@ -762,10 +762,10 @@ def create_ui(wrap_gradio_gpu_call): with gr.Row(): download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False) - with gr.Group(): - html_info = gr.HTML() - generation_info = gr.Textbox(visible=False) - + with gr.Group(): + html_info = gr.HTML() + generation_info = gr.Textbox(visible=False) + connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) @@ -1016,6 +1016,13 @@ def create_ui(wrap_gradio_gpu_call): inputs=[image], outputs=[html, generation_info, html2], ) + #images history + images_history_switch_dict = { + "fn":modules.generation_parameters_copypaste.connect_paste, + "t2i":txt2img_paste_fields, + "i2i":img2img_paste_fields + } + images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) with gr.Blocks() as modelmerger_interface: with gr.Row().style(equal_height=False): @@ -1285,16 +1292,7 @@ Requested path was: {f} opts.save(shared.config_filename) - return f'{changed} settings changed.', opts.dumpjson() - - #images history - images_history_switch_dict = { - "fn":modules.generation_parameters_copypaste.connect_paste, - "t2i":txt2img_paste_fields, - "i2i":img2img_paste_fields - } - images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) - + return f'{changed} settings changed.', opts.dumpjson() def run_settings_single(value, key): if not opts.same_type(value, opts.data_labels[key].default): @@ -1393,11 +1391,10 @@ Requested path was: {f} (img2img_interface, "img2img", "img2img"), (extras_interface, "Extras", "extras"), (pnginfo_interface, "PNG Info", "pnginfo"), - (modelmerger_interface, "Checkpoint Merger", "modelmerger"), (images_history, "History", "images_history"), + (modelmerger_interface, "Checkpoint Merger", "modelmerger"), (train_interface, "Train", "ti"), (settings_interface, "Settings", "settings"), - ] with open(os.path.join(script_path, "style.css"), "r", encoding="utf8") as file: @@ -1616,3 +1613,4 @@ if 'gradio_routes_templates_response' not in globals(): gradio_routes_templates_response = gradio.routes.templates.TemplateResponse gradio.routes.templates.TemplateResponse = template_response + -- cgit v1.2.3 From c3c8eef9fd5a0c8b26319e32ca4a19b56204e6df Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 12 Oct 2022 20:49:47 +0300 Subject: train: change filename processing to be more simple and configurable train: make it possible to make text files with prompts train: rework scheduler so that there's less repeating code in textual inversion and hypernets train: move epochs setting to options --- javascript/hints.js | 3 ++ modules/hypernetworks/hypernetwork.py | 40 +++++++++------------- modules/shared.py | 3 ++ modules/textual_inversion/dataset.py | 47 +++++++++++++++++++------- modules/textual_inversion/learn_schedule.py | 37 +++++++++++++++++++- modules/textual_inversion/textual_inversion.py | 35 +++++++------------ modules/ui.py | 2 -- 7 files changed, 105 insertions(+), 62 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/hints.js b/javascript/hints.js index b81c181b..d51ee14c 100644 --- a/javascript/hints.js +++ b/javascript/hints.js @@ -81,6 +81,9 @@ titles = { "Eta noise seed delta": "If this values is non-zero, it will be added to seed and used to initialize RNG for noises when using samplers with Eta. You can use this to produce even more variation of images, or you can use this to match images of other software if you know what you are doing.", "Do not add watermark to images": "If this option is enabled, watermark will not be added to created images. Warning: if you do not add watermark, you may be behaving in an unethical manner.", + + "Filename word regex": "This regular expression will be used extract words from filename, and they will be joined using the option below into label text used for training. Leave empty to keep filename text as it is.", + "Filename join string": "This string will be used to hoin split words into a single line if the option above is enabled.", } diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 8314450a..b6c06d49 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -14,7 +14,7 @@ import torch from torch import einsum from einops import rearrange, repeat import modules.textual_inversion.dataset -from modules.textual_inversion.learn_schedule import LearnSchedule +from modules.textual_inversion.learn_schedule import LearnRateScheduler class HypernetworkModule(torch.nn.Module): @@ -223,31 +223,23 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, if ititial_step > steps: return hypernetwork, filename - schedules = iter(LearnSchedule(learn_rate, steps, ititial_step)) - (learn_rate, end_step) = next(schedules) - print(f'Training at rate of {learn_rate} until step {end_step}') - - optimizer = torch.optim.AdamW(weights, lr=learn_rate) + scheduler = LearnRateScheduler(learn_rate, steps, ititial_step) + optimizer = torch.optim.AdamW(weights, lr=scheduler.learn_rate) pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step) - for i, (x, text, cond) in pbar: + for i, entry in pbar: hypernetwork.step = i + ititial_step - if hypernetwork.step > end_step: - try: - (learn_rate, end_step) = next(schedules) - except Exception: - break - tqdm.tqdm.write(f'Training at rate of {learn_rate} until step {end_step}') - for pg in optimizer.param_groups: - pg['lr'] = learn_rate + scheduler.apply(optimizer, hypernetwork.step) + if scheduler.finished: + break if shared.state.interrupted: break with torch.autocast("cuda"): - cond = cond.to(devices.device) - x = x.to(devices.device) + cond = entry.cond.to(devices.device) + x = entry.latent.to(devices.device) loss = shared.sd_model(x.unsqueeze(0), cond)[0] del x del cond @@ -267,7 +259,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0: last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png') - preview_text = text if preview_image_prompt == "" else preview_image_prompt + preview_text = entry.cond_text if preview_image_prompt == "" else preview_image_prompt optimizer.zero_grad() shared.sd_model.cond_stage_model.to(devices.device) @@ -282,16 +274,16 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, ) processed = processing.process_images(p) - image = processed.images[0] + image = processed.images[0] if len(processed.images)>0 else None if unload: shared.sd_model.cond_stage_model.to(devices.cpu) shared.sd_model.first_stage_model.to(devices.cpu) - shared.state.current_image = image - image.save(last_saved_image) - - last_saved_image += f", prompt: {preview_text}" + if image is not None: + shared.state.current_image = image + image.save(last_saved_image) + last_saved_image += f", prompt: {preview_text}" shared.state.job_no = hypernetwork.step @@ -299,7 +291,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,

Loss: {losses.mean():.7f}
Step: {hypernetwork.step}
-Last prompt: {html.escape(text)}
+Last prompt: {html.escape(entry.cond_text)}
Last saved embedding: {html.escape(last_saved_file)}
Last saved image: {html.escape(last_saved_image)}

diff --git a/modules/shared.py b/modules/shared.py index 42e99741..e64e69fc 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -231,6 +231,9 @@ options_templates.update(options_section(('system', "System"), { options_templates.update(options_section(('training', "Training"), { "unload_models_when_training": OptionInfo(False, "Unload VAE and CLIP from VRAM when training"), + "dataset_filename_word_regex": OptionInfo("", "Filename word regex"), + "dataset_filename_join_string": OptionInfo(" ", "Filename join string"), + "training_image_repeats_per_epoch": OptionInfo(100, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}), })) options_templates.update(options_section(('sd', "Stable Diffusion"), { diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py index f61f40d3..67e90afe 100644 --- a/modules/textual_inversion/dataset.py +++ b/modules/textual_inversion/dataset.py @@ -11,11 +11,21 @@ import tqdm from modules import devices, shared import re -re_tag = re.compile(r"[a-zA-Z][_\w\d()]+") +re_numbers_at_start = re.compile(r"^[-\d]+\s*") + + +class DatasetEntry: + def __init__(self, filename=None, latent=None, filename_text=None): + self.filename = filename + self.latent = latent + self.filename_text = filename_text + self.cond = None + self.cond_text = None class PersonalizedBase(Dataset): def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None, include_cond=False): + re_word = re.compile(shared.opts.dataset_filename_word_regex) if len(shared.opts.dataset_filename_word_regex)>0 else None self.placeholder_token = placeholder_token @@ -42,9 +52,18 @@ class PersonalizedBase(Dataset): except Exception: continue + text_filename = os.path.splitext(path)[0] + ".txt" filename = os.path.basename(path) - filename_tokens = os.path.splitext(filename)[0] - filename_tokens = re_tag.findall(filename_tokens) + + if os.path.exists(text_filename): + with open(text_filename, "r", encoding="utf8") as file: + filename_text = file.read() + else: + filename_text = os.path.splitext(filename)[0] + filename_text = re.sub(re_numbers_at_start, '', filename_text) + if re_word: + tokens = re_word.findall(filename_text) + filename_text = (shared.opts.dataset_filename_join_string or "").join(tokens) npimage = np.array(image).astype(np.uint8) npimage = (npimage / 127.5 - 1.0).astype(np.float32) @@ -55,13 +74,13 @@ class PersonalizedBase(Dataset): init_latent = model.get_first_stage_encoding(model.encode_first_stage(torchdata.unsqueeze(dim=0))).squeeze() init_latent = init_latent.to(devices.cpu) + entry = DatasetEntry(filename=path, filename_text=filename_text, latent=init_latent) + if include_cond: - text = self.create_text(filename_tokens) - cond = cond_model([text]).to(devices.cpu) - else: - cond = None + entry.cond_text = self.create_text(filename_text) + entry.cond = cond_model([entry.cond_text]).to(devices.cpu) - self.dataset.append((init_latent, filename_tokens, cond)) + self.dataset.append(entry) self.length = len(self.dataset) * repeats @@ -72,10 +91,10 @@ class PersonalizedBase(Dataset): def shuffle(self): self.indexes = self.initial_indexes[torch.randperm(self.initial_indexes.shape[0])] - def create_text(self, filename_tokens): + def create_text(self, filename_text): text = random.choice(self.lines) text = text.replace("[name]", self.placeholder_token) - text = text.replace("[filewords]", ' '.join(filename_tokens)) + text = text.replace("[filewords]", filename_text) return text def __len__(self): @@ -86,7 +105,9 @@ class PersonalizedBase(Dataset): self.shuffle() index = self.indexes[i % len(self.indexes)] - x, filename_tokens, cond = self.dataset[index] + entry = self.dataset[index] + + if entry.cond is None: + entry.cond_text = self.create_text(entry.filename_text) - text = self.create_text(filename_tokens) - return x, text, cond + return entry diff --git a/modules/textual_inversion/learn_schedule.py b/modules/textual_inversion/learn_schedule.py index db720271..2062726a 100644 --- a/modules/textual_inversion/learn_schedule.py +++ b/modules/textual_inversion/learn_schedule.py @@ -1,6 +1,12 @@ +import tqdm -class LearnSchedule: + +class LearnScheduleIterator: def __init__(self, learn_rate, max_steps, cur_step=0): + """ + specify learn_rate as "0.001:100, 0.00001:1000, 1e-5:10000" to have lr of 0.001 until step 100, 0.00001 until 1000, 1e-5:10000 until 10000 + """ + pairs = learn_rate.split(',') self.rates = [] self.it = 0 @@ -32,3 +38,32 @@ class LearnSchedule: return self.rates[self.it - 1] else: raise StopIteration + + +class LearnRateScheduler: + def __init__(self, learn_rate, max_steps, cur_step=0, verbose=True): + self.schedules = LearnScheduleIterator(learn_rate, max_steps, cur_step) + (self.learn_rate, self.end_step) = next(self.schedules) + self.verbose = verbose + + if self.verbose: + print(f'Training at rate of {self.learn_rate} until step {self.end_step}') + + self.finished = False + + def apply(self, optimizer, step_number): + if step_number <= self.end_step: + return + + try: + (self.learn_rate, self.end_step) = next(self.schedules) + except Exception: + self.finished = True + return + + if self.verbose: + tqdm.tqdm.write(f'Training at rate of {self.learn_rate} until step {self.end_step}') + + for pg in optimizer.param_groups: + pg['lr'] = self.learn_rate + diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index c5153e4a..fa0e33a2 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -11,7 +11,7 @@ from PIL import Image, PngImagePlugin from modules import shared, devices, sd_hijack, processing, sd_models import modules.textual_inversion.dataset -from modules.textual_inversion.learn_schedule import LearnSchedule +from modules.textual_inversion.learn_schedule import LearnRateScheduler from modules.textual_inversion.image_embedding import (embedding_to_b64, embedding_from_b64, insert_image_data_embed, extract_image_data_embed, @@ -172,8 +172,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'): return fn - -def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, num_repeats, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_image_prompt): +def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_image_prompt): assert embedding_name, 'embedding not selected' shared.state.textinfo = "Initializing textual inversion training..." @@ -205,7 +204,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..." with torch.autocast("cuda"): - ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=num_repeats, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file) + ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file) hijack = sd_hijack.model_hijack @@ -221,32 +220,24 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini if ititial_step > steps: return embedding, filename - schedules = iter(LearnSchedule(learn_rate, steps, ititial_step)) - (learn_rate, end_step) = next(schedules) - print(f'Training at rate of {learn_rate} until step {end_step}') - - optimizer = torch.optim.AdamW([embedding.vec], lr=learn_rate) + scheduler = LearnRateScheduler(learn_rate, steps, ititial_step) + optimizer = torch.optim.AdamW([embedding.vec], lr=scheduler.learn_rate) pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step) - for i, (x, text, _) in pbar: + for i, entry in pbar: embedding.step = i + ititial_step - if embedding.step > end_step: - try: - (learn_rate, end_step) = next(schedules) - except: - break - tqdm.tqdm.write(f'Training at rate of {learn_rate} until step {end_step}') - for pg in optimizer.param_groups: - pg['lr'] = learn_rate + scheduler.apply(optimizer, embedding.step) + if scheduler.finished: + break if shared.state.interrupted: break with torch.autocast("cuda"): - c = cond_model([text]) + c = cond_model([entry.cond_text]) - x = x.to(devices.device) + x = entry.latent.to(devices.device) loss = shared.sd_model(x.unsqueeze(0), c)[0] del x @@ -268,7 +259,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0: last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png') - preview_text = text if preview_image_prompt == "" else preview_image_prompt + preview_text = entry.cond_text if preview_image_prompt == "" else preview_image_prompt p = processing.StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, @@ -314,7 +305,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini

Loss: {losses.mean():.7f}
Step: {embedding.step}
-Last prompt: {html.escape(text)}
+Last prompt: {html.escape(entry.cond_text)}
Last saved embedding: {html.escape(last_saved_file)}
Last saved image: {html.escape(last_saved_image)}

diff --git a/modules/ui.py b/modules/ui.py index 2b332267..c42535c8 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1098,7 +1098,6 @@ def create_ui(wrap_gradio_gpu_call): training_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512) training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) steps = gr.Number(label='Max steps', value=100000, precision=0) - num_repeats = gr.Number(label='Number of repeats for a single input image per epoch', value=100, precision=0) create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0) save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0) save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True) @@ -1176,7 +1175,6 @@ def create_ui(wrap_gradio_gpu_call): training_width, training_height, steps, - num_repeats, create_image_every, save_embedding_every, template_file, -- cgit v1.2.3 From 698d303b04e293635bfb49c525409f3bcf671dce Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 12 Oct 2022 21:55:43 +0300 Subject: deepbooru: added option to use spaces or underscores deepbooru: added option to quote (\) in tags deepbooru/BLIP: write caption to file instead of image filename deepbooru/BLIP: now possible to use both for captions deepbooru: process is stopped even if an exception occurs --- modules/deepbooru.py | 65 ++++++++++++++++++----- modules/shared.py | 2 + modules/textual_inversion/preprocess.py | 92 ++++++++++++++------------------- modules/ui.py | 7 +-- 4 files changed, 95 insertions(+), 71 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/deepbooru.py b/modules/deepbooru.py index 29529949..419e6a9c 100644 --- a/modules/deepbooru.py +++ b/modules/deepbooru.py @@ -2,33 +2,44 @@ import os.path from concurrent.futures import ProcessPoolExecutor import multiprocessing import time +import re + +re_special = re.compile(r'([\\()])') def get_deepbooru_tags(pil_image): """ This method is for running only one image at a time for simple use. Used to the img2img interrogate. """ from modules import shared # prevents circular reference - create_deepbooru_process(shared.opts.interrogate_deepbooru_score_threshold, shared.opts.deepbooru_sort_alpha) - shared.deepbooru_process_return["value"] = -1 - shared.deepbooru_process_queue.put(pil_image) - while shared.deepbooru_process_return["value"] == -1: - time.sleep(0.2) - tags = shared.deepbooru_process_return["value"] - release_process() - return tags + try: + create_deepbooru_process(shared.opts.interrogate_deepbooru_score_threshold, create_deepbooru_opts()) + return get_tags_from_process(pil_image) + finally: + release_process() + + +def create_deepbooru_opts(): + from modules import shared -def deepbooru_process(queue, deepbooru_process_return, threshold, alpha_sort): + return { + "use_spaces": shared.opts.deepbooru_use_spaces, + "use_escape": shared.opts.deepbooru_escape, + "alpha_sort": shared.opts.deepbooru_sort_alpha, + } + + +def deepbooru_process(queue, deepbooru_process_return, threshold, deepbooru_opts): model, tags = get_deepbooru_tags_model() while True: # while process is running, keep monitoring queue for new image pil_image = queue.get() if pil_image == "QUIT": break else: - deepbooru_process_return["value"] = get_deepbooru_tags_from_model(model, tags, pil_image, threshold, alpha_sort) + deepbooru_process_return["value"] = get_deepbooru_tags_from_model(model, tags, pil_image, threshold, deepbooru_opts) -def create_deepbooru_process(threshold, alpha_sort): +def create_deepbooru_process(threshold, deepbooru_opts): """ Creates deepbooru process. A queue is created to send images into the process. This enables multiple images to be processed in a row without reloading the model or creating a new process. To return the data, a shared @@ -41,10 +52,23 @@ def create_deepbooru_process(threshold, alpha_sort): shared.deepbooru_process_queue = shared.deepbooru_process_manager.Queue() shared.deepbooru_process_return = shared.deepbooru_process_manager.dict() shared.deepbooru_process_return["value"] = -1 - shared.deepbooru_process = multiprocessing.Process(target=deepbooru_process, args=(shared.deepbooru_process_queue, shared.deepbooru_process_return, threshold, alpha_sort)) + shared.deepbooru_process = multiprocessing.Process(target=deepbooru_process, args=(shared.deepbooru_process_queue, shared.deepbooru_process_return, threshold, deepbooru_opts)) shared.deepbooru_process.start() +def get_tags_from_process(image): + from modules import shared + + shared.deepbooru_process_return["value"] = -1 + shared.deepbooru_process_queue.put(image) + while shared.deepbooru_process_return["value"] == -1: + time.sleep(0.2) + caption = shared.deepbooru_process_return["value"] + shared.deepbooru_process_return["value"] = -1 + + return caption + + def release_process(): """ Stops the deepbooru process to return used memory @@ -81,10 +105,15 @@ def get_deepbooru_tags_model(): return model, tags -def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, alpha_sort): +def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, deepbooru_opts): import deepdanbooru as dd import tensorflow as tf import numpy as np + + alpha_sort = deepbooru_opts['alpha_sort'] + use_spaces = deepbooru_opts['use_spaces'] + use_escape = deepbooru_opts['use_escape'] + width = model.input_shape[2] height = model.input_shape[1] image = np.array(pil_image) @@ -129,4 +158,12 @@ def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, alpha_sort) print('\n'.join(sorted(result_tags_print, reverse=True))) - return ', '.join(result_tags_out).replace('_', ' ').replace(':', ' ') + tags_text = ', '.join(result_tags_out) + + if use_spaces: + tags_text = tags_text.replace('_', ' ') + + if use_escape: + tags_text = re.sub(re_special, r'\\\1', tags_text) + + return tags_text.replace(':', ' ') diff --git a/modules/shared.py b/modules/shared.py index e64e69fc..78b73aae 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -260,6 +260,8 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"), "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}), "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), "deepbooru_sort_alpha": OptionInfo(True, "Interrogate: deepbooru sort alphabetically"), + "deepbooru_use_spaces": OptionInfo(False, "use spaces for tags in deepbooru"), + "deepbooru_escape": OptionInfo(True, "escape (\\) brackets in deepbooru (so they are used as literal brackets and not for emphasis)"), })) options_templates.update(options_section(('ui', "User interface"), { diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index 113cecf1..3047bede 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -10,7 +10,28 @@ from modules.shared import opts, cmd_opts if cmd_opts.deepdanbooru: import modules.deepbooru as deepbooru + def preprocess(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru=False): + try: + if process_caption: + shared.interrogator.load() + + if process_caption_deepbooru: + deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, deepbooru.create_deepbooru_opts()) + + preprocess_work(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru) + + finally: + + if process_caption: + shared.interrogator.send_blip_to_ram() + + if process_caption_deepbooru: + deepbooru.release_process() + + + +def preprocess_work(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru=False): width = process_width height = process_height src = os.path.abspath(process_src) @@ -25,30 +46,28 @@ def preprocess(process_src, process_dst, process_width, process_height, process_ shared.state.textinfo = "Preprocessing..." shared.state.job_count = len(files) - if process_caption: - shared.interrogator.load() - - if process_caption_deepbooru: - deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, opts.deepbooru_sort_alpha) - def save_pic_with_caption(image, index): + caption = "" + if process_caption: - caption = "-" + shared.interrogator.generate_caption(image) - caption = sanitize_caption(os.path.join(dst, f"{index:05}-{subindex[0]}"), caption, ".png") - elif process_caption_deepbooru: - shared.deepbooru_process_return["value"] = -1 - shared.deepbooru_process_queue.put(image) - while shared.deepbooru_process_return["value"] == -1: - time.sleep(0.2) - caption = "-" + shared.deepbooru_process_return["value"] - caption = sanitize_caption(os.path.join(dst, f"{index:05}-{subindex[0]}"), caption, ".png") - shared.deepbooru_process_return["value"] = -1 - else: - caption = filename - caption = os.path.splitext(caption)[0] - caption = os.path.basename(caption) + caption += shared.interrogator.generate_caption(image) + + if process_caption_deepbooru: + if len(caption) > 0: + caption += ", " + caption += deepbooru.get_tags_from_process(image) + + filename_part = filename + filename_part = os.path.splitext(filename_part)[0] + filename_part = os.path.basename(filename_part) + + basename = f"{index:05}-{subindex[0]}-{filename_part}" + image.save(os.path.join(dst, f"{basename}.png")) + + if len(caption) > 0: + with open(os.path.join(dst, f"{basename}.txt"), "w", encoding="utf8") as file: + file.write(caption) - image.save(os.path.join(dst, f"{index:05}-{subindex[0]}{caption}.png")) subindex[0] += 1 def save_pic(image, index): @@ -93,34 +112,3 @@ def preprocess(process_src, process_dst, process_width, process_height, process_ save_pic(img, index) shared.state.nextjob() - - if process_caption: - shared.interrogator.send_blip_to_ram() - - if process_caption_deepbooru: - deepbooru.release_process() - - -def sanitize_caption(base_path, original_caption, suffix): - operating_system = platform.system().lower() - if (operating_system == "windows"): - invalid_path_characters = "\\/:*?\"<>|" - max_path_length = 259 - else: - invalid_path_characters = "/" #linux/macos - max_path_length = 1023 - caption = original_caption - for invalid_character in invalid_path_characters: - caption = caption.replace(invalid_character, "") - fixed_path_length = len(base_path) + len(suffix) - if fixed_path_length + len(caption) <= max_path_length: - return caption - caption_tokens = caption.split() - new_caption = "" - for token in caption_tokens: - last_caption = new_caption - new_caption = new_caption + token + " " - if (len(new_caption) + fixed_path_length - 1 > max_path_length): - break - print(f"\nPath will be too long. Truncated caption: {original_caption}\nto: {last_caption}", file=sys.stderr) - return last_caption.strip() diff --git a/modules/ui.py b/modules/ui.py index c42535c8..e07ee0e1 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1074,11 +1074,8 @@ def create_ui(wrap_gradio_gpu_call): with gr.Row(): process_flip = gr.Checkbox(label='Create flipped copies') process_split = gr.Checkbox(label='Split oversized images into two') - process_caption = gr.Checkbox(label='Use BLIP caption as filename') - if cmd_opts.deepdanbooru: - process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename') - else: - process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename', visible=False) + process_caption = gr.Checkbox(label='Use BLIP for caption') + process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True if cmd_opts.deepdanbooru else False) with gr.Row(): with gr.Column(scale=3): -- cgit v1.2.3 From 1cfc2a18981ee56bdb69a2de7b463a11ad05e329 Mon Sep 17 00:00:00 2001 From: Melan Date: Wed, 12 Oct 2022 23:36:29 +0200 Subject: Save a csv containing the loss while training --- modules/hypernetworks/hypernetwork.py | 17 ++++++++++++++++- modules/textual_inversion/textual_inversion.py | 17 ++++++++++++++++- modules/ui.py | 3 +++ 3 files changed, 35 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index b6c06d49..6522078f 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -5,6 +5,7 @@ import os import sys import traceback import tqdm +import csv import torch @@ -174,7 +175,7 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None): return self.to_out(out) -def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt): +def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, write_csv_every, template_file, preview_image_prompt): assert hypernetwork_name, 'hypernetwork not selected' path = shared.hypernetworks.get(hypernetwork_name, None) @@ -256,6 +257,20 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, last_saved_file = os.path.join(hypernetwork_dir, f'{hypernetwork_name}-{hypernetwork.step}.pt') hypernetwork.save(last_saved_file) + print(f"{write_csv_every} > {hypernetwork.step % write_csv_every == 0}, {write_csv_every}") + if write_csv_every > 0 and hypernetwork_dir is not None and hypernetwork.step % write_csv_every == 0: + write_csv_header = False if os.path.exists(os.path.join(hypernetwork_dir, "hypernetwork_loss.csv")) else True + + with open(os.path.join(hypernetwork_dir, "hypernetwork_loss.csv"), "a+") as fout: + + csv_writer = csv.DictWriter(fout, fieldnames=["step", "loss"]) + + if write_csv_header: + csv_writer.writeheader() + + csv_writer.writerow({"step": hypernetwork.step, + "loss": f"{losses.mean():.7f}"}) + if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0: last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png') diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index fa0e33a2..25038a89 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -6,6 +6,7 @@ import torch import tqdm import html import datetime +import csv from PIL import Image, PngImagePlugin @@ -172,7 +173,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'): return fn -def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_image_prompt): +def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, write_csv_every, template_file, save_image_with_stored_embedding, preview_image_prompt): assert embedding_name, 'embedding not selected' shared.state.textinfo = "Initializing textual inversion training..." @@ -256,6 +257,20 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini last_saved_file = os.path.join(embedding_dir, f'{embedding_name}-{embedding.step}.pt') embedding.save(last_saved_file) + if write_csv_every > 0 and log_directory is not None and embedding.step % write_csv_every == 0: + write_csv_header = False if os.path.exists(os.path.join(log_directory, "textual_inversion_loss.csv")) else True + + with open(os.path.join(log_directory, "textual_inversion_loss.csv"), "a+") as fout: + + csv_writer = csv.DictWriter(fout, fieldnames=["epoch", "epoch_step", "loss"]) + + if write_csv_header: + csv_writer.writeheader() + + csv_writer.writerow({"epoch": epoch_num + 1, + "epoch_step": epoch_step - 1, + "loss": f"{losses.mean():.7f}"}) + if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0: last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png') diff --git a/modules/ui.py b/modules/ui.py index e07ee0e1..1195c2f1 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1096,6 +1096,7 @@ def create_ui(wrap_gradio_gpu_call): training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) steps = gr.Number(label='Max steps', value=100000, precision=0) create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0) + write_csv_every = gr.Number(label='Save an csv containing the loss to log directory every N steps, 0 to disable', value=500, precision=0) save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0) save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True) preview_image_prompt = gr.Textbox(label='Preview prompt', value="") @@ -1174,6 +1175,7 @@ def create_ui(wrap_gradio_gpu_call): steps, create_image_every, save_embedding_every, + write_csv_every, template_file, save_image_with_stored_embedding, preview_image_prompt, @@ -1195,6 +1197,7 @@ def create_ui(wrap_gradio_gpu_call): steps, create_image_every, save_embedding_every, + write_csv_every, template_file, preview_image_prompt, ], -- cgit v1.2.3 From 54e0051bdd7dea7348825c09600ec61ea0771cb8 Mon Sep 17 00:00:00 2001 From: d8ahazard Date: Wed, 12 Oct 2022 18:17:26 -0500 Subject: Add drag/drop param loading. Drop an image or generational text onto the prompt bar, it loads the info for parsing. --- javascript/dragdrop.js | 3 +++ javascript/imageParams.js | 22 ++++++++++++++++++++++ modules/images.py | 20 ++++++++++++++++++++ modules/ui.py | 30 +++++++++++++++++++++++++++++- 4 files changed, 74 insertions(+), 1 deletion(-) create mode 100644 javascript/imageParams.js (limited to 'modules/ui.py') diff --git a/javascript/dragdrop.js b/javascript/dragdrop.js index 5aac57f7..cf900f50 100644 --- a/javascript/dragdrop.js +++ b/javascript/dragdrop.js @@ -53,6 +53,9 @@ window.document.addEventListener('dragover', e => { window.document.addEventListener('drop', e => { const target = e.composedPath()[0]; + if (target.placeholder === "Prompt") { + return; + } const imgWrap = target.closest('[data-testid="image"]'); if ( !imgWrap ) { return; diff --git a/javascript/imageParams.js b/javascript/imageParams.js new file mode 100644 index 00000000..f9d0c0aa --- /dev/null +++ b/javascript/imageParams.js @@ -0,0 +1,22 @@ +window.onload = (function(){ + window.addEventListener('drop', e => { + const target = e.composedPath()[0]; + const idx = selected_gallery_index(); + let prompt_target = "txt2img_prompt_image"; + if (idx === 1) { + prompt_target = "img2img_prompt_image"; + } + if (target.placeholder === "Prompt") { + e.stopPropagation(); + e.preventDefault(); + const imgParent = gradioApp().getElementById(prompt_target); + const files = e.dataTransfer.files; + const fileInput = imgParent.querySelector('input[type="file"]'); + if ( fileInput ) { + fileInput.files = files; + fileInput.dispatchEvent(new Event('change')); + } + } + }); + +}); \ No newline at end of file diff --git a/modules/images.py b/modules/images.py index c0a90676..f1155b7f 100644 --- a/modules/images.py +++ b/modules/images.py @@ -463,3 +463,23 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i txt_fullfn = None return fullfn, txt_fullfn + + +def image_data(image_path): + file, ext = os.path.splitext(image_path.name) + data = {} + if "png" in ext: + image = Image.open(image_path.name, "r") + print(f"Image data requested for {image_path.name} {image.format} of {type(image)}") + try: + data = image.text["parameters"] + except Exception as e: + print(f"Exception: {e}") + pass + print(f"Image data: {data}") + if "txt" in ext: + myfile = open(image_path.name, 'r') + data = myfile.read() + myfile.close() + + return data, None diff --git a/modules/ui.py b/modules/ui.py index 2b332267..dd793c39 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -431,7 +431,6 @@ def create_toprow(is_img2img): with gr.Column(scale=80): with gr.Row(): prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, placeholder="Prompt", lines=2) - with gr.Column(scale=1, elem_id="roll_col"): roll = gr.Button(value=art_symbol, elem_id="roll", visible=len(shared.artist_db.artists) > 0) paste = gr.Button(value=paste_symbol, elem_id="paste") @@ -513,6 +512,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Blocks(analytics_enabled=False) as txt2img_interface: txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=False) dummy_component = gr.Label(visible=False) + txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="file", visible=False) with gr.Row(elem_id='txt2img_progress_row'): with gr.Column(scale=1): @@ -614,6 +614,18 @@ def create_ui(wrap_gradio_gpu_call): txt2img_prompt.submit(**txt2img_args) submit.click(**txt2img_args) + txt_prompt_img.change( + fn=modules.images.image_data, + # _js = "get_extras_tab_index", + inputs=[ + txt_prompt_img + ], + outputs=[ + txt2img_prompt, + txt_prompt_img + ] + ) + enable_hr.change( fn=lambda x: gr_show(x), inputs=[enable_hr], @@ -674,6 +686,9 @@ def create_ui(wrap_gradio_gpu_call): img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True) with gr.Row(elem_id='img2img_progress_row'): + img2img_prompt_img = gr.File(label="", elem_id="txt_prompt_image", file_count="single", type="file", + visible=False) + with gr.Column(scale=1): pass @@ -768,6 +783,18 @@ def create_ui(wrap_gradio_gpu_call): connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) + img2img_prompt_img.change( + fn=modules.images.image_data, + # _js = "get_extras_tab_index", + inputs=[ + txt_prompt_img + ], + outputs=[ + img2img_prompt, + img2img_prompt_img + ] + ) + mask_mode.change( lambda mode, img: { init_img_with_mask: gr_show(mode == 0), @@ -956,6 +983,7 @@ def create_ui(wrap_gradio_gpu_call): button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else '' open_extras_folder = gr.Button('Open output directory', elem_id=button_id) + submit.click( fn=wrap_gradio_gpu_call(modules.extras.run_extras), _js="get_extras_tab_index", -- cgit v1.2.3 From aeacbac218c47f61f1d0d3f3b429c9038b8faf0f Mon Sep 17 00:00:00 2001 From: Greg Fuller Date: Tue, 11 Oct 2022 19:46:33 -0700 Subject: Fix save error --- modules/ui.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index e07ee0e1..4fa405a9 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -148,7 +148,10 @@ def save_files(js_data, images, do_make_zip, index): is_grid = image_index < p.index_of_first_image i = 0 if is_grid else (image_index - p.index_of_first_image) - fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs) + seed = p.all_seeds[i] if len(p.all_seeds) > 1 else p.seed + prompt = p.all_prompts[i] if len(p.all_prompts) > 1 else p.prompt + info = p.infotexts[image_index] if len(p.infotexts) > 1 else p.infotexts[0] + fullfn, txt_fullfn = save_image(image, path, "", seed=seed, prompt=prompt, extension=extension, info=info, grid=is_grid, p=p, save_to_dirs=save_to_dirs) filename = os.path.relpath(fullfn, path) filenames.append(filename) -- cgit v1.2.3 From 8711c2fe0135d5c160a57db41cb79ed1942ce7fa Mon Sep 17 00:00:00 2001 From: Greg Fuller Date: Wed, 12 Oct 2022 16:12:12 -0700 Subject: Fix metadata contents --- modules/ui.py | 5 +---- scripts/xy_grid.py | 52 ++++++++++++++++++++++++++++++++++------------------ 2 files changed, 35 insertions(+), 22 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 4fa405a9..e07ee0e1 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -148,10 +148,7 @@ def save_files(js_data, images, do_make_zip, index): is_grid = image_index < p.index_of_first_image i = 0 if is_grid else (image_index - p.index_of_first_image) - seed = p.all_seeds[i] if len(p.all_seeds) > 1 else p.seed - prompt = p.all_prompts[i] if len(p.all_prompts) > 1 else p.prompt - info = p.infotexts[image_index] if len(p.infotexts) > 1 else p.infotexts[0] - fullfn, txt_fullfn = save_image(image, path, "", seed=seed, prompt=prompt, extension=extension, info=info, grid=is_grid, p=p, save_to_dirs=save_to_dirs) + fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs) filename = os.path.relpath(fullfn, path) filenames.append(filename) diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py index 14edacc1..02931ae6 100644 --- a/scripts/xy_grid.py +++ b/scripts/xy_grid.py @@ -176,13 +176,16 @@ axis_options = [ def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend, include_lone_images): - res = [] - successful_images = [] - ver_texts = [[images.GridAnnotation(y)] for y in y_labels] hor_texts = [[images.GridAnnotation(x)] for x in x_labels] - first_processed = None + # Temporary list of all the images that are generated to be populated into the grid. + # Will be filled with empty images for any individual step that fails to process properly + image_cache = [] + + processed_result = None + cell_mode = "P" + cell_size = (1,1) state.job_count = len(xs) * len(ys) * p.n_iter @@ -190,26 +193,39 @@ def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend, include_lone_ for ix, x in enumerate(xs): state.job = f"{ix + iy * len(xs) + 1} out of {len(xs) * len(ys)}" - processed = cell(x, y) - if first_processed is None: - first_processed = processed - + processed:Processed = cell(x, y) try: - processed_image = processed.images[0] - res.append(processed_image) - successful_images.append(processed_image) + # this dereference will throw an exception if the image was not processed + # (this happens in cases such as if the user stops the process from the UI) + processed_image = processed.images[0] + + if processed_result is None: + # Use our first valid processed result as a template container to hold our full results + processed_result = copy(processed) + cell_mode = processed_image.mode + cell_size = processed_image.size + processed_result.images = [Image.new(cell_mode, cell_size)] + + image_cache.append(processed_image) + if include_lone_images: + processed_result.images.append(processed_image) + processed_result.all_prompts.append(processed.prompt) + processed_result.all_seeds.append(processed.seed) + processed_result.infotexts.append(processed.infotexts[0]) except: - res.append(Image.new(res[0].mode, res[0].size)) + image_cache.append(Image.new(cell_mode, cell_size)) + + if not processed_result: + print("Unexpected error: draw_xy_grid failed to return even a single processed image") + return Processed() - grid = images.image_grid(res, rows=len(ys)) + grid = images.image_grid(image_cache, rows=len(ys)) if draw_legend: - grid = images.draw_grid_annotations(grid, res[0].width, res[0].height, hor_texts, ver_texts) + grid = images.draw_grid_annotations(grid, cell_size[0], cell_size[1], hor_texts, ver_texts) - first_processed.images = [grid] - if include_lone_images: - first_processed.images += successful_images + processed_result.images[0] = grid - return first_processed + return processed_result re_range = re.compile(r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\(([+-]\d+)\s*\))?\s*") -- cgit v1.2.3 From a3f02e4690844715a510b7bc857a0971dd05c4d8 Mon Sep 17 00:00:00 2001 From: Greg Fuller Date: Wed, 12 Oct 2022 16:48:53 -0700 Subject: fix prompt in log.csv --- modules/ui.py | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index e07ee0e1..edb4dab1 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -139,6 +139,8 @@ def save_files(js_data, images, do_make_zip, index): if at_start: writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"]) + log_prompt=data["prompt"] + log_seed=data["seed"] for image_index, filedata in enumerate(images, start_index): if filedata.startswith("data:image/png;base64,"): filedata = filedata[len("data:image/png;base64,"):] @@ -148,7 +150,9 @@ def save_files(js_data, images, do_make_zip, index): is_grid = image_index < p.index_of_first_image i = 0 if is_grid else (image_index - p.index_of_first_image) - fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs) + log_seed=p.all_seeds[i] + log_prompt=p.all_prompts[i] + fullfn, txt_fullfn = save_image(image, path, "", seed=log_seed, prompt=log_prompt, extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs) filename = os.path.relpath(fullfn, path) filenames.append(filename) @@ -157,7 +161,7 @@ def save_files(js_data, images, do_make_zip, index): filenames.append(os.path.basename(txt_fullfn)) fullfns.append(txt_fullfn) - writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]]) + writer.writerow([log_prompt, log_seed, data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]]) # Make Zip if do_make_zip: -- cgit v1.2.3 From fed7f0e281a42ea962bbe422e018468bafa6f1e6 Mon Sep 17 00:00:00 2001 From: Greg Fuller Date: Wed, 12 Oct 2022 23:09:30 -0700 Subject: Revert "fix prompt in log.csv" This reverts commit e4b5d1696429ab78dae9779420ce6ec4cd9c5f67. --- modules/ui.py | 8 ++------ 1 file changed, 2 insertions(+), 6 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index edb4dab1..e07ee0e1 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -139,8 +139,6 @@ def save_files(js_data, images, do_make_zip, index): if at_start: writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"]) - log_prompt=data["prompt"] - log_seed=data["seed"] for image_index, filedata in enumerate(images, start_index): if filedata.startswith("data:image/png;base64,"): filedata = filedata[len("data:image/png;base64,"):] @@ -150,9 +148,7 @@ def save_files(js_data, images, do_make_zip, index): is_grid = image_index < p.index_of_first_image i = 0 if is_grid else (image_index - p.index_of_first_image) - log_seed=p.all_seeds[i] - log_prompt=p.all_prompts[i] - fullfn, txt_fullfn = save_image(image, path, "", seed=log_seed, prompt=log_prompt, extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs) + fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs) filename = os.path.relpath(fullfn, path) filenames.append(filename) @@ -161,7 +157,7 @@ def save_files(js_data, images, do_make_zip, index): filenames.append(os.path.basename(txt_fullfn)) fullfns.append(txt_fullfn) - writer.writerow([log_prompt, log_seed, data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]]) + writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]]) # Make Zip if do_make_zip: -- cgit v1.2.3 From bb7baf6b9cb6b4b9fa09b6f07ef997db32fe6e58 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Thu, 13 Oct 2022 16:07:18 +0300 Subject: add option to change what's shown in quicksettings bar --- javascript/hints.js | 2 ++ modules/shared.py | 4 ++-- modules/ui.py | 16 +++++++++------- style.css | 1 + 4 files changed, 14 insertions(+), 9 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/hints.js b/javascript/hints.js index 32f10fde..06bbd9e2 100644 --- a/javascript/hints.js +++ b/javascript/hints.js @@ -84,6 +84,8 @@ titles = { "Filename word regex": "This regular expression will be used extract words from filename, and they will be joined using the option below into label text used for training. Leave empty to keep filename text as it is.", "Filename join string": "This string will be used to hoin split words into a single line if the option above is enabled.", + + "Quicksettings list": "List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual stetting tab. See modules/shared.py for setting names. Requires restart to apply." } diff --git a/modules/shared.py b/modules/shared.py index 5f6101a4..4d3ed625 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -152,7 +152,6 @@ class OptionInfo: self.component_args = component_args self.onchange = onchange self.section = None - self.show_on_main_page = show_on_main_page def options_section(section_identifier, options_dict): @@ -237,7 +236,7 @@ options_templates.update(options_section(('training', "Training"), { })) options_templates.update(options_section(('sd', "Stable Diffusion"), { - "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, show_on_main_page=True), + "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}), "sd_hypernetwork": OptionInfo("None", "Stable Diffusion finetune hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}), "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."), "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"), @@ -250,6 +249,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "filter_nsfw": OptionInfo(False, "Filter NSFW content"), 'CLIP_stop_at_last_layers': OptionInfo(1, "Stop At last layers of CLIP model", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}), "random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}), + 'quicksettings': OptionInfo("sd_model_checkpoint", "Quicksettings list"), })) options_templates.update(options_section(('interrogate', "Interrogate Options"), { diff --git a/modules/ui.py b/modules/ui.py index e07ee0e1..a0529860 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1305,6 +1305,9 @@ Requested path was: {f} settings_cols = 3 items_per_col = int(len(opts.data_labels) * 0.9 / settings_cols) + quicksettings_names = [x.strip() for x in opts.quicksettings.split(",")] + quicksettings_names = set(x for x in quicksettings_names if x != 'quicksettings') + quicksettings_list = [] cols_displayed = 0 @@ -1329,7 +1332,7 @@ Requested path was: {f} gr.HTML(elem_id="settings_header_text_{}".format(item.section[0]), value='

{}

'.format(item.section[1])) - if item.show_on_main_page: + if k in quicksettings_names: quicksettings_list.append((i, k, item)) components.append(dummy_component) else: @@ -1338,7 +1341,11 @@ Requested path was: {f} components.append(component) items_displayed += 1 - request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications") + with gr.Row(): + request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications") + reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary') + restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary') + request_notifications.click( fn=lambda: None, inputs=[], @@ -1346,10 +1353,6 @@ Requested path was: {f} _js='function(){}' ) - with gr.Row(): - reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary') - restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary') - def reload_scripts(): modules.scripts.reload_script_body_only() @@ -1364,7 +1367,6 @@ Requested path was: {f} shared.state.interrupt() settings_interface.gradio_ref.do_restart = True - restart_gradio.click( fn=request_restart, inputs=[], diff --git a/style.css b/style.css index e6fa10b4..55c41971 100644 --- a/style.css +++ b/style.css @@ -488,6 +488,7 @@ input[type="range"]{ #quicksettings > div > div{ max-width: 32em; padding: 0; + margin-right: 0.75em; } canvas[key="mask"] { -- cgit v1.2.3 From a10b0e11fc22cc67b6a3664f2ddd17425d8433a8 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Thu, 13 Oct 2022 19:22:41 +0300 Subject: options to refresh list of models and hypernetworks --- modules/shared.py | 9 +++++---- modules/ui.py | 33 +++++++++++++++++++++++++++++---- style.css | 21 ++++++++++++++++++++- 3 files changed, 54 insertions(+), 9 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/shared.py b/modules/shared.py index 4d3ed625..d8e3a286 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -13,7 +13,7 @@ import modules.memmon import modules.sd_models import modules.styles import modules.devices as devices -from modules import sd_samplers +from modules import sd_samplers, sd_models from modules.hypernetworks import hypernetwork from modules.paths import models_path, script_path, sd_path @@ -145,13 +145,14 @@ def realesrgan_models_names(): class OptionInfo: - def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, show_on_main_page=False): + def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, show_on_main_page=False, refresh=None): self.default = default self.label = label self.component = component self.component_args = component_args self.onchange = onchange self.section = None + self.refresh = refresh def options_section(section_identifier, options_dict): @@ -236,8 +237,8 @@ options_templates.update(options_section(('training', "Training"), { })) options_templates.update(options_section(('sd', "Stable Diffusion"), { - "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}), - "sd_hypernetwork": OptionInfo("None", "Stable Diffusion finetune hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}), + "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, refresh=sd_models.list_models), + "sd_hypernetwork": OptionInfo("None", "Stable Diffusion finetune hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks), "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."), "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"), "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies (normally you'd do less with less denoising)."), diff --git a/modules/ui.py b/modules/ui.py index a0529860..0a58f6be 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -78,6 +78,8 @@ reuse_symbol = '\u267b\ufe0f' # ♻️ art_symbol = '\U0001f3a8' # 🎨 paste_symbol = '\u2199\ufe0f' # ↙ folder_symbol = '\U0001f4c2' # 📂 +refresh_symbol = '\U0001f504' # 🔄 + def plaintext_to_html(text): text = "

" + "
\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "

" @@ -1210,8 +1212,7 @@ def create_ui(wrap_gradio_gpu_call): outputs=[], ) - - def create_setting_component(key): + def create_setting_component(key, is_quicksettings=False): def fun(): return opts.data[key] if key in opts.data else opts.data_labels[key].default @@ -1231,7 +1232,31 @@ def create_ui(wrap_gradio_gpu_call): else: raise Exception(f'bad options item type: {str(t)} for key {key}') - return comp(label=info.label, value=fun, **(args or {})) + if info.refresh is not None: + if is_quicksettings: + res = comp(label=info.label, value=fun, **(args or {})) + refresh_button = gr.Button(value=refresh_symbol, elem_id="refresh_"+key) + else: + with gr.Row(variant="compact"): + res = comp(label=info.label, value=fun, **(args or {})) + refresh_button = gr.Button(value=refresh_symbol, elem_id="refresh_" + key) + + def refresh(): + info.refresh() + refreshed_args = info.component_args() if callable(info.component_args) else info.component_args + res.choices = refreshed_args["choices"] + return gr.update(**(refreshed_args or {})) + + refresh_button.click( + fn=refresh, + inputs=[], + outputs=[res], + ) + else: + res = comp(label=info.label, value=fun, **(args or {})) + + + return res components = [] component_dict = {} @@ -1401,7 +1426,7 @@ Requested path was: {f} with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo: with gr.Row(elem_id="quicksettings"): for i, k, item in quicksettings_list: - component = create_setting_component(k) + component = create_setting_component(k, is_quicksettings=True) component_dict[k] = component settings_interface.gradio_ref = demo diff --git a/style.css b/style.css index 55c41971..ad2a52cc 100644 --- a/style.css +++ b/style.css @@ -228,6 +228,8 @@ fieldset span.text-gray-500, .gr-block.gr-box span.text-gray-500, label.block s border-top: 1px solid #eee; border-left: 1px solid #eee; border-right: 1px solid #eee; + + z-index: 300; } .dark fieldset span.text-gray-500, .dark .gr-block.gr-box span.text-gray-500, .dark label.block span{ @@ -480,17 +482,30 @@ input[type="range"]{ background: #a55000; } +#quicksettings { + gap: 0.4em; +} + #quicksettings > div{ border: none; background: none; + flex: unset; + gap: 0.5em; } #quicksettings > div > div{ max-width: 32em; + min-width: 24em; padding: 0; - margin-right: 0.75em; } +#refresh_sd_model_checkpoint, #refresh_sd_hypernetwork{ + max-width: 2.5em; + min-width: 2.5em; + height: 2.4em; +} + + canvas[key="mask"] { z-index: 12 !important; filter: invert(); @@ -507,3 +522,7 @@ canvas[key="mask"] { z-index: 200; width: 8em; } + +.row.gr-compact{ + overflow: visible; +} -- cgit v1.2.3 From 354ef0da3b1f0fa5c113d04b6c79e3908c848d23 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Thu, 13 Oct 2022 20:12:37 +0300 Subject: add hypernetwork multipliers --- modules/hypernetworks/hypernetwork.py | 8 +++++++- modules/shared.py | 5 ++++- modules/ui.py | 5 ++++- scripts/xy_grid.py | 9 ++++++++- style.css | 3 +++ webui.py | 2 +- 6 files changed, 27 insertions(+), 5 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index b6c06d49..f1248bb7 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -18,6 +18,8 @@ from modules.textual_inversion.learn_schedule import LearnRateScheduler class HypernetworkModule(torch.nn.Module): + multiplier = 1.0 + def __init__(self, dim, state_dict=None): super().__init__() @@ -36,7 +38,11 @@ class HypernetworkModule(torch.nn.Module): self.to(devices.device) def forward(self, x): - return x + (self.linear2(self.linear1(x))) + return x + (self.linear2(self.linear1(x))) * self.multiplier + + +def apply_strength(value=None): + HypernetworkModule.multiplier = value if value is not None else shared.opts.sd_hypernetwork_strength class Hypernetwork: diff --git a/modules/shared.py b/modules/shared.py index d8e3a286..5901e605 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -238,7 +238,8 @@ options_templates.update(options_section(('training', "Training"), { options_templates.update(options_section(('sd', "Stable Diffusion"), { "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, refresh=sd_models.list_models), - "sd_hypernetwork": OptionInfo("None", "Stable Diffusion finetune hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks), + "sd_hypernetwork": OptionInfo("None", "Hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks), + "sd_hypernetwork_strength": OptionInfo(1.0, "Hypernetwork strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.001}), "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."), "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"), "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies (normally you'd do less with less denoising)."), @@ -348,6 +349,8 @@ class Options: item = self.data_labels.get(key) item.onchange = func + func() + def dumpjson(self): d = {k: self.data.get(k, self.data_labels.get(k).default) for k in self.data_labels.keys()} return json.dumps(d) diff --git a/modules/ui.py b/modules/ui.py index 0a58f6be..673014f2 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1244,7 +1244,10 @@ def create_ui(wrap_gradio_gpu_call): def refresh(): info.refresh() refreshed_args = info.component_args() if callable(info.component_args) else info.component_args - res.choices = refreshed_args["choices"] + + for k, v in refreshed_args.items(): + setattr(res, k, v) + return gr.update(**(refreshed_args or {})) refresh_button.click( diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py index 02931ae6..efb63af5 100644 --- a/scripts/xy_grid.py +++ b/scripts/xy_grid.py @@ -107,6 +107,10 @@ def apply_hypernetwork(p, x, xs): hypernetwork.load_hypernetwork(name) +def apply_hypernetwork_strength(p, x, xs): + hypernetwork.apply_strength(x) + + def confirm_hypernetworks(p, xs): for x in xs: if x.lower() in ["", "none"]: @@ -165,6 +169,7 @@ axis_options = [ AxisOption("Sampler", str, apply_sampler, format_value, confirm_samplers), AxisOption("Checkpoint name", str, apply_checkpoint, format_value, confirm_checkpoints), AxisOption("Hypernetwork", str, apply_hypernetwork, format_value, confirm_hypernetworks), + AxisOption("Hypernet str.", float, apply_hypernetwork_strength, format_value_add_label, None), AxisOption("Sigma Churn", float, apply_field("s_churn"), format_value_add_label, None), AxisOption("Sigma min", float, apply_field("s_tmin"), format_value_add_label, None), AxisOption("Sigma max", float, apply_field("s_tmax"), format_value_add_label, None), @@ -250,7 +255,7 @@ class Script(scripts.Script): y_values = gr.Textbox(label="Y values", visible=False, lines=1) draw_legend = gr.Checkbox(label='Draw legend', value=True) - include_lone_images = gr.Checkbox(label='Include Separate Images', value=True) + include_lone_images = gr.Checkbox(label='Include Separate Images', value=False) no_fixed_seeds = gr.Checkbox(label='Keep -1 for seeds', value=False) return [x_type, x_values, y_type, y_values, draw_legend, include_lone_images, no_fixed_seeds] @@ -377,6 +382,8 @@ class Script(scripts.Script): modules.sd_models.reload_model_weights(shared.sd_model) hypernetwork.load_hypernetwork(opts.sd_hypernetwork) + hypernetwork.apply_strength() + opts.data["CLIP_stop_at_last_layers"] = CLIP_stop_at_last_layers diff --git a/style.css b/style.css index ad2a52cc..aa3d379c 100644 --- a/style.css +++ b/style.css @@ -522,6 +522,9 @@ canvas[key="mask"] { z-index: 200; width: 8em; } +#quicksettings .gr-box > div > div > input.gr-text-input { + top: -1.12em; +} .row.gr-compact{ overflow: visible; diff --git a/webui.py b/webui.py index 33ba7905..fe0ce321 100644 --- a/webui.py +++ b/webui.py @@ -72,7 +72,6 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs) - def initialize(): modelloader.cleanup_models() modules.sd_models.setup_model() @@ -86,6 +85,7 @@ def initialize(): shared.sd_model = modules.sd_models.load_model() shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model))) shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork))) + shared.opts.onchange("sd_hypernetwork_strength", modules.hypernetworks.hypernetwork.apply_strength) def webui(): -- cgit v1.2.3 From 08b3f7aef15f74f4d2254b1274dd66fcc7940348 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Thu, 13 Oct 2022 20:42:27 +0300 Subject: emergency fix for broken send to buttons --- javascript/ui.js | 8 ++++---- modules/ui.py | 2 +- 2 files changed, 5 insertions(+), 5 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index 4100944e..0f8fe68e 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -33,27 +33,27 @@ function args_to_array(args){ } function switch_to_txt2img(){ - gradioApp().querySelectorAll('button')[0].click(); + gradioApp().querySelector('#tabs').querySelectorAll('button')[0].click(); return args_to_array(arguments); } function switch_to_img2img_img2img(){ - gradioApp().querySelectorAll('button')[1].click(); + gradioApp().querySelector('#tabs').querySelectorAll('button')[1].click(); gradioApp().getElementById('mode_img2img').querySelectorAll('button')[0].click(); return args_to_array(arguments); } function switch_to_img2img_inpaint(){ - gradioApp().querySelectorAll('button')[1].click(); + gradioApp().querySelector('#tabs').querySelectorAll('button')[1].click(); gradioApp().getElementById('mode_img2img').querySelectorAll('button')[1].click(); return args_to_array(arguments); } function switch_to_extras(){ - gradioApp().querySelectorAll('button')[2].click(); + gradioApp().querySelector('#tabs').querySelectorAll('button')[2].click(); return args_to_array(arguments); } diff --git a/modules/ui.py b/modules/ui.py index 673014f2..7446439d 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1434,7 +1434,7 @@ Requested path was: {f} settings_interface.gradio_ref = demo - with gr.Tabs() as tabs: + with gr.Tabs(elem_id="tabs") as tabs: for interface, label, ifid in interfaces: with gr.TabItem(label, id=ifid, elem_id='tab_' + ifid): interface.render() -- cgit v1.2.3 From fdecb636855748e03efc40c846a0043800aadfcc Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 14 Oct 2022 09:05:06 +0300 Subject: add an ability to merge three checkpoints --- javascript/hints.js | 5 ++++- modules/extras.py | 29 +++++++++++++++++++++-------- modules/ui.py | 11 +++++++---- 3 files changed, 32 insertions(+), 13 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/hints.js b/javascript/hints.js index 94438c5c..af010a59 100644 --- a/javascript/hints.js +++ b/javascript/hints.js @@ -85,7 +85,10 @@ titles = { "Filename word regex": "This regular expression will be used extract words from filename, and they will be joined using the option below into label text used for training. Leave empty to keep filename text as it is.", "Filename join string": "This string will be used to join split words into a single line if the option above is enabled.", - "Quicksettings list": "List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual setting tab. See modules/shared.py for setting names. Requires restarting to apply." + "Quicksettings list": "List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual setting tab. See modules/shared.py for setting names. Requires restarting to apply.", + + "Weighted Sum": "Result = A * (1 - M) + B * M", + "Add difference": "Result = A + (B - C) * (1 - M)", } diff --git a/modules/extras.py b/modules/extras.py index b24d7de3..532d869f 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -159,48 +159,61 @@ def run_pnginfo(image): return '', geninfo, info -def run_modelmerger(primary_model_name, secondary_model_name, interp_method, interp_amount, save_as_half, custom_name): +def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, interp_amount, save_as_half, custom_name): # Linear interpolation (https://en.wikipedia.org/wiki/Linear_interpolation) - def weighted_sum(theta0, theta1, alpha): + def weighted_sum(theta0, theta1, theta2, alpha): return ((1 - alpha) * theta0) + (alpha * theta1) # Smoothstep (https://en.wikipedia.org/wiki/Smoothstep) - def sigmoid(theta0, theta1, alpha): + def sigmoid(theta0, theta1, theta2, alpha): alpha = alpha * alpha * (3 - (2 * alpha)) return theta0 + ((theta1 - theta0) * alpha) # Inverse Smoothstep (https://en.wikipedia.org/wiki/Smoothstep) - def inv_sigmoid(theta0, theta1, alpha): + def inv_sigmoid(theta0, theta1, theta2, alpha): import math alpha = 0.5 - math.sin(math.asin(1.0 - 2.0 * alpha) / 3.0) return theta0 + ((theta1 - theta0) * alpha) + def add_difference(theta0, theta1, theta2, alpha): + return theta0 + (theta1 - theta2) * (1.0 - alpha) + primary_model_info = sd_models.checkpoints_list[primary_model_name] secondary_model_info = sd_models.checkpoints_list[secondary_model_name] + teritary_model_info = sd_models.checkpoints_list.get(teritary_model_name, None) print(f"Loading {primary_model_info.filename}...") primary_model = torch.load(primary_model_info.filename, map_location='cpu') + theta_0 = sd_models.get_state_dict_from_checkpoint(primary_model) print(f"Loading {secondary_model_info.filename}...") secondary_model = torch.load(secondary_model_info.filename, map_location='cpu') - - theta_0 = sd_models.get_state_dict_from_checkpoint(primary_model) theta_1 = sd_models.get_state_dict_from_checkpoint(secondary_model) + if teritary_model_info is not None: + print(f"Loading {teritary_model_info.filename}...") + teritary_model = torch.load(teritary_model_info.filename, map_location='cpu') + theta_2 = sd_models.get_state_dict_from_checkpoint(teritary_model) + else: + theta_2 = None + theta_funcs = { "Weighted Sum": weighted_sum, "Sigmoid": sigmoid, "Inverse Sigmoid": inv_sigmoid, + "Add difference": add_difference, } theta_func = theta_funcs[interp_method] print(f"Merging...") + for key in tqdm.tqdm(theta_0.keys()): if 'model' in key and key in theta_1: - theta_0[key] = theta_func(theta_0[key], theta_1[key], (float(1.0) - interp_amount)) # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint + theta_0[key] = theta_func(theta_0[key], theta_1[key], theta_2[key] if theta_2 else None, (float(1.0) - interp_amount)) # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint if save_as_half: theta_0[key] = theta_0[key].half() + # I believe this part should be discarded, but I'll leave it for now until I am sure for key in theta_1.keys(): if 'model' in key and key not in theta_0: theta_0[key] = theta_1[key] @@ -219,4 +232,4 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int sd_models.list_models() print(f"Checkpoint saved.") - return ["Checkpoint saved to " + output_modelname] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(3)] + return ["Checkpoint saved to " + output_modelname] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)] diff --git a/modules/ui.py b/modules/ui.py index 7446439d..220fb80b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1024,11 +1024,12 @@ def create_ui(wrap_gradio_gpu_call): gr.HTML(value="

A merger of the two checkpoints will be generated in your checkpoint directory.

") with gr.Row(): - primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary Model Name") - secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary Model Name") + primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)") + secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)") + tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)") custom_name = gr.Textbox(label="Custom Name (Optional)") - interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Interpolation Amount', value=0.3) - interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid", "Inverse Sigmoid"], value="Weighted Sum", label="Interpolation Method") + interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Interpolation amount (1 - M)', value=0.3) + interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid", "Inverse Sigmoid", "Add difference"], value="Weighted Sum", label="Interpolation Method") save_as_half = gr.Checkbox(value=False, label="Save as float16") modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary') @@ -1473,6 +1474,7 @@ Requested path was: {f} inputs=[ primary_model_name, secondary_model_name, + tertiary_model_name, interp_method, interp_amount, save_as_half, @@ -1482,6 +1484,7 @@ Requested path was: {f} submit_result, primary_model_name, secondary_model_name, + tertiary_model_name, component_dict['sd_model_checkpoint'], ] ) -- cgit v1.2.3 From bb57f30c2de46cfca5419ad01738a41705f96cc3 Mon Sep 17 00:00:00 2001 From: MalumaDev Date: Fri, 14 Oct 2022 10:56:41 +0200 Subject: init --- README.md | 1 + aesthetic_embeddings/insert_embs_here.txt | 0 modules/processing.py | 17 +++++- modules/sd_hijack.py | 80 +++++++++++++++++++++++++- modules/shared.py | 5 ++ modules/textual_inversion/dataset.py | 2 +- modules/textual_inversion/textual_inversion.py | 35 +++++++---- modules/txt2img.py | 11 +++- modules/ui.py | 59 ++++++++++++------- 9 files changed, 172 insertions(+), 38 deletions(-) create mode 100644 aesthetic_embeddings/insert_embs_here.txt (limited to 'modules/ui.py') diff --git a/README.md b/README.md index 859a91b6..7b8d018b 100644 --- a/README.md +++ b/README.md @@ -70,6 +70,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web - No token limit for prompts (original stable diffusion lets you use up to 75 tokens) - DeepDanbooru integration, creates danbooru style tags for anime prompts (add --deepdanbooru to commandline args) - [xformers](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers), major speed increase for select cards: (add --xformers to commandline args) +- Aesthetic, a way to generate images with a specific aesthetic by using clip images embds (implementation of https://github.com/vicgalle/stable-diffusion-aesthetic-gradients) ## Installation and Running Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs. diff --git a/aesthetic_embeddings/insert_embs_here.txt b/aesthetic_embeddings/insert_embs_here.txt new file mode 100644 index 00000000..e69de29b diff --git a/modules/processing.py b/modules/processing.py index d5172f00..9a033759 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -316,11 +316,16 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration return f"{all_prompts[index]}{negative_prompt_text}\n{generation_params_text}".strip() -def process_images(p: StableDiffusionProcessing) -> Processed: +def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, + aesthetic_imgs=None,aesthetic_slerp=False) -> Processed: """this is the main loop that both txt2img and img2img use; it calls func_init once inside all the scopes and func_sample once per batch""" + aesthetic_lr = float(aesthetic_lr) + aesthetic_weight = float(aesthetic_weight) + aesthetic_steps = int(aesthetic_steps) + if type(p.prompt) == list: - assert(len(p.prompt) > 0) + assert (len(p.prompt) > 0) else: assert p.prompt is not None @@ -394,7 +399,13 @@ def process_images(p: StableDiffusionProcessing) -> Processed: #uc = p.sd_model.get_learned_conditioning(len(prompts) * [p.negative_prompt]) #c = p.sd_model.get_learned_conditioning(prompts) with devices.autocast(): - uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], p.steps) + if hasattr(shared.sd_model.cond_stage_model, "set_aesthetic_params"): + shared.sd_model.cond_stage_model.set_aesthetic_params(0, 0, 0) + uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], + p.steps) + if hasattr(shared.sd_model.cond_stage_model, "set_aesthetic_params"): + shared.sd_model.cond_stage_model.set_aesthetic_params(aesthetic_lr, aesthetic_weight, + aesthetic_steps, aesthetic_imgs,aesthetic_slerp) c = prompt_parser.get_multicond_learned_conditioning(shared.sd_model, prompts, p.steps) if len(model_hijack.comments) > 0: diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index c81722a0..6d5196fe 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -9,11 +9,14 @@ from torch.nn.functional import silu import modules.textual_inversion.textual_inversion from modules import prompt_parser, devices, sd_hijack_optimizations, shared -from modules.shared import opts, device, cmd_opts +from modules.shared import opts, device, cmd_opts, aesthetic_embeddings from modules.sd_hijack_optimizations import invokeAI_mps_available import ldm.modules.attention import ldm.modules.diffusionmodules.model +from transformers import CLIPVisionModel, CLIPModel +import torch.optim as optim +import copy attention_CrossAttention_forward = ldm.modules.attention.CrossAttention.forward diffusionmodules_model_nonlinearity = ldm.modules.diffusionmodules.model.nonlinearity @@ -109,13 +112,29 @@ class StableDiffusionModelHijack: _, remade_batch_tokens, _, _, _, token_count = self.clip.process_text([text]) return remade_batch_tokens[0], token_count, get_target_prompt_token_count(token_count) +def slerp(low, high, val): + low_norm = low/torch.norm(low, dim=1, keepdim=True) + high_norm = high/torch.norm(high, dim=1, keepdim=True) + omega = torch.acos((low_norm*high_norm).sum(1)) + so = torch.sin(omega) + res = (torch.sin((1.0-val)*omega)/so).unsqueeze(1)*low + (torch.sin(val*omega)/so).unsqueeze(1) * high + return res class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): def __init__(self, wrapped, hijack): super().__init__() self.wrapped = wrapped + self.clipModel = CLIPModel.from_pretrained( + self.wrapped.transformer.name_or_path + ) + del self.clipModel.vision_model self.hijack: StableDiffusionModelHijack = hijack self.tokenizer = wrapped.tokenizer + # self.vision = CLIPVisionModel.from_pretrained(self.wrapped.transformer.name_or_path).eval() + self.image_embs_name = None + self.image_embs = None + self.load_image_embs(None) + self.token_mults = {} self.comma_token = [v for k, v in self.tokenizer.get_vocab().items() if k == ','][0] @@ -136,6 +155,23 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): if mult != 1.0: self.token_mults[ident] = mult + def set_aesthetic_params(self, aesthetic_lr, aesthetic_weight, aesthetic_steps, image_embs_name=None, + aesthetic_slerp=True): + self.slerp = aesthetic_slerp + self.aesthetic_lr = aesthetic_lr + self.aesthetic_weight = aesthetic_weight + self.aesthetic_steps = aesthetic_steps + self.load_image_embs(image_embs_name) + + def load_image_embs(self, image_embs_name): + if image_embs_name is None or len(image_embs_name) == 0: + image_embs_name = None + if image_embs_name is not None and self.image_embs_name != image_embs_name: + self.image_embs_name = image_embs_name + self.image_embs = torch.load(aesthetic_embeddings[self.image_embs_name], map_location=device) + self.image_embs /= self.image_embs.norm(dim=-1, keepdim=True) + self.image_embs.requires_grad_(False) + def tokenize_line(self, line, used_custom_terms, hijack_comments): id_end = self.wrapped.tokenizer.eos_token_id @@ -333,7 +369,47 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): z1 = self.process_tokens(tokens, multipliers) z = z1 if z is None else torch.cat((z, z1), axis=-2) - + + if len(text[ + 0]) != 0 and self.aesthetic_steps != 0 and self.aesthetic_lr != 0 and self.aesthetic_weight != 0 and self.image_embs_name != None: + if not opts.use_old_emphasis_implementation: + remade_batch_tokens = [ + [self.wrapped.tokenizer.bos_token_id] + x[:75] + [self.wrapped.tokenizer.eos_token_id] for x in + remade_batch_tokens] + + tokens = torch.asarray(remade_batch_tokens).to(device) + with torch.enable_grad(): + model = copy.deepcopy(self.clipModel).to(device) + model.requires_grad_(True) + + # We optimize the model to maximize the similarity + optimizer = optim.Adam( + model.text_model.parameters(), lr=self.aesthetic_lr + ) + + for i in range(self.aesthetic_steps): + text_embs = model.get_text_features(input_ids=tokens) + text_embs = text_embs / text_embs.norm(dim=-1, keepdim=True) + sim = text_embs @ self.image_embs.T + loss = -sim + optimizer.zero_grad() + loss.mean().backward() + optimizer.step() + + zn = model.text_model(input_ids=tokens, output_hidden_states=-opts.CLIP_stop_at_last_layers) + if opts.CLIP_stop_at_last_layers > 1: + zn = zn.hidden_states[-opts.CLIP_stop_at_last_layers] + zn = model.text_model.final_layer_norm(zn) + else: + zn = zn.last_hidden_state + model.cpu() + del model + + if self.slerp: + z = slerp(z, zn, self.aesthetic_weight) + else: + z = z * (1 - self.aesthetic_weight) + zn * self.aesthetic_weight + remade_batch_tokens = rem_tokens batch_multipliers = rem_multipliers i += 1 diff --git a/modules/shared.py b/modules/shared.py index 5901e605..cf13a10d 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -30,6 +30,8 @@ parser.add_argument("--no-half-vae", action='store_true', help="do not switch th parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)") parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI") parser.add_argument("--embeddings-dir", type=str, default=os.path.join(script_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)") +parser.add_argument("--aesthetic_embeddings-dir", type=str, default=os.path.join(script_path, 'aesthetic_embeddings'), + help="aesthetic_embeddings directory(default: aesthetic_embeddings)") parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory") parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui") parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage") @@ -90,6 +92,9 @@ os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True) hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) loaded_hypernetwork = None +aesthetic_embeddings = {f.replace(".pt",""): os.path.join(cmd_opts.aesthetic_embeddings_dir, f) for f in + os.listdir(cmd_opts.aesthetic_embeddings_dir) if f.endswith(".pt")} + def reload_hypernetworks(): global hypernetworks diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py index 67e90afe..59b2b021 100644 --- a/modules/textual_inversion/dataset.py +++ b/modules/textual_inversion/dataset.py @@ -48,7 +48,7 @@ class PersonalizedBase(Dataset): print("Preparing dataset...") for path in tqdm.tqdm(self.image_paths): try: - image = Image.open(path).convert('RGB').resize((self.width, self.height), PIL.Image.BICUBIC) + image = Image.open(path).convert('RGB').resize((self.width, self.height), PIL.Image.Resampling.BICUBIC) except Exception: continue diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index fa0e33a2..b12a8e6d 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -172,7 +172,15 @@ def create_embedding(name, num_vectors_per_token, init_text='*'): return fn -def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_image_prompt): +def batched(dataset, total, n=1): + for ndx in range(0, total, n): + yield [dataset.__getitem__(i) for i in range(ndx, min(ndx + n, total))] + + +def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, + create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, + preview_image_prompt, batch_size=1, + gradient_accumulation=1): assert embedding_name, 'embedding not selected' shared.state.textinfo = "Initializing textual inversion training..." @@ -204,7 +212,11 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..." with torch.autocast("cuda"): - ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file) + ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, + height=training_height, + repeats=shared.opts.training_image_repeats_per_epoch, + placeholder_token=embedding_name, model=shared.sd_model, + device=devices.device, template_file=template_file) hijack = sd_hijack.model_hijack @@ -223,7 +235,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini scheduler = LearnRateScheduler(learn_rate, steps, ititial_step) optimizer = torch.optim.AdamW([embedding.vec], lr=scheduler.learn_rate) - pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step) + pbar = tqdm.tqdm(enumerate(batched(ds, steps - ititial_step, batch_size)), total=steps - ititial_step) for i, entry in pbar: embedding.step = i + ititial_step @@ -235,17 +247,20 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini break with torch.autocast("cuda"): - c = cond_model([entry.cond_text]) + c = cond_model([e.cond_text for e in entry]) + + x = torch.stack([e.latent for e in entry]).to(devices.device) + loss = shared.sd_model(x, c)[0] - x = entry.latent.to(devices.device) - loss = shared.sd_model(x.unsqueeze(0), c)[0] del x losses[embedding.step % losses.shape[0]] = loss.item() - optimizer.zero_grad() loss.backward() - optimizer.step() + if ((i + 1) % gradient_accumulation == 0) or (i + 1 == steps - ititial_step): + optimizer.step() + optimizer.zero_grad() + epoch_num = embedding.step // len(ds) epoch_step = embedding.step - (epoch_num * len(ds)) + 1 @@ -259,7 +274,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0: last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png') - preview_text = entry.cond_text if preview_image_prompt == "" else preview_image_prompt + preview_text = entry[0].cond_text if preview_image_prompt == "" else preview_image_prompt p = processing.StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, @@ -305,7 +320,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini

Loss: {losses.mean():.7f}
Step: {embedding.step}
-Last prompt: {html.escape(entry.cond_text)}
+Last prompt: {html.escape(entry[-1].cond_text)}
Last saved embedding: {html.escape(last_saved_file)}
Last saved image: {html.escape(last_saved_image)}

diff --git a/modules/txt2img.py b/modules/txt2img.py index e985242b..78342024 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -6,7 +6,14 @@ import modules.processing as processing from modules.ui import plaintext_to_html -def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, scale_latent: bool, denoising_strength: float, *args): +def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, + restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, + subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, + height: int, width: int, enable_hr: bool, scale_latent: bool, denoising_strength: float, + aesthetic_lr=0, + aesthetic_weight=0, aesthetic_steps=0, + aesthetic_imgs=None, + aesthetic_slerp=False, *args): p = StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples, @@ -40,7 +47,7 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: processed = modules.scripts.scripts_txt2img.run(p, *args) if processed is None: - processed = process_images(p) + processed = process_images(p, aesthetic_lr, aesthetic_weight, aesthetic_steps, aesthetic_imgs, aesthetic_slerp) shared.total_tqdm.clear() diff --git a/modules/ui.py b/modules/ui.py index 220fb80b..d961d126 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -24,7 +24,8 @@ import gradio.routes from modules import sd_hijack from modules.paths import script_path -from modules.shared import opts, cmd_opts +from modules.shared import opts, cmd_opts,aesthetic_embeddings + if cmd_opts.deepdanbooru: from modules.deepbooru import get_deepbooru_tags import modules.shared as shared @@ -534,6 +535,14 @@ def create_ui(wrap_gradio_gpu_call): width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512) height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) + with gr.Group(): + aesthetic_lr = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.005") + aesthetic_weight = gr.Slider(minimum=0, maximum=1, step=0.01, label="Aesthetic weight", value=0.7) + aesthetic_steps = gr.Slider(minimum=0, maximum=50, step=1, label="Aesthetic steps", value=50) + + aesthetic_imgs = gr.Dropdown(sorted(aesthetic_embeddings.keys()), label="Imgs embedding", value=sorted(aesthetic_embeddings.keys())[0] if len(aesthetic_embeddings) > 0 else None) + aesthetic_slerp = gr.Checkbox(label="Slerp interpolation", value=False) + with gr.Row(): restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1) tiling = gr.Checkbox(label='Tiling', value=False) @@ -586,25 +595,30 @@ def create_ui(wrap_gradio_gpu_call): fn=wrap_gradio_gpu_call(modules.txt2img.txt2img), _js="submit", inputs=[ - txt2img_prompt, - txt2img_negative_prompt, - txt2img_prompt_style, - txt2img_prompt_style2, - steps, - sampler_index, - restore_faces, - tiling, - batch_count, - batch_size, - cfg_scale, - seed, - subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox, - height, - width, - enable_hr, - scale_latent, - denoising_strength, - ] + custom_inputs, + txt2img_prompt, + txt2img_negative_prompt, + txt2img_prompt_style, + txt2img_prompt_style2, + steps, + sampler_index, + restore_faces, + tiling, + batch_count, + batch_size, + cfg_scale, + seed, + subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox, + height, + width, + enable_hr, + scale_latent, + denoising_strength, + aesthetic_lr, + aesthetic_weight, + aesthetic_steps, + aesthetic_imgs, + aesthetic_slerp + ] + custom_inputs, outputs=[ txt2img_gallery, generation_info, @@ -1097,6 +1111,9 @@ def create_ui(wrap_gradio_gpu_call): template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt")) training_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512) training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) + batch_size = gr.Slider(minimum=1, maximum=64, step=1, label="Batch Size", value=4) + gradient_accumulation = gr.Slider(minimum=1, maximum=256, step=1, label="Gradient accumulation", + value=1) steps = gr.Number(label='Max steps', value=100000, precision=0) create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0) save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0) @@ -1180,6 +1197,8 @@ def create_ui(wrap_gradio_gpu_call): template_file, save_image_with_stored_embedding, preview_image_prompt, + batch_size, + gradient_accumulation ], outputs=[ ti_output, -- cgit v1.2.3 From b2261b53ae4ad01b3713bc73ff62ab7b6f479e26 Mon Sep 17 00:00:00 2001 From: Buckzor Date: Thu, 13 Oct 2022 17:07:06 +0100 Subject: Added first_pass_width and height as adjustable inputs to "High Res Fix" --- modules/processing.py | 6 ++++-- modules/txt2img.py | 5 ++++- modules/ui.py | 6 ++++++ 3 files changed, 14 insertions(+), 3 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/processing.py b/modules/processing.py index d5172f00..abbfdf98 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -506,11 +506,13 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): firstphase_width_truncated = 0 firstphase_height_truncated = 0 - def __init__(self, enable_hr=False, scale_latent=True, denoising_strength=0.75, **kwargs): + def __init__(self, enable_hr=False, scale_latent=True, denoising_strength=0.75, first_pass_width=512, first_pass_height=512, **kwargs): super().__init__(**kwargs) self.enable_hr = enable_hr self.scale_latent = scale_latent self.denoising_strength = denoising_strength + self.first_pass_width = first_pass_width + self.first_pass_height = first_pass_height def init(self, all_prompts, all_seeds, all_subseeds): if self.enable_hr: @@ -519,7 +521,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): else: state.job_count = state.job_count * 2 - desired_pixel_count = 512 * 512 + desired_pixel_count = self.first_pass_width * self.first_pass_height actual_pixel_count = self.width * self.height scale = math.sqrt(desired_pixel_count / actual_pixel_count) diff --git a/modules/txt2img.py b/modules/txt2img.py index e985242b..85cbece4 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -6,7 +6,7 @@ import modules.processing as processing from modules.ui import plaintext_to_html -def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, scale_latent: bool, denoising_strength: float, *args): +def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, scale_latent: bool, denoising_strength: float, first_pass_width: int, first_pass_height: int, *args): p = StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples, @@ -32,6 +32,9 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: enable_hr=enable_hr, scale_latent=scale_latent if enable_hr else None, denoising_strength=denoising_strength if enable_hr else None, + first_pass_width=first_pass_width if enable_hr else None, + first_pass_height=first_pass_height if enable_hr else None, + ) if cmd_opts.enable_console_prompts: diff --git a/modules/ui.py b/modules/ui.py index 220fb80b..544419b2 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -540,6 +540,8 @@ def create_ui(wrap_gradio_gpu_call): enable_hr = gr.Checkbox(label='Highres. fix', value=False) with gr.Row(visible=False) as hr_options: + first_pass_width = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass width", value=512) + first_pass_height = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass height", value=512) scale_latent = gr.Checkbox(label='Scale latent', value=False) denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7) @@ -604,6 +606,8 @@ def create_ui(wrap_gradio_gpu_call): enable_hr, scale_latent, denoising_strength, + first_pass_width, + first_pass_height, ] + custom_inputs, outputs=[ txt2img_gallery, @@ -668,6 +672,8 @@ def create_ui(wrap_gradio_gpu_call): (denoising_strength, "Denoising strength"), (enable_hr, lambda d: "Denoising strength" in d), (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)), + (first_pass_width, "First pass width"), + (first_pass_height, "First pass height"), ] modules.generation_parameters_copypaste.connect_paste(paste, txt2img_paste_fields, txt2img_prompt) token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter]) -- cgit v1.2.3 From 40d1c6e423b4dc52b3bdae43d9e2442960760ced Mon Sep 17 00:00:00 2001 From: Buckzor Date: Thu, 13 Oct 2022 20:04:22 +0100 Subject: Option between stretch and crop for Highres. fix --- modules/processing.py | 34 ++++++++++++++++++++++------------ modules/txt2img.py | 7 ++++--- modules/ui.py | 25 ++++++++++++++++--------- 3 files changed, 42 insertions(+), 24 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/processing.py b/modules/processing.py index abbfdf98..0246f5dd 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -506,13 +506,14 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): firstphase_width_truncated = 0 firstphase_height_truncated = 0 - def __init__(self, enable_hr=False, scale_latent=True, denoising_strength=0.75, first_pass_width=512, first_pass_height=512, **kwargs): + def __init__(self, enable_hr=False, scale_latent=True, denoising_strength=0.75, firstphase_width=512, firstphase_height=512, crop_scale=False, **kwargs): super().__init__(**kwargs) self.enable_hr = enable_hr self.scale_latent = scale_latent self.denoising_strength = denoising_strength - self.first_pass_width = first_pass_width - self.first_pass_height = first_pass_height + self.firstphase_width = firstphase_width + self.firstphase_height = firstphase_height + self.crop_scale = crop_scale def init(self, all_prompts, all_seeds, all_subseeds): if self.enable_hr: @@ -521,14 +522,14 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): else: state.job_count = state.job_count * 2 - desired_pixel_count = self.first_pass_width * self.first_pass_height - actual_pixel_count = self.width * self.height - scale = math.sqrt(desired_pixel_count / actual_pixel_count) + #desired_pixel_count = self.firstphase_width * self.firstphase_height + #actual_pixel_count = self.width * self.height + #scale = math.sqrt(desired_pixel_count / actual_pixel_count) - self.firstphase_width = math.ceil(scale * self.width / 64) * 64 - self.firstphase_height = math.ceil(scale * self.height / 64) * 64 - self.firstphase_width_truncated = int(scale * self.width) - self.firstphase_height_truncated = int(scale * self.height) + #self.firstphase_width = math.ceil(scale * self.width / 64) * 64 + #self.firstphase_height = math.ceil(scale * self.height / 64) * 64 + #self.firstphase_width_truncated = int(scale * self.width) + #self.firstphase_height_truncated = int(scale * self.height) def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength): self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model) @@ -541,8 +542,17 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): x = create_random_tensors([opt_C, self.firstphase_height // opt_f, self.firstphase_width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning) - truncate_x = (self.firstphase_width - self.firstphase_width_truncated) // opt_f - truncate_y = (self.firstphase_height - self.firstphase_height_truncated) // opt_f + truncate_x = 0 + truncate_y = 0 + + if self.crop_scale: + if self.width/self.firstphase_width > self.height/self.firstphase_height: + #Crop to landscape + truncate_y = (self.width - self.firstphase_width)//2 // opt_f + + elif self.width/self.firstphase_width < self.height/self.firstphase_height: + #Crop to portrait + truncate_x = (self.height - self.firstphase_height)//2 // opt_f samples = samples[:, :, truncate_y//2:samples.shape[2]-truncate_y//2, truncate_x//2:samples.shape[3]-truncate_x//2] diff --git a/modules/txt2img.py b/modules/txt2img.py index 85cbece4..447ec3d3 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -6,7 +6,7 @@ import modules.processing as processing from modules.ui import plaintext_to_html -def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, scale_latent: bool, denoising_strength: float, first_pass_width: int, first_pass_height: int, *args): +def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, scale_latent: bool, denoising_strength: float, firstphase_width: int, firstphase_height: int, crop_scale: bool, *args): p = StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples, @@ -32,8 +32,9 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: enable_hr=enable_hr, scale_latent=scale_latent if enable_hr else None, denoising_strength=denoising_strength if enable_hr else None, - first_pass_width=first_pass_width if enable_hr else None, - first_pass_height=first_pass_height if enable_hr else None, + firstphase_width=firstphase_width if enable_hr else None, + firstphase_height=firstphase_height if enable_hr else None, + crop_scale=crop_scale if enable_hr else None, ) diff --git a/modules/ui.py b/modules/ui.py index 544419b2..f2d81f68 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -540,12 +540,18 @@ def create_ui(wrap_gradio_gpu_call): enable_hr = gr.Checkbox(label='Highres. fix', value=False) with gr.Row(visible=False) as hr_options: - first_pass_width = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass width", value=512) - first_pass_height = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass height", value=512) - scale_latent = gr.Checkbox(label='Scale latent', value=False) - denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7) + with gr.Column(scale=1.0): + firstphase_width = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass width", value=512) + firstphase_height = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass height", value=512) + + with gr.Column(scale=1.0): + with gr.Row(): + crop_scale = gr.Checkbox(label='Crop when scaling', value=False) + scale_latent = gr.Checkbox(label='Scale latent', value=False) + with gr.Row(): + denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7) - with gr.Row(): + with gr.Row(equal_height=True): batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1) batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1) @@ -606,8 +612,9 @@ def create_ui(wrap_gradio_gpu_call): enable_hr, scale_latent, denoising_strength, - first_pass_width, - first_pass_height, + firstphase_width, + firstphase_height, + crop_scale, ] + custom_inputs, outputs=[ txt2img_gallery, @@ -672,8 +679,8 @@ def create_ui(wrap_gradio_gpu_call): (denoising_strength, "Denoising strength"), (enable_hr, lambda d: "Denoising strength" in d), (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)), - (first_pass_width, "First pass width"), - (first_pass_height, "First pass height"), + (firstphase_width, "First pass width"), + (firstphase_height, "First pass height"), ] modules.generation_parameters_copypaste.connect_paste(paste, txt2img_paste_fields, txt2img_prompt) token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter]) -- cgit v1.2.3 From e644b5a80beb54b6df4caa63fb19d889dd4ceff6 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 14 Oct 2022 17:03:03 +0300 Subject: remove scale latent and no-crop options from hires fix support copy-pasting new parameters for hires fix --- modules/processing.py | 64 ++++++++++++++++++++++----------------------------- modules/txt2img.py | 9 +++----- modules/ui.py | 19 ++++----------- 3 files changed, 35 insertions(+), 57 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/processing.py b/modules/processing.py index d9b0e0e7..100a259f 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -506,14 +506,12 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): firstphase_width_truncated = 0 firstphase_height_truncated = 0 - def __init__(self, enable_hr=False, scale_latent=True, denoising_strength=0.75, firstphase_width=512, firstphase_height=512, crop_scale=False, **kwargs): + def __init__(self, enable_hr=False, denoising_strength=0.75, firstphase_width=512, firstphase_height=512, **kwargs): super().__init__(**kwargs) self.enable_hr = enable_hr - self.scale_latent = scale_latent self.denoising_strength = denoising_strength self.firstphase_width = firstphase_width self.firstphase_height = firstphase_height - self.crop_scale = crop_scale def init(self, all_prompts, all_seeds, all_subseeds): if self.enable_hr: @@ -530,6 +528,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning) return samples + self.extra_generation_params["First pass size"] = f"{self.firstphase_width}x{self.firstphase_height}" + x = create_random_tensors([opt_C, self.firstphase_height // opt_f, self.firstphase_width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning) @@ -538,46 +538,36 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): width_ratio = self.width/self.firstphase_width height_ratio = self.height/self.firstphase_height - if self.crop_scale: - if width_ratio > height_ratio: - #Crop to landscape - truncate_y = int((self.width - self.firstphase_width) / width_ratio / height_ratio / opt_f) + if width_ratio > height_ratio: + truncate_y = int((self.width - self.firstphase_width) / width_ratio / height_ratio / opt_f) - elif width_ratio < height_ratio: - #Crop to portrait - truncate_x = int((self.height - self.firstphase_height) / width_ratio / height_ratio / opt_f) + elif width_ratio < height_ratio: + truncate_x = int((self.height - self.firstphase_height) / width_ratio / height_ratio / opt_f) - samples = samples[:, :, truncate_y//2:samples.shape[2]-truncate_y//2, truncate_x//2:samples.shape[3]-truncate_x//2] - - + samples = samples[:, :, truncate_y//2:samples.shape[2]-truncate_y//2, truncate_x//2:samples.shape[3]-truncate_x//2] - + decoded_samples = decode_first_stage(self.sd_model, samples) - if self.scale_latent: - samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear") + if opts.upscaler_for_img2img is None or opts.upscaler_for_img2img == "None": + decoded_samples = torch.nn.functional.interpolate(decoded_samples, size=(self.height, self.width), mode="bilinear") else: - decoded_samples = decode_first_stage(self.sd_model, samples) + lowres_samples = torch.clamp((decoded_samples + 1.0) / 2.0, min=0.0, max=1.0) - if opts.upscaler_for_img2img is None or opts.upscaler_for_img2img == "None": - decoded_samples = torch.nn.functional.interpolate(decoded_samples, size=(self.height, self.width), mode="bilinear") - else: - lowres_samples = torch.clamp((decoded_samples + 1.0) / 2.0, min=0.0, max=1.0) - - batch_images = [] - for i, x_sample in enumerate(lowres_samples): - x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) - x_sample = x_sample.astype(np.uint8) - image = Image.fromarray(x_sample) - image = images.resize_image(0, image, self.width, self.height) - image = np.array(image).astype(np.float32) / 255.0 - image = np.moveaxis(image, 2, 0) - batch_images.append(image) - - decoded_samples = torch.from_numpy(np.array(batch_images)) - decoded_samples = decoded_samples.to(shared.device) - decoded_samples = 2. * decoded_samples - 1. - - samples = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(decoded_samples)) + batch_images = [] + for i, x_sample in enumerate(lowres_samples): + x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) + x_sample = x_sample.astype(np.uint8) + image = Image.fromarray(x_sample) + image = images.resize_image(0, image, self.width, self.height) + image = np.array(image).astype(np.float32) / 255.0 + image = np.moveaxis(image, 2, 0) + batch_images.append(image) + + decoded_samples = torch.from_numpy(np.array(batch_images)) + decoded_samples = decoded_samples.to(shared.device) + decoded_samples = 2. * decoded_samples - 1. + + samples = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(decoded_samples)) shared.state.nextjob() diff --git a/modules/txt2img.py b/modules/txt2img.py index 447ec3d3..2381347f 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -6,7 +6,7 @@ import modules.processing as processing from modules.ui import plaintext_to_html -def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, scale_latent: bool, denoising_strength: float, firstphase_width: int, firstphase_height: int, crop_scale: bool, *args): +def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, firstphase_width: int, firstphase_height: int, *args): p = StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples, @@ -30,12 +30,9 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: restore_faces=restore_faces, tiling=tiling, enable_hr=enable_hr, - scale_latent=scale_latent if enable_hr else None, denoising_strength=denoising_strength if enable_hr else None, - firstphase_width=firstphase_width if enable_hr else None, - firstphase_height=firstphase_height if enable_hr else None, - crop_scale=crop_scale if enable_hr else None, - + firstphase_width=firstphase_width if enable_hr else None, + firstphase_height=firstphase_height if enable_hr else None, ) if cmd_opts.enable_console_prompts: diff --git a/modules/ui.py b/modules/ui.py index f2d81f68..d66ddc14 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -540,16 +540,9 @@ def create_ui(wrap_gradio_gpu_call): enable_hr = gr.Checkbox(label='Highres. fix', value=False) with gr.Row(visible=False) as hr_options: - with gr.Column(scale=1.0): - firstphase_width = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass width", value=512) - firstphase_height = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass height", value=512) - - with gr.Column(scale=1.0): - with gr.Row(): - crop_scale = gr.Checkbox(label='Crop when scaling', value=False) - scale_latent = gr.Checkbox(label='Scale latent', value=False) - with gr.Row(): - denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7) + firstphase_width = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass width", value=512) + firstphase_height = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass height", value=512) + denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7) with gr.Row(equal_height=True): batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1) @@ -610,11 +603,9 @@ def create_ui(wrap_gradio_gpu_call): height, width, enable_hr, - scale_latent, denoising_strength, firstphase_width, firstphase_height, - crop_scale, ] + custom_inputs, outputs=[ txt2img_gallery, @@ -679,8 +670,8 @@ def create_ui(wrap_gradio_gpu_call): (denoising_strength, "Denoising strength"), (enable_hr, lambda d: "Denoising strength" in d), (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)), - (firstphase_width, "First pass width"), - (firstphase_height, "First pass height"), + (firstphase_width, "First pass size-1"), + (firstphase_height, "First pass size-2"), ] modules.generation_parameters_copypaste.connect_paste(paste, txt2img_paste_fields, txt2img_prompt) token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter]) -- cgit v1.2.3 From 0aec19d7837d8564355fdb286541db7165852e41 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 14 Oct 2022 18:15:03 +0300 Subject: make pasting into img2img prompt work make image params request not use temp files --- modules/images.py | 36 ++++++++++++++++++------------------ modules/ui.py | 9 +++------ 2 files changed, 21 insertions(+), 24 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/images.py b/modules/images.py index f1155b7f..68cdbc93 100644 --- a/modules/images.py +++ b/modules/images.py @@ -1,4 +1,5 @@ import datetime +import io import math import os from collections import namedtuple @@ -465,21 +466,20 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i return fullfn, txt_fullfn -def image_data(image_path): - file, ext = os.path.splitext(image_path.name) - data = {} - if "png" in ext: - image = Image.open(image_path.name, "r") - print(f"Image data requested for {image_path.name} {image.format} of {type(image)}") - try: - data = image.text["parameters"] - except Exception as e: - print(f"Exception: {e}") - pass - print(f"Image data: {data}") - if "txt" in ext: - myfile = open(image_path.name, 'r') - data = myfile.read() - myfile.close() - - return data, None +def image_data(data): + try: + image = Image.open(io.BytesIO(data)) + textinfo = image.text["parameters"] + return textinfo, None + except Exception: + pass + + try: + text = data.decode('utf8') + assert len(text) < 10000 + return text, None + + except Exception: + pass + + return '', None diff --git a/modules/ui.py b/modules/ui.py index 0a3ee887..6266db49 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -514,7 +514,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Blocks(analytics_enabled=False) as txt2img_interface: txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=False) dummy_component = gr.Label(visible=False) - txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="file", visible=False) + txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False) with gr.Row(elem_id='txt2img_progress_row'): with gr.Column(scale=1): @@ -620,7 +620,6 @@ def create_ui(wrap_gradio_gpu_call): txt_prompt_img.change( fn=modules.images.image_data, - # _js = "get_extras_tab_index", inputs=[ txt_prompt_img ], @@ -692,8 +691,7 @@ def create_ui(wrap_gradio_gpu_call): img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True) with gr.Row(elem_id='img2img_progress_row'): - img2img_prompt_img = gr.File(label="", elem_id="txt_prompt_image", file_count="single", type="file", - visible=False) + img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False) with gr.Column(scale=1): pass @@ -791,9 +789,8 @@ def create_ui(wrap_gradio_gpu_call): img2img_prompt_img.change( fn=modules.images.image_data, - # _js = "get_extras_tab_index", inputs=[ - txt_prompt_img + img2img_prompt_img ], outputs=[ img2img_prompt, -- cgit v1.2.3 From 67f447ddcc8a17d11939c3801dca635dc22944c7 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 14 Oct 2022 19:30:28 +0300 Subject: possibility to load checkpoint, clip skip, and hypernet from infotext --- modules/ui.py | 52 +++++++++++++++++++++++++++++++++++++++++++++------- 1 file changed, 45 insertions(+), 7 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 6266db49..a37a4e17 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -22,7 +22,7 @@ import gradio as gr import gradio.utils import gradio.routes -from modules import sd_hijack +from modules import sd_hijack, sd_models from modules.paths import script_path from modules.shared import opts, cmd_opts if cmd_opts.deepdanbooru: @@ -507,12 +507,38 @@ def setup_progressbar(progressbar, preview, id_part, textinfo=None): ) +def apply_setting(key, value): + if value is None: + return gr.update() + + if key == "sd_model_checkpoint": + ckpt_info = sd_models.get_closet_checkpoint_match(value) + + if ckpt_info is not None: + value = ckpt_info.title + else: + return gr.update() + + comp_args = opts.data_labels[key].component_args + if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False: + return + + valtype = type(opts.data_labels[key].default) + oldval = opts.data[key] + opts.data[key] = valtype(value) if valtype != type(None) else value + if oldval != value and opts.data_labels[key].onchange is not None: + opts.data_labels[key].onchange() + + opts.save(shared.config_filename) + return value + + def create_ui(wrap_gradio_gpu_call): import modules.img2img import modules.txt2img with gr.Blocks(analytics_enabled=False) as txt2img_interface: - txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=False) + txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False) dummy_component = gr.Label(visible=False) txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False) @@ -684,11 +710,10 @@ def create_ui(wrap_gradio_gpu_call): (firstphase_width, "First pass size-1"), (firstphase_height, "First pass size-2"), ] - modules.generation_parameters_copypaste.connect_paste(paste, txt2img_paste_fields, txt2img_prompt) token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter]) with gr.Blocks(analytics_enabled=False) as img2img_interface: - img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True) + img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste, token_counter, token_button = create_toprow(is_img2img=True) with gr.Row(elem_id='img2img_progress_row'): img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False) @@ -938,7 +963,6 @@ def create_ui(wrap_gradio_gpu_call): (seed_resize_from_h, "Seed resize from-2"), (denoising_strength, "Denoising strength"), ] - modules.generation_parameters_copypaste.connect_paste(paste, img2img_paste_fields, img2img_prompt) token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter]) with gr.Blocks(analytics_enabled=False) as extras_interface: @@ -1580,8 +1604,22 @@ Requested path was: {f} outputs=[extras_image], ) - modules.generation_parameters_copypaste.connect_paste(pnginfo_send_to_txt2img, txt2img_paste_fields, generation_info, 'switch_to_txt2img') - modules.generation_parameters_copypaste.connect_paste(pnginfo_send_to_img2img, img2img_paste_fields, generation_info, 'switch_to_img2img_img2img') + settings_map = { + 'sd_hypernetwork': 'Hypernet', + 'CLIP_stop_at_last_layers': 'Clip skip', + 'sd_model_checkpoint': 'Model hash', + } + + settings_paste_fields = [ + (component_dict[k], lambda d, k=k, v=v: apply_setting(k, d.get(v, None))) + for k, v in settings_map.items() + ] + + modules.generation_parameters_copypaste.connect_paste(txt2img_paste, txt2img_paste_fields + settings_paste_fields, txt2img_prompt) + modules.generation_parameters_copypaste.connect_paste(img2img_paste, img2img_paste_fields + settings_paste_fields, img2img_prompt) + + modules.generation_parameters_copypaste.connect_paste(pnginfo_send_to_txt2img, txt2img_paste_fields + settings_paste_fields, generation_info, 'switch_to_txt2img') + modules.generation_parameters_copypaste.connect_paste(pnginfo_send_to_img2img, img2img_paste_fields + settings_paste_fields, generation_info, 'switch_to_img2img_img2img') ui_config_file = cmd_opts.ui_config_file ui_settings = {} -- cgit v1.2.3 From c344ba3b325459abbf9b0df2c1b18f7bf99805b2 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 14 Oct 2022 20:31:49 +0300 Subject: add option to read generation params for learning previews from txt2img --- modules/hypernetworks/hypernetwork.py | 21 ++++++++++++++++----- modules/textual_inversion/textual_inversion.py | 25 ++++++++++++++++++------- modules/ui.py | 20 +++++++++++++++++--- 3 files changed, 51 insertions(+), 15 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index f1248bb7..e5cb1817 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -180,7 +180,7 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None): return self.to_out(out) -def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt): +def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height): assert hypernetwork_name, 'hypernetwork not selected' path = shared.hypernetworks.get(hypernetwork_name, None) @@ -265,20 +265,31 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0: last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png') - preview_text = entry.cond_text if preview_image_prompt == "" else preview_image_prompt - optimizer.zero_grad() shared.sd_model.cond_stage_model.to(devices.device) shared.sd_model.first_stage_model.to(devices.device) p = processing.StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, - prompt=preview_text, - steps=20, do_not_save_grid=True, do_not_save_samples=True, ) + if preview_from_txt2img: + p.prompt = preview_prompt + p.negative_prompt = preview_negative_prompt + p.steps = preview_steps + p.sampler_index = preview_sampler_index + p.cfg_scale = preview_cfg_scale + p.seed = preview_seed + p.width = preview_width + p.height = preview_height + else: + p.prompt = entry.cond_text + p.steps = 20 + + preview_text = p.prompt + processed = processing.process_images(p) image = processed.images[0] if len(processed.images)>0 else None diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index fa0e33a2..3d835358 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -172,7 +172,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'): return fn -def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_image_prompt): +def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height): assert embedding_name, 'embedding not selected' shared.state.textinfo = "Initializing textual inversion training..." @@ -259,18 +259,29 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0: last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png') - preview_text = entry.cond_text if preview_image_prompt == "" else preview_image_prompt - p = processing.StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, - prompt=preview_text, - steps=20, - height=training_height, - width=training_width, do_not_save_grid=True, do_not_save_samples=True, ) + if preview_from_txt2img: + p.prompt = preview_prompt + p.negative_prompt = preview_negative_prompt + p.steps = preview_steps + p.sampler_index = preview_sampler_index + p.cfg_scale = preview_cfg_scale + p.seed = preview_seed + p.width = preview_width + p.height = preview_height + else: + p.prompt = entry.cond_text + p.steps = 20 + p.width = training_width + p.height = training_height + + preview_text = p.prompt + processed = processing.process_images(p) image = processed.images[0] diff --git a/modules/ui.py b/modules/ui.py index 828bfeea..4a04c2cc 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -711,6 +711,18 @@ def create_ui(wrap_gradio_gpu_call): (firstphase_width, "First pass size-1"), (firstphase_height, "First pass size-2"), ] + + txt2img_preview_params = [ + txt2img_prompt, + txt2img_negative_prompt, + steps, + sampler_index, + cfg_scale, + seed, + width, + height, + ] + token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter]) with gr.Blocks(analytics_enabled=False) as img2img_interface: @@ -1162,7 +1174,7 @@ def create_ui(wrap_gradio_gpu_call): create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0) save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0) save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True) - preview_image_prompt = gr.Textbox(label='Preview prompt', value="") + preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False) with gr.Row(): interrupt_training = gr.Button(value="Interrupt") @@ -1240,7 +1252,8 @@ def create_ui(wrap_gradio_gpu_call): save_embedding_every, template_file, save_image_with_stored_embedding, - preview_image_prompt, + preview_from_txt2img, + *txt2img_preview_params, ], outputs=[ ti_output, @@ -1260,7 +1273,8 @@ def create_ui(wrap_gradio_gpu_call): create_image_every, save_embedding_every, template_file, - preview_image_prompt, + preview_from_txt2img, + *txt2img_preview_params, ], outputs=[ ti_output, -- cgit v1.2.3 From c250cb289c97fe303cef69064bf45899406f6a40 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 14 Oct 2022 22:01:49 +0300 Subject: change checkpoint merger to work in a more obvious way remove sigmoid and inverse sigmoid because they just did the same thing as weighed sum only with changed multiplier --- javascript/hints.js | 4 ++-- modules/extras.py | 24 +++++------------------- modules/ui.py | 4 ++-- 3 files changed, 9 insertions(+), 23 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/hints.js b/javascript/hints.js index af010a59..8fec907d 100644 --- a/javascript/hints.js +++ b/javascript/hints.js @@ -87,8 +87,8 @@ titles = { "Quicksettings list": "List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual setting tab. See modules/shared.py for setting names. Requires restarting to apply.", - "Weighted Sum": "Result = A * (1 - M) + B * M", - "Add difference": "Result = A + (B - C) * (1 - M)", + "Weighted sum": "Result = A * (1 - M) + B * M", + "Add difference": "Result = A + (B - C) * M", } diff --git a/modules/extras.py b/modules/extras.py index 2e7b3751..f2f5a7b0 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -159,24 +159,12 @@ def run_pnginfo(image): return '', geninfo, info -def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, interp_amount, save_as_half, custom_name): - # Linear interpolation (https://en.wikipedia.org/wiki/Linear_interpolation) +def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, multiplier, save_as_half, custom_name): def weighted_sum(theta0, theta1, theta2, alpha): return ((1 - alpha) * theta0) + (alpha * theta1) - # Smoothstep (https://en.wikipedia.org/wiki/Smoothstep) - def sigmoid(theta0, theta1, theta2, alpha): - alpha = alpha * alpha * (3 - (2 * alpha)) - return theta0 + ((theta1 - theta0) * alpha) - - # Inverse Smoothstep (https://en.wikipedia.org/wiki/Smoothstep) - def inv_sigmoid(theta0, theta1, theta2, alpha): - import math - alpha = 0.5 - math.sin(math.asin(1.0 - 2.0 * alpha) / 3.0) - return theta0 + ((theta1 - theta0) * alpha) - def add_difference(theta0, theta1, theta2, alpha): - return theta0 + (theta1 - theta2) * (1.0 - alpha) + return theta0 + (theta1 - theta2) * alpha primary_model_info = sd_models.checkpoints_list[primary_model_name] secondary_model_info = sd_models.checkpoints_list[secondary_model_name] @@ -198,9 +186,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam theta_2 = None theta_funcs = { - "Weighted Sum": weighted_sum, - "Sigmoid": sigmoid, - "Inverse Sigmoid": inv_sigmoid, + "Weighted sum": weighted_sum, "Add difference": add_difference, } theta_func = theta_funcs[interp_method] @@ -213,7 +199,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam if t2 is None: t2 = torch.zeros_like(theta_0[key]) - theta_0[key] = theta_func(theta_0[key], theta_1[key], t2, (float(1.0) - interp_amount)) # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint + theta_0[key] = theta_func(theta_0[key], theta_1[key], t2, multiplier) if save_as_half: theta_0[key] = theta_0[key].half() @@ -227,7 +213,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path - filename = primary_model_info.model_name + '_' + str(round(interp_amount, 2)) + '-' + secondary_model_info.model_name + '_' + str(round((float(1.0) - interp_amount), 2)) + '-' + interp_method.replace(" ", "_") + '-merged.ckpt' + filename = primary_model_info.model_name + '_' + str(round(1-multiplier, 2)) + '-' + secondary_model_info.model_name + '_' + str(round(multiplier, 2)) + '-' + interp_method.replace(" ", "_") + '-merged.ckpt' filename = filename if custom_name == '' else (custom_name + '.ckpt') output_modelname = os.path.join(ckpt_dir, filename) diff --git a/modules/ui.py b/modules/ui.py index 4a04c2cc..a08ffc9b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1101,8 +1101,8 @@ def create_ui(wrap_gradio_gpu_call): secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)") tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)") custom_name = gr.Textbox(label="Custom Name (Optional)") - interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Interpolation amount (1 - M)', value=0.3) - interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid", "Inverse Sigmoid", "Add difference"], value="Weighted Sum", label="Interpolation Method") + interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3) + interp_method = gr.Radio(choices=["Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method") save_as_half = gr.Checkbox(value=False, label="Save as float16") modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary') -- cgit v1.2.3 From 03d62538aebeff51713619fe808c953bdb70193d Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 14 Oct 2022 22:43:55 +0300 Subject: remove duplicate code for log loss, add step, make it read from options rather than gradio input --- modules/hypernetworks/hypernetwork.py | 20 ++++-------- modules/shared.py | 3 +- modules/textual_inversion/textual_inversion.py | 44 ++++++++++++++++++-------- modules/ui.py | 3 -- 4 files changed, 38 insertions(+), 32 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index edb8cba1..59c7ac6e 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -15,6 +15,7 @@ import torch from torch import einsum from einops import rearrange, repeat import modules.textual_inversion.dataset +from modules.textual_inversion import textual_inversion from modules.textual_inversion.learn_schedule import LearnRateScheduler @@ -210,7 +211,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..." with torch.autocast("cuda"): - ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=1, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file, include_cond=True) + ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file, include_cond=True) if unload: shared.sd_model.cond_stage_model.to(devices.cpu) @@ -263,19 +264,10 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, last_saved_file = os.path.join(hypernetwork_dir, f'{hypernetwork_name}-{hypernetwork.step}.pt') hypernetwork.save(last_saved_file) - if write_csv_every > 0 and hypernetwork_dir is not None and hypernetwork.step % write_csv_every == 0: - write_csv_header = False if os.path.exists(os.path.join(hypernetwork_dir, "hypernetwork_loss.csv")) else True - - with open(os.path.join(hypernetwork_dir, "hypernetwork_loss.csv"), "a+") as fout: - - csv_writer = csv.DictWriter(fout, fieldnames=["step", "loss", "learn_rate"]) - - if write_csv_header: - csv_writer.writeheader() - - csv_writer.writerow({"step": hypernetwork.step, - "loss": f"{losses.mean():.7f}", - "learn_rate": scheduler.learn_rate}) + textual_inversion.write_loss(log_directory, "hypernetwork_loss.csv", hypernetwork.step, len(ds), { + "loss": f"{losses.mean():.7f}", + "learn_rate": scheduler.learn_rate + }) if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0: last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png') diff --git a/modules/shared.py b/modules/shared.py index 695d29b6..d41a7ab3 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -236,7 +236,8 @@ options_templates.update(options_section(('training', "Training"), { "unload_models_when_training": OptionInfo(False, "Unload VAE and CLIP from VRAM when training"), "dataset_filename_word_regex": OptionInfo("", "Filename word regex"), "dataset_filename_join_string": OptionInfo(" ", "Filename join string"), - "training_image_repeats_per_epoch": OptionInfo(100, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}), + "training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}), + "training_write_csv_every": OptionInfo(500, "Save an csv containing the loss to log directory every N steps, 0 to disable"), })) options_templates.update(options_section(('sd', "Stable Diffusion"), { diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 1f5ace6f..da0d77a0 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -173,6 +173,32 @@ def create_embedding(name, num_vectors_per_token, init_text='*'): return fn +def write_loss(log_directory, filename, step, epoch_len, values): + if shared.opts.training_write_csv_every == 0: + return + + if step % shared.opts.training_write_csv_every != 0: + return + + write_csv_header = False if os.path.exists(os.path.join(log_directory, filename)) else True + + with open(os.path.join(log_directory, filename), "a+", newline='') as fout: + csv_writer = csv.DictWriter(fout, fieldnames=["step", "epoch", "epoch_step", *(values.keys())]) + + if write_csv_header: + csv_writer.writeheader() + + epoch = step // epoch_len + epoch_step = step - epoch * epoch_len + + csv_writer.writerow({ + "step": step + 1, + "epoch": epoch + 1, + "epoch_step": epoch_step + 1, + **values, + }) + + def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height): assert embedding_name, 'embedding not selected' @@ -257,20 +283,10 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini last_saved_file = os.path.join(embedding_dir, f'{embedding_name}-{embedding.step}.pt') embedding.save(last_saved_file) - if write_csv_every > 0 and log_directory is not None and embedding.step % write_csv_every == 0: - write_csv_header = False if os.path.exists(os.path.join(log_directory, "textual_inversion_loss.csv")) else True - - with open(os.path.join(log_directory, "textual_inversion_loss.csv"), "a+") as fout: - - csv_writer = csv.DictWriter(fout, fieldnames=["epoch", "epoch_step", "loss", "learn_rate"]) - - if write_csv_header: - csv_writer.writeheader() - - csv_writer.writerow({"epoch": epoch_num + 1, - "epoch_step": epoch_step - 1, - "loss": f"{losses.mean():.7f}", - "learn_rate": scheduler.learn_rate}) + write_loss(log_directory, "textual_inversion_loss.csv", embedding.step, len(ds), { + "loss": f"{losses.mean():.7f}", + "learn_rate": scheduler.learn_rate + }) if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0: last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png') diff --git a/modules/ui.py b/modules/ui.py index be4a43a7..a08ffc9b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1172,7 +1172,6 @@ def create_ui(wrap_gradio_gpu_call): training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) steps = gr.Number(label='Max steps', value=100000, precision=0) create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0) - write_csv_every = gr.Number(label='Save an csv containing the loss to log directory every N steps, 0 to disable', value=500, precision=0) save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0) save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True) preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False) @@ -1251,7 +1250,6 @@ def create_ui(wrap_gradio_gpu_call): steps, create_image_every, save_embedding_every, - write_csv_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, @@ -1274,7 +1272,6 @@ def create_ui(wrap_gradio_gpu_call): steps, create_image_every, save_embedding_every, - write_csv_every, template_file, preview_from_txt2img, *txt2img_preview_params, -- cgit v1.2.3 From cd58e44051f658f2efb544203a92837f43786372 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 14 Oct 2022 23:17:28 +0300 Subject: disabling history - i knew it was slow as fuck but i didn't realize it would also show galleries on launch --- modules/ui.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index a08ffc9b..6d193955 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1089,7 +1089,8 @@ def create_ui(wrap_gradio_gpu_call): "t2i":txt2img_paste_fields, "i2i":img2img_paste_fields } - images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) + + #images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) with gr.Blocks() as modelmerger_interface: with gr.Row().style(equal_height=False): @@ -1486,7 +1487,7 @@ Requested path was: {f} (img2img_interface, "img2img", "img2img"), (extras_interface, "Extras", "extras"), (pnginfo_interface, "PNG Info", "pnginfo"), - (images_history, "History", "images_history"), + #(images_history, "History", "images_history"), (modelmerger_interface, "Checkpoint Merger", "modelmerger"), (train_interface, "Train", "ti"), (settings_interface, "Settings", "settings"), -- cgit v1.2.3 From 368f4cc4c73509c1968cd9defe068d8bf4ff7c4f Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 14 Oct 2022 23:19:05 +0300 Subject: set firstpass w/h to 0 by default and rever to old behavior when any are 0 --- modules/processing.py | 49 ++++++++++++++++++++++++++++++------------------- modules/ui.py | 4 ++-- 2 files changed, 32 insertions(+), 21 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/processing.py b/modules/processing.py index 100a259f..a75b9f84 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -501,17 +501,15 @@ def process_images(p: StableDiffusionProcessing) -> Processed: class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): sampler = None - firstphase_width = 0 - firstphase_height = 0 - firstphase_width_truncated = 0 - firstphase_height_truncated = 0 - def __init__(self, enable_hr=False, denoising_strength=0.75, firstphase_width=512, firstphase_height=512, **kwargs): + def __init__(self, enable_hr=False, denoising_strength=0.75, firstphase_width=0, firstphase_height=0, **kwargs): super().__init__(**kwargs) self.enable_hr = enable_hr self.denoising_strength = denoising_strength self.firstphase_width = firstphase_width self.firstphase_height = firstphase_height + self.truncate_x = 0 + self.truncate_y = 0 def init(self, all_prompts, all_seeds, all_subseeds): if self.enable_hr: @@ -520,6 +518,32 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): else: state.job_count = state.job_count * 2 + if self.firstphase_width == 0 or self.firstphase_height == 0: + desired_pixel_count = 512 * 512 + actual_pixel_count = self.width * self.height + scale = math.sqrt(desired_pixel_count / actual_pixel_count) + self.firstphase_width = math.ceil(scale * self.width / 64) * 64 + self.firstphase_height = math.ceil(scale * self.height / 64) * 64 + firstphase_width_truncated = int(scale * self.width) + firstphase_height_truncated = int(scale * self.height) + + else: + self.extra_generation_params["First pass size"] = f"{self.firstphase_width}x{self.firstphase_height}" + + width_ratio = self.width / self.firstphase_width + height_ratio = self.height / self.firstphase_height + + if width_ratio > height_ratio: + firstphase_width_truncated = self.firstphase_width + firstphase_height_truncated = self.firstphase_width * self.height / self.width + else: + firstphase_width_truncated = self.firstphase_height * self.width / self.height + firstphase_height_truncated = self.firstphase_height + + self.truncate_x = int(self.firstphase_width - firstphase_width_truncated) // opt_f + self.truncate_y = int(self.firstphase_height - firstphase_height_truncated) // opt_f + + def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength): self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model) @@ -528,23 +552,10 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning) return samples - self.extra_generation_params["First pass size"] = f"{self.firstphase_width}x{self.firstphase_height}" - x = create_random_tensors([opt_C, self.firstphase_height // opt_f, self.firstphase_width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning) - truncate_x = 0 - truncate_y = 0 - width_ratio = self.width/self.firstphase_width - height_ratio = self.height/self.firstphase_height - - if width_ratio > height_ratio: - truncate_y = int((self.width - self.firstphase_width) / width_ratio / height_ratio / opt_f) - - elif width_ratio < height_ratio: - truncate_x = int((self.height - self.firstphase_height) / width_ratio / height_ratio / opt_f) - - samples = samples[:, :, truncate_y//2:samples.shape[2]-truncate_y//2, truncate_x//2:samples.shape[3]-truncate_x//2] + samples = samples[:, :, self.truncate_y//2:samples.shape[2]-self.truncate_y//2, self.truncate_x//2:samples.shape[3]-self.truncate_x//2] decoded_samples = decode_first_stage(self.sd_model, samples) diff --git a/modules/ui.py b/modules/ui.py index 6d193955..a1d18be9 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -567,8 +567,8 @@ def create_ui(wrap_gradio_gpu_call): enable_hr = gr.Checkbox(label='Highres. fix', value=False) with gr.Row(visible=False) as hr_options: - firstphase_width = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass width", value=512) - firstphase_height = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass height", value=512) + firstphase_width = gr.Slider(minimum=0, maximum=1024, step=64, label="First pass width", value=0) + firstphase_height = gr.Slider(minimum=0, maximum=1024, step=64, label="First pass height", value=0) denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7) with gr.Row(equal_height=True): -- cgit v1.2.3 From 4dc426509918e90bf4557ecfd1f84031362360c0 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 15 Oct 2022 00:21:48 +0300 Subject: rename firstpass w/h to discard old user settings --- modules/ui.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index a1d18be9..c5d295ea 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -567,8 +567,8 @@ def create_ui(wrap_gradio_gpu_call): enable_hr = gr.Checkbox(label='Highres. fix', value=False) with gr.Row(visible=False) as hr_options: - firstphase_width = gr.Slider(minimum=0, maximum=1024, step=64, label="First pass width", value=0) - firstphase_height = gr.Slider(minimum=0, maximum=1024, step=64, label="First pass height", value=0) + firstphase_width = gr.Slider(minimum=0, maximum=1024, step=64, label="Firstpass width", value=0) + firstphase_height = gr.Slider(minimum=0, maximum=1024, step=64, label="Firstpass height", value=0) denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7) with gr.Row(equal_height=True): -- cgit v1.2.3 From acedbe67d2b8a3af99ca3b9a2f809e7a2db285d1 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 15 Oct 2022 00:43:15 +0300 Subject: bring history tab back, make it behave; it's still slow but won't fuck anything up until you use it --- javascript/images_history.js | 16 ++++++++++++---- modules/ui.py | 4 ++-- 2 files changed, 14 insertions(+), 6 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/images_history.js b/javascript/images_history.js index 3a20056b..f7d052c3 100644 --- a/javascript/images_history.js +++ b/javascript/images_history.js @@ -163,10 +163,15 @@ function images_history_init(){ for (var i in images_history_tab_list){ var tabname = images_history_tab_list[i] tab_btns[i].setAttribute("tabname", tabname); - tab_btns[i].addEventListener('click', images_history_click_tab); + + // this refreshes history upon tab switch + // until the history is known to work well, which is not the case now, we do not do this at startup + //tab_btns[i].addEventListener('click', images_history_click_tab); } - tabs_box.classList.add(images_history_tab_list[0]); - load_txt2img_button.click(); + tabs_box.classList.add(images_history_tab_list[0]); + + // same as above, at page load + //load_txt2img_button.click(); } else { setTimeout(images_history_init, 500); } @@ -182,12 +187,15 @@ document.addEventListener("DOMContentLoaded", function() { buttons.forEach(function(bnt){ bnt.addEventListener('click', images_history_click_image, true); }); + + // same as load_txt2img_button.click() above + /* var cls_btn = gradioApp().getElementById(tabname + '_images_history_gallery').querySelector("svg"); if (cls_btn){ cls_btn.addEventListener('click', function(){ gradioApp().getElementById(tabname + '_images_history_renew_page').click(); }, false); - } + }*/ } }); diff --git a/modules/ui.py b/modules/ui.py index c5d295ea..1bc919c7 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1090,7 +1090,7 @@ def create_ui(wrap_gradio_gpu_call): "i2i":img2img_paste_fields } - #images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) + images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) with gr.Blocks() as modelmerger_interface: with gr.Row().style(equal_height=False): @@ -1487,7 +1487,7 @@ Requested path was: {f} (img2img_interface, "img2img", "img2img"), (extras_interface, "Extras", "extras"), (pnginfo_interface, "PNG Info", "pnginfo"), - #(images_history, "History", "images_history"), + (images_history, "History", "images_history"), (modelmerger_interface, "Checkpoint Merger", "modelmerger"), (train_interface, "Train", "ti"), (settings_interface, "Settings", "settings"), -- cgit v1.2.3 From c7a86f7fe9c0b8967a87e8d709f507d2f44400d8 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 15 Oct 2022 09:24:59 +0300 Subject: add option to use batch size for training --- modules/hypernetworks/hypernetwork.py | 33 +++++++++++++++++++------- modules/textual_inversion/dataset.py | 31 ++++++++++++++---------- modules/textual_inversion/textual_inversion.py | 17 +++++++------ modules/ui.py | 3 +++ 4 files changed, 54 insertions(+), 30 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 59c7ac6e..a2b3bc0a 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -182,7 +182,21 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None): return self.to_out(out) -def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height): +def stack_conds(conds): + if len(conds) == 1: + return torch.stack(conds) + + # same as in reconstruct_multicond_batch + token_count = max([x.shape[0] for x in conds]) + for i in range(len(conds)): + if conds[i].shape[0] != token_count: + last_vector = conds[i][-1:] + last_vector_repeated = last_vector.repeat([token_count - conds[i].shape[0], 1]) + conds[i] = torch.vstack([conds[i], last_vector_repeated]) + + return torch.stack(conds) + +def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height): assert hypernetwork_name, 'hypernetwork not selected' path = shared.hypernetworks.get(hypernetwork_name, None) @@ -211,7 +225,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..." with torch.autocast("cuda"): - ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file, include_cond=True) + ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file, include_cond=True, batch_size=batch_size) if unload: shared.sd_model.cond_stage_model.to(devices.cpu) @@ -235,7 +249,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, optimizer = torch.optim.AdamW(weights, lr=scheduler.learn_rate) pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step) - for i, entry in pbar: + for i, entries in pbar: hypernetwork.step = i + ititial_step scheduler.apply(optimizer, hypernetwork.step) @@ -246,11 +260,12 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, break with torch.autocast("cuda"): - cond = entry.cond.to(devices.device) - x = entry.latent.to(devices.device) - loss = shared.sd_model(x.unsqueeze(0), cond)[0] + c = stack_conds([entry.cond for entry in entries]).to(devices.device) +# c = torch.vstack([entry.cond for entry in entries]).to(devices.device) + x = torch.stack([entry.latent for entry in entries]).to(devices.device) + loss = shared.sd_model(x, c)[0] del x - del cond + del c losses[hypernetwork.step % losses.shape[0]] = loss.item() @@ -292,7 +307,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, p.width = preview_width p.height = preview_height else: - p.prompt = entry.cond_text + p.prompt = entries[0].cond_text p.steps = 20 preview_text = p.prompt @@ -315,7 +330,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,

Loss: {losses.mean():.7f}
Step: {hypernetwork.step}
-Last prompt: {html.escape(entry.cond_text)}
+Last prompt: {html.escape(entries[0].cond_text)}
Last saved embedding: {html.escape(last_saved_file)}
Last saved image: {html.escape(last_saved_image)}

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py index 67e90afe..bd99c0cb 100644 --- a/modules/textual_inversion/dataset.py +++ b/modules/textual_inversion/dataset.py @@ -24,11 +24,12 @@ class DatasetEntry: class PersonalizedBase(Dataset): - def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None, include_cond=False): - re_word = re.compile(shared.opts.dataset_filename_word_regex) if len(shared.opts.dataset_filename_word_regex)>0 else None + def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None, include_cond=False, batch_size=1): + re_word = re.compile(shared.opts.dataset_filename_word_regex) if len(shared.opts.dataset_filename_word_regex) > 0 else None self.placeholder_token = placeholder_token + self.batch_size = batch_size self.width = width self.height = height self.flip = transforms.RandomHorizontalFlip(p=flip_p) @@ -78,13 +79,13 @@ class PersonalizedBase(Dataset): if include_cond: entry.cond_text = self.create_text(filename_text) - entry.cond = cond_model([entry.cond_text]).to(devices.cpu) + entry.cond = cond_model([entry.cond_text]).to(devices.cpu).squeeze(0) self.dataset.append(entry) - self.length = len(self.dataset) * repeats + self.length = len(self.dataset) * repeats // batch_size - self.initial_indexes = np.arange(self.length) % len(self.dataset) + self.initial_indexes = np.arange(len(self.dataset)) self.indexes = None self.shuffle() @@ -101,13 +102,19 @@ class PersonalizedBase(Dataset): return self.length def __getitem__(self, i): - if i % len(self.dataset) == 0: - self.shuffle() + res = [] - index = self.indexes[i % len(self.indexes)] - entry = self.dataset[index] + for j in range(self.batch_size): + position = i * self.batch_size + j + if position % len(self.indexes) == 0: + self.shuffle() - if entry.cond is None: - entry.cond_text = self.create_text(entry.filename_text) + index = self.indexes[position % len(self.indexes)] + entry = self.dataset[index] - return entry + if entry.cond is None: + entry.cond_text = self.create_text(entry.filename_text) + + res.append(entry) + + return res diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index da0d77a0..e754747e 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -199,7 +199,7 @@ def write_loss(log_directory, filename, step, epoch_len, values): }) -def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height): +def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height): assert embedding_name, 'embedding not selected' shared.state.textinfo = "Initializing textual inversion training..." @@ -231,7 +231,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..." with torch.autocast("cuda"): - ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file) + ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file, batch_size=batch_size) hijack = sd_hijack.model_hijack @@ -251,7 +251,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini optimizer = torch.optim.AdamW([embedding.vec], lr=scheduler.learn_rate) pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step) - for i, entry in pbar: + for i, entries in pbar: embedding.step = i + ititial_step scheduler.apply(optimizer, embedding.step) @@ -262,10 +262,9 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini break with torch.autocast("cuda"): - c = cond_model([entry.cond_text]) - - x = entry.latent.to(devices.device) - loss = shared.sd_model(x.unsqueeze(0), c)[0] + c = cond_model([entry.cond_text for entry in entries]) + x = torch.stack([entry.latent for entry in entries]).to(devices.device) + loss = shared.sd_model(x, c)[0] del x losses[embedding.step % losses.shape[0]] = loss.item() @@ -307,7 +306,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini p.width = preview_width p.height = preview_height else: - p.prompt = entry.cond_text + p.prompt = entries[0].cond_text p.steps = 20 p.width = training_width p.height = training_height @@ -348,7 +347,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini

Loss: {losses.mean():.7f}
Step: {embedding.step}
-Last prompt: {html.escape(entry.cond_text)}
+Last prompt: {html.escape(entries[0].cond_text)}
Last saved embedding: {html.escape(last_saved_file)}
Last saved image: {html.escape(last_saved_image)}

diff --git a/modules/ui.py b/modules/ui.py index 1bc919c7..45550ea8 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1166,6 +1166,7 @@ def create_ui(wrap_gradio_gpu_call): train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()]) learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.005") + batch_size = gr.Number(label='Batch size', value=1, precision=0) dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images") log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion") template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt")) @@ -1244,6 +1245,7 @@ def create_ui(wrap_gradio_gpu_call): inputs=[ train_embedding_name, learn_rate, + batch_size, dataset_directory, log_directory, training_width, @@ -1268,6 +1270,7 @@ def create_ui(wrap_gradio_gpu_call): inputs=[ train_hypernetwork_name, learn_rate, + batch_size, dataset_directory, log_directory, steps, -- cgit v1.2.3 From db27b987a97fc8b7894a9dd34bd7641536f9c424 Mon Sep 17 00:00:00 2001 From: aoirusann Date: Sat, 15 Oct 2022 11:48:13 +0800 Subject: Add hint for `ctrl/alt enter` And duplicate implementations are removed --- javascript/ui.js | 10 ---------- modules/ui.py | 10 ++++++++-- script.js | 4 ++-- 3 files changed, 10 insertions(+), 14 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index 0f8fe68e..56f4216f 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -187,12 +187,10 @@ onUiUpdate(function(){ if (!txt2img_textarea) { txt2img_textarea = gradioApp().querySelector("#txt2img_prompt > label > textarea"); txt2img_textarea?.addEventListener("input", () => update_token_counter("txt2img_token_button")); - txt2img_textarea?.addEventListener("keyup", (event) => submit_prompt(event, "txt2img_generate")); } if (!img2img_textarea) { img2img_textarea = gradioApp().querySelector("#img2img_prompt > label > textarea"); img2img_textarea?.addEventListener("input", () => update_token_counter("img2img_token_button")); - img2img_textarea?.addEventListener("keyup", (event) => submit_prompt(event, "img2img_generate")); } }) @@ -220,14 +218,6 @@ function update_token_counter(button_id) { token_timeout = setTimeout(() => gradioApp().getElementById(button_id)?.click(), wait_time); } -function submit_prompt(event, generate_button_id) { - if (event.altKey && event.keyCode === 13) { - event.preventDefault(); - gradioApp().getElementById(generate_button_id).click(); - return; - } -} - function restart_reload(){ document.body.innerHTML='

Reloading...

'; setTimeout(function(){location.reload()},2000) diff --git a/modules/ui.py b/modules/ui.py index 45550ea8..baf4c397 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -433,7 +433,10 @@ def create_toprow(is_img2img): with gr.Row(): with gr.Column(scale=80): with gr.Row(): - prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, placeholder="Prompt", lines=2) + prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2, + placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)" + ) + with gr.Column(scale=1, elem_id="roll_col"): roll = gr.Button(value=art_symbol, elem_id="roll", visible=len(shared.artist_db.artists) > 0) paste = gr.Button(value=paste_symbol, elem_id="paste") @@ -446,7 +449,10 @@ def create_toprow(is_img2img): with gr.Row(): with gr.Column(scale=8): with gr.Row(): - negative_prompt = gr.Textbox(label="Negative prompt", elem_id="negative_prompt", show_label=False, placeholder="Negative prompt", lines=2) + negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2, + placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)" + ) + with gr.Column(scale=1, elem_id="roll_col"): sh = gr.Button(elem_id="sh", visible=True) diff --git a/script.js b/script.js index 9543cbe6..88f2c839 100644 --- a/script.js +++ b/script.js @@ -50,9 +50,9 @@ document.addEventListener("DOMContentLoaded", function() { document.addEventListener('keydown', function(e) { var handled = false; if (e.key !== undefined) { - if((e.key == "Enter" && (e.metaKey || e.ctrlKey))) handled = true; + if((e.key == "Enter" && (e.metaKey || e.ctrlKey || e.altKey))) handled = true; } else if (e.keyCode !== undefined) { - if((e.keyCode == 13 && (e.metaKey || e.ctrlKey))) handled = true; + if((e.keyCode == 13 && (e.metaKey || e.ctrlKey || e.altKey))) handled = true; } if (handled) { button = get_uiCurrentTabContent().querySelector('button[id$=_generate]'); -- cgit v1.2.3 From e8729dd0511f8410db967d9ef192645cfef1be8a Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 15 Oct 2022 12:54:23 +0300 Subject: re-apply height hacks to work with new gradio --- modules/ui.py | 4 ++-- style.css | 16 ++++++++-------- 2 files changed, 10 insertions(+), 10 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index baf4c397..9c7a67dd 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -750,10 +750,10 @@ def create_ui(wrap_gradio_gpu_call): with gr.Tabs(elem_id="mode_img2img") as tabs_img2img_mode: with gr.TabItem('img2img', id='img2img'): - init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_img2img_tool) + init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_img2img_tool).style(height=480) with gr.TabItem('Inpaint', id='inpaint'): - init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA") + init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA").style(height=480) init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_base") init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_mask") diff --git a/style.css b/style.css index 2306c002..c27e53f8 100644 --- a/style.css +++ b/style.css @@ -167,10 +167,6 @@ button{ align-self: stretch !important; } -#img2maskimg .h-60{ - height: 30rem; -} - .overflow-hidden, .gr-panel{ overflow: visible !important; } @@ -443,10 +439,6 @@ input[type="range"]{ --tw-bg-opacity: 0 !important; } -#img2img_image div.h-60{ - height: 480px; -} - #context-menu{ z-index:9999; position:absolute; @@ -521,3 +513,11 @@ canvas[key="mask"] { .row.gr-compact{ overflow: visible; } + +#img2img_image, #img2img_image > .h-60, #img2img_image > .h-60 > div, #img2img_image > .h-60 > div > img, +img2maskimg, #img2maskimg > .h-60, #img2maskimg > .h-60 > div, #img2maskimg > .h-60 > div > img +{ + height: 480px !important; + max-height: 480px !important; + min-height: 480px !important; +} \ No newline at end of file -- cgit v1.2.3 From 5967d07d1aa4e2fef031a57b1612b1ab04a3cd78 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 15 Oct 2022 13:11:28 +0300 Subject: fix new gradio failing to preserve image params --- modules/ui.py | 18 ++++++++++++++++++ 1 file changed, 18 insertions(+) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 9c7a67dd..de5ab929 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -7,6 +7,7 @@ import mimetypes import os import random import sys +import tempfile import time import traceback import platform @@ -176,6 +177,23 @@ def save_files(js_data, images, do_make_zip, index): return gr.File.update(value=fullfns, visible=True), '', '', plaintext_to_html(f"Saved: {filenames[0]}") +def save_pil_to_file(pil_image, dir=None): + use_metadata = False + metadata = PngImagePlugin.PngInfo() + for key, value in pil_image.info.items(): + if isinstance(key, str) and isinstance(value, str): + metadata.add_text(key, value) + use_metadata = True + + file_obj = tempfile.NamedTemporaryFile(delete=False, suffix=".png", dir=dir) + pil_image.save(file_obj, pnginfo=(metadata if use_metadata else None)) + return file_obj + + +# override save to file function so that it also writes PNG info +gr.processing_utils.save_pil_to_file = save_pil_to_file + + def wrap_gradio_call(func, extra_outputs=None): def f(*args, extra_outputs_array=extra_outputs, **kwargs): run_memmon = opts.memmon_poll_rate > 0 and not shared.mem_mon.disabled -- cgit v1.2.3 From d3463bc59a44d62c2de8b357184c49876d84f654 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 15 Oct 2022 14:22:30 +0300 Subject: change styling for top right corner UI made save style button not die when you cancel --- javascript/hints.js | 2 ++ javascript/ui.js | 2 +- modules/ui.py | 57 ++++++++++++++++++++++++++--------------------------- style.css | 16 +++++++-------- 4 files changed, 39 insertions(+), 38 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/hints.js b/javascript/hints.js index 8fec907d..b98012f5 100644 --- a/javascript/hints.js +++ b/javascript/hints.js @@ -16,6 +16,8 @@ titles = { "\u{1f3a8}": "Add a random artist to the prompt.", "\u2199\ufe0f": "Read generation parameters from prompt or last generation if prompt is empty into user interface.", "\u{1f4c2}": "Open images output directory", + "\u{1f4be}": "Save style", + "\u{1f4cb}": "Apply selected styles to current prompt", "Inpaint a part of image": "Draw a mask over an image, and the script will regenerate the masked area with content according to prompt", "SD upscale": "Upscale image normally, split result into tiles, improve each tile using img2img, merge whole image back", diff --git a/javascript/ui.js b/javascript/ui.js index 56f4216f..9e1bed4c 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -141,7 +141,7 @@ function submit_img2img(){ function ask_for_style_name(_, prompt_text, negative_prompt_text) { name_ = prompt('Style name:') - return name_ === null ? [null, null, null]: [name_, prompt_text, negative_prompt_text] + return [name_, prompt_text, negative_prompt_text] } diff --git a/modules/ui.py b/modules/ui.py index de5ab929..cab8ab11 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -81,6 +81,8 @@ art_symbol = '\U0001f3a8' # 🎨 paste_symbol = '\u2199\ufe0f' # ↙ folder_symbol = '\U0001f4c2' # 📂 refresh_symbol = '\U0001f504' # 🔄 +save_style_symbol = '\U0001f4be' # 💾 +apply_style_symbol = '\U0001f4cb' # 📋 def plaintext_to_html(text): @@ -322,7 +324,7 @@ def visit(x, func, path=""): def add_style(name: str, prompt: str, negative_prompt: str): if name is None: - return [gr_show(), gr_show()] + return [gr_show() for x in range(4)] style = modules.styles.PromptStyle(name, prompt, negative_prompt) shared.prompt_styles.styles[style.name] = style @@ -447,7 +449,7 @@ def create_toprow(is_img2img): id_part = "img2img" if is_img2img else "txt2img" with gr.Row(elem_id="toprow"): - with gr.Column(scale=4): + with gr.Column(scale=6): with gr.Row(): with gr.Column(scale=80): with gr.Row(): @@ -455,27 +457,30 @@ def create_toprow(is_img2img): placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)" ) - with gr.Column(scale=1, elem_id="roll_col"): - roll = gr.Button(value=art_symbol, elem_id="roll", visible=len(shared.artist_db.artists) > 0) - paste = gr.Button(value=paste_symbol, elem_id="paste") - token_counter = gr.HTML(value="", elem_id=f"{id_part}_token_counter") - token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button") - - with gr.Column(scale=10, elem_id="style_pos_col"): - prompt_style = gr.Dropdown(label="Style 1", elem_id=f"{id_part}_style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())), visible=len(shared.prompt_styles.styles) > 1) - with gr.Row(): - with gr.Column(scale=8): + with gr.Column(scale=80): with gr.Row(): negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2, placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)" ) - with gr.Column(scale=1, elem_id="roll_col"): - sh = gr.Button(elem_id="sh", visible=True) + with gr.Column(scale=1, elem_id="roll_col"): + roll = gr.Button(value=art_symbol, elem_id="roll", visible=len(shared.artist_db.artists) > 0) + paste = gr.Button(value=paste_symbol, elem_id="paste") + save_style = gr.Button(value=save_style_symbol, elem_id="style_create") + prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply") - with gr.Column(scale=1, elem_id="style_neg_col"): - prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())), visible=len(shared.prompt_styles.styles) > 1) + token_counter = gr.HTML(value="", elem_id=f"{id_part}_token_counter") + token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button") + + button_interrogate = None + button_deepbooru = None + if is_img2img: + with gr.Column(scale=1, elem_id="interrogate_col"): + button_interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate") + + if cmd_opts.deepdanbooru: + button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru") with gr.Column(scale=1): with gr.Row(): @@ -495,20 +500,14 @@ def create_toprow(is_img2img): outputs=[], ) - with gr.Row(scale=1): - if is_img2img: - interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate") - if cmd_opts.deepdanbooru: - deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru") - else: - deepbooru = None - else: - interrogate = None - deepbooru = None - prompt_style_apply = gr.Button('Apply style', elem_id="style_apply") - save_style = gr.Button('Create style', elem_id="style_create") + with gr.Row(): + with gr.Column(scale=1, elem_id="style_pos_col"): + prompt_style = gr.Dropdown(label="Style 1", elem_id=f"{id_part}_style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys()))) + + with gr.Column(scale=1, elem_id="style_neg_col"): + prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys()))) - return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, interrogate, deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button + return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button def setup_progressbar(progressbar, preview, id_part, textinfo=None): diff --git a/style.css b/style.css index c27e53f8..b534f950 100644 --- a/style.css +++ b/style.css @@ -115,7 +115,7 @@ padding: 0.4em 0; } -#roll, #paste{ +#roll, #paste, #style_create, #style_apply{ min-width: 2em; min-height: 2em; max-width: 2em; @@ -126,14 +126,14 @@ margin: 0.1em 0; } -#style_apply, #style_create, #interrogate{ - margin: 0.75em 0.25em 0.25em 0.25em; - min-width: 5em; +#interrogate_col{ + min-width: 0 !important; + max-width: 8em !important; } - -#style_apply, #style_create, #deepbooru{ - margin: 0.75em 0.25em 0.25em 0.25em; - min-width: 5em; +#interrogate, #deepbooru{ + margin: 0em 0.25em 0.9em 0.25em; + min-width: 8em; + max-width: 8em; } #style_pos_col, #style_neg_col{ -- cgit v1.2.3 From 20a1f68c752f8e37492ea00911c97bfc572a6e67 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 15 Oct 2022 15:44:46 +0300 Subject: fix gadio issue with sending files between tabs --- modules/ui.py | 8 ++++++++ 1 file changed, 8 insertions(+) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index cab8ab11..c9b53247 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -91,6 +91,14 @@ def plaintext_to_html(text): def image_from_url_text(filedata): + if type(filedata) == dict and filedata["is_file"]: + filename = filedata["name"] + tempdir = os.path.normpath(tempfile.gettempdir()) + normfn = os.path.normpath(filename) + assert normfn.startswith(tempdir), 'trying to open image file not in temporary directory' + + return Image.open(filename) + if type(filedata) == list: if len(filedata) == 0: return None -- cgit v1.2.3 From 37d7ffb415cd8c69b3c0bb5f61844dde0b169f78 Mon Sep 17 00:00:00 2001 From: MalumaDev Date: Sat, 15 Oct 2022 15:59:37 +0200 Subject: fix to tokens lenght, addend embs generator, add new features to edit the embedding before the generation using text --- modules/aesthetic_clip.py | 78 ++++++++++++++++++++++++ modules/processing.py | 148 +++++++++++++++++++++++++++++++--------------- modules/sd_hijack.py | 111 ++++++++++++++++++++++------------ modules/shared.py | 4 ++ modules/txt2img.py | 10 +++- modules/ui.py | 47 ++++++++++++--- 6 files changed, 302 insertions(+), 96 deletions(-) create mode 100644 modules/aesthetic_clip.py (limited to 'modules/ui.py') diff --git a/modules/aesthetic_clip.py b/modules/aesthetic_clip.py new file mode 100644 index 00000000..f15cfd47 --- /dev/null +++ b/modules/aesthetic_clip.py @@ -0,0 +1,78 @@ +import itertools +import os +from pathlib import Path +import html +import gc + +import gradio as gr +import torch +from PIL import Image +from modules import shared +from modules.shared import device, aesthetic_embeddings +from transformers import CLIPModel, CLIPProcessor + +from tqdm.auto import tqdm + + +def get_all_images_in_folder(folder): + return [os.path.join(folder, f) for f in os.listdir(folder) if + os.path.isfile(os.path.join(folder, f)) and check_is_valid_image_file(f)] + + +def check_is_valid_image_file(filename): + return filename.lower().endswith(('.png', '.jpg', '.jpeg')) + + +def batched(dataset, total, n=1): + for ndx in range(0, total, n): + yield [dataset.__getitem__(i) for i in range(ndx, min(ndx + n, total))] + + +def iter_to_batched(iterable, n=1): + it = iter(iterable) + while True: + chunk = tuple(itertools.islice(it, n)) + if not chunk: + return + yield chunk + + +def generate_imgs_embd(name, folder, batch_size): + # clipModel = CLIPModel.from_pretrained( + # shared.sd_model.cond_stage_model.clipModel.name_or_path + # ) + model = CLIPModel.from_pretrained(shared.sd_model.cond_stage_model.clipModel.name_or_path).to(device) + processor = CLIPProcessor.from_pretrained(shared.sd_model.cond_stage_model.clipModel.name_or_path) + + with torch.no_grad(): + embs = [] + for paths in tqdm(iter_to_batched(get_all_images_in_folder(folder), batch_size), + desc=f"Generating embeddings for {name}"): + if shared.state.interrupted: + break + inputs = processor(images=[Image.open(path) for path in paths], return_tensors="pt").to(device) + outputs = model.get_image_features(**inputs).cpu() + embs.append(torch.clone(outputs)) + inputs.to("cpu") + del inputs, outputs + + embs = torch.cat(embs, dim=0).mean(dim=0, keepdim=True) + + # The generated embedding will be located here + path = str(Path(shared.cmd_opts.aesthetic_embeddings_dir) / f"{name}.pt") + torch.save(embs, path) + + model = model.cpu() + del model + del processor + del embs + gc.collect() + torch.cuda.empty_cache() + res = f""" + Done generating embedding for {name}! + Hypernetwork saved to {html.escape(path)} + """ + shared.update_aesthetic_embeddings() + return gr.Dropdown(sorted(aesthetic_embeddings.keys()), label="Imgs embedding", + value=sorted(aesthetic_embeddings.keys())[0] if len( + aesthetic_embeddings) > 0 else None), res, "" diff --git a/modules/processing.py b/modules/processing.py index 9a033759..ab68d63a 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -20,7 +20,6 @@ import modules.images as images import modules.styles import logging - # some of those options should not be changed at all because they would break the model, so I removed them from options. opt_C = 4 opt_f = 8 @@ -52,8 +51,13 @@ def get_correct_sampler(p): elif isinstance(p, modules.processing.StableDiffusionProcessingImg2Img): return sd_samplers.samplers_for_img2img + class StableDiffusionProcessing: - def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt="", styles=None, seed=-1, subseed=-1, subseed_strength=0, seed_resize_from_h=-1, seed_resize_from_w=-1, seed_enable_extras=True, sampler_index=0, batch_size=1, n_iter=1, steps=50, cfg_scale=7.0, width=512, height=512, restore_faces=False, tiling=False, do_not_save_samples=False, do_not_save_grid=False, extra_generation_params=None, overlay_images=None, negative_prompt=None, eta=None): + def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt="", styles=None, seed=-1, + subseed=-1, subseed_strength=0, seed_resize_from_h=-1, seed_resize_from_w=-1, seed_enable_extras=True, + sampler_index=0, batch_size=1, n_iter=1, steps=50, cfg_scale=7.0, width=512, height=512, + restore_faces=False, tiling=False, do_not_save_samples=False, do_not_save_grid=False, + extra_generation_params=None, overlay_images=None, negative_prompt=None, eta=None): self.sd_model = sd_model self.outpath_samples: str = outpath_samples self.outpath_grids: str = outpath_grids @@ -104,7 +108,8 @@ class StableDiffusionProcessing: class Processed: - def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1, info="", subseed=None, all_prompts=None, all_seeds=None, all_subseeds=None, index_of_first_image=0, infotexts=None): + def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1, info="", subseed=None, all_prompts=None, + all_seeds=None, all_subseeds=None, index_of_first_image=0, infotexts=None): self.images = images_list self.prompt = p.prompt self.negative_prompt = p.negative_prompt @@ -141,7 +146,8 @@ class Processed: self.prompt = self.prompt if type(self.prompt) != list else self.prompt[0] self.negative_prompt = self.negative_prompt if type(self.negative_prompt) != list else self.negative_prompt[0] self.seed = int(self.seed if type(self.seed) != list else self.seed[0]) - self.subseed = int(self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1 + self.subseed = int( + self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1 self.all_prompts = all_prompts or [self.prompt] self.all_seeds = all_seeds or [self.seed] @@ -181,39 +187,43 @@ class Processed: return json.dumps(obj) - def infotext(self, p: StableDiffusionProcessing, index): - return create_infotext(p, self.all_prompts, self.all_seeds, self.all_subseeds, comments=[], position_in_batch=index % self.batch_size, iteration=index // self.batch_size) + def infotext(self, p: StableDiffusionProcessing, index): + return create_infotext(p, self.all_prompts, self.all_seeds, self.all_subseeds, comments=[], + position_in_batch=index % self.batch_size, iteration=index // self.batch_size) # from https://discuss.pytorch.org/t/help-regarding-slerp-function-for-generative-model-sampling/32475/3 def slerp(val, low, high): - low_norm = low/torch.norm(low, dim=1, keepdim=True) - high_norm = high/torch.norm(high, dim=1, keepdim=True) - dot = (low_norm*high_norm).sum(1) + low_norm = low / torch.norm(low, dim=1, keepdim=True) + high_norm = high / torch.norm(high, dim=1, keepdim=True) + dot = (low_norm * high_norm).sum(1) if dot.mean() > 0.9995: return low * val + high * (1 - val) omega = torch.acos(dot) so = torch.sin(omega) - res = (torch.sin((1.0-val)*omega)/so).unsqueeze(1)*low + (torch.sin(val*omega)/so).unsqueeze(1) * high + res = (torch.sin((1.0 - val) * omega) / so).unsqueeze(1) * low + (torch.sin(val * omega) / so).unsqueeze(1) * high return res -def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, seed_resize_from_h=0, seed_resize_from_w=0, p=None): +def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, seed_resize_from_h=0, seed_resize_from_w=0, + p=None): xs = [] # if we have multiple seeds, this means we are working with batch size>1; this then # enables the generation of additional tensors with noise that the sampler will use during its processing. # Using those pre-generated tensors instead of simple torch.randn allows a batch with seeds [100, 101] to # produce the same images as with two batches [100], [101]. - if p is not None and p.sampler is not None and (len(seeds) > 1 and opts.enable_batch_seeds or opts.eta_noise_seed_delta > 0): + if p is not None and p.sampler is not None and ( + len(seeds) > 1 and opts.enable_batch_seeds or opts.eta_noise_seed_delta > 0): sampler_noises = [[] for _ in range(p.sampler.number_of_needed_noises(p))] else: sampler_noises = None for i, seed in enumerate(seeds): - noise_shape = shape if seed_resize_from_h <= 0 or seed_resize_from_w <= 0 else (shape[0], seed_resize_from_h//8, seed_resize_from_w//8) + noise_shape = shape if seed_resize_from_h <= 0 or seed_resize_from_w <= 0 else ( + shape[0], seed_resize_from_h // 8, seed_resize_from_w // 8) subnoise = None if subseeds is not None: @@ -241,7 +251,7 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see dx = max(-dx, 0) dy = max(-dy, 0) - x[:, ty:ty+h, tx:tx+w] = noise[:, dy:dy+h, dx:dx+w] + x[:, ty:ty + h, tx:tx + w] = noise[:, dy:dy + h, dx:dx + w] noise = x if sampler_noises is not None: @@ -293,14 +303,20 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration "Seed": all_seeds[index], "Face restoration": (opts.face_restoration_model if p.restore_faces else None), "Size": f"{p.width}x{p.height}", - "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash), - "Model": (None if not opts.add_model_name_to_info or not shared.sd_model.sd_checkpoint_info.model_name else shared.sd_model.sd_checkpoint_info.model_name.replace(',', '').replace(':', '')), - "Hypernet": (None if shared.loaded_hypernetwork is None else shared.loaded_hypernetwork.name.replace(',', '').replace(':', '')), + "Model hash": getattr(p, 'sd_model_hash', + None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash), + "Model": ( + None if not opts.add_model_name_to_info or not shared.sd_model.sd_checkpoint_info.model_name else shared.sd_model.sd_checkpoint_info.model_name.replace( + ',', '').replace(':', '')), + "Hypernet": ( + None if shared.loaded_hypernetwork is None else shared.loaded_hypernetwork.name.replace(',', '').replace( + ':', '')), "Batch size": (None if p.batch_size < 2 else p.batch_size), "Batch pos": (None if p.batch_size < 2 else position_in_batch), "Variation seed": (None if p.subseed_strength == 0 else all_subseeds[index]), "Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength), - "Seed resize from": (None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"), + "Seed resize from": ( + None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"), "Denoising strength": getattr(p, 'denoising_strength', None), "Eta": (None if p.sampler is None or p.sampler.eta == p.sampler.default_eta else p.sampler.eta), "Clip skip": None if clip_skip <= 1 else clip_skip, @@ -309,7 +325,8 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration generation_params.update(p.extra_generation_params) - generation_params_text = ", ".join([k if k == v else f'{k}: {v}' for k, v in generation_params.items() if v is not None]) + generation_params_text = ", ".join( + [k if k == v else f'{k}: {v}' for k, v in generation_params.items() if v is not None]) negative_prompt_text = "\nNegative prompt: " + p.negative_prompt if p.negative_prompt else "" @@ -317,7 +334,9 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, - aesthetic_imgs=None,aesthetic_slerp=False) -> Processed: + aesthetic_imgs=None, aesthetic_slerp=False, aesthetic_imgs_text="", + aesthetic_slerp_angle=0.15, + aesthetic_text_negative=False) -> Processed: """this is the main loop that both txt2img and img2img use; it calls func_init once inside all the scopes and func_sample once per batch""" aesthetic_lr = float(aesthetic_lr) @@ -385,7 +404,7 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh for n in range(p.n_iter): if state.skipped: state.skipped = False - + if state.interrupted: break @@ -396,16 +415,19 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh if (len(prompts) == 0): break - #uc = p.sd_model.get_learned_conditioning(len(prompts) * [p.negative_prompt]) - #c = p.sd_model.get_learned_conditioning(prompts) + # uc = p.sd_model.get_learned_conditioning(len(prompts) * [p.negative_prompt]) + # c = p.sd_model.get_learned_conditioning(prompts) with devices.autocast(): if hasattr(shared.sd_model.cond_stage_model, "set_aesthetic_params"): - shared.sd_model.cond_stage_model.set_aesthetic_params(0, 0, 0) + shared.sd_model.cond_stage_model.set_aesthetic_params() uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], p.steps) if hasattr(shared.sd_model.cond_stage_model, "set_aesthetic_params"): shared.sd_model.cond_stage_model.set_aesthetic_params(aesthetic_lr, aesthetic_weight, - aesthetic_steps, aesthetic_imgs,aesthetic_slerp) + aesthetic_steps, aesthetic_imgs, + aesthetic_slerp, aesthetic_imgs_text, + aesthetic_slerp_angle, + aesthetic_text_negative) c = prompt_parser.get_multicond_learned_conditioning(shared.sd_model, prompts, p.steps) if len(model_hijack.comments) > 0: @@ -413,13 +435,13 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh comments[comment] = 1 if p.n_iter > 1: - shared.state.job = f"Batch {n+1} out of {p.n_iter}" + shared.state.job = f"Batch {n + 1} out of {p.n_iter}" with devices.autocast(): - samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength) + samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, + subseed_strength=p.subseed_strength) if state.interrupted or state.skipped: - # if we are interrupted, sample returns just noise # use the image collected previously in sampler loop samples_ddim = shared.state.current_latent @@ -445,7 +467,9 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh if p.restore_faces: if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration: - images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-face-restoration") + images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", seeds[i], prompts[i], + opts.samples_format, info=infotext(n, i), p=p, + suffix="-before-face-restoration") devices.torch_gc() @@ -456,7 +480,8 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh if p.color_corrections is not None and i < len(p.color_corrections): if opts.save and not p.do_not_save_samples and opts.save_images_before_color_correction: - images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-color-correction") + images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, + info=infotext(n, i), p=p, suffix="-before-color-correction") image = apply_color_correction(p.color_corrections[i], image) if p.overlay_images is not None and i < len(p.overlay_images): @@ -474,7 +499,8 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh image = image.convert('RGB') if opts.samples_save and not p.do_not_save_samples: - images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p) + images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, + info=infotext(n, i), p=p) text = infotext(n, i) infotexts.append(text) @@ -482,7 +508,7 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh image.info["parameters"] = text output_images.append(image) - del x_samples_ddim + del x_samples_ddim devices.torch_gc() @@ -504,10 +530,13 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh index_of_first_image = 1 if opts.grid_save: - images.save_image(grid, p.outpath_grids, "grid", all_seeds[0], all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True) + images.save_image(grid, p.outpath_grids, "grid", all_seeds[0], all_prompts[0], opts.grid_format, + info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True) devices.torch_gc() - return Processed(p, output_images, all_seeds[0], infotext() + "".join(["\n\n" + x for x in comments]), subseed=all_subseeds[0], all_prompts=all_prompts, all_seeds=all_seeds, all_subseeds=all_subseeds, index_of_first_image=index_of_first_image, infotexts=infotexts) + return Processed(p, output_images, all_seeds[0], infotext() + "".join(["\n\n" + x for x in comments]), + subseed=all_subseeds[0], all_prompts=all_prompts, all_seeds=all_seeds, all_subseeds=all_subseeds, + index_of_first_image=index_of_first_image, infotexts=infotexts) class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): @@ -543,25 +572,34 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model) if not self.enable_hr: - x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) + x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, + subseeds=subseeds, subseed_strength=self.subseed_strength, + seed_resize_from_h=self.seed_resize_from_h, + seed_resize_from_w=self.seed_resize_from_w, p=self) samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning) return samples - x = create_random_tensors([opt_C, self.firstphase_height // opt_f, self.firstphase_width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) + x = create_random_tensors([opt_C, self.firstphase_height // opt_f, self.firstphase_width // opt_f], seeds=seeds, + subseeds=subseeds, subseed_strength=self.subseed_strength, + seed_resize_from_h=self.seed_resize_from_h, + seed_resize_from_w=self.seed_resize_from_w, p=self) samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning) truncate_x = (self.firstphase_width - self.firstphase_width_truncated) // opt_f truncate_y = (self.firstphase_height - self.firstphase_height_truncated) // opt_f - samples = samples[:, :, truncate_y//2:samples.shape[2]-truncate_y//2, truncate_x//2:samples.shape[3]-truncate_x//2] + samples = samples[:, :, truncate_y // 2:samples.shape[2] - truncate_y // 2, + truncate_x // 2:samples.shape[3] - truncate_x // 2] if self.scale_latent: - samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear") + samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), + mode="bilinear") else: decoded_samples = decode_first_stage(self.sd_model, samples) if opts.upscaler_for_img2img is None or opts.upscaler_for_img2img == "None": - decoded_samples = torch.nn.functional.interpolate(decoded_samples, size=(self.height, self.width), mode="bilinear") + decoded_samples = torch.nn.functional.interpolate(decoded_samples, size=(self.height, self.width), + mode="bilinear") else: lowres_samples = torch.clamp((decoded_samples + 1.0) / 2.0, min=0.0, max=1.0) @@ -585,13 +623,16 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model) - noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) + noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, + subseed_strength=subseed_strength, seed_resize_from_h=self.seed_resize_from_h, + seed_resize_from_w=self.seed_resize_from_w, p=self) # GC now before running the next img2img to prevent running out of memory x = None devices.torch_gc() - samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.steps) + samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, + steps=self.steps) return samples @@ -599,7 +640,9 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): sampler = None - def __init__(self, init_images=None, resize_mode=0, denoising_strength=0.75, mask=None, mask_blur=4, inpainting_fill=0, inpaint_full_res=True, inpaint_full_res_padding=0, inpainting_mask_invert=0, **kwargs): + def __init__(self, init_images=None, resize_mode=0, denoising_strength=0.75, mask=None, mask_blur=4, + inpainting_fill=0, inpaint_full_res=True, inpaint_full_res_padding=0, inpainting_mask_invert=0, + **kwargs): super().__init__(**kwargs) self.init_images = init_images @@ -607,7 +650,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): self.denoising_strength: float = denoising_strength self.init_latent = None self.image_mask = mask - #self.image_unblurred_mask = None + # self.image_unblurred_mask = None self.latent_mask = None self.mask_for_overlay = None self.mask_blur = mask_blur @@ -619,7 +662,8 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): self.nmask = None def init(self, all_prompts, all_seeds, all_subseeds): - self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers_for_img2img, self.sampler_index, self.sd_model) + self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers_for_img2img, self.sampler_index, + self.sd_model) crop_region = None if self.image_mask is not None: @@ -628,7 +672,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): if self.inpainting_mask_invert: self.image_mask = ImageOps.invert(self.image_mask) - #self.image_unblurred_mask = self.image_mask + # self.image_unblurred_mask = self.image_mask if self.mask_blur > 0: self.image_mask = self.image_mask.filter(ImageFilter.GaussianBlur(self.mask_blur)) @@ -642,7 +686,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): mask = mask.crop(crop_region) self.image_mask = images.resize_image(2, mask, self.width, self.height) - self.paste_to = (x1, y1, x2-x1, y2-y1) + self.paste_to = (x1, y1, x2 - x1, y2 - y1) else: self.image_mask = images.resize_image(self.resize_mode, self.image_mask, self.width, self.height) np_mask = np.array(self.image_mask) @@ -665,7 +709,8 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): if self.image_mask is not None: image_masked = Image.new('RGBa', (image.width, image.height)) - image_masked.paste(image.convert("RGBA").convert("RGBa"), mask=ImageOps.invert(self.mask_for_overlay.convert('L'))) + image_masked.paste(image.convert("RGBA").convert("RGBa"), + mask=ImageOps.invert(self.mask_for_overlay.convert('L'))) self.overlay_images.append(image_masked.convert('RGBA')) @@ -714,12 +759,17 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): # this needs to be fixed to be done in sample() using actual seeds for batches if self.inpainting_fill == 2: - self.init_latent = self.init_latent * self.mask + create_random_tensors(self.init_latent.shape[1:], all_seeds[0:self.init_latent.shape[0]]) * self.nmask + self.init_latent = self.init_latent * self.mask + create_random_tensors(self.init_latent.shape[1:], + all_seeds[ + 0:self.init_latent.shape[ + 0]]) * self.nmask elif self.inpainting_fill == 3: self.init_latent = self.init_latent * self.mask def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength): - x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) + x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, subseeds=subseeds, + subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, + seed_resize_from_w=self.seed_resize_from_w, p=self) samples = self.sampler.sample_img2img(self, self.init_latent, x, conditioning, unconditional_conditioning) diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index 6d5196fe..192883b2 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -14,7 +14,8 @@ from modules.sd_hijack_optimizations import invokeAI_mps_available import ldm.modules.attention import ldm.modules.diffusionmodules.model -from transformers import CLIPVisionModel, CLIPModel +from tqdm import trange +from transformers import CLIPVisionModel, CLIPModel, CLIPTokenizer import torch.optim as optim import copy @@ -22,21 +23,25 @@ attention_CrossAttention_forward = ldm.modules.attention.CrossAttention.forward diffusionmodules_model_nonlinearity = ldm.modules.diffusionmodules.model.nonlinearity diffusionmodules_model_AttnBlock_forward = ldm.modules.diffusionmodules.model.AttnBlock.forward + def apply_optimizations(): undo_optimizations() ldm.modules.diffusionmodules.model.nonlinearity = silu - if cmd_opts.force_enable_xformers or (cmd_opts.xformers and shared.xformers_available and torch.version.cuda and (6, 0) <= torch.cuda.get_device_capability(shared.device) <= (8, 6)): + if cmd_opts.force_enable_xformers or (cmd_opts.xformers and shared.xformers_available and torch.version.cuda and ( + 6, 0) <= torch.cuda.get_device_capability(shared.device) <= (8, 6)): print("Applying xformers cross attention optimization.") ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward elif cmd_opts.opt_split_attention_v1: print("Applying v1 cross attention optimization.") ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1 - elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention_invokeai or not torch.cuda.is_available()): + elif not cmd_opts.disable_opt_split_attention and ( + cmd_opts.opt_split_attention_invokeai or not torch.cuda.is_available()): if not invokeAI_mps_available and shared.device.type == 'mps': - print("The InvokeAI cross attention optimization for MPS requires the psutil package which is not installed.") + print( + "The InvokeAI cross attention optimization for MPS requires the psutil package which is not installed.") print("Applying v1 cross attention optimization.") ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1 else: @@ -112,14 +117,16 @@ class StableDiffusionModelHijack: _, remade_batch_tokens, _, _, _, token_count = self.clip.process_text([text]) return remade_batch_tokens[0], token_count, get_target_prompt_token_count(token_count) + def slerp(low, high, val): - low_norm = low/torch.norm(low, dim=1, keepdim=True) - high_norm = high/torch.norm(high, dim=1, keepdim=True) - omega = torch.acos((low_norm*high_norm).sum(1)) + low_norm = low / torch.norm(low, dim=1, keepdim=True) + high_norm = high / torch.norm(high, dim=1, keepdim=True) + omega = torch.acos((low_norm * high_norm).sum(1)) so = torch.sin(omega) - res = (torch.sin((1.0-val)*omega)/so).unsqueeze(1)*low + (torch.sin(val*omega)/so).unsqueeze(1) * high + res = (torch.sin((1.0 - val) * omega) / so).unsqueeze(1) * low + (torch.sin(val * omega) / so).unsqueeze(1) * high return res + class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): def __init__(self, wrapped, hijack): super().__init__() @@ -128,6 +135,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): self.wrapped.transformer.name_or_path ) del self.clipModel.vision_model + self.tokenizer = CLIPTokenizer.from_pretrained(self.wrapped.transformer.name_or_path) self.hijack: StableDiffusionModelHijack = hijack self.tokenizer = wrapped.tokenizer # self.vision = CLIPVisionModel.from_pretrained(self.wrapped.transformer.name_or_path).eval() @@ -139,7 +147,8 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): self.comma_token = [v for k, v in self.tokenizer.get_vocab().items() if k == ','][0] - tokens_with_parens = [(k, v) for k, v in self.tokenizer.get_vocab().items() if '(' in k or ')' in k or '[' in k or ']' in k] + tokens_with_parens = [(k, v) for k, v in self.tokenizer.get_vocab().items() if + '(' in k or ')' in k or '[' in k or ']' in k] for text, ident in tokens_with_parens: mult = 1.0 for c in text: @@ -155,8 +164,13 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): if mult != 1.0: self.token_mults[ident] = mult - def set_aesthetic_params(self, aesthetic_lr, aesthetic_weight, aesthetic_steps, image_embs_name=None, - aesthetic_slerp=True): + def set_aesthetic_params(self, aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, image_embs_name=None, + aesthetic_slerp=True, aesthetic_imgs_text="", + aesthetic_slerp_angle=0.15, + aesthetic_text_negative=False): + self.aesthetic_imgs_text = aesthetic_imgs_text + self.aesthetic_slerp_angle = aesthetic_slerp_angle + self.aesthetic_text_negative = aesthetic_text_negative self.slerp = aesthetic_slerp self.aesthetic_lr = aesthetic_lr self.aesthetic_weight = aesthetic_weight @@ -180,7 +194,8 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): else: parsed = [[line, 1.0]] - tokenized = self.wrapped.tokenizer([text for text, _ in parsed], truncation=False, add_special_tokens=False)["input_ids"] + tokenized = self.wrapped.tokenizer([text for text, _ in parsed], truncation=False, add_special_tokens=False)[ + "input_ids"] fixes = [] remade_tokens = [] @@ -196,18 +211,20 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): if token == self.comma_token: last_comma = len(remade_tokens) - elif opts.comma_padding_backtrack != 0 and max(len(remade_tokens), 1) % 75 == 0 and last_comma != -1 and len(remade_tokens) - last_comma <= opts.comma_padding_backtrack: + elif opts.comma_padding_backtrack != 0 and max(len(remade_tokens), + 1) % 75 == 0 and last_comma != -1 and len( + remade_tokens) - last_comma <= opts.comma_padding_backtrack: last_comma += 1 reloc_tokens = remade_tokens[last_comma:] reloc_mults = multipliers[last_comma:] remade_tokens = remade_tokens[:last_comma] length = len(remade_tokens) - + rem = int(math.ceil(length / 75)) * 75 - length remade_tokens += [id_end] * rem + reloc_tokens multipliers = multipliers[:last_comma] + [1.0] * rem + reloc_mults - + if embedding is None: remade_tokens.append(token) multipliers.append(weight) @@ -248,7 +265,8 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): if line in cache: remade_tokens, fixes, multipliers = cache[line] else: - remade_tokens, fixes, multipliers, current_token_count = self.tokenize_line(line, used_custom_terms, hijack_comments) + remade_tokens, fixes, multipliers, current_token_count = self.tokenize_line(line, used_custom_terms, + hijack_comments) token_count = max(current_token_count, token_count) cache[line] = (remade_tokens, fixes, multipliers) @@ -259,7 +277,6 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): return batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count - def process_text_old(self, text): id_start = self.wrapped.tokenizer.bos_token_id id_end = self.wrapped.tokenizer.eos_token_id @@ -289,7 +306,8 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): while i < len(tokens): token = tokens[i] - embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i) + embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, + i) mult_change = self.token_mults.get(token) if opts.enable_emphasis else None if mult_change is not None: @@ -312,11 +330,12 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): ovf = remade_tokens[maxlen - 2:] overflowing_words = [vocab.get(int(x), "") for x in ovf] overflowing_text = self.wrapped.tokenizer.convert_tokens_to_string(''.join(overflowing_words)) - hijack_comments.append(f"Warning: too many input tokens; some ({len(overflowing_words)}) have been truncated:\n{overflowing_text}\n") + hijack_comments.append( + f"Warning: too many input tokens; some ({len(overflowing_words)}) have been truncated:\n{overflowing_text}\n") token_count = len(remade_tokens) remade_tokens = remade_tokens + [id_end] * (maxlen - 2 - len(remade_tokens)) - remade_tokens = [id_start] + remade_tokens[0:maxlen-2] + [id_end] + remade_tokens = [id_start] + remade_tokens[0:maxlen - 2] + [id_end] cache[tuple_tokens] = (remade_tokens, fixes, multipliers) multipliers = multipliers + [1.0] * (maxlen - 2 - len(multipliers)) @@ -326,23 +345,26 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): hijack_fixes.append(fixes) batch_multipliers.append(multipliers) return batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count - + def forward(self, text): use_old = opts.use_old_emphasis_implementation if use_old: - batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text_old(text) + batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text_old( + text) else: - batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text(text) + batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text( + text) self.hijack.comments += hijack_comments if len(used_custom_terms) > 0: - self.hijack.comments.append("Used embeddings: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms])) - + self.hijack.comments.append( + "Used embeddings: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms])) + if use_old: self.hijack.fixes = hijack_fixes return self.process_tokens(remade_batch_tokens, batch_multipliers) - + z = None i = 0 while max(map(len, remade_batch_tokens)) != 0: @@ -356,7 +378,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): if fix[0] == i: fixes.append(fix[1]) self.hijack.fixes.append(fixes) - + tokens = [] multipliers = [] for j in range(len(remade_batch_tokens)): @@ -378,19 +400,30 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): remade_batch_tokens] tokens = torch.asarray(remade_batch_tokens).to(device) + + model = copy.deepcopy(self.clipModel).to(device) + model.requires_grad_(True) + if self.aesthetic_imgs_text is not None and len(self.aesthetic_imgs_text) > 0: + text_embs_2 = model.get_text_features( + **self.tokenizer([self.aesthetic_imgs_text], padding=True, return_tensors="pt").to(device)) + if self.aesthetic_text_negative: + text_embs_2 = self.image_embs - text_embs_2 + text_embs_2 /= text_embs_2.norm(dim=-1, keepdim=True) + img_embs = slerp(self.image_embs, text_embs_2, self.aesthetic_slerp_angle) + else: + img_embs = self.image_embs + with torch.enable_grad(): - model = copy.deepcopy(self.clipModel).to(device) - model.requires_grad_(True) # We optimize the model to maximize the similarity optimizer = optim.Adam( model.text_model.parameters(), lr=self.aesthetic_lr ) - for i in range(self.aesthetic_steps): + for i in trange(self.aesthetic_steps, desc="Aesthetic optimization"): text_embs = model.get_text_features(input_ids=tokens) text_embs = text_embs / text_embs.norm(dim=-1, keepdim=True) - sim = text_embs @ self.image_embs.T + sim = text_embs @ img_embs.T loss = -sim optimizer.zero_grad() loss.mean().backward() @@ -405,6 +438,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): model.cpu() del model + zn = torch.concat([zn for i in range(z.shape[1] // 77)], 1) if self.slerp: z = slerp(z, zn, self.aesthetic_weight) else: @@ -413,15 +447,16 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): remade_batch_tokens = rem_tokens batch_multipliers = rem_multipliers i += 1 - + return z - - + def process_tokens(self, remade_batch_tokens, batch_multipliers): if not opts.use_old_emphasis_implementation: - remade_batch_tokens = [[self.wrapped.tokenizer.bos_token_id] + x[:75] + [self.wrapped.tokenizer.eos_token_id] for x in remade_batch_tokens] + remade_batch_tokens = [ + [self.wrapped.tokenizer.bos_token_id] + x[:75] + [self.wrapped.tokenizer.eos_token_id] for x in + remade_batch_tokens] batch_multipliers = [[1.0] + x[:75] + [1.0] for x in batch_multipliers] - + tokens = torch.asarray(remade_batch_tokens).to(device) outputs = self.wrapped.transformer(input_ids=tokens, output_hidden_states=-opts.CLIP_stop_at_last_layers) @@ -461,8 +496,8 @@ class EmbeddingsWithFixes(torch.nn.Module): for fixes, tensor in zip(batch_fixes, inputs_embeds): for offset, embedding in fixes: emb = embedding.vec - emb_len = min(tensor.shape[0]-offset-1, emb.shape[0]) - tensor = torch.cat([tensor[0:offset+1], emb[0:emb_len], tensor[offset+1+emb_len:]]) + emb_len = min(tensor.shape[0] - offset - 1, emb.shape[0]) + tensor = torch.cat([tensor[0:offset + 1], emb[0:emb_len], tensor[offset + 1 + emb_len:]]) vecs.append(tensor) diff --git a/modules/shared.py b/modules/shared.py index cf13a10d..7cd608ca 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -95,6 +95,10 @@ loaded_hypernetwork = None aesthetic_embeddings = {f.replace(".pt",""): os.path.join(cmd_opts.aesthetic_embeddings_dir, f) for f in os.listdir(cmd_opts.aesthetic_embeddings_dir) if f.endswith(".pt")} +def update_aesthetic_embeddings(): + global aesthetic_embeddings + aesthetic_embeddings = {f.replace(".pt",""): os.path.join(cmd_opts.aesthetic_embeddings_dir, f) for f in + os.listdir(cmd_opts.aesthetic_embeddings_dir) if f.endswith(".pt")} def reload_hypernetworks(): global hypernetworks diff --git a/modules/txt2img.py b/modules/txt2img.py index 78342024..eedcdfe0 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -13,7 +13,11 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, aesthetic_imgs=None, - aesthetic_slerp=False, *args): + aesthetic_slerp=False, + aesthetic_imgs_text="", + aesthetic_slerp_angle=0.15, + aesthetic_text_negative=False, + *args): p = StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples, @@ -47,7 +51,9 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: processed = modules.scripts.scripts_txt2img.run(p, *args) if processed is None: - processed = process_images(p, aesthetic_lr, aesthetic_weight, aesthetic_steps, aesthetic_imgs, aesthetic_slerp) + processed = process_images(p, aesthetic_lr, aesthetic_weight, aesthetic_steps, aesthetic_imgs, aesthetic_slerp,aesthetic_imgs_text, + aesthetic_slerp_angle, + aesthetic_text_negative) shared.total_tqdm.clear() diff --git a/modules/ui.py b/modules/ui.py index d961d126..e98e2113 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -41,6 +41,7 @@ from modules import prompt_parser from modules.images import save_image import modules.textual_inversion.ui import modules.hypernetworks.ui +import modules.aesthetic_clip # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() @@ -449,7 +450,7 @@ def create_toprow(is_img2img): with gr.Row(): negative_prompt = gr.Textbox(label="Negative prompt", elem_id="negative_prompt", show_label=False, placeholder="Negative prompt", lines=2) with gr.Column(scale=1, elem_id="roll_col"): - sh = gr.Button(elem_id="sh", visible=True) + sh = gr.Button(elem_id="sh", visible=True) with gr.Column(scale=1, elem_id="style_neg_col"): prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())), visible=len(shared.prompt_styles.styles) > 1) @@ -536,9 +537,13 @@ def create_ui(wrap_gradio_gpu_call): height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) with gr.Group(): - aesthetic_lr = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.005") - aesthetic_weight = gr.Slider(minimum=0, maximum=1, step=0.01, label="Aesthetic weight", value=0.7) - aesthetic_steps = gr.Slider(minimum=0, maximum=50, step=1, label="Aesthetic steps", value=50) + aesthetic_lr = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.0001") + aesthetic_weight = gr.Slider(minimum=0, maximum=1, step=0.01, label="Aesthetic weight", value=0.9) + aesthetic_steps = gr.Slider(minimum=0, maximum=256, step=1, label="Aesthetic steps", value=5) + with gr.Row(): + aesthetic_imgs_text = gr.Textbox(label='Aesthetic text for imgs', placeholder="This text is used to rotate the feature space of the imgs embs", value="") + aesthetic_slerp_angle = gr.Slider(label='Slerp angle',minimum=0, maximum=1, step=0.01, value=0.1) + aesthetic_text_negative = gr.Checkbox(label="Is negative text", value=False) aesthetic_imgs = gr.Dropdown(sorted(aesthetic_embeddings.keys()), label="Imgs embedding", value=sorted(aesthetic_embeddings.keys())[0] if len(aesthetic_embeddings) > 0 else None) aesthetic_slerp = gr.Checkbox(label="Slerp interpolation", value=False) @@ -617,7 +622,10 @@ def create_ui(wrap_gradio_gpu_call): aesthetic_weight, aesthetic_steps, aesthetic_imgs, - aesthetic_slerp + aesthetic_slerp, + aesthetic_imgs_text, + aesthetic_slerp_angle, + aesthetic_text_negative ] + custom_inputs, outputs=[ txt2img_gallery, @@ -721,7 +729,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Row(): inpaint_full_res = gr.Checkbox(label='Inpaint at full resolution', value=False) - inpaint_full_res_padding = gr.Slider(label='Inpaint at full resolution padding, pixels', minimum=0, maximum=256, step=4, value=32) + inpaint_full_res_padding = gr.Slider(label='Inpaint at full resolution padding, pixels', minimum=0, maximum=1024, step=4, value=32) with gr.TabItem('Batch img2img', id='batch'): hidden = '
Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else '' @@ -1071,6 +1079,17 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column(): create_embedding = gr.Button(value="Create embedding", variant='primary') + with gr.Tab(label="Create images embedding"): + new_embedding_name_ae = gr.Textbox(label="Name") + process_src_ae = gr.Textbox(label='Source directory') + batch_ae = gr.Slider(minimum=1, maximum=1024, step=1, label="Batch size", value=256) + with gr.Row(): + with gr.Column(scale=3): + gr.HTML(value="") + + with gr.Column(): + create_embedding_ae = gr.Button(value="Create images embedding", variant='primary') + with gr.Tab(label="Create hypernetwork"): new_hypernetwork_name = gr.Textbox(label="Name") new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) @@ -1139,7 +1158,7 @@ def create_ui(wrap_gradio_gpu_call): fn=modules.textual_inversion.ui.create_embedding, inputs=[ new_embedding_name, - initialization_text, + process_src, nvpt, ], outputs=[ @@ -1149,6 +1168,20 @@ def create_ui(wrap_gradio_gpu_call): ] ) + create_embedding_ae.click( + fn=modules.aesthetic_clip.generate_imgs_embd, + inputs=[ + new_embedding_name_ae, + process_src_ae, + batch_ae + ], + outputs=[ + aesthetic_imgs, + ti_output, + ti_outcome, + ] + ) + create_hypernetwork.click( fn=modules.hypernetworks.ui.create_hypernetwork, inputs=[ -- cgit v1.2.3 From 5fd638f14d75a71a37157ded5d33c716ab9eb8ca Mon Sep 17 00:00:00 2001 From: ruocaled Date: Sat, 15 Oct 2022 02:00:46 -0700 Subject: fix download section layout --- modules/ui.py | 4 ++-- style.css | 7 ------- 2 files changed, 2 insertions(+), 9 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index c9b53247..3206113e 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -619,7 +619,7 @@ def create_ui(wrap_gradio_gpu_call): txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False) txt2img_gallery = gr.Gallery(label='Output', show_label=False, elem_id='txt2img_gallery').style(grid=4) - with gr.Group(): + with gr.Column(): with gr.Row(): save = gr.Button('Save') send_to_img2img = gr.Button('Send to img2img') @@ -834,7 +834,7 @@ def create_ui(wrap_gradio_gpu_call): img2img_preview = gr.Image(elem_id='img2img_preview', visible=False) img2img_gallery = gr.Gallery(label='Output', show_label=False, elem_id='img2img_gallery').style(grid=4) - with gr.Group(): + with gr.Column(): with gr.Row(): save = gr.Button('Save') img2img_send_to_img2img = gr.Button('Send to img2img') diff --git a/style.css b/style.css index b534f950..920c32ab 100644 --- a/style.css +++ b/style.css @@ -237,13 +237,6 @@ fieldset span.text-gray-500, .gr-block.gr-box span.text-gray-500, label.block s margin: 0; } -.gr-panel div.flex-col div.justify-between div{ - position: absolute; - top: -0.1em; - right: 1em; - padding: 0 0.5em; -} - #settings .gr-panel div.flex-col div.justify-between div{ position: relative; z-index: 200; -- cgit v1.2.3 From 4387e4fe6479c08f7bc7e42924c3a1093e3a1872 Mon Sep 17 00:00:00 2001 From: MalumaDev Date: Sat, 15 Oct 2022 18:39:29 +0200 Subject: Update modules/ui.py MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Víctor Gallego --- modules/ui.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index d0696101..5bb961b2 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -599,7 +599,8 @@ def create_ui(wrap_gradio_gpu_call): with gr.Group(): aesthetic_lr = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.0001") aesthetic_weight = gr.Slider(minimum=0, maximum=1, step=0.01, label="Aesthetic weight", value=0.9) - aesthetic_steps = gr.Slider(minimum=0, maximum=256, step=1, label="Aesthetic steps", value=5) + aesthetic_steps = gr.Slider(minimum=0, maximum=50, step=1, label="Aesthetic steps", value=5) + with gr.Row(): aesthetic_imgs_text = gr.Textbox(label='Aesthetic text for imgs', placeholder="This text is used to rotate the feature space of the imgs embs", value="") aesthetic_slerp_angle = gr.Slider(label='Slerp angle',minimum=0, maximum=1, step=0.01, value=0.1) -- cgit v1.2.3 From 0d4f5db235357aeb4c7a8738179ba33aaf5a6b75 Mon Sep 17 00:00:00 2001 From: MalumaDev Date: Sat, 15 Oct 2022 18:40:58 +0200 Subject: Update modules/ui.py MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Víctor Gallego --- modules/ui.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 5bb961b2..25eba548 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -597,7 +597,8 @@ def create_ui(wrap_gradio_gpu_call): height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) with gr.Group(): - aesthetic_lr = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.0001") + aesthetic_lr = gr.Textbox(label='Aesthetic learning rate', placeholder="Aesthetic learning rate", value="0.0001") + aesthetic_weight = gr.Slider(minimum=0, maximum=1, step=0.01, label="Aesthetic weight", value=0.9) aesthetic_steps = gr.Slider(minimum=0, maximum=50, step=1, label="Aesthetic steps", value=5) -- cgit v1.2.3 From ad9bc604a8fadcfebe72be37f66cec51e7e87fb5 Mon Sep 17 00:00:00 2001 From: MalumaDev Date: Sat, 15 Oct 2022 18:41:18 +0200 Subject: Update modules/ui.py MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Víctor Gallego --- modules/ui.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 25eba548..3b28b69c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -607,7 +607,8 @@ def create_ui(wrap_gradio_gpu_call): aesthetic_slerp_angle = gr.Slider(label='Slerp angle',minimum=0, maximum=1, step=0.01, value=0.1) aesthetic_text_negative = gr.Checkbox(label="Is negative text", value=False) - aesthetic_imgs = gr.Dropdown(sorted(aesthetic_embeddings.keys()), label="Imgs embedding", value=sorted(aesthetic_embeddings.keys())[0] if len(aesthetic_embeddings) > 0 else None) + aesthetic_imgs = gr.Dropdown(sorted(aesthetic_embeddings.keys()), label="Aesthetic imgs embedding", value=sorted(aesthetic_embeddings.keys())[0] if len(aesthetic_embeddings) > 0 else None) + aesthetic_slerp = gr.Checkbox(label="Slerp interpolation", value=False) with gr.Row(): -- cgit v1.2.3 From 3f5c3b981e46c16bb10948d012575b25170efb3b Mon Sep 17 00:00:00 2001 From: MalumaDev Date: Sat, 15 Oct 2022 18:41:46 +0200 Subject: Update modules/ui.py MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Víctor Gallego --- modules/ui.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 3b28b69c..1f6fcdc9 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1190,7 +1190,8 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column(): create_embedding = gr.Button(value="Create embedding", variant='primary') - with gr.Tab(label="Create images embedding"): + with gr.Tab(label="Create aesthetic images embedding"): + new_embedding_name_ae = gr.Textbox(label="Name") process_src_ae = gr.Textbox(label='Source directory') batch_ae = gr.Slider(minimum=1, maximum=1024, step=1, label="Batch size", value=256) -- cgit v1.2.3 From 74a9ee70020ffa2746c82300c533de3f7e523f22 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 15 Oct 2022 17:25:35 +0300 Subject: fix saving images compatibility with gradio update --- modules/ui.py | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 3206113e..b867d40f 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -154,10 +154,7 @@ def save_files(js_data, images, do_make_zip, index): writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"]) for image_index, filedata in enumerate(images, start_index): - if filedata.startswith("data:image/png;base64,"): - filedata = filedata[len("data:image/png;base64,"):] - - image = Image.open(io.BytesIO(base64.decodebytes(filedata.encode('utf-8')))) + image = image_from_url_text(filedata) is_grid = image_index < p.index_of_first_image i = 0 if is_grid else (image_index - p.index_of_first_image) -- cgit v1.2.3 From 9a33292ce41b01252cdb8ab6214a11d274e32fa0 Mon Sep 17 00:00:00 2001 From: zhengxiaoyao0716 <1499383852@qq.com> Date: Sat, 15 Oct 2022 01:04:47 +0800 Subject: reload javascript files when custom script bodies --- modules/ui.py | 28 ++++++++++++++++------------ 1 file changed, 16 insertions(+), 12 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index b867d40f..90b8646b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -12,7 +12,7 @@ import time import traceback import platform import subprocess as sp -from functools import reduce +from functools import partial, reduce import numpy as np import torch @@ -1491,6 +1491,7 @@ Requested path was: {f} def reload_scripts(): modules.scripts.reload_script_body_only() + reload_javascript() # need to refresh the html page reload_script_bodies.click( fn=reload_scripts, @@ -1738,22 +1739,25 @@ Requested path was: {f} return demo -with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile: - javascript = f'' +def load_javascript(raw_response): + with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile: + javascript = f'' -jsdir = os.path.join(script_path, "javascript") -for filename in sorted(os.listdir(jsdir)): - with open(os.path.join(jsdir, filename), "r", encoding="utf8") as jsfile: - javascript += f"\n" + jsdir = os.path.join(script_path, "javascript") + for filename in sorted(os.listdir(jsdir)): + with open(os.path.join(jsdir, filename), "r", encoding="utf8") as jsfile: + javascript += f"\n" - -if 'gradio_routes_templates_response' not in globals(): def template_response(*args, **kwargs): - res = gradio_routes_templates_response(*args, **kwargs) - res.body = res.body.replace(b'', f'{javascript}'.encode("utf8")) + res = raw_response(*args, **kwargs) + res.body = res.body.replace( + b'', f'{javascript}'.encode("utf8")) res.init_headers() return res - gradio_routes_templates_response = gradio.routes.templates.TemplateResponse gradio.routes.templates.TemplateResponse = template_response + +reload_javascript = partial(load_javascript, + gradio.routes.templates.TemplateResponse) +reload_javascript() -- cgit v1.2.3 From 2ce27728f6433911274efa67856315d22df56629 Mon Sep 17 00:00:00 2001 From: winterspringsummer Date: Sun, 16 Oct 2022 13:50:55 +0900 Subject: added extras batch work from directory --- modules/extras.py | 23 ++++++++++++++++++----- modules/ui.py | 12 ++++++++++++ 2 files changed, 30 insertions(+), 5 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/extras.py b/modules/extras.py index f2f5a7b0..5b52b27d 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -20,26 +20,38 @@ import gradio as gr cached_images = {} -def run_extras(extras_mode, resize_mode, image, image_folder, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility): +def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_dir, show_extras_results, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility): devices.torch_gc() imageArr = [] # Also keep track of original file names imageNameArr = [] - + outputs = [] + if extras_mode == 1: #convert file to pillow image for img in image_folder: image = Image.open(img) imageArr.append(image) imageNameArr.append(os.path.splitext(img.orig_name)[0]) + elif extras_mode == 2: + if input_dir == '': + return outputs, "Please select an input directory.", '' + image_list = [file for file in [os.path.join(input_dir, x) for x in os.listdir(input_dir)] if os.path.isfile(file)] + for img in image_list: + image = Image.open(img) + imageArr.append(image) + imageNameArr.append(img) else: imageArr.append(image) imageNameArr.append(None) - outpath = opts.outdir_samples or opts.outdir_extras_samples + if extras_mode == 2 and output_dir != '': + outpath = output_dir + else: + outpath = opts.outdir_samples or opts.outdir_extras_samples - outputs = [] + for image, image_name in zip(imageArr, imageNameArr): if image is None: return outputs, "Please select an input image.", '' @@ -112,7 +124,8 @@ def run_extras(extras_mode, resize_mode, image, image_folder, gfpgan_visibility, image.info = existing_pnginfo image.info["extras"] = info - outputs.append(image) + if extras_mode != 2 or show_extras_results : + outputs.append(image) devices.torch_gc() diff --git a/modules/ui.py b/modules/ui.py index b867d40f..08fa72c6 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1016,6 +1016,15 @@ def create_ui(wrap_gradio_gpu_call): with gr.TabItem('Batch Process'): image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file") + with gr.TabItem('Batch from Directory'): + extras_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, + placeholder="A directory on the same machine where the server is running." + ) + extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, + placeholder="Leave blank to save images to the default path." + ) + show_extras_results = gr.Checkbox(label='Show result images', value=True) + with gr.Tabs(elem_id="extras_resize_mode"): with gr.TabItem('Scale by'): upscaling_resize = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Resize", value=2) @@ -1060,6 +1069,9 @@ def create_ui(wrap_gradio_gpu_call): dummy_component, extras_image, image_batch, + extras_batch_input_dir, + extras_batch_output_dir, + show_extras_results, gfpgan_visibility, codeformer_visibility, codeformer_weight, -- cgit v1.2.3 From 3395ba493f93214cf037d084d45693a37610bd85 Mon Sep 17 00:00:00 2001 From: ddPn08 Date: Sun, 16 Oct 2022 09:24:01 +0900 Subject: Allow specifying the region of ngrok. --- modules/ngrok.py | 8 +++++--- modules/shared.py | 1 + modules/ui.py | 2 +- 3 files changed, 7 insertions(+), 4 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ngrok.py b/modules/ngrok.py index 7d03a6df..5c5f349a 100644 --- a/modules/ngrok.py +++ b/modules/ngrok.py @@ -1,12 +1,14 @@ from pyngrok import ngrok, conf, exception -def connect(token, port): +def connect(token, port, region): if token == None: token = 'None' - conf.get_default().auth_token = token + config = conf.PyngrokConfig( + auth_token=token, region=region + ) try: - public_url = ngrok.connect(port).public_url + public_url = ngrok.connect(port, pyngrok_config=config).public_url except exception.PyngrokNgrokError: print(f'Invalid ngrok authtoken, ngrok connection aborted.\n' f'Your token: {token}, get the right one on https://dashboard.ngrok.com/get-started/your-authtoken') diff --git a/modules/shared.py b/modules/shared.py index fa30bbb0..dcab0af9 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -40,6 +40,7 @@ parser.add_argument("--unload-gfpgan", action='store_true', help="does not do an parser.add_argument("--precision", type=str, help="evaluate at this precision", choices=["full", "autocast"], default="autocast") parser.add_argument("--share", action='store_true', help="use share=True for gradio and make the UI accessible through their site (doesn't work for me but you might have better luck)") parser.add_argument("--ngrok", type=str, help="ngrok authtoken, alternative to gradio --share", default=None) +parser.add_argument("--ngrok-region", type=str, help="The region in which ngrok should start.", default="us") parser.add_argument("--codeformer-models-path", type=str, help="Path to directory with codeformer model file(s).", default=os.path.join(models_path, 'Codeformer')) parser.add_argument("--gfpgan-models-path", type=str, help="Path to directory with GFPGAN model file(s).", default=os.path.join(models_path, 'GFPGAN')) parser.add_argument("--esrgan-models-path", type=str, help="Path to directory with ESRGAN model file(s).", default=os.path.join(models_path, 'ESRGAN')) diff --git a/modules/ui.py b/modules/ui.py index 08fa72c6..5c0eaf73 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -56,7 +56,7 @@ if not cmd_opts.share and not cmd_opts.listen: if cmd_opts.ngrok != None: import modules.ngrok as ngrok print('ngrok authtoken detected, trying to connect...') - ngrok.connect(cmd_opts.ngrok, cmd_opts.port if cmd_opts.port != None else 7860) + ngrok.connect(cmd_opts.ngrok, cmd_opts.port if cmd_opts.port != None else 7860, cmd_opts.ngrok_region) def gr_show(visible=True): -- cgit v1.2.3 From 20bf99052a9d50b5f99d199f4c449ef1ddd6e3cb Mon Sep 17 00:00:00 2001 From: CookieHCl Date: Sun, 16 Oct 2022 04:47:03 +0900 Subject: Make style configurable in ui-config.json --- modules/ui.py | 7 +++++++ 1 file changed, 7 insertions(+) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 5c0eaf73..78096f27 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -508,9 +508,11 @@ def create_toprow(is_img2img): with gr.Row(): with gr.Column(scale=1, elem_id="style_pos_col"): prompt_style = gr.Dropdown(label="Style 1", elem_id=f"{id_part}_style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys()))) + prompt_style.save_to_config = True with gr.Column(scale=1, elem_id="style_neg_col"): prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys()))) + prompt_style2.save_to_config = True return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button @@ -1739,6 +1741,11 @@ Requested path was: {f} if type(x) == gr.Number: apply_field(x, 'value') + # Since there are many dropdowns that shouldn't be saved, + # we only mark dropdowns that should be saved. + if type(x) == gr.Dropdown and getattr(x, 'save_to_config', False): + apply_field(x, 'value') + visit(txt2img_interface, loadsave, "txt2img") visit(img2img_interface, loadsave, "img2img") visit(extras_interface, loadsave, "extras") -- cgit v1.2.3 From b65a3101ce82b42b4ccc525044548e66cc44ae4a Mon Sep 17 00:00:00 2001 From: CookieHCl Date: Sun, 16 Oct 2022 04:54:53 +0900 Subject: Use default value when dropdown ui setting is bad Default value is the first value of selectables. Particually, None in styles. --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 78096f27..c8e68bd6 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1744,7 +1744,7 @@ Requested path was: {f} # Since there are many dropdowns that shouldn't be saved, # we only mark dropdowns that should be saved. if type(x) == gr.Dropdown and getattr(x, 'save_to_config', False): - apply_field(x, 'value') + apply_field(x, 'value', lambda val: val in x.choices) visit(txt2img_interface, loadsave, "txt2img") visit(img2img_interface, loadsave, "img2img") -- cgit v1.2.3 From 9258a33e3755c76922cd47a03cd59419b6426304 Mon Sep 17 00:00:00 2001 From: CookieHCl Date: Sun, 16 Oct 2022 05:09:11 +0900 Subject: Warn when user uses bad ui setting --- modules/ui.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index c8e68bd6..10bdf121 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1717,7 +1717,9 @@ Requested path was: {f} saved_value = ui_settings.get(key, None) if saved_value is None: ui_settings[key] = getattr(obj, field) - elif condition is None or condition(saved_value): + elif condition and not condition(saved_value): + print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.') + else: setattr(obj, field, saved_value) if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number] and x.visible: -- cgit v1.2.3 From 36a0ba357ab0742c3c4a28437b68fb29a235afbe Mon Sep 17 00:00:00 2001 From: Junpeng Qiu Date: Sat, 15 Oct 2022 21:42:52 -0700 Subject: Added Refresh Button to embedding and hypernetwork names in Train Tab Problem everytime I modified pt files in embedding_dir or hypernetwork_dir, I need to restart webui to have the new files shown in the dropdown of Train Tab Solution refactored create_refresh_button out of create_setting_component so we can use this method to create button next to gr.Dropdowns of embedding name and hypernetworks Extra Modification hypernetwork pt are now sorted in alphabetic order --- modules/ui.py | 45 ++++++++++++++++++++++++++------------------- style.css | 2 +- 2 files changed, 27 insertions(+), 20 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 10bdf121..ee3d0248 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -568,6 +568,24 @@ def create_ui(wrap_gradio_gpu_call): import modules.img2img import modules.txt2img + def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id): + def refresh(): + refresh_method() + args = refreshed_args() if callable(refreshed_args) else refreshed_args + + for k, v in args.items(): + setattr(refresh_component, k, v) + + return gr.update(**(args or {})) + + refresh_button = gr.Button(value=refresh_symbol, elem_id=elem_id) + refresh_button.click( + fn = refresh, + inputs = [], + outputs = [refresh_component] + ) + return refresh_button + with gr.Blocks(analytics_enabled=False) as txt2img_interface: txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False) dummy_component = gr.Label(visible=False) @@ -1205,8 +1223,12 @@ def create_ui(wrap_gradio_gpu_call): with gr.Tab(label="Train"): gr.HTML(value="

Train an embedding; must specify a directory with a set of 1:1 ratio images

") - train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) - train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()]) + with gr.Row(): + train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) + create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name") + with gr.Row(): + train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()]) + create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted([x for x in shared.hypernetworks.keys()])}, "refresh_train_hypernetwork_name") learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.005") batch_size = gr.Number(label='Batch size', value=1, precision=0) dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images") @@ -1357,26 +1379,11 @@ def create_ui(wrap_gradio_gpu_call): if info.refresh is not None: if is_quicksettings: res = comp(label=info.label, value=fun, **(args or {})) - refresh_button = gr.Button(value=refresh_symbol, elem_id="refresh_"+key) + refresh_button = create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key) else: with gr.Row(variant="compact"): res = comp(label=info.label, value=fun, **(args or {})) - refresh_button = gr.Button(value=refresh_symbol, elem_id="refresh_" + key) - - def refresh(): - info.refresh() - refreshed_args = info.component_args() if callable(info.component_args) else info.component_args - - for k, v in refreshed_args.items(): - setattr(res, k, v) - - return gr.update(**(refreshed_args or {})) - - refresh_button.click( - fn=refresh, - inputs=[], - outputs=[res], - ) + refresh_button = create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key) else: res = comp(label=info.label, value=fun, **(args or {})) diff --git a/style.css b/style.css index 33832ebf..71eb4d20 100644 --- a/style.css +++ b/style.css @@ -478,7 +478,7 @@ input[type="range"]{ padding: 0; } -#refresh_sd_model_checkpoint, #refresh_sd_hypernetwork{ +#refresh_sd_model_checkpoint, #refresh_sd_hypernetwork, #refresh_train_hypernetwork_name, #refresh_train_embedding_name{ max-width: 2.5em; min-width: 2.5em; height: 2.4em; -- cgit v1.2.3 From 523140d7805c644700009b8a2483ff4eb4a22304 Mon Sep 17 00:00:00 2001 From: MalumaDev Date: Sun, 16 Oct 2022 10:23:30 +0200 Subject: ui fix --- modules/aesthetic_clip.py | 3 +-- modules/sd_hijack.py | 3 +-- modules/shared.py | 2 ++ modules/ui.py | 24 ++++++++++++++---------- 4 files changed, 18 insertions(+), 14 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/aesthetic_clip.py b/modules/aesthetic_clip.py index 68264284..ccb35c73 100644 --- a/modules/aesthetic_clip.py +++ b/modules/aesthetic_clip.py @@ -74,5 +74,4 @@ def generate_imgs_embd(name, folder, batch_size): """ shared.update_aesthetic_embeddings() return gr.Dropdown.update(choices=sorted(shared.aesthetic_embeddings.keys()), label="Imgs embedding", - value=sorted(shared.aesthetic_embeddings.keys())[0] if len( - shared.aesthetic_embeddings) > 0 else None), res, "" + value="None"), res, "" diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index 01fcb78f..2de2eed5 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -392,8 +392,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): z1 = self.process_tokens(tokens, multipliers) z = z1 if z is None else torch.cat((z, z1), axis=-2) - if len(text[ - 0]) != 0 and self.aesthetic_steps != 0 and self.aesthetic_lr != 0 and self.aesthetic_weight != 0 and self.image_embs_name != None: + if self.aesthetic_steps != 0 and self.aesthetic_lr != 0 and self.aesthetic_weight != 0 and self.image_embs_name != None: if not opts.use_old_emphasis_implementation: remade_batch_tokens = [ [self.wrapped.tokenizer.bos_token_id] + x[:75] + [self.wrapped.tokenizer.eos_token_id] for x in diff --git a/modules/shared.py b/modules/shared.py index 3c5ffef1..e2c98b2d 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -96,11 +96,13 @@ loaded_hypernetwork = None aesthetic_embeddings = {f.replace(".pt",""): os.path.join(cmd_opts.aesthetic_embeddings_dir, f) for f in os.listdir(cmd_opts.aesthetic_embeddings_dir) if f.endswith(".pt")} +aesthetic_embeddings = aesthetic_embeddings | {"None": None} def update_aesthetic_embeddings(): global aesthetic_embeddings aesthetic_embeddings = {f.replace(".pt",""): os.path.join(cmd_opts.aesthetic_embeddings_dir, f) for f in os.listdir(cmd_opts.aesthetic_embeddings_dir) if f.endswith(".pt")} + aesthetic_embeddings = aesthetic_embeddings | {"None": None} def reload_hypernetworks(): global hypernetworks diff --git a/modules/ui.py b/modules/ui.py index 13ba3142..4069f0d2 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -594,19 +594,23 @@ def create_ui(wrap_gradio_gpu_call): height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) with gr.Group(): - aesthetic_lr = gr.Textbox(label='Aesthetic learning rate', placeholder="Aesthetic learning rate", value="0.0001") - - aesthetic_weight = gr.Slider(minimum=0, maximum=1, step=0.01, label="Aesthetic weight", value=0.9) - aesthetic_steps = gr.Slider(minimum=0, maximum=50, step=1, label="Aesthetic steps", value=5) + with gr.Accordion("Open for Clip Aesthetic!",open=False): + with gr.Row(): + aesthetic_weight = gr.Slider(minimum=0, maximum=1, step=0.01, label="Aesthetic weight", value=0.9) + aesthetic_steps = gr.Slider(minimum=0, maximum=50, step=1, label="Aesthetic steps", value=5) - with gr.Row(): - aesthetic_imgs_text = gr.Textbox(label='Aesthetic text for imgs', placeholder="This text is used to rotate the feature space of the imgs embs", value="") - aesthetic_slerp_angle = gr.Slider(label='Slerp angle',minimum=0, maximum=1, step=0.01, value=0.1) - aesthetic_text_negative = gr.Checkbox(label="Is negative text", value=False) + with gr.Row(): + aesthetic_lr = gr.Textbox(label='Aesthetic learning rate', placeholder="Aesthetic learning rate", value="0.0001") + aesthetic_slerp = gr.Checkbox(label="Slerp interpolation", value=False) + aesthetic_imgs = gr.Dropdown(sorted(aesthetic_embeddings.keys()), + label="Aesthetic imgs embedding", + value="None") - aesthetic_imgs = gr.Dropdown(sorted(aesthetic_embeddings.keys()), label="Aesthetic imgs embedding", value=sorted(aesthetic_embeddings.keys())[0] if len(aesthetic_embeddings) > 0 else None) + with gr.Row(): + aesthetic_imgs_text = gr.Textbox(label='Aesthetic text for imgs', placeholder="This text is used to rotate the feature space of the imgs embs", value="") + aesthetic_slerp_angle = gr.Slider(label='Slerp angle',minimum=0, maximum=1, step=0.01, value=0.1) + aesthetic_text_negative = gr.Checkbox(label="Is negative text", value=False) - aesthetic_slerp = gr.Checkbox(label="Slerp interpolation", value=False) with gr.Row(): restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1) -- cgit v1.2.3 From c9836279f58461e04c1dda0a86e718f8bd3f41e4 Mon Sep 17 00:00:00 2001 From: CookieHCl Date: Sun, 16 Oct 2022 21:59:05 +0900 Subject: Only make output dir when creating output --- modules/processing.py | 6 ------ modules/ui.py | 5 ++++- 2 files changed, 4 insertions(+), 7 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/processing.py b/modules/processing.py index 833fed8a..deb6125e 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -334,12 +334,6 @@ def process_images(p: StableDiffusionProcessing) -> Processed: seed = get_fixed_seed(p.seed) subseed = get_fixed_seed(p.subseed) - if p.outpath_samples is not None: - os.makedirs(p.outpath_samples, exist_ok=True) - - if p.outpath_grids is not None: - os.makedirs(p.outpath_grids, exist_ok=True) - modules.sd_hijack.model_hijack.apply_circular(p.tiling) modules.sd_hijack.model_hijack.clear_comments() diff --git a/modules/ui.py b/modules/ui.py index ee3d0248..fa73627a 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1394,7 +1394,10 @@ def create_ui(wrap_gradio_gpu_call): component_dict = {} def open_folder(f): - if not os.path.isdir(f): + if not os.path.exists(f): + print(f"{f} doesn't exist. After you create an image, the folder will be created.") + return + elif not os.path.isdir(f): print(f""" WARNING An open_folder request was made with an argument that is not a folder. -- cgit v1.2.3 From adc0ea74e1ee9791f15c3a74bc6c5ad789e10d17 Mon Sep 17 00:00:00 2001 From: CookieHCl Date: Sun, 16 Oct 2022 22:03:18 +0900 Subject: Better readablity of logs --- modules/images_history.py | 2 +- modules/ui.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/images_history.py b/modules/images_history.py index e6284142..e06e07bf 100644 --- a/modules/images_history.py +++ b/modules/images_history.py @@ -31,7 +31,7 @@ def get_recent_images(dir_name, page_index, step, image_index, tabname): image_list = traverse_all_files(dir_name, image_list) image_list = sorted(image_list, key=lambda file: -os.path.getctime(os.path.join(dir_name, file))) else: - print(f"ERROR: {dir_name} is not a directory. Check the path in the settings.", file=sys.stderr) + print(f'ERROR: "{dir_name}" is not a directory. Check the path in the settings.', file=sys.stderr) num = 48 if tabname != "extras" else 12 max_page_index = len(image_list) // num + 1 page_index = max_page_index if page_index == -1 else page_index + step diff --git a/modules/ui.py b/modules/ui.py index fa73627a..7b0d5a92 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1395,7 +1395,7 @@ def create_ui(wrap_gradio_gpu_call): def open_folder(f): if not os.path.exists(f): - print(f"{f} doesn't exist. After you create an image, the folder will be created.") + print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.') return elif not os.path.isdir(f): print(f""" -- cgit v1.2.3 From 9324cdaa3199d65c182858785dd1eca42b192b8e Mon Sep 17 00:00:00 2001 From: MalumaDev Date: Sun, 16 Oct 2022 17:53:56 +0200 Subject: ui fix, re organization of the code --- modules/aesthetic_clip.py | 154 +++++++++++++++++++++++++++++++++-- modules/img2img.py | 14 +++- modules/processing.py | 29 ++----- modules/sd_hijack.py | 102 ++--------------------- modules/sd_models.py | 5 +- modules/shared.py | 14 +++- modules/textual_inversion/dataset.py | 2 +- modules/txt2img.py | 18 ++-- modules/ui.py | 52 +++++++----- 9 files changed, 233 insertions(+), 157 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/aesthetic_clip.py b/modules/aesthetic_clip.py index ccb35c73..34efa931 100644 --- a/modules/aesthetic_clip.py +++ b/modules/aesthetic_clip.py @@ -1,3 +1,4 @@ +import copy import itertools import os from pathlib import Path @@ -7,11 +8,12 @@ import gc import gradio as gr import torch from PIL import Image -from modules import shared -from modules.shared import device -from transformers import CLIPModel, CLIPProcessor +from torch import optim -from tqdm.auto import tqdm +from modules import shared +from transformers import CLIPModel, CLIPProcessor, CLIPTokenizer +from tqdm.auto import tqdm, trange +from modules.shared import opts, device def get_all_images_in_folder(folder): @@ -37,12 +39,39 @@ def iter_to_batched(iterable, n=1): yield chunk +def create_ui(): + with gr.Group(): + with gr.Accordion("Open for Clip Aesthetic!", open=False): + with gr.Row(): + aesthetic_weight = gr.Slider(minimum=0, maximum=1, step=0.01, label="Aesthetic weight", + value=0.9) + aesthetic_steps = gr.Slider(minimum=0, maximum=50, step=1, label="Aesthetic steps", value=5) + + with gr.Row(): + aesthetic_lr = gr.Textbox(label='Aesthetic learning rate', + placeholder="Aesthetic learning rate", value="0.0001") + aesthetic_slerp = gr.Checkbox(label="Slerp interpolation", value=False) + aesthetic_imgs = gr.Dropdown(sorted(shared.aesthetic_embeddings.keys()), + label="Aesthetic imgs embedding", + value="None") + + with gr.Row(): + aesthetic_imgs_text = gr.Textbox(label='Aesthetic text for imgs', + placeholder="This text is used to rotate the feature space of the imgs embs", + value="") + aesthetic_slerp_angle = gr.Slider(label='Slerp angle', minimum=0, maximum=1, step=0.01, + value=0.1) + aesthetic_text_negative = gr.Checkbox(label="Is negative text", value=False) + + return aesthetic_weight, aesthetic_steps, aesthetic_lr, aesthetic_slerp, aesthetic_imgs, aesthetic_imgs_text, aesthetic_slerp_angle, aesthetic_text_negative + + def generate_imgs_embd(name, folder, batch_size): # clipModel = CLIPModel.from_pretrained( # shared.sd_model.cond_stage_model.clipModel.name_or_path # ) - model = CLIPModel.from_pretrained(shared.sd_model.cond_stage_model.clipModel.name_or_path).to(device) - processor = CLIPProcessor.from_pretrained(shared.sd_model.cond_stage_model.clipModel.name_or_path) + model = shared.clip_model.to(device) + processor = CLIPProcessor.from_pretrained(model.name_or_path) with torch.no_grad(): embs = [] @@ -63,7 +92,6 @@ def generate_imgs_embd(name, folder, batch_size): torch.save(embs, path) model = model.cpu() - del model del processor del embs gc.collect() @@ -74,4 +102,114 @@ def generate_imgs_embd(name, folder, batch_size): """ shared.update_aesthetic_embeddings() return gr.Dropdown.update(choices=sorted(shared.aesthetic_embeddings.keys()), label="Imgs embedding", - value="None"), res, "" + value="None"), \ + gr.Dropdown.update(choices=sorted(shared.aesthetic_embeddings.keys()), + label="Imgs embedding", + value="None"), res, "" + + +def slerp(low, high, val): + low_norm = low / torch.norm(low, dim=1, keepdim=True) + high_norm = high / torch.norm(high, dim=1, keepdim=True) + omega = torch.acos((low_norm * high_norm).sum(1)) + so = torch.sin(omega) + res = (torch.sin((1.0 - val) * omega) / so).unsqueeze(1) * low + (torch.sin(val * omega) / so).unsqueeze(1) * high + return res + + +class AestheticCLIP: + def __init__(self): + self.skip = False + self.aesthetic_steps = 0 + self.aesthetic_weight = 0 + self.aesthetic_lr = 0 + self.slerp = False + self.aesthetic_text_negative = "" + self.aesthetic_slerp_angle = 0 + self.aesthetic_imgs_text = "" + + self.image_embs_name = None + self.image_embs = None + self.load_image_embs(None) + + def set_aesthetic_params(self, aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, image_embs_name=None, + aesthetic_slerp=True, aesthetic_imgs_text="", + aesthetic_slerp_angle=0.15, + aesthetic_text_negative=False): + self.aesthetic_imgs_text = aesthetic_imgs_text + self.aesthetic_slerp_angle = aesthetic_slerp_angle + self.aesthetic_text_negative = aesthetic_text_negative + self.slerp = aesthetic_slerp + self.aesthetic_lr = aesthetic_lr + self.aesthetic_weight = aesthetic_weight + self.aesthetic_steps = aesthetic_steps + self.load_image_embs(image_embs_name) + + def set_skip(self, skip): + self.skip = skip + + def load_image_embs(self, image_embs_name): + if image_embs_name is None or len(image_embs_name) == 0 or image_embs_name == "None": + image_embs_name = None + self.image_embs_name = None + if image_embs_name is not None and self.image_embs_name != image_embs_name: + self.image_embs_name = image_embs_name + self.image_embs = torch.load(shared.aesthetic_embeddings[self.image_embs_name], map_location=device) + self.image_embs /= self.image_embs.norm(dim=-1, keepdim=True) + self.image_embs.requires_grad_(False) + + def __call__(self, z, remade_batch_tokens): + if not self.skip and self.aesthetic_steps != 0 and self.aesthetic_lr != 0 and self.aesthetic_weight != 0 and self.image_embs_name is not None: + tokenizer = shared.sd_model.cond_stage_model.tokenizer + if not opts.use_old_emphasis_implementation: + remade_batch_tokens = [ + [tokenizer.bos_token_id] + x[:75] + [tokenizer.eos_token_id] for x in + remade_batch_tokens] + + tokens = torch.asarray(remade_batch_tokens).to(device) + + model = copy.deepcopy(shared.clip_model).to(device) + model.requires_grad_(True) + if self.aesthetic_imgs_text is not None and len(self.aesthetic_imgs_text) > 0: + text_embs_2 = model.get_text_features( + **tokenizer([self.aesthetic_imgs_text], padding=True, return_tensors="pt").to(device)) + if self.aesthetic_text_negative: + text_embs_2 = self.image_embs - text_embs_2 + text_embs_2 /= text_embs_2.norm(dim=-1, keepdim=True) + img_embs = slerp(self.image_embs, text_embs_2, self.aesthetic_slerp_angle) + else: + img_embs = self.image_embs + + with torch.enable_grad(): + + # We optimize the model to maximize the similarity + optimizer = optim.Adam( + model.text_model.parameters(), lr=self.aesthetic_lr + ) + + for _ in trange(self.aesthetic_steps, desc="Aesthetic optimization"): + text_embs = model.get_text_features(input_ids=tokens) + text_embs = text_embs / text_embs.norm(dim=-1, keepdim=True) + sim = text_embs @ img_embs.T + loss = -sim + optimizer.zero_grad() + loss.mean().backward() + optimizer.step() + + zn = model.text_model(input_ids=tokens, output_hidden_states=-opts.CLIP_stop_at_last_layers) + if opts.CLIP_stop_at_last_layers > 1: + zn = zn.hidden_states[-opts.CLIP_stop_at_last_layers] + zn = model.text_model.final_layer_norm(zn) + else: + zn = zn.last_hidden_state + model.cpu() + del model + gc.collect() + torch.cuda.empty_cache() + zn = torch.concat([zn[77 * i:77 * (i + 1)] for i in range(max(z.shape[1] // 77, 1))], 1) + if self.slerp: + z = slerp(z, zn, self.aesthetic_weight) + else: + z = z * (1 - self.aesthetic_weight) + zn * self.aesthetic_weight + + return z diff --git a/modules/img2img.py b/modules/img2img.py index 24126774..4ed80c4b 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -56,7 +56,14 @@ def process_batch(p, input_dir, output_dir, args): processed_image.save(os.path.join(output_dir, filename)) -def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, init_img_with_mask, init_img_inpaint, init_mask_inpaint, mask_mode, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args): +def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, init_img_with_mask, init_img_inpaint, init_mask_inpaint, mask_mode, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, + aesthetic_lr=0, + aesthetic_weight=0, aesthetic_steps=0, + aesthetic_imgs=None, + aesthetic_slerp=False, + aesthetic_imgs_text="", + aesthetic_slerp_angle=0.15, + aesthetic_text_negative=False, *args): is_inpaint = mode == 1 is_batch = mode == 2 @@ -109,6 +116,11 @@ def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, pro inpainting_mask_invert=inpainting_mask_invert, ) + shared.aesthetic_clip.set_aesthetic_params(float(aesthetic_lr), float(aesthetic_weight), int(aesthetic_steps), + aesthetic_imgs, aesthetic_slerp, aesthetic_imgs_text, + aesthetic_slerp_angle, + aesthetic_text_negative) + if shared.cmd_opts.enable_console_prompts: print(f"\nimg2img: {prompt}", file=shared.progress_print_out) diff --git a/modules/processing.py b/modules/processing.py index 1db26c3e..685f9fcd 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -146,7 +146,8 @@ class Processed: self.prompt = self.prompt if type(self.prompt) != list else self.prompt[0] self.negative_prompt = self.negative_prompt if type(self.negative_prompt) != list else self.negative_prompt[0] self.seed = int(self.seed if type(self.seed) != list else self.seed[0]) if self.seed is not None else -1 - self.subseed = int(self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1 + self.subseed = int( + self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1 self.all_prompts = all_prompts or [self.prompt] self.all_seeds = all_seeds or [self.seed] @@ -332,16 +333,9 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration return f"{all_prompts[index]}{negative_prompt_text}\n{generation_params_text}".strip() -def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, - aesthetic_imgs=None, aesthetic_slerp=False, aesthetic_imgs_text="", - aesthetic_slerp_angle=0.15, - aesthetic_text_negative=False) -> Processed: +def process_images(p: StableDiffusionProcessing) -> Processed: """this is the main loop that both txt2img and img2img use; it calls func_init once inside all the scopes and func_sample once per batch""" - aesthetic_lr = float(aesthetic_lr) - aesthetic_weight = float(aesthetic_weight) - aesthetic_steps = int(aesthetic_steps) - if type(p.prompt) == list: assert (len(p.prompt) > 0) else: @@ -417,16 +411,10 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh # uc = p.sd_model.get_learned_conditioning(len(prompts) * [p.negative_prompt]) # c = p.sd_model.get_learned_conditioning(prompts) with devices.autocast(): - if hasattr(shared.sd_model.cond_stage_model, "set_aesthetic_params"): - shared.sd_model.cond_stage_model.set_aesthetic_params() + shared.aesthetic_clip.set_skip(True) uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], p.steps) - if hasattr(shared.sd_model.cond_stage_model, "set_aesthetic_params"): - shared.sd_model.cond_stage_model.set_aesthetic_params(aesthetic_lr, aesthetic_weight, - aesthetic_steps, aesthetic_imgs, - aesthetic_slerp, aesthetic_imgs_text, - aesthetic_slerp_angle, - aesthetic_text_negative) + shared.aesthetic_clip.set_skip(False) c = prompt_parser.get_multicond_learned_conditioning(shared.sd_model, prompts, p.steps) if len(model_hijack.comments) > 0: @@ -582,7 +570,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.truncate_x = int(self.firstphase_width - firstphase_width_truncated) // opt_f self.truncate_y = int(self.firstphase_height - firstphase_height_truncated) // opt_f - def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength): self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model) @@ -600,10 +587,12 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): seed_resize_from_w=self.seed_resize_from_w, p=self) samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning) - samples = samples[:, :, self.truncate_y//2:samples.shape[2]-self.truncate_y//2, self.truncate_x//2:samples.shape[3]-self.truncate_x//2] + samples = samples[:, :, self.truncate_y // 2:samples.shape[2] - self.truncate_y // 2, + self.truncate_x // 2:samples.shape[3] - self.truncate_x // 2] if opts.use_scale_latent_for_hires_fix: - samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear") + samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), + mode="bilinear") else: decoded_samples = decode_first_stage(self.sd_model, samples) lowres_samples = torch.clamp((decoded_samples + 1.0) / 2.0, min=0.0, max=1.0) diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index 5d0590af..227e7670 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -29,8 +29,8 @@ def apply_optimizations(): ldm.modules.diffusionmodules.model.nonlinearity = silu - - if cmd_opts.force_enable_xformers or (cmd_opts.xformers and shared.xformers_available and torch.version.cuda and (6, 0) <= torch.cuda.get_device_capability(shared.device) <= (9, 0)): + if cmd_opts.force_enable_xformers or (cmd_opts.xformers and shared.xformers_available and torch.version.cuda and ( + 6, 0) <= torch.cuda.get_device_capability(shared.device) <= (9, 0)): print("Applying xformers cross attention optimization.") ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward @@ -118,33 +118,14 @@ class StableDiffusionModelHijack: return remade_batch_tokens[0], token_count, get_target_prompt_token_count(token_count) -def slerp(low, high, val): - low_norm = low / torch.norm(low, dim=1, keepdim=True) - high_norm = high / torch.norm(high, dim=1, keepdim=True) - omega = torch.acos((low_norm * high_norm).sum(1)) - so = torch.sin(omega) - res = (torch.sin((1.0 - val) * omega) / so).unsqueeze(1) * low + (torch.sin(val * omega) / so).unsqueeze(1) * high - return res - - class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): def __init__(self, wrapped, hijack): super().__init__() self.wrapped = wrapped - self.clipModel = CLIPModel.from_pretrained( - self.wrapped.transformer.name_or_path - ) - del self.clipModel.vision_model - self.tokenizer = CLIPTokenizer.from_pretrained(self.wrapped.transformer.name_or_path) - self.hijack: StableDiffusionModelHijack = hijack - self.tokenizer = wrapped.tokenizer - # self.vision = CLIPVisionModel.from_pretrained(self.wrapped.transformer.name_or_path).eval() - self.image_embs_name = None - self.image_embs = None - self.load_image_embs(None) self.token_mults = {} - + self.hijack: StableDiffusionModelHijack = hijack + self.tokenizer = wrapped.tokenizer self.comma_token = [v for k, v in self.tokenizer.get_vocab().items() if k == ','][0] tokens_with_parens = [(k, v) for k, v in self.tokenizer.get_vocab().items() if @@ -164,28 +145,6 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): if mult != 1.0: self.token_mults[ident] = mult - def set_aesthetic_params(self, aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, image_embs_name=None, - aesthetic_slerp=True, aesthetic_imgs_text="", - aesthetic_slerp_angle=0.15, - aesthetic_text_negative=False): - self.aesthetic_imgs_text = aesthetic_imgs_text - self.aesthetic_slerp_angle = aesthetic_slerp_angle - self.aesthetic_text_negative = aesthetic_text_negative - self.slerp = aesthetic_slerp - self.aesthetic_lr = aesthetic_lr - self.aesthetic_weight = aesthetic_weight - self.aesthetic_steps = aesthetic_steps - self.load_image_embs(image_embs_name) - - def load_image_embs(self, image_embs_name): - if image_embs_name is None or len(image_embs_name) == 0 or image_embs_name == "None": - image_embs_name = None - if image_embs_name is not None and self.image_embs_name != image_embs_name: - self.image_embs_name = image_embs_name - self.image_embs = torch.load(shared.aesthetic_embeddings[self.image_embs_name], map_location=device) - self.image_embs /= self.image_embs.norm(dim=-1, keepdim=True) - self.image_embs.requires_grad_(False) - def tokenize_line(self, line, used_custom_terms, hijack_comments): id_end = self.wrapped.tokenizer.eos_token_id @@ -391,58 +350,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): z1 = self.process_tokens(tokens, multipliers) z = z1 if z is None else torch.cat((z, z1), axis=-2) - - if self.aesthetic_steps != 0 and self.aesthetic_lr != 0 and self.aesthetic_weight != 0 and self.image_embs_name != None: - if not opts.use_old_emphasis_implementation: - remade_batch_tokens = [ - [self.wrapped.tokenizer.bos_token_id] + x[:75] + [self.wrapped.tokenizer.eos_token_id] for x in - remade_batch_tokens] - - tokens = torch.asarray(remade_batch_tokens).to(device) - - model = copy.deepcopy(self.clipModel).to(device) - model.requires_grad_(True) - if self.aesthetic_imgs_text is not None and len(self.aesthetic_imgs_text) > 0: - text_embs_2 = model.get_text_features( - **self.tokenizer([self.aesthetic_imgs_text], padding=True, return_tensors="pt").to(device)) - if self.aesthetic_text_negative: - text_embs_2 = self.image_embs - text_embs_2 - text_embs_2 /= text_embs_2.norm(dim=-1, keepdim=True) - img_embs = slerp(self.image_embs, text_embs_2, self.aesthetic_slerp_angle) - else: - img_embs = self.image_embs - - with torch.enable_grad(): - - # We optimize the model to maximize the similarity - optimizer = optim.Adam( - model.text_model.parameters(), lr=self.aesthetic_lr - ) - - for i in trange(self.aesthetic_steps, desc="Aesthetic optimization"): - text_embs = model.get_text_features(input_ids=tokens) - text_embs = text_embs / text_embs.norm(dim=-1, keepdim=True) - sim = text_embs @ img_embs.T - loss = -sim - optimizer.zero_grad() - loss.mean().backward() - optimizer.step() - - zn = model.text_model(input_ids=tokens, output_hidden_states=-opts.CLIP_stop_at_last_layers) - if opts.CLIP_stop_at_last_layers > 1: - zn = zn.hidden_states[-opts.CLIP_stop_at_last_layers] - zn = model.text_model.final_layer_norm(zn) - else: - zn = zn.last_hidden_state - model.cpu() - del model - - zn = torch.concat([zn for i in range(z.shape[1] // 77)], 1) - if self.slerp: - z = slerp(z, zn, self.aesthetic_weight) - else: - z = z * (1 - self.aesthetic_weight) + zn * self.aesthetic_weight - + z = shared.aesthetic_clip(z, remade_batch_tokens) remade_batch_tokens = rem_tokens batch_multipliers = rem_multipliers i += 1 diff --git a/modules/sd_models.py b/modules/sd_models.py index 3aa21ec1..8e4ee435 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -20,7 +20,7 @@ checkpoints_loaded = collections.OrderedDict() try: # this silences the annoying "Some weights of the model checkpoint were not used when initializing..." message at start. - from transformers import logging + from transformers import logging, CLIPModel logging.set_verbosity_error() except Exception: @@ -196,6 +196,9 @@ def load_model(): sd_hijack.model_hijack.hijack(sd_model) + if shared.clip_model is None or shared.clip_model.transformer.name_or_path != sd_model.cond_stage_model.wrapped.transformer.name_or_path: + shared.clip_model = CLIPModel.from_pretrained(sd_model.cond_stage_model.wrapped.transformer.name_or_path) + sd_model.eval() print(f"Model loaded.") diff --git a/modules/shared.py b/modules/shared.py index e2c98b2d..e19ca779 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -3,6 +3,7 @@ import datetime import json import os import sys +from collections import OrderedDict import gradio as gr import tqdm @@ -94,15 +95,15 @@ os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True) hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) loaded_hypernetwork = None -aesthetic_embeddings = {f.replace(".pt",""): os.path.join(cmd_opts.aesthetic_embeddings_dir, f) for f in - os.listdir(cmd_opts.aesthetic_embeddings_dir) if f.endswith(".pt")} -aesthetic_embeddings = aesthetic_embeddings | {"None": None} +aesthetic_embeddings = {} def update_aesthetic_embeddings(): global aesthetic_embeddings aesthetic_embeddings = {f.replace(".pt",""): os.path.join(cmd_opts.aesthetic_embeddings_dir, f) for f in os.listdir(cmd_opts.aesthetic_embeddings_dir) if f.endswith(".pt")} - aesthetic_embeddings = aesthetic_embeddings | {"None": None} + aesthetic_embeddings = OrderedDict(**{"None": None}, **aesthetic_embeddings) + +update_aesthetic_embeddings() def reload_hypernetworks(): global hypernetworks @@ -381,6 +382,11 @@ sd_upscalers = [] sd_model = None +clip_model = None + +from modules.aesthetic_clip import AestheticCLIP +aesthetic_clip = AestheticCLIP() + progress_print_out = sys.stdout diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py index 68ceffe3..23bb4b6a 100644 --- a/modules/textual_inversion/dataset.py +++ b/modules/textual_inversion/dataset.py @@ -49,7 +49,7 @@ class PersonalizedBase(Dataset): print("Preparing dataset...") for path in tqdm.tqdm(self.image_paths): try: - image = Image.open(path).convert('RGB').resize((self.width, self.height), PIL.Image.Resampling.BICUBIC) + image = Image.open(path).convert('RGB').resize((self.width, self.height), PIL.Image.BICUBIC) except Exception: continue diff --git a/modules/txt2img.py b/modules/txt2img.py index 8f394d05..6cbc50fc 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -1,12 +1,17 @@ import modules.scripts -from modules.processing import StableDiffusionProcessing, Processed, StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images +from modules.processing import StableDiffusionProcessing, Processed, StableDiffusionProcessingTxt2Img, \ + StableDiffusionProcessingImg2Img, process_images from modules.shared import opts, cmd_opts import modules.shared as shared import modules.processing as processing from modules.ui import plaintext_to_html -def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, firstphase_width: int, firstphase_height: int,aesthetic_lr=0, +def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, + restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, + subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, + height: int, width: int, enable_hr: bool, denoising_strength: float, firstphase_width: int, + firstphase_height: int, aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, aesthetic_imgs=None, aesthetic_slerp=False, @@ -41,15 +46,17 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: firstphase_height=firstphase_height if enable_hr else None, ) + shared.aesthetic_clip.set_aesthetic_params(float(aesthetic_lr), float(aesthetic_weight), int(aesthetic_steps), + aesthetic_imgs, aesthetic_slerp, aesthetic_imgs_text, aesthetic_slerp_angle, + aesthetic_text_negative) + if cmd_opts.enable_console_prompts: print(f"\ntxt2img: {prompt}", file=shared.progress_print_out) processed = modules.scripts.scripts_txt2img.run(p, *args) if processed is None: - processed = process_images(p, aesthetic_lr, aesthetic_weight, aesthetic_steps, aesthetic_imgs, aesthetic_slerp,aesthetic_imgs_text, - aesthetic_slerp_angle, - aesthetic_text_negative) + processed = process_images(p) shared.total_tqdm.clear() @@ -61,4 +68,3 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: processed.images = [] return processed.images, generation_info_js, plaintext_to_html(processed.info) - diff --git a/modules/ui.py b/modules/ui.py index 4069f0d2..0e5d73f0 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -43,7 +43,7 @@ from modules.images import save_image import modules.textual_inversion.ui import modules.hypernetworks.ui -import modules.aesthetic_clip +import modules.aesthetic_clip as aesthetic_clip import modules.images_history as img_his @@ -593,23 +593,25 @@ def create_ui(wrap_gradio_gpu_call): width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512) height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) - with gr.Group(): - with gr.Accordion("Open for Clip Aesthetic!",open=False): - with gr.Row(): - aesthetic_weight = gr.Slider(minimum=0, maximum=1, step=0.01, label="Aesthetic weight", value=0.9) - aesthetic_steps = gr.Slider(minimum=0, maximum=50, step=1, label="Aesthetic steps", value=5) - - with gr.Row(): - aesthetic_lr = gr.Textbox(label='Aesthetic learning rate', placeholder="Aesthetic learning rate", value="0.0001") - aesthetic_slerp = gr.Checkbox(label="Slerp interpolation", value=False) - aesthetic_imgs = gr.Dropdown(sorted(aesthetic_embeddings.keys()), - label="Aesthetic imgs embedding", - value="None") - - with gr.Row(): - aesthetic_imgs_text = gr.Textbox(label='Aesthetic text for imgs', placeholder="This text is used to rotate the feature space of the imgs embs", value="") - aesthetic_slerp_angle = gr.Slider(label='Slerp angle',minimum=0, maximum=1, step=0.01, value=0.1) - aesthetic_text_negative = gr.Checkbox(label="Is negative text", value=False) + # with gr.Group(): + # with gr.Accordion("Open for Clip Aesthetic!",open=False): + # with gr.Row(): + # aesthetic_weight = gr.Slider(minimum=0, maximum=1, step=0.01, label="Aesthetic weight", value=0.9) + # aesthetic_steps = gr.Slider(minimum=0, maximum=50, step=1, label="Aesthetic steps", value=5) + # + # with gr.Row(): + # aesthetic_lr = gr.Textbox(label='Aesthetic learning rate', placeholder="Aesthetic learning rate", value="0.0001") + # aesthetic_slerp = gr.Checkbox(label="Slerp interpolation", value=False) + # aesthetic_imgs = gr.Dropdown(sorted(aesthetic_embeddings.keys()), + # label="Aesthetic imgs embedding", + # value="None") + # + # with gr.Row(): + # aesthetic_imgs_text = gr.Textbox(label='Aesthetic text for imgs', placeholder="This text is used to rotate the feature space of the imgs embs", value="") + # aesthetic_slerp_angle = gr.Slider(label='Slerp angle',minimum=0, maximum=1, step=0.01, value=0.1) + # aesthetic_text_negative = gr.Checkbox(label="Is negative text", value=False) + + aesthetic_weight, aesthetic_steps, aesthetic_lr, aesthetic_slerp, aesthetic_imgs, aesthetic_imgs_text, aesthetic_slerp_angle, aesthetic_text_negative = aesthetic_clip.create_ui() with gr.Row(): @@ -840,6 +842,9 @@ def create_ui(wrap_gradio_gpu_call): width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512) height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) + aesthetic_weight_im, aesthetic_steps_im, aesthetic_lr_im, aesthetic_slerp_im, aesthetic_imgs_im, aesthetic_imgs_text_im, aesthetic_slerp_angle_im, aesthetic_text_negative_im = aesthetic_clip.create_ui() + + with gr.Row(): restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1) tiling = gr.Checkbox(label='Tiling', value=False) @@ -944,6 +949,14 @@ def create_ui(wrap_gradio_gpu_call): inpainting_mask_invert, img2img_batch_input_dir, img2img_batch_output_dir, + aesthetic_lr_im, + aesthetic_weight_im, + aesthetic_steps_im, + aesthetic_imgs_im, + aesthetic_slerp_im, + aesthetic_imgs_text_im, + aesthetic_slerp_angle_im, + aesthetic_text_negative_im, ] + custom_inputs, outputs=[ img2img_gallery, @@ -1283,7 +1296,7 @@ def create_ui(wrap_gradio_gpu_call): ) create_embedding_ae.click( - fn=modules.aesthetic_clip.generate_imgs_embd, + fn=aesthetic_clip.generate_imgs_embd, inputs=[ new_embedding_name_ae, process_src_ae, @@ -1291,6 +1304,7 @@ def create_ui(wrap_gradio_gpu_call): ], outputs=[ aesthetic_imgs, + aesthetic_imgs_im, ti_output, ti_outcome, ] -- cgit v1.2.3 From c8045c5ad4f99deb3a19add06e0457de1df62b05 Mon Sep 17 00:00:00 2001 From: SGKoishi Date: Sun, 16 Oct 2022 10:08:23 -0700 Subject: The hide_ui_dir_config flag also restrict write attempt to path settings --- modules/shared.py | 10 ++++++++++ modules/ui.py | 8 +++++++- 2 files changed, 17 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/shared.py b/modules/shared.py index dcab0af9..c2775603 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -77,6 +77,16 @@ parser.add_argument("--disable-safe-unpickle", action='store_true', help="disabl cmd_opts = parser.parse_args() +restricted_opts = [ + "samples_filename_pattern", + "outdir_samples", + "outdir_txt2img_samples", + "outdir_img2img_samples", + "outdir_extras_samples", + "outdir_grids", + "outdir_txt2img_grids", + "outdir_save", +] devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_bsrgan, devices.device_esrgan, devices.device_scunet, devices.device_codeformer = \ (devices.cpu if any(y in cmd_opts.use_cpu for y in [x, 'all']) else devices.get_optimal_device() for x in ['sd', 'interrogate', 'gfpgan', 'bsrgan', 'esrgan', 'scunet', 'codeformer']) diff --git a/modules/ui.py b/modules/ui.py index 7b0d5a92..43dc88fc 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -25,7 +25,7 @@ import gradio.routes from modules import sd_hijack, sd_models from modules.paths import script_path -from modules.shared import opts, cmd_opts +from modules.shared import opts, cmd_opts, restricted_opts if cmd_opts.deepdanbooru: from modules.deepbooru import get_deepbooru_tags import modules.shared as shared @@ -1430,6 +1430,9 @@ Requested path was: {f} if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False: continue + if cmd_opts.hide_ui_dir_config and key in restricted_opts: + continue + oldval = opts.data.get(key, None) opts.data[key] = value @@ -1447,6 +1450,9 @@ Requested path was: {f} if not opts.same_type(value, opts.data_labels[key].default): return gr.update(visible=True), opts.dumpjson() + if cmd_opts.hide_ui_dir_config and key in restricted_opts: + return gr.update(value=oldval), opts.dumpjson() + oldval = opts.data.get(key, None) opts.data[key] = value -- cgit v1.2.3 From 8c6a981d5d9ef30381ac2327460285111550acbc Mon Sep 17 00:00:00 2001 From: Michoko Date: Mon, 17 Oct 2022 11:05:05 +0200 Subject: Added dark mode switch Launch the UI in dark mode with the --dark-mode switch --- javascript/ui.js | 7 +++++++ modules/shared.py | 2 +- modules/ui.py | 2 ++ 3 files changed, 10 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index 9e1bed4c..bfa72885 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -1,5 +1,12 @@ // various functions for interation with ui.py not large enough to warrant putting them in separate files +function go_dark_mode(){ + gradioURL = window.location.href + if (!gradioURL.endsWith('?__theme=dark')) { + window.location.replace(gradioURL + '?__theme=dark'); + } +} + function selected_gallery_index(){ var buttons = gradioApp().querySelectorAll('[style="display: block;"].tabitem .gallery-item') var button = gradioApp().querySelector('[style="display: block;"].tabitem .gallery-item.\\!ring-2') diff --git a/modules/shared.py b/modules/shared.py index c2775603..cbf158e4 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -69,13 +69,13 @@ parser.add_argument("--gradio-img2img-tool", type=str, help='gradio image upload parser.add_argument("--opt-channelslast", action='store_true', help="change memory type for stable diffusion to channels last") parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(script_path, 'styles.csv')) parser.add_argument("--autolaunch", action='store_true', help="open the webui URL in the system's default browser upon launch", default=False) +parser.add_argument("--dark-mode", action='store_true', help="launches the UI in dark mode", default=False) parser.add_argument("--use-textbox-seed", action='store_true', help="use textbox for seeds in UI (no up/down, but possible to input long seeds)", default=False) parser.add_argument("--disable-console-progressbars", action='store_true', help="do not output progressbars to console", default=False) parser.add_argument("--enable-console-prompts", action='store_true', help="print prompts to console when generating with txt2img and img2img", default=False) parser.add_argument('--vae-path', type=str, help='Path to Variational Autoencoders model', default=None) parser.add_argument("--disable-safe-unpickle", action='store_true', help="disable checking pytorch models for malicious code", default=False) - cmd_opts = parser.parse_args() restricted_opts = [ "samples_filename_pattern", diff --git a/modules/ui.py b/modules/ui.py index 43dc88fc..a0cd052e 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1783,6 +1783,8 @@ for filename in sorted(os.listdir(jsdir)): with open(os.path.join(jsdir, filename), "r", encoding="utf8") as jsfile: javascript += f"\n" +if cmd_opts.dark_mode: + javascript += "\n\n" if 'gradio_routes_templates_response' not in globals(): def template_response(*args, **kwargs): -- cgit v1.2.3 From 665beebc0825a6fad410c8252f27f6f6f0bd900b Mon Sep 17 00:00:00 2001 From: Michoko Date: Mon, 17 Oct 2022 18:24:24 +0200 Subject: Use of a --theme argument for more flexibility Added possibility to set the theme (light or dark) --- javascript/ui.js | 6 +++--- modules/shared.py | 2 +- modules/ui.py | 4 ++-- 3 files changed, 6 insertions(+), 6 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index bfa72885..cfd0dcd3 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -1,9 +1,9 @@ // various functions for interation with ui.py not large enough to warrant putting them in separate files -function go_dark_mode(){ +function set_theme(theme){ gradioURL = window.location.href - if (!gradioURL.endsWith('?__theme=dark')) { - window.location.replace(gradioURL + '?__theme=dark'); + if (!gradioURL.includes('?__theme=')) { + window.location.replace(gradioURL + '?__theme=' + theme); } } diff --git a/modules/shared.py b/modules/shared.py index cbf158e4..fa084c69 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -69,7 +69,7 @@ parser.add_argument("--gradio-img2img-tool", type=str, help='gradio image upload parser.add_argument("--opt-channelslast", action='store_true', help="change memory type for stable diffusion to channels last") parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(script_path, 'styles.csv')) parser.add_argument("--autolaunch", action='store_true', help="open the webui URL in the system's default browser upon launch", default=False) -parser.add_argument("--dark-mode", action='store_true', help="launches the UI in dark mode", default=False) +parser.add_argument("--theme", type=str, help="launches the UI with light or dark theme", default=None) parser.add_argument("--use-textbox-seed", action='store_true', help="use textbox for seeds in UI (no up/down, but possible to input long seeds)", default=False) parser.add_argument("--disable-console-progressbars", action='store_true', help="do not output progressbars to console", default=False) parser.add_argument("--enable-console-prompts", action='store_true', help="print prompts to console when generating with txt2img and img2img", default=False) diff --git a/modules/ui.py b/modules/ui.py index a0cd052e..d41715fa 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1783,8 +1783,8 @@ for filename in sorted(os.listdir(jsdir)): with open(os.path.join(jsdir, filename), "r", encoding="utf8") as jsfile: javascript += f"\n" -if cmd_opts.dark_mode: - javascript += "\n\n" +if cmd_opts.theme is not None: + javascript += f"\n\n" if 'gradio_routes_templates_response' not in globals(): def template_response(*args, **kwargs): -- cgit v1.2.3 From 695377a8b9f7de28b880d96487a9ddf7230cff14 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Mon, 17 Oct 2022 19:56:23 +0300 Subject: make modelmerger work with ui-config.json --- modules/ui.py | 1 + 1 file changed, 1 insertion(+) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 43dc88fc..533b1db3 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1767,6 +1767,7 @@ Requested path was: {f} visit(txt2img_interface, loadsave, "txt2img") visit(img2img_interface, loadsave, "img2img") visit(extras_interface, loadsave, "extras") + visit(modelmerger_interface, loadsave, "modelmerger") if not error_loading and (not os.path.exists(ui_config_file) or settings_count != len(ui_settings)): with open(ui_config_file, "w", encoding="utf8") as file: -- cgit v1.2.3 From cf47d13c1e11fcb7169bac7488d2c39e579ee491 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Mon, 17 Oct 2022 21:15:32 +0300 Subject: localization support --- javascript/localization.js | 146 ++++++++++++++++++++++++++ localizations/Put localization files here.txt | 0 modules/localization.py | 31 ++++++ modules/shared.py | 7 +- modules/ui.py | 33 ++++-- script.js | 10 +- style.css | 2 +- 7 files changed, 211 insertions(+), 18 deletions(-) create mode 100644 javascript/localization.js create mode 100644 localizations/Put localization files here.txt create mode 100644 modules/localization.py (limited to 'modules/ui.py') diff --git a/javascript/localization.js b/javascript/localization.js new file mode 100644 index 00000000..e6644635 --- /dev/null +++ b/javascript/localization.js @@ -0,0 +1,146 @@ + +// localization = {} -- the dict with translations is created by the backend + +ignore_ids_for_localization={ + setting_sd_hypernetwork: 'OPTION', + setting_sd_model_checkpoint: 'OPTION', + setting_realesrgan_enabled_models: 'OPTION', + modelmerger_primary_model_name: 'OPTION', + modelmerger_secondary_model_name: 'OPTION', + modelmerger_tertiary_model_name: 'OPTION', + train_embedding: 'OPTION', + train_hypernetwork: 'OPTION', + txt2img_style_index: 'OPTION', + txt2img_style2_index: 'OPTION', + img2img_style_index: 'OPTION', + img2img_style2_index: 'OPTION', + setting_random_artist_categories: 'SPAN', + setting_face_restoration_model: 'SPAN', + setting_realesrgan_enabled_models: 'SPAN', + extras_upscaler_1: 'SPAN', + extras_upscaler_2: 'SPAN', +} + +re_num = /^[\.\d]+$/ +re_emoji = /[\p{Extended_Pictographic}\u{1F3FB}-\u{1F3FF}\u{1F9B0}-\u{1F9B3}]/u + +original_lines = {} +translated_lines = {} + +function textNodesUnder(el){ + var n, a=[], walk=document.createTreeWalker(el,NodeFilter.SHOW_TEXT,null,false); + while(n=walk.nextNode()) a.push(n); + return a; +} + +function canBeTranslated(node, text){ + if(! text) return false; + if(! node.parentElement) return false; + + parentType = node.parentElement.nodeName + if(parentType=='SCRIPT' || parentType=='STYLE' || parentType=='TEXTAREA') return false; + + if (parentType=='OPTION' || parentType=='SPAN'){ + pnode = node + for(var level=0; level<4; level++){ + pnode = pnode.parentElement + if(! pnode) break; + + if(ignore_ids_for_localization[pnode.id] == parentType) return false; + } + } + + if(re_num.test(text)) return false; + if(re_emoji.test(text)) return false; + return true +} + +function getTranslation(text){ + if(! text) return undefined + + if(translated_lines[text] === undefined){ + original_lines[text] = 1 + } + + tl = localization[text] + if(tl !== undefined){ + translated_lines[tl] = 1 + } + + return tl +} + +function processTextNode(node){ + text = node.textContent.trim() + + if(! canBeTranslated(node, text)) return + + tl = getTranslation(text) + if(tl !== undefined){ + node.textContent = tl + } +} + +function processNode(node){ + if(node.nodeType == 3){ + processTextNode(node) + return + } + + if(node.title){ + tl = getTranslation(node.title) + if(tl !== undefined){ + node.title = tl + } + } + + if(node.placeholder){ + tl = getTranslation(node.placeholder) + if(tl !== undefined){ + node.placeholder = tl + } + } + + textNodesUnder(node).forEach(function(node){ + processTextNode(node) + }) +} + +function dumpTranslations(){ + dumped = {} + + Object.keys(original_lines).forEach(function(text){ + if(dumped[text] !== undefined) return + + dumped[text] = localization[text] || text + }) + + return dumped +} + +onUiUpdate(function(m){ + m.forEach(function(mutation){ + mutation.addedNodes.forEach(function(node){ + processNode(node) + }) + }); +}) + + +document.addEventListener("DOMContentLoaded", function() { + processNode(gradioApp()) +}) + +function download_localization() { + text = JSON.stringify(dumpTranslations(), null, 4) + + var element = document.createElement('a'); + element.setAttribute('href', 'data:text/plain;charset=utf-8,' + encodeURIComponent(text)); + element.setAttribute('download', "localization.json"); + element.style.display = 'none'; + document.body.appendChild(element); + + element.click(); + + document.body.removeChild(element); +} diff --git a/localizations/Put localization files here.txt b/localizations/Put localization files here.txt new file mode 100644 index 00000000..e69de29b diff --git a/modules/localization.py b/modules/localization.py new file mode 100644 index 00000000..b1810cda --- /dev/null +++ b/modules/localization.py @@ -0,0 +1,31 @@ +import json +import os +import sys +import traceback + +localizations = {} + + +def list_localizations(dirname): + localizations.clear() + + for file in os.listdir(dirname): + fn, ext = os.path.splitext(file) + if ext.lower() != ".json": + continue + + localizations[fn] = os.path.join(dirname, file) + + +def localization_js(current_localization_name): + fn = localizations.get(current_localization_name, None) + data = {} + if fn is not None: + try: + with open(fn, "r", encoding="utf8") as file: + data = json.load(file) + except Exception: + print(f"Error loading localization from {fn}:", file=sys.stderr) + print(traceback.format_exc(), file=sys.stderr) + + return f"var localization = {json.dumps(data)}\n" diff --git a/modules/shared.py b/modules/shared.py index c2775603..2a2b0427 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -13,7 +13,7 @@ import modules.memmon import modules.sd_models import modules.styles import modules.devices as devices -from modules import sd_samplers, sd_models +from modules import sd_samplers, sd_models, localization from modules.hypernetworks import hypernetwork from modules.paths import models_path, script_path, sd_path @@ -31,6 +31,7 @@ parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI") parser.add_argument("--embeddings-dir", type=str, default=os.path.join(script_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)") parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory") +parser.add_argument("--localizations-dir", type=str, default=os.path.join(script_path, 'localizations'), help="localizations directory") parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui") parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage") parser.add_argument("--lowvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a lot of speed for very low VRM usage") @@ -103,7 +104,6 @@ os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True) hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) loaded_hypernetwork = None - def reload_hypernetworks(): global hypernetworks @@ -151,6 +151,8 @@ interrogator = modules.interrogate.InterrogateModels("interrogate") face_restorers = [] +localization.list_localizations(cmd_opts.localizations_dir) + def realesrgan_models_names(): import modules.realesrgan_model @@ -296,6 +298,7 @@ options_templates.update(options_section(('ui', "User interface"), { "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"), "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."), 'quicksettings': OptionInfo("sd_model_checkpoint", "Quicksettings list"), + 'localization': OptionInfo("None", "Localization (requires restart)", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)), })) options_templates.update(options_section(('sampler-params', "Sampler parameters"), { diff --git a/modules/ui.py b/modules/ui.py index 533b1db3..656bab7a 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -23,7 +23,7 @@ import gradio as gr import gradio.utils import gradio.routes -from modules import sd_hijack, sd_models +from modules import sd_hijack, sd_models, localization from modules.paths import script_path from modules.shared import opts, cmd_opts, restricted_opts if cmd_opts.deepdanbooru: @@ -1056,10 +1056,10 @@ def create_ui(wrap_gradio_gpu_call): upscaling_crop = gr.Checkbox(label='Crop to fit', value=True) with gr.Group(): - extras_upscaler_1 = gr.Radio(label='Upscaler 1', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") + extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") with gr.Group(): - extras_upscaler_2 = gr.Radio(label='Upscaler 2', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") + extras_upscaler_2 = gr.Radio(label='Upscaler 2', celem_id="extras_upscaler_2", hoices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=1) with gr.Group(): @@ -1224,10 +1224,10 @@ def create_ui(wrap_gradio_gpu_call): with gr.Tab(label="Train"): gr.HTML(value="

Train an embedding; must specify a directory with a set of 1:1 ratio images

") with gr.Row(): - train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) + train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name") with gr.Row(): - train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()]) + train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=[x for x in shared.hypernetworks.keys()]) create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted([x for x in shared.hypernetworks.keys()])}, "refresh_train_hypernetwork_name") learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.005") batch_size = gr.Number(label='Batch size', value=1, precision=0) @@ -1376,16 +1376,18 @@ def create_ui(wrap_gradio_gpu_call): else: raise Exception(f'bad options item type: {str(t)} for key {key}') + elem_id = "setting_"+key + if info.refresh is not None: if is_quicksettings: - res = comp(label=info.label, value=fun, **(args or {})) - refresh_button = create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key) + res = comp(label=info.label, value=fun, elem_id=elem_id, **(args or {})) + create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key) else: with gr.Row(variant="compact"): - res = comp(label=info.label, value=fun, **(args or {})) - refresh_button = create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key) + res = comp(label=info.label, value=fun, elem_id=elem_id, **(args or {})) + create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key) else: - res = comp(label=info.label, value=fun, **(args or {})) + res = comp(label=info.label, value=fun, elem_id=elem_id, **(args or {})) return res @@ -1509,6 +1511,9 @@ Requested path was: {f} with gr.Row(): request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications") + download_localization = gr.Button(value='Download localization template', elem_id="download_localization") + + with gr.Row(): reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary') restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary') @@ -1519,6 +1524,13 @@ Requested path was: {f} _js='function(){}' ) + download_localization.click( + fn=lambda: None, + inputs=[], + outputs=[], + _js='download_localization' + ) + def reload_scripts(): modules.scripts.reload_script_body_only() @@ -1784,6 +1796,7 @@ for filename in sorted(os.listdir(jsdir)): with open(os.path.join(jsdir, filename), "r", encoding="utf8") as jsfile: javascript += f"\n" +javascript += f"\n" if 'gradio_routes_templates_response' not in globals(): def template_response(*args, **kwargs): diff --git a/script.js b/script.js index 88f2c839..8b3b67e3 100644 --- a/script.js +++ b/script.js @@ -21,20 +21,20 @@ function onUiTabChange(callback){ uiTabChangeCallbacks.push(callback) } -function runCallback(x){ +function runCallback(x, m){ try { - x() + x(m) } catch (e) { (console.error || console.log).call(console, e.message, e); } } -function executeCallbacks(queue) { - queue.forEach(runCallback) +function executeCallbacks(queue, m) { + queue.forEach(function(x){runCallback(x, m)}) } document.addEventListener("DOMContentLoaded", function() { var mutationObserver = new MutationObserver(function(m){ - executeCallbacks(uiUpdateCallbacks); + executeCallbacks(uiUpdateCallbacks, m); const newTab = get_uiCurrentTab(); if ( newTab && ( newTab !== uiCurrentTab ) ) { uiCurrentTab = newTab; diff --git a/style.css b/style.css index 71eb4d20..9dc4b696 100644 --- a/style.css +++ b/style.css @@ -478,7 +478,7 @@ input[type="range"]{ padding: 0; } -#refresh_sd_model_checkpoint, #refresh_sd_hypernetwork, #refresh_train_hypernetwork_name, #refresh_train_embedding_name{ +#refresh_sd_model_checkpoint, #refresh_sd_hypernetwork, #refresh_train_hypernetwork_name, #refresh_train_embedding_name, #refresh_localization{ max-width: 2.5em; min-width: 2.5em; height: 2.4em; -- cgit v1.2.3 From ab3f997c0c4a1423a82623ae1d4d3c66005bb8da Mon Sep 17 00:00:00 2001 From: Jordan Hall Date: Mon, 17 Oct 2022 20:59:44 +0100 Subject: Fix typo in 'choices' when loading upscaler 2 config --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 656bab7a..e4ead347 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1059,7 +1059,7 @@ def create_ui(wrap_gradio_gpu_call): extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") with gr.Group(): - extras_upscaler_2 = gr.Radio(label='Upscaler 2', celem_id="extras_upscaler_2", hoices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") + extras_upscaler_2 = gr.Radio(label='Upscaler 2', celem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=1) with gr.Group(): -- cgit v1.2.3 From 7432b6f4d2c3001895fc75411a34afae1810c1a2 Mon Sep 17 00:00:00 2001 From: Mykeehu Date: Tue, 18 Oct 2022 07:15:38 +0200 Subject: Fix typo "celem_id" to "elem_id" --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index e4ead347..2a7f64f9 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1059,7 +1059,7 @@ def create_ui(wrap_gradio_gpu_call): extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") with gr.Group(): - extras_upscaler_2 = gr.Radio(label='Upscaler 2', celem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") + extras_upscaler_2 = gr.Radio(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=1) with gr.Group(): -- cgit v1.2.3 From 8b02662215917d39f76f86b703a322818d5a8ad4 Mon Sep 17 00:00:00 2001 From: trufty Date: Mon, 17 Oct 2022 10:58:21 -0400 Subject: Disable auto weights swap with config option --- modules/shared.py | 1 + modules/ui.py | 4 ++++ 2 files changed, 5 insertions(+) (limited to 'modules/ui.py') diff --git a/modules/shared.py b/modules/shared.py index 9603d26e..8a1d1881 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -266,6 +266,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "enable_emphasis": OptionInfo(True, "Emphasis: use (text) to make model pay more attention to text and [text] to make it pay less attention"), "use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."), "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"), + "disable_weights_auto_swap": OptionInfo(False, "Disable auto swapping weights to match model hash in prompts"), "comma_padding_backtrack": OptionInfo(20, "Increase coherency by padding from the last comma within n tokens when using more than 75 tokens", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1 }), "filter_nsfw": OptionInfo(False, "Filter NSFW content"), 'CLIP_stop_at_last_layers': OptionInfo(1, "Stop At last layers of CLIP model", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}), diff --git a/modules/ui.py b/modules/ui.py index 1dae4a65..75eb0b0c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -542,6 +542,10 @@ def apply_setting(key, value): if value is None: return gr.update() + # dont allow model to be swapped when model hash exists in prompt + if key == "sd_model_checkpoint" and opts.disable_weights_auto_swap: + return gr.update() + if key == "sd_model_checkpoint": ckpt_info = sd_models.get_closet_checkpoint_match(value) -- cgit v1.2.3 From 97d3ba3941536215ea15431886c7f28300a9d915 Mon Sep 17 00:00:00 2001 From: ふぁ <34892635+fa0311@users.noreply.github.com> Date: Tue, 18 Oct 2022 17:29:42 +0900 Subject: Add scripts to ui-config,json --- modules/scripts.py | 15 +++++++++++++-- modules/ui.py | 5 +++++ 2 files changed, 18 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/scripts.py b/modules/scripts.py index ac66d448..3402066d 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -96,6 +96,7 @@ def wrap_call(func, filename, funcname, *args, default=None, **kwargs): class ScriptRunner: def __init__(self): self.scripts = [] + self.titles = [] def setup_ui(self, is_img2img): for script_class, path in scripts_data: @@ -107,9 +108,10 @@ class ScriptRunner: self.scripts.append(script) - titles = [wrap_call(script.title, script.filename, "title") or f"{script.filename} [error]" for script in self.scripts] + self.titles = [wrap_call(script.title, script.filename, "title") or f"{script.filename} [error]" for script in self.scripts] - dropdown = gr.Dropdown(label="Script", choices=["None"] + titles, value="None", type="index") + dropdown = gr.Dropdown(label="Script", choices=["None"] + self.titles, value="None", type="index") + dropdown.save_to_config = True inputs = [dropdown] for script in self.scripts: @@ -139,6 +141,15 @@ class ScriptRunner: return [ui.gr_show(True if i == 0 else args_from <= i < args_to) for i in range(len(inputs))] + def init_field(title): + if title == "None": + return + script_index = self.titles.index(title) + script = self.scripts[script_index] + for i in range(script.args_from, script.args_to): + inputs[i].visible = True + + dropdown.init_field = init_field dropdown.change( fn=select_script, inputs=[dropdown], diff --git a/modules/ui.py b/modules/ui.py index 75eb0b0c..39afbc4e 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1753,6 +1753,11 @@ Requested path was: {f} print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.') else: setattr(obj, field, saved_value) + if getattr(x, 'init_field', False): + try: + x.init_field(saved_value) + except Exception: + print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.') if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number] and x.visible: apply_field(x, 'visible') -- cgit v1.2.3 From de29ec0743fcfb141d8891a3ccbd537ea71bf5b4 Mon Sep 17 00:00:00 2001 From: ふぁ <34892635+fa0311@users.noreply.github.com> Date: Tue, 18 Oct 2022 18:15:00 +0900 Subject: Remove exception handling --- modules/ui.py | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 39afbc4e..b38bfb3f 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1754,10 +1754,7 @@ Requested path was: {f} else: setattr(obj, field, saved_value) if getattr(x, 'init_field', False): - try: - x.init_field(saved_value) - except Exception: - print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.') + x.init_field(saved_value) if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number] and x.visible: apply_field(x, 'visible') -- cgit v1.2.3 From 3003438088502774628656790d83fc8074d51ab4 Mon Sep 17 00:00:00 2001 From: ふぁ <34892635+fa0311@users.noreply.github.com> Date: Tue, 18 Oct 2022 18:51:57 +0900 Subject: Add visible for dropdown --- modules/ui.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index b38bfb3f..fb6eb5a0 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1737,7 +1737,7 @@ Requested path was: {f} print(traceback.format_exc(), file=sys.stderr) def loadsave(path, x): - def apply_field(obj, field, condition=None): + def apply_field(obj, field, condition=None, init_field=None): key = path + "/" + field if getattr(obj,'custom_script_source',None) is not None: @@ -1753,8 +1753,8 @@ Requested path was: {f} print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.') else: setattr(obj, field, saved_value) - if getattr(x, 'init_field', False): - x.init_field(saved_value) + if init_field is not None: + init_field(saved_value) if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number] and x.visible: apply_field(x, 'visible') @@ -1780,7 +1780,8 @@ Requested path was: {f} # Since there are many dropdowns that shouldn't be saved, # we only mark dropdowns that should be saved. if type(x) == gr.Dropdown and getattr(x, 'save_to_config', False): - apply_field(x, 'value', lambda val: val in x.choices) + apply_field(x, 'value', lambda val: val in x.choices, getattr(x, 'init_field', None)) + apply_field(x, 'visible') visit(txt2img_interface, loadsave, "txt2img") visit(img2img_interface, loadsave, "img2img") -- cgit v1.2.3 From eb299527b1e5d1f83a14641647fca72e8fb305ac Mon Sep 17 00:00:00 2001 From: yfszzx Date: Tue, 18 Oct 2022 20:14:11 +0800 Subject: Image browser --- javascript/images_history.js | 19 ++-- modules/images_history.py | 227 ++++++++++++++++++++++++++++--------------- modules/shared.py | 7 +- modules/ui.py | 2 +- uitest.bat | 2 + uitest.py | 124 +++++++++++++++++++++++ 6 files changed, 289 insertions(+), 92 deletions(-) create mode 100644 uitest.bat create mode 100644 uitest.py (limited to 'modules/ui.py') diff --git a/javascript/images_history.js b/javascript/images_history.js index 3c028bc6..182d730b 100644 --- a/javascript/images_history.js +++ b/javascript/images_history.js @@ -145,9 +145,10 @@ function images_history_enable_del_buttons(){ } function images_history_init(){ - var loaded = gradioApp().getElementById("images_history_reconstruct_directory") - if (loaded){ - var init_status = loaded.querySelector("input").checked + // var loaded = gradioApp().getElementById("images_history_reconstruct_directory") + // if (loaded){ + // var init_status = loaded.querySelector("input").checked + if (gradioApp().getElementById("images_history_finish_render")){ for (var i in images_history_tab_list ){ tab = images_history_tab_list[i]; gradioApp().getElementById(tab + '_images_history').classList.add("images_history_cantainor"); @@ -163,19 +164,17 @@ function images_history_init(){ for (var i in images_history_tab_list){ var tabname = images_history_tab_list[i] tab_btns[i].setAttribute("tabname", tabname); - if (init_status){ - tab_btns[i].addEventListener('click', images_history_click_tab); - } - } - if (init_status){ - tab_btns[0].click(); + // if (!init_status){ + // tab_btns[i].addEventListener('click', images_history_click_tab); + // } + tab_btns[i].addEventListener('click', images_history_click_tab); } } else { setTimeout(images_history_init, 500); } } -var images_history_tab_list = ["txt2img", "img2img", "extras", "saved"]; +var images_history_tab_list = ["custom", "txt2img", "img2img", "extras", "saved"]; setTimeout(images_history_init, 500); document.addEventListener("DOMContentLoaded", function() { var mutationObserver = new MutationObserver(function(m){ diff --git a/modules/images_history.py b/modules/images_history.py index 20324557..d56f3a25 100644 --- a/modules/images_history.py +++ b/modules/images_history.py @@ -4,6 +4,7 @@ import time import hashlib import gradio system_bak_path = "webui_log_and_bak" +browser_tabname = "custom" def is_valid_date(date): try: time.strptime(date, "%Y%m%d") @@ -99,13 +100,15 @@ def auto_sorting(dir_name): date_list.append(today) return sorted(date_list, reverse=True) -def archive_images(dir_name, date_to): +def archive_images(dir_name, date_to): + filenames = [] loads_num =int(opts.images_history_num_per_page * opts.images_history_pages_num) + today = time.strftime("%Y%m%d",time.localtime(time.time())) + date_to = today if date_to is None or date_to == "" else date_to + date_to_bak = date_to if opts.images_history_reconstruct_directory: - date_list = auto_sorting(dir_name) - today = time.strftime("%Y%m%d",time.localtime(time.time())) - date_to = today if date_to is None or date_to == "" else date_to + date_list = auto_sorting(dir_name) for date in date_list: if date <= date_to: path = os.path.join(dir_name, date) @@ -120,7 +123,7 @@ def archive_images(dir_name, date_to): tmparray = [(os.path.getmtime(file), file) for file in filenames ] date_stamp = time.mktime(time.strptime(date_to, "%Y%m%d")) + 86400 filenames = [] - date_list = {} + date_list = {date_to:None} date = time.strftime("%Y%m%d",time.localtime(time.time())) for t, f in tmparray: date = time.strftime("%Y%m%d",time.localtime(t)) @@ -133,22 +136,29 @@ def archive_images(dir_name, date_to): date = sort_array[loads_num][2] filenames = [x[1] for x in sort_array] else: - date = None if len(sort_array) == 0 else sort_array[-1][2] + date = date_to if len(sort_array) == 0 else sort_array[-1][2] filenames = [x[1] for x in sort_array] - filenames = [x[1] for x in sort_array if x[2]>= date] - _, image_list, _, visible_num = get_recent_images(1, 0, filenames) + filenames = [x[1] for x in sort_array if x[2]>= date] + num = len(filenames) + last_date_from = date_to_bak if num == 0 else time.strftime("%Y%m%d", time.localtime(time.mktime(time.strptime(date, "%Y%m%d")) - 1000)) + date = date[:4] + "-" + date[4:6] + "-" + date[6:8] + date_to_bak = date_to_bak[:4] + "-" + date_to_bak[4:6] + "-" + date_to_bak[6:8] + load_info = f"Loaded {(num + 1) // opts.images_history_pages_num} pades, {num} images, during {date} - {date_to_bak}" + _, image_list, _, _, visible_num = get_recent_images(1, 0, filenames) return ( gradio.Dropdown.update(choices=date_list, value=date_to), - date, + load_info, filenames, 1, image_list, "", - visible_num + "", + visible_num, + last_date_from ) -def newest_click(dir_name, date_to): - return archive_images(dir_name, time.strftime("%Y%m%d",time.localtime(time.time()))) + + def delete_image(delete_num, name, filenames, image_index, visible_num): if name == "": @@ -196,7 +206,29 @@ def get_recent_images(page_index, step, filenames): length = len(filenames) visible_num = num_of_imgs_per_page if idx_frm + num_of_imgs_per_page <= length else length % num_of_imgs_per_page visible_num = num_of_imgs_per_page if visible_num == 0 else visible_num - return page_index, image_list, "", visible_num + return page_index, image_list, "", "", visible_num + +def newest_click(date_to): + if date_to is None: + return time.strftime("%Y%m%d",time.localtime(time.time())), [] + else: + return None, [] +def forward_click(last_date_from, date_to_recorder): + if len(date_to_recorder) == 0: + return None, [] + if last_date_from == date_to_recorder[-1]: + date_to_recorder = date_to_recorder[:-1] + if len(date_to_recorder) == 0: + return None, [] + return date_to_recorder[-1], date_to_recorder[:-1] + +def backward_click(last_date_from, date_to_recorder): + if last_date_from is None or last_date_from == "": + return time.strftime("%Y%m%d",time.localtime(time.time())), [] + if len(date_to_recorder) == 0 or last_date_from != date_to_recorder[-1]: + date_to_recorder.append(last_date_from) + return last_date_from, date_to_recorder + def first_page_click(page_index, filenames): return get_recent_images(1, 0, filenames) @@ -214,13 +246,33 @@ def page_index_change(page_index, filenames): return get_recent_images(page_index, 0, filenames) def show_image_info(tabname_box, num, page_index, filenames): - file = filenames[int(num) + int((page_index - 1) * int(opts.images_history_num_per_page))] - return file, num, file + file = filenames[int(num) + int((page_index - 1) * int(opts.images_history_num_per_page))] + tm = time.strftime("%Y-%m-%d %H:%M:%S",time.localtime(os.path.getmtime(file))) + return file, tm, num, file def enable_page_buttons(): return gradio.update(visible=True) +def change_dir(img_dir, date_to): + warning = None + try: + if os.path.exists(img_dir): + try: + f = os.listdir(img_dir) + except: + warning = f"'{img_dir} is not a directory" + else: + warning = "The directory is not exist" + except: + warning = "The format of the directory is incorrect" + if warning is None: + today = time.strftime("%Y%m%d",time.localtime(time.time())) + return gradio.update(visible=False), gradio.update(visible=True), None, None if date_to != today else today + else: + return gradio.update(visible=True), gradio.update(visible=False), warning, date_to + def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): + custom_dir = False if tabname == "txt2img": dir_name = opts.outdir_txt2img_samples elif tabname == "img2img": @@ -229,69 +281,85 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): dir_name = opts.outdir_extras_samples elif tabname == "saved": dir_name = opts.outdir_save + else: + custom_dir = True + dir_name = None + + if not custom_dir: + d = dir_name.split("/") + dir_name = d[0] + for p in d[1:]: + dir_name = os.path.join(dir_name, p) + if not os.path.exists(dir_name): + os.makedirs(dir_name) - d = dir_name.split("/") - dir_name = d[0] - for p in d[1:]: - dir_name = os.path.join(dir_name, p) - if not os.path.exists(dir_name): - os.makedirs(dir_name) - - with gr.Column() as page_panel: - with gr.Row(visible=False) as turn_page_buttons: - renew_page = gr.Button('Refresh page', elem_id=tabname + "_images_history_renew_page") - first_page = gr.Button('First Page') - prev_page = gr.Button('Prev Page') - page_index = gr.Number(value=1, label="Page Index") - next_page = gr.Button('Next Page') - end_page = gr.Button('End Page') - - with gr.Row(elem_id=tabname + "_images_history"): - with gr.Column(scale=2): - with gr.Row(): - newest = gr.Button('Reload', elem_id=tabname + "_images_history_start") - date_from = gr.Textbox(label="Date from", interactive=False) - date_to = gr.Dropdown(label="Date to") - - history_gallery = gr.Gallery(show_label=False, elem_id=tabname + "_images_history_gallery").style(grid=6) - with gr.Row(): - delete_num = gr.Number(value=1, interactive=True, label="number of images to delete consecutively next") - delete = gr.Button('Delete', elem_id=tabname + "_images_history_del_button") - - with gr.Column(): - with gr.Row(): - if tabname != "saved": - save_btn = gr.Button('Save') - pnginfo_send_to_txt2img = gr.Button('Send to txt2img') - pnginfo_send_to_img2img = gr.Button('Send to img2img') - with gr.Row(): - with gr.Column(): - img_file_info = gr.Textbox(label="Generate Info", interactive=False) - img_file_name = gr.Textbox(value="", label="File Name", interactive=False) + with gr.Column() as page_panel: + with gr.Row(): + img_path = gr.Textbox(dir_name, label="Images directory", placeholder="Input images directory") + with gr.Row(visible=False) as warning: + warning_box = gr.Textbox("Message", interactive=False) + with gr.Row(visible=not custom_dir, elem_id=tabname + "_images_history") as main_panel: + with gr.Column(scale=2): + with gr.Row(): + backward = gr.Button('Backward') + date_to = gr.Dropdown(label="Date to") + forward = gr.Button('Forward') + newest = gr.Button('Reload', elem_id=tabname + "_images_history_start") + with gr.Row(): + load_info = gr.Textbox(show_label=False, interactive=False) + with gr.Row(visible=False) as turn_page_buttons: + renew_page = gr.Button('Refresh page', elem_id=tabname + "_images_history_renew_page") + first_page = gr.Button('First Page') + prev_page = gr.Button('Prev Page') + page_index = gr.Number(value=1, label="Page Index") + next_page = gr.Button('Next Page') + end_page = gr.Button('End Page') + + history_gallery = gr.Gallery(show_label=False, elem_id=tabname + "_images_history_gallery").style(grid=opts.images_history_grid_num) + with gr.Row(): + delete_num = gr.Number(value=1, interactive=True, label="number of images to delete consecutively next") + delete = gr.Button('Delete', elem_id=tabname + "_images_history_del_button") - # hiden items - with gr.Row(visible=False): - visible_img_num = gr.Number() - img_path = gr.Textbox(dir_name) - tabname_box = gr.Textbox(tabname) - image_index = gr.Textbox(value=-1) - set_index = gr.Button('set_index', elem_id=tabname + "_images_history_set_index") - filenames = gr.State() - all_images_list = gr.State() - hidden = gr.Image(type="pil") - info1 = gr.Textbox() - info2 = gr.Textbox() + with gr.Column(): + with gr.Row(): + if tabname != "saved": + save_btn = gr.Button('Save') + pnginfo_send_to_txt2img = gr.Button('Send to txt2img') + pnginfo_send_to_img2img = gr.Button('Send to img2img') + with gr.Row(): + with gr.Column(): + img_file_info = gr.Textbox(label="Generate Info", interactive=False) + img_file_name = gr.Textbox(value="", label="File Name", interactive=False) + img_file_time= gr.Textbox(value="", label="Create Time", interactive=False) - + + # hiden items + with gr.Row(): #visible=False): + visible_img_num = gr.Number() + date_to_recorder = gr.State([]) + last_date_from = gr.Textbox() + tabname_box = gr.Textbox(tabname) + image_index = gr.Textbox(value=-1) + set_index = gr.Button('set_index', elem_id=tabname + "_images_history_set_index") + filenames = gr.State() + all_images_list = gr.State() + hidden = gr.Image(type="pil") + info1 = gr.Textbox() + info2 = gr.Textbox() + + img_path.submit(change_dir, inputs=[img_path, date_to], outputs=[warning, main_panel, warning_box, date_to]) #change date - change_date_output = [date_to, date_from, filenames, page_index, history_gallery, img_file_name, visible_img_num] - newest.click(newest_click, inputs=[img_path, date_to], outputs=change_date_output) - date_to.change(archive_images, inputs=[img_path, date_to], outputs=change_date_output) - newest.click(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") - date_to.change(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") - date_to.change(enable_page_buttons, inputs=None, outputs=[turn_page_buttons]) - newest.click(enable_page_buttons, inputs=None, outputs=[turn_page_buttons]) + change_date_output = [date_to, load_info, filenames, page_index, history_gallery, img_file_name, img_file_time, visible_img_num, last_date_from] + + date_to.change(archive_images, inputs=[img_path, date_to], outputs=change_date_output) + date_to.change(enable_page_buttons, inputs=None, outputs=[turn_page_buttons]) + date_to.change(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") + + newest.click(newest_click, inputs=[date_to], outputs=[date_to, date_to_recorder]) + forward.click(forward_click, inputs=[last_date_from, date_to_recorder], outputs=[date_to, date_to_recorder]) + backward.click(backward_click, inputs=[last_date_from, date_to_recorder], outputs=[date_to, date_to_recorder]) + #delete delete.click(delete_image, inputs=[delete_num, img_file_name, filenames, image_index, visible_img_num], outputs=[filenames, delete_num, visible_img_num]) @@ -301,7 +369,7 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): #turn page gallery_inputs = [page_index, filenames] - gallery_outputs = [page_index, history_gallery, img_file_name, visible_img_num] + gallery_outputs = [page_index, history_gallery, img_file_name, img_file_time, visible_img_num] first_page.click(first_page_click, inputs=gallery_inputs, outputs=gallery_outputs) next_page.click(next_page_click, inputs=gallery_inputs, outputs=gallery_outputs) prev_page.click(prev_page_click, inputs=gallery_inputs, outputs=gallery_outputs) @@ -317,12 +385,14 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): renew_page.click(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") # other funcitons - set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[tabname_box, image_index, page_index, filenames], outputs=[img_file_name, image_index, hidden]) + set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[tabname_box, image_index, page_index, filenames], outputs=[img_file_name, img_file_time, image_index, hidden]) img_file_name.change(fn=None, _js="images_history_enable_del_buttons", inputs=None, outputs=None) hidden.change(fn=run_pnginfo, inputs=[hidden], outputs=[info1, img_file_info, info2]) switch_dict["fn"](pnginfo_send_to_txt2img, switch_dict["t2i"], img_file_info, 'switch_to_txt2img') switch_dict["fn"](pnginfo_send_to_img2img, switch_dict["i2i"], img_file_info, 'switch_to_img2img_img2img') + + def create_history_tabs(gr, sys_opts, run_pnginfo, switch_dict): global opts; opts = sys_opts @@ -330,10 +400,11 @@ def create_history_tabs(gr, sys_opts, run_pnginfo, switch_dict): num_of_imgs_per_page = int(opts.images_history_num_per_page * opts.images_history_pages_num) with gr.Blocks(analytics_enabled=False) as images_history: with gr.Tabs() as tabs: - for tab in ["txt2img", "img2img", "extras", "saved"]: + for tab in [browser_tabname, "txt2img", "img2img", "extras", "saved"]: with gr.Tab(tab): - with gr.Blocks(analytics_enabled=False) as images_history_img2img: + with gr.Blocks(analytics_enabled=False) : show_images_history(gr, opts, tab, run_pnginfo, switch_dict) - gradio.Checkbox(opts.images_history_reconstruct_directory, elem_id="images_history_reconstruct_directory", visible=False) + #gradio.Checkbox(opts.images_history_reconstruct_directory, elem_id="images_history_reconstruct_directory", visible=False) + gradio.Checkbox(opts.images_history_reconstruct_directory, elem_id="images_history_finish_render", visible=False) return images_history diff --git a/modules/shared.py b/modules/shared.py index c2ea4186..1811018d 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -309,10 +309,11 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}), })) -options_templates.update(options_section(('images-history', "Images history"), { - "images_history_reconstruct_directory": OptionInfo(False, "Reconstruct output directory structure.This can greatly improve the speed of loading , but will change the original output directory structure"), +options_templates.update(options_section(('images-history', "Images Browser"), { + #"images_history_reconstruct_directory": OptionInfo(False, "Reconstruct output directory structure.This can greatly improve the speed of loading , but will change the original output directory structure"), "images_history_num_per_page": OptionInfo(36, "Number of pictures displayed on each page"), - "images_history_pages_num": OptionInfo(6, "Maximum number of pages per load "), + "images_history_pages_num": OptionInfo(6, "Minimum number of pages per load "), + "images_history_grid_num": OptionInfo(6, "Number of grids in each row"), })) diff --git a/modules/ui.py b/modules/ui.py index 43dc88fc..85abac4d 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1548,7 +1548,7 @@ Requested path was: {f} (img2img_interface, "img2img", "img2img"), (extras_interface, "Extras", "extras"), (pnginfo_interface, "PNG Info", "pnginfo"), - (images_history, "History", "images_history"), + (images_history, "Image Browser", "images_history"), (modelmerger_interface, "Checkpoint Merger", "modelmerger"), (train_interface, "Train", "ti"), (settings_interface, "Settings", "settings"), diff --git a/uitest.bat b/uitest.bat new file mode 100644 index 00000000..ae863af6 --- /dev/null +++ b/uitest.bat @@ -0,0 +1,2 @@ +venv\Scripts\python.exe uitest.py +pause diff --git a/uitest.py b/uitest.py new file mode 100644 index 00000000..393e2d81 --- /dev/null +++ b/uitest.py @@ -0,0 +1,124 @@ +import os +import threading +import time +import importlib +import signal +import threading + +from modules.paths import script_path + +from modules import devices, sd_samplers +import modules.codeformer_model as codeformer +import modules.extras +import modules.face_restoration +import modules.gfpgan_model as gfpgan +import modules.img2img + +import modules.lowvram +import modules.paths +import modules.scripts +import modules.sd_hijack +import modules.sd_models +import modules.shared as shared +import modules.txt2img + +import modules.ui +from modules import devices +from modules import modelloader +from modules.paths import script_path +from modules.shared import cmd_opts + +modelloader.cleanup_models() +modules.sd_models.setup_model() +codeformer.setup_model(cmd_opts.codeformer_models_path) +gfpgan.setup_model(cmd_opts.gfpgan_models_path) +shared.face_restorers.append(modules.face_restoration.FaceRestoration()) +modelloader.load_upscalers() +queue_lock = threading.Lock() + + +def wrap_queued_call(func): + def f(*args, **kwargs): + with queue_lock: + res = func(*args, **kwargs) + + return res + + return f + + +def wrap_gradio_gpu_call(func, extra_outputs=None): + def f(*args, **kwargs): + devices.torch_gc() + + shared.state.sampling_step = 0 + shared.state.job_count = -1 + shared.state.job_no = 0 + shared.state.job_timestamp = shared.state.get_job_timestamp() + shared.state.current_latent = None + shared.state.current_image = None + shared.state.current_image_sampling_step = 0 + shared.state.interrupted = False + shared.state.textinfo = None + + with queue_lock: + res = func(*args, **kwargs) + + shared.state.job = "" + shared.state.job_count = 0 + + devices.torch_gc() + + return res + + return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs) + + +modules.scripts.load_scripts(os.path.join(script_path, "scripts")) + +shared.sd_model = None #modules.sd_models.load_model() +#shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model))) + + +def webui(): + # make the program just exit at ctrl+c without waiting for anything + def sigint_handler(sig, frame): + print(f'Interrupted with signal {sig} in {frame}') + os._exit(0) + + signal.signal(signal.SIGINT, sigint_handler) + + while 1: + + demo = modules.ui.create_ui(wrap_gradio_gpu_call=wrap_gradio_gpu_call) + + demo.launch( + share=cmd_opts.share, + server_name="0.0.0.0" if cmd_opts.listen else None, + server_port=cmd_opts.port, + debug=cmd_opts.gradio_debug, + auth=[tuple(cred.split(':')) for cred in cmd_opts.gradio_auth.strip('"').split(',')] if cmd_opts.gradio_auth else None, + inbrowser=cmd_opts.autolaunch, + prevent_thread_lock=True + ) + + while 1: + time.sleep(0.5) + if getattr(demo, 'do_restart', False): + time.sleep(0.5) + demo.close() + time.sleep(0.5) + break + + sd_samplers.set_samplers() + + print('Reloading Custom Scripts') + modules.scripts.reload_scripts(os.path.join(script_path, "scripts")) + print('Reloading modules: modules.ui') + importlib.reload(modules.ui) + print('Restarting Gradio') + + + +if __name__ == "__main__": + webui() \ No newline at end of file -- cgit v1.2.3 From 538bc89c269743e56b07ef2b471d1ce0a39b6776 Mon Sep 17 00:00:00 2001 From: yfszzx Date: Wed, 19 Oct 2022 11:27:51 +0800 Subject: Image browser improved --- javascript/images_history.js | 87 ++++++++++++++-------------- modules/images_history.py | 135 ++++++++++++++++++++++++------------------- modules/shared.py | 5 ++ modules/ui.py | 2 +- 4 files changed, 123 insertions(+), 106 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/images_history.js b/javascript/images_history.js index 182d730b..c9aa76f8 100644 --- a/javascript/images_history.js +++ b/javascript/images_history.js @@ -17,14 +17,6 @@ var images_history_click_image = function(){ images_history_set_image_info(this); } -var images_history_click_tab = function(){ - var tabs_box = gradioApp().getElementById("images_history_tab"); - if (!tabs_box.classList.contains(this.getAttribute("tabname"))) { - gradioApp().getElementById(this.getAttribute("tabname") + "_images_history_start").click(); - tabs_box.classList.add(this.getAttribute("tabname")) - } -} - function images_history_disabled_del(){ gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){ btn.setAttribute('disabled','disabled'); @@ -145,57 +137,64 @@ function images_history_enable_del_buttons(){ } function images_history_init(){ - // var loaded = gradioApp().getElementById("images_history_reconstruct_directory") - // if (loaded){ - // var init_status = loaded.querySelector("input").checked - if (gradioApp().getElementById("images_history_finish_render")){ + var tabnames = gradioApp().getElementById("images_history_tabnames_list") + if (tabnames){ + images_history_tab_list = tabnames.querySelector("textarea").value.split(",") for (var i in images_history_tab_list ){ - tab = images_history_tab_list[i]; + var tab = images_history_tab_list[i]; gradioApp().getElementById(tab + '_images_history').classList.add("images_history_cantainor"); gradioApp().getElementById(tab + '_images_history_set_index').classList.add("images_history_set_index"); gradioApp().getElementById(tab + '_images_history_del_button').classList.add("images_history_del_button"); - gradioApp().getElementById(tab + '_images_history_gallery').classList.add("images_history_gallery"); - + gradioApp().getElementById(tab + '_images_history_gallery').classList.add("images_history_gallery"); + gradioApp().getElementById(tab + "_images_history_start").setAttribute("style","padding:20px;font-size:25px"); + } + + //preload + if (gradioApp().getElementById("images_history_preload").querySelector("input").checked ){ + var tabs_box = gradioApp().getElementById("tab_images_history").querySelector("div").querySelector("div").querySelector("div"); + tabs_box.setAttribute("id", "images_history_tab"); + var tab_btns = tabs_box.querySelectorAll("button"); + for (var i in images_history_tab_list){ + var tabname = images_history_tab_list[i] + tab_btns[i].setAttribute("tabname", tabname); + tab_btns[i].addEventListener('click', function(){ + var tabs_box = gradioApp().getElementById("images_history_tab"); + if (!tabs_box.classList.contains(this.getAttribute("tabname"))) { + gradioApp().getElementById(this.getAttribute("tabname") + "_images_history_start").click(); + tabs_box.classList.add(this.getAttribute("tabname")) + } + }); + } + tab_btns[0].click() } - var tabs_box = gradioApp().getElementById("tab_images_history").querySelector("div").querySelector("div").querySelector("div"); - tabs_box.setAttribute("id", "images_history_tab"); - var tab_btns = tabs_box.querySelectorAll("button"); - - for (var i in images_history_tab_list){ - var tabname = images_history_tab_list[i] - tab_btns[i].setAttribute("tabname", tabname); - // if (!init_status){ - // tab_btns[i].addEventListener('click', images_history_click_tab); - // } - tab_btns[i].addEventListener('click', images_history_click_tab); - } } else { setTimeout(images_history_init, 500); } } -var images_history_tab_list = ["custom", "txt2img", "img2img", "extras", "saved"]; +var images_history_tab_list = ""; setTimeout(images_history_init, 500); document.addEventListener("DOMContentLoaded", function() { var mutationObserver = new MutationObserver(function(m){ - for (var i in images_history_tab_list ){ - let tabname = images_history_tab_list[i] - var buttons = gradioApp().querySelectorAll('#' + tabname + '_images_history .gallery-item'); - buttons.forEach(function(bnt){ - bnt.addEventListener('click', images_history_click_image, true); - }); - - var cls_btn = gradioApp().getElementById(tabname + '_images_history_gallery').querySelector("svg"); - if (cls_btn){ - cls_btn.addEventListener('click', function(){ - gradioApp().getElementById(tabname + '_images_history_del_button').setAttribute('disabled','disabled'); - }, false); - } - - } + if (images_history_tab_list != ""){ + for (var i in images_history_tab_list ){ + let tabname = images_history_tab_list[i] + var buttons = gradioApp().querySelectorAll('#' + tabname + '_images_history .gallery-item'); + buttons.forEach(function(bnt){ + bnt.addEventListener('click', images_history_click_image, true); + }); + + var cls_btn = gradioApp().getElementById(tabname + '_images_history_gallery').querySelector("svg"); + if (cls_btn){ + cls_btn.addEventListener('click', function(){ + gradioApp().getElementById(tabname + '_images_history_renew_page').click(); + }, false); + } + + } + } }); mutationObserver.observe(gradioApp(), { childList:true, subtree:true }); - }); diff --git a/modules/images_history.py b/modules/images_history.py index a40cdc0e..78fd0543 100644 --- a/modules/images_history.py +++ b/modules/images_history.py @@ -4,7 +4,9 @@ import time import hashlib import gradio system_bak_path = "webui_log_and_bak" -browser_tabname = "custom" +custom_tab_name = "custom fold" +faverate_tab_name = "favorites" +tabs_list = ["txt2img", "img2img", "extras", faverate_tab_name] def is_valid_date(date): try: time.strptime(date, "%Y%m%d") @@ -122,7 +124,6 @@ def archive_images(dir_name, date_to): else: filenames = traverse_all_files(dir_name, filenames) total_num = len(filenames) - batch_count = len(filenames) + 1 // batch_size + 1 tmparray = [(os.path.getmtime(file), file) for file in filenames ] date_stamp = time.mktime(time.strptime(date_to, "%Y%m%d")) + 86400 filenames = [] @@ -146,10 +147,12 @@ def archive_images(dir_name, date_to): last_date_from = date_to_bak if num == 0 else time.strftime("%Y%m%d", time.localtime(time.mktime(time.strptime(date, "%Y%m%d")) - 1000)) date = date[:4] + "/" + date[4:6] + "/" + date[6:8] date_to_bak = date_to_bak[:4] + "/" + date_to_bak[4:6] + "/" + date_to_bak[6:8] - load_info = f"{total_num} images in this directory. Loaded {num} images during {date} - {date_to_bak}, divided into {int((num + 1) // opts.images_history_num_per_page + 1)} pages" + load_info = "
" + load_info += f"{total_num} images in this directory. Loaded {num} images during {date} - {date_to_bak}, divided into {int((num + 1) // opts.images_history_num_per_page + 1)} pages" + load_info += "
" _, image_list, _, _, visible_num = get_recent_images(1, 0, filenames) return ( - gradio.Dropdown.update(choices=date_list, value=date_to), + date_to, load_info, filenames, 1, @@ -158,7 +161,7 @@ def archive_images(dir_name, date_to): "", visible_num, last_date_from, - #gradio.update(visible=batch_count > 1) + gradio.update(visible=total_num > num) ) def delete_image(delete_num, name, filenames, image_index, visible_num): @@ -209,7 +212,7 @@ def get_recent_images(page_index, step, filenames): visible_num = num_of_imgs_per_page if visible_num == 0 else visible_num return page_index, image_list, "", "", visible_num -def newest_click(date_to): +def loac_batch_click(date_to): if date_to is None: return time.strftime("%Y%m%d",time.localtime(time.time())), [] else: @@ -248,7 +251,7 @@ def page_index_change(page_index, filenames): def show_image_info(tabname_box, num, page_index, filenames): file = filenames[int(num) + int((page_index - 1) * int(opts.images_history_num_per_page))] - tm = time.strftime("%Y-%m-%d %H:%M:%S",time.localtime(os.path.getmtime(file))) + tm = "
" + time.strftime("%Y-%m-%d %H:%M:%S",time.localtime(os.path.getmtime(file))) + "
" return file, tm, num, file def enable_page_buttons(): @@ -268,9 +271,9 @@ def change_dir(img_dir, date_to): warning = "The format of the directory is incorrect" if warning is None: today = time.strftime("%Y%m%d",time.localtime(time.time())) - return gradio.update(visible=False), gradio.update(visible=True), None, None if date_to != today else today + return gradio.update(visible=False), gradio.update(visible=True), None, None if date_to != today else today, gradio.update(visible=True), gradio.update(visible=True) else: - return gradio.update(visible=True), gradio.update(visible=False), warning, date_to + return gradio.update(visible=True), gradio.update(visible=False), warning, date_to, gradio.update(visible=False), gradio.update(visible=False) def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): custom_dir = False @@ -280,7 +283,7 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): dir_name = opts.outdir_img2img_samples elif tabname == "extras": dir_name = opts.outdir_extras_samples - elif tabname == "saved": + elif tabname == faverate_tab_name: dir_name = opts.outdir_save else: custom_dir = True @@ -295,22 +298,26 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): os.makedirs(dir_name) with gr.Column() as page_panel: - with gr.Row(): - img_path = gr.Textbox(dir_name, label="Images directory", placeholder="Input images directory", interactive=custom_dir) + with gr.Row(): + with gr.Column(scale=1, visible=not custom_dir) as load_batch_box: + load_batch = gr.Button('Load', elem_id=tabname + "_images_history_start", full_width=True) + with gr.Column(scale=4): + with gr.Row(): + img_path = gr.Textbox(dir_name, label="Images directory", placeholder="Input images directory", interactive=custom_dir) + with gr.Row(): + with gr.Column(visible=False, scale=1) as batch_panel: + with gr.Row(): + forward = gr.Button('Prev batch') + backward = gr.Button('Next batch') + with gr.Column(scale=3): + load_info = gr.HTML(visible=not custom_dir) with gr.Row(visible=False) as warning: warning_box = gr.Textbox("Message", interactive=False) with gr.Row(visible=not custom_dir, elem_id=tabname + "_images_history") as main_panel: - with gr.Column(scale=2): - with gr.Row() as batch_panel: - forward = gr.Button('Forward') - date_to = gr.Dropdown(label="Date to") - backward = gr.Button('Backward') - newest = gr.Button('Reload', elem_id=tabname + "_images_history_start") - with gr.Row(): - load_info = gr.Textbox(show_label=False, interactive=False) - with gr.Row(visible=False) as turn_page_buttons: - renew_page = gr.Button('Refresh page', elem_id=tabname + "_images_history_renew_page") + with gr.Column(scale=2): + with gr.Row(visible=True) as turn_page_buttons: + #date_to = gr.Dropdown(label="Date to") first_page = gr.Button('First Page') prev_page = gr.Button('Prev Page') page_index = gr.Number(value=1, label="Page Index") @@ -322,50 +329,54 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): delete_num = gr.Number(value=1, interactive=True, label="number of images to delete consecutively next") delete = gr.Button('Delete', elem_id=tabname + "_images_history_del_button") - with gr.Column(): - with gr.Row(): - if tabname != "saved": - save_btn = gr.Button('Save') - pnginfo_send_to_txt2img = gr.Button('Send to txt2img') - pnginfo_send_to_img2img = gr.Button('Send to img2img') + with gr.Column(): with gr.Row(): with gr.Column(): - img_file_info = gr.Textbox(label="Generate Info", interactive=False) + img_file_info = gr.Textbox(label="Generate Info", interactive=False, lines=6) + gr.HTML("
") img_file_name = gr.Textbox(value="", label="File Name", interactive=False) - img_file_time= gr.Textbox(value="", label="Create Time", interactive=False) - + img_file_time= gr.HTML() + with gr.Row(): + if tabname != faverate_tab_name: + save_btn = gr.Button('Collect') + pnginfo_send_to_txt2img = gr.Button('Send to txt2img') + pnginfo_send_to_img2img = gr.Button('Send to img2img') + - # hiden items - with gr.Row(visible=False): - visible_img_num = gr.Number() - date_to_recorder = gr.State([]) - last_date_from = gr.Textbox() - tabname_box = gr.Textbox(tabname) - image_index = gr.Textbox(value=-1) - set_index = gr.Button('set_index', elem_id=tabname + "_images_history_set_index") - filenames = gr.State() - all_images_list = gr.State() - hidden = gr.Image(type="pil") - info1 = gr.Textbox() - info2 = gr.Textbox() - - img_path.submit(change_dir, inputs=[img_path, date_to], outputs=[warning, main_panel, warning_box, date_to]) - #change date - change_date_output = [date_to, load_info, filenames, page_index, history_gallery, img_file_name, img_file_time, visible_img_num, last_date_from] + # hiden items + with gr.Row(visible=False): + renew_page = gr.Button('Refresh page', elem_id=tabname + "_images_history_renew_page") + batch_date_to = gr.Textbox(label="Date to") + visible_img_num = gr.Number() + date_to_recorder = gr.State([]) + last_date_from = gr.Textbox() + tabname_box = gr.Textbox(tabname) + image_index = gr.Textbox(value=-1) + set_index = gr.Button('set_index', elem_id=tabname + "_images_history_set_index") + filenames = gr.State() + all_images_list = gr.State() + hidden = gr.Image(type="pil") + info1 = gr.Textbox() + info2 = gr.Textbox() + + img_path.submit(change_dir, inputs=[img_path, batch_date_to], outputs=[warning, main_panel, warning_box, batch_date_to, load_batch_box, load_info]) + + #change batch + change_date_output = [batch_date_to, load_info, filenames, page_index, history_gallery, img_file_name, img_file_time, visible_img_num, last_date_from, batch_panel] - date_to.change(archive_images, inputs=[img_path, date_to], outputs=change_date_output) - date_to.change(enable_page_buttons, inputs=None, outputs=[turn_page_buttons]) - date_to.change(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") + batch_date_to.change(archive_images, inputs=[img_path, batch_date_to], outputs=change_date_output) + batch_date_to.change(enable_page_buttons, inputs=None, outputs=[turn_page_buttons]) + batch_date_to.change(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") - newest.click(newest_click, inputs=[date_to], outputs=[date_to, date_to_recorder]) - forward.click(forward_click, inputs=[last_date_from, date_to_recorder], outputs=[date_to, date_to_recorder]) - backward.click(backward_click, inputs=[last_date_from, date_to_recorder], outputs=[date_to, date_to_recorder]) + load_batch.click(loac_batch_click, inputs=[batch_date_to], outputs=[batch_date_to, date_to_recorder]) + forward.click(forward_click, inputs=[last_date_from, date_to_recorder], outputs=[batch_date_to, date_to_recorder]) + backward.click(backward_click, inputs=[last_date_from, date_to_recorder], outputs=[batch_date_to, date_to_recorder]) #delete delete.click(delete_image, inputs=[delete_num, img_file_name, filenames, image_index, visible_img_num], outputs=[filenames, delete_num, visible_img_num]) delete.click(fn=None, _js="images_history_delete", inputs=[delete_num, tabname_box, image_index], outputs=None) - if tabname != "saved": + if tabname != faverate_tab_name: save_btn.click(save_image, inputs=[img_file_name], outputs=None) #turn page @@ -394,18 +405,20 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): -def create_history_tabs(gr, sys_opts, run_pnginfo, switch_dict): +def create_history_tabs(gr, sys_opts, cmp_ops, run_pnginfo, switch_dict): global opts; opts = sys_opts loads_files_num = int(opts.images_history_num_per_page) num_of_imgs_per_page = int(opts.images_history_num_per_page * opts.images_history_pages_num) + if cmp_ops.browse_all_images: + tabs_list.append(custom_tab_name) with gr.Blocks(analytics_enabled=False) as images_history: with gr.Tabs() as tabs: - for tab in [browser_tabname, "txt2img", "img2img", "extras", "saved"]: + for tab in tabs_list: with gr.Tab(tab): with gr.Blocks(analytics_enabled=False) : - show_images_history(gr, opts, tab, run_pnginfo, switch_dict) - #gradio.Checkbox(opts.images_history_reconstruct_directory, elem_id="images_history_reconstruct_directory", visible=False) - gradio.Checkbox(opts.images_history_reconstruct_directory, elem_id="images_history_finish_render", visible=False) - + show_images_history(gr, opts, tab, run_pnginfo, switch_dict) + gradio.Checkbox(opts.images_history_preload, elem_id="images_history_preload", visible=False) + gradio.Textbox(",".join(tabs_list), elem_id="images_history_tabnames_list", visible=False) + return images_history diff --git a/modules/shared.py b/modules/shared.py index 1811018d..4d735414 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -74,6 +74,10 @@ parser.add_argument("--disable-console-progressbars", action='store_true', help= parser.add_argument("--enable-console-prompts", action='store_true', help="print prompts to console when generating with txt2img and img2img", default=False) parser.add_argument('--vae-path', type=str, help='Path to Variational Autoencoders model', default=None) parser.add_argument("--disable-safe-unpickle", action='store_true', help="disable checking pytorch models for malicious code", default=False) +parser.add_argument("--browse-all-images", action='store_true', help="Allow browsing all images by Image Browser", default=False) + + +cmd_opts = parser.parse_args() cmd_opts = parser.parse_args() @@ -311,6 +315,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" options_templates.update(options_section(('images-history', "Images Browser"), { #"images_history_reconstruct_directory": OptionInfo(False, "Reconstruct output directory structure.This can greatly improve the speed of loading , but will change the original output directory structure"), + "images_history_preload": OptionInfo(False, "Preload images at startup"), "images_history_num_per_page": OptionInfo(36, "Number of pictures displayed on each page"), "images_history_pages_num": OptionInfo(6, "Minimum number of pages per load "), "images_history_grid_num": OptionInfo(6, "Number of grids in each row"), diff --git a/modules/ui.py b/modules/ui.py index 85abac4d..88f46659 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1150,7 +1150,7 @@ def create_ui(wrap_gradio_gpu_call): "i2i":img2img_paste_fields } - images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) + images_history = img_his.create_history_tabs(gr, opts, cmd_opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) with gr.Blocks() as modelmerger_interface: with gr.Row().style(equal_height=False): -- cgit v1.2.3 From da72becb13e4b750fbcb3d158c3f843311ef9938 Mon Sep 17 00:00:00 2001 From: Silent <16026653+s-ilent@users.noreply.github.com> Date: Wed, 19 Oct 2022 16:14:33 +1030 Subject: Use training width/height when training hypernetworks. --- modules/hypernetworks/hypernetwork.py | 4 ++-- modules/ui.py | 2 ++ 2 files changed, 4 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 4905710e..b8695fc1 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -196,7 +196,7 @@ def stack_conds(conds): return torch.stack(conds) -def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height): +def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log_directory, training_width, training_height, steps, create_image_every, save_hypernetwork_every, template_file, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height): assert hypernetwork_name, 'hypernetwork not selected' path = shared.hypernetworks.get(hypernetwork_name, None) @@ -225,7 +225,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..." with torch.autocast("cuda"): - ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file, include_cond=True, batch_size=batch_size) + ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file, include_cond=True, batch_size=batch_size) if unload: shared.sd_model.cond_stage_model.to(devices.cpu) diff --git a/modules/ui.py b/modules/ui.py index fb6eb5a0..ca46343f 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1341,6 +1341,8 @@ def create_ui(wrap_gradio_gpu_call): batch_size, dataset_directory, log_directory, + training_width, + training_height, steps, create_image_every, save_embedding_every, -- cgit v1.2.3 From bcfbb33e50a48b237d8d961cc2be038db53774d5 Mon Sep 17 00:00:00 2001 From: Anastasius Date: Mon, 17 Oct 2022 13:35:20 -0700 Subject: Added time left estimation --- modules/ui.py | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index ca46343f..9a54aa16 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -261,6 +261,15 @@ def wrap_gradio_call(func, extra_outputs=None): return f +def calc_time_left(progress): + if progress == 0: + return "N/A" + else: + time_since_start = time.time() - shared.state.time_start + eta = (time_since_start/progress) + return time.strftime('%H:%M:%S', time.gmtime(eta-time_since_start)) + + def check_progress_call(id_part): if shared.state.job_count == 0: return "", gr_show(False), gr_show(False), gr_show(False) @@ -272,11 +281,13 @@ def check_progress_call(id_part): if shared.state.sampling_steps > 0: progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps + time_left = calc_time_left( progress ) + progress = min(progress, 1) progressbar = "" if opts.show_progressbar: - progressbar = f"""
{str(int(progress*100))+"%" if progress > 0.01 else ""}
""" + progressbar = f"""
{str(int(progress*100))+"% ETA:"+time_left if progress > 0.01 else ""}
""" image = gr_show(False) preview_visibility = gr_show(False) @@ -308,6 +319,7 @@ def check_progress_call_initial(id_part): shared.state.current_latent = None shared.state.current_image = None shared.state.textinfo = None + shared.state.time_start = time.time() return check_progress_call(id_part) -- cgit v1.2.3 From 442dbedc159bb7e9cf94f0c3626f8a409e0a50eb Mon Sep 17 00:00:00 2001 From: Anastasius Date: Tue, 18 Oct 2022 10:38:07 -0700 Subject: Estimated time displayed if jobs take more 60 sec --- modules/ui.py | 17 ++++++++++++----- 1 file changed, 12 insertions(+), 5 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 9a54aa16..fa54110b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -261,13 +261,17 @@ def wrap_gradio_call(func, extra_outputs=None): return f -def calc_time_left(progress): +def calc_time_left(progress, threshold, label, force_display): if progress == 0: - return "N/A" + return "" else: time_since_start = time.time() - shared.state.time_start eta = (time_since_start/progress) - return time.strftime('%H:%M:%S', time.gmtime(eta-time_since_start)) + eta_relative = eta-time_since_start + if eta_relative > threshold or force_display: + return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative)) + else: + return "" def check_progress_call(id_part): @@ -281,13 +285,15 @@ def check_progress_call(id_part): if shared.state.sampling_steps > 0: progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps - time_left = calc_time_left( progress ) + time_left = calc_time_left( progress, 60, " ETA:", shared.state.time_left_force_display ) + if time_left != "": + shared.state.time_left_force_display = True progress = min(progress, 1) progressbar = "" if opts.show_progressbar: - progressbar = f"""
{str(int(progress*100))+"% ETA:"+time_left if progress > 0.01 else ""}
""" + progressbar = f"""
{str(int(progress*100))+"%"+time_left if progress > 0.01 else ""}
""" image = gr_show(False) preview_visibility = gr_show(False) @@ -320,6 +326,7 @@ def check_progress_call_initial(id_part): shared.state.current_image = None shared.state.textinfo = None shared.state.time_start = time.time() + shared.state.time_left_force_display = False return check_progress_call(id_part) -- cgit v1.2.3 From 1d4aa376e6111e90888a30ae24d2bcd7f978ec51 Mon Sep 17 00:00:00 2001 From: Anastasius Date: Tue, 18 Oct 2022 12:42:39 -0700 Subject: Predictable long operation check for time estimation --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index fa54110b..38ba1138 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -268,7 +268,7 @@ def calc_time_left(progress, threshold, label, force_display): time_since_start = time.time() - shared.state.time_start eta = (time_since_start/progress) eta_relative = eta-time_since_start - if eta_relative > threshold or force_display: + if (eta_relative > threshold and progress > 0.02) or force_display: return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative)) else: return "" -- cgit v1.2.3 From 087609ee181a91a523647435ffffa6288a317e2f Mon Sep 17 00:00:00 2001 From: captin411 Date: Wed, 19 Oct 2022 03:19:35 -0700 Subject: UI changes for focal point image cropping --- modules/ui.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 1ff7eb4f..b6be713b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1234,6 +1234,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Row(): process_flip = gr.Checkbox(label='Create flipped copies') process_split = gr.Checkbox(label='Split oversized images into two') + process_entropy_focus = gr.Checkbox(label='Create auto focal point crop') process_caption = gr.Checkbox(label='Use BLIP for caption') process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True if cmd_opts.deepdanbooru else False) @@ -1318,7 +1319,8 @@ def create_ui(wrap_gradio_gpu_call): process_flip, process_split, process_caption, - process_caption_deepbooru + process_caption_deepbooru, + process_entropy_focus ], outputs=[ ti_output, -- cgit v1.2.3 From 42fbda83bb9830af18187fddb50c1bedd01da502 Mon Sep 17 00:00:00 2001 From: discus0434 Date: Wed, 19 Oct 2022 14:30:33 +0000 Subject: layer options moves into create hnet ui --- modules/hypernetworks/hypernetwork.py | 64 +++++++++++++++++------------------ modules/hypernetworks/ui.py | 9 +++-- modules/shared.py | 2 -- modules/ui.py | 8 +++-- webui.py | 8 ++--- 5 files changed, 48 insertions(+), 43 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 583ada31..7d519cd9 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -19,37 +19,21 @@ from modules.textual_inversion import textual_inversion from modules.textual_inversion.learn_schedule import LearnRateScheduler -def parse_layer_structure(dim, state_dict): - i = 0 - res = [1] - while (key := "linear.{}.weight".format(i)) in state_dict: - weight = state_dict[key] - res.append(len(weight) // dim) - i += 1 - return res - - class HypernetworkModule(torch.nn.Module): multiplier = 1.0 - layer_structure = None - add_layer_norm = False - def __init__(self, dim, state_dict=None): + def __init__(self, dim, state_dict=None, layer_structure=None, add_layer_norm=False): super().__init__() - if (state_dict is None or 'linear.0.weight' not in state_dict) and self.layer_structure is None: - layer_structure = (1, 2, 1) + if layer_structure is not None: + assert layer_structure[0] == 1, "Multiplier Sequence should start with size 1!" + assert layer_structure[-1] == 1, "Multiplier Sequence should end with size 1!" else: - if self.layer_structure is not None: - assert self.layer_structure[0] == 1, "Multiplier Sequence should start with size 1!" - assert self.layer_structure[-1] == 1, "Multiplier Sequence should end with size 1!" - layer_structure = self.layer_structure - else: - layer_structure = parse_layer_structure(dim, state_dict) + layer_structure = parse_layer_structure(dim, state_dict) linears = [] for i in range(len(layer_structure) - 1): linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i+1]))) - if self.add_layer_norm: + if add_layer_norm: linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1]))) self.linear = torch.nn.Sequential(*linears) @@ -77,38 +61,47 @@ class HypernetworkModule(torch.nn.Module): return x + self.linear(x) * self.multiplier def trainables(self): - res = [] + layer_structure = [] for layer in self.linear: - res += [layer.weight, layer.bias] - return res + layer_structure += [layer.weight, layer.bias] + return layer_structure def apply_strength(value=None): HypernetworkModule.multiplier = value if value is not None else shared.opts.sd_hypernetwork_strength -def apply_layer_structure(value=None): - HypernetworkModule.layer_structure = value if value is not None else shared.opts.sd_hypernetwork_layer_structure +def parse_layer_structure(dim, state_dict): + i = 0 + layer_structure = [1] + while (key := "linear.{}.weight".format(i)) in state_dict: + weight = state_dict[key] + layer_structure.append(len(weight) // dim) + i += 1 -def apply_layer_norm(value=None): - HypernetworkModule.add_layer_norm = value if value is not None else shared.opts.sd_hypernetwork_add_layer_norm + return layer_structure class Hypernetwork: filename = None name = None - def __init__(self, name=None, enable_sizes=None): + def __init__(self, name=None, enable_sizes=None, layer_structure=None, add_layer_norm=False): self.filename = None self.name = name self.layers = {} self.step = 0 self.sd_checkpoint = None self.sd_checkpoint_name = None + self.layer_structure = layer_structure + self.add_layer_norm = add_layer_norm for size in enable_sizes or []: - self.layers[size] = (HypernetworkModule(size), HypernetworkModule(size)) + self.layers[size] = ( + HypernetworkModule(size, None, self.layer_structure, self.add_layer_norm), + HypernetworkModule(size, None, self.layer_structure, self.add_layer_norm), + ) def weights(self): res = [] @@ -128,6 +121,8 @@ class Hypernetwork: state_dict['step'] = self.step state_dict['name'] = self.name + state_dict['layer_structure'] = self.layer_structure + state_dict['is_layer_norm'] = self.add_layer_norm state_dict['sd_checkpoint'] = self.sd_checkpoint state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name @@ -142,10 +137,15 @@ class Hypernetwork: for size, sd in state_dict.items(): if type(size) == int: - self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1])) + self.layers[size] = ( + HypernetworkModule(size, sd[0], state_dict["layer_structure"], state_dict["is_layer_norm"]), + HypernetworkModule(size, sd[1], state_dict["layer_structure"], state_dict["is_layer_norm"]), + ) self.name = state_dict.get('name', self.name) self.step = state_dict.get('step', 0) + self.layer_structure = state_dict.get('layer_structure', None) + self.add_layer_norm = state_dict.get('is_layer_norm', False) self.sd_checkpoint = state_dict.get('sd_checkpoint', None) self.sd_checkpoint_name = state_dict.get('sd_checkpoint_name', None) diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py index dfa599af..7e8ea95e 100644 --- a/modules/hypernetworks/ui.py +++ b/modules/hypernetworks/ui.py @@ -9,11 +9,16 @@ from modules import sd_hijack, shared, devices from modules.hypernetworks import hypernetwork -def create_hypernetwork(name, enable_sizes): +def create_hypernetwork(name, enable_sizes, layer_structure=None, add_layer_norm=False): fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt") assert not os.path.exists(fn), f"file {fn} already exists" - hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(name=name, enable_sizes=[int(x) for x in enable_sizes]) + hypernet = modules.hypernetworks.hypernetwork.Hypernetwork( + name=name, + enable_sizes=[int(x) for x in enable_sizes], + layer_structure=layer_structure, + add_layer_norm=add_layer_norm, + ) hypernet.save(fn) shared.reload_hypernetworks() diff --git a/modules/shared.py b/modules/shared.py index 0540cae9..faede821 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -260,8 +260,6 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, refresh=sd_models.list_models), "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), "sd_hypernetwork": OptionInfo("None", "Hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks), - "sd_hypernetwork_layer_structure": OptionInfo(None, "Hypernetwork layer structure Default: (1,2,1).", gr.Dropdown, lambda: {"choices": [(1, 2, 1), (1, 2, 2, 1), (1, 2, 4, 2, 1)]}), - "sd_hypernetwork_add_layer_norm": OptionInfo(False, "Add layer normalization to hypernetwork architecture."), "sd_hypernetwork_strength": OptionInfo(1.0, "Hypernetwork strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.001}), "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."), "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"), diff --git a/modules/ui.py b/modules/ui.py index ca46343f..d9ee462f 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -458,14 +458,14 @@ def create_toprow(is_img2img): with gr.Row(): with gr.Column(scale=80): with gr.Row(): - prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2, + prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2, placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)" ) with gr.Row(): with gr.Column(scale=80): with gr.Row(): - negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2, + negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2, placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)" ) @@ -1198,6 +1198,8 @@ def create_ui(wrap_gradio_gpu_call): with gr.Tab(label="Create hypernetwork"): new_hypernetwork_name = gr.Textbox(label="Name") new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) + new_hypernetwork_layer_structure = gr.Dropdown(label="Hypernetwork layer structure", choices=[(1, 2, 1), (1, 2, 2, 1), (1, 2, 4, 2, 1)]) + new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization") with gr.Row(): with gr.Column(scale=3): @@ -1280,6 +1282,8 @@ def create_ui(wrap_gradio_gpu_call): inputs=[ new_hypernetwork_name, new_hypernetwork_sizes, + new_hypernetwork_layer_structure, + new_hypernetwork_add_layer_norm, ], outputs=[ train_hypernetwork_name, diff --git a/webui.py b/webui.py index c7260c7a..177bef74 100644 --- a/webui.py +++ b/webui.py @@ -85,9 +85,7 @@ def initialize(): shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model))) shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork))) shared.opts.onchange("sd_hypernetwork_strength", modules.hypernetworks.hypernetwork.apply_strength) - shared.opts.onchange("sd_hypernetwork_layer_structure", modules.hypernetworks.hypernetwork.apply_layer_structure) - shared.opts.onchange("sd_hypernetwork_add_layer_norm", modules.hypernetworks.hypernetwork.apply_layer_norm) - + # make the program just exit at ctrl+c without waiting for anything def sigint_handler(sig, frame): print(f'Interrupted with signal {sig} in {frame}') @@ -142,7 +140,7 @@ def webui(launch_api=False): create_api(app) wait_on_server(demo) - + sd_samplers.set_samplers() print('Reloading Custom Scripts') @@ -160,4 +158,4 @@ if __name__ == "__main__": if cmd_opts.nowebui: api_only() else: - webui(cmd_opts.api) \ No newline at end of file + webui(cmd_opts.api) -- cgit v1.2.3 From 3770b8d2fa62066d472a04739c7b84bce8538832 Mon Sep 17 00:00:00 2001 From: discus0434 Date: Wed, 19 Oct 2022 15:28:42 +0000 Subject: enable to write layer structure of hn himself --- modules/hypernetworks/ui.py | 4 ++++ modules/ui.py | 2 +- 2 files changed, 5 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py index 7e8ea95e..08f75f15 100644 --- a/modules/hypernetworks/ui.py +++ b/modules/hypernetworks/ui.py @@ -1,5 +1,6 @@ import html import os +import re import gradio as gr @@ -13,6 +14,9 @@ def create_hypernetwork(name, enable_sizes, layer_structure=None, add_layer_norm fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt") assert not os.path.exists(fn), f"file {fn} already exists" + if type(layer_structure) == str: + layer_structure = tuple(map(int, re.sub(r'\D', '', layer_structure))) + hypernet = modules.hypernetworks.hypernetwork.Hypernetwork( name=name, enable_sizes=[int(x) for x in enable_sizes], diff --git a/modules/ui.py b/modules/ui.py index d9ee462f..18a2add0 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1198,7 +1198,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Tab(label="Create hypernetwork"): new_hypernetwork_name = gr.Textbox(label="Name") new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) - new_hypernetwork_layer_structure = gr.Dropdown(label="Hypernetwork layer structure", choices=[(1, 2, 1), (1, 2, 2, 1), (1, 2, 4, 2, 1)]) + new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'") new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization") with gr.Row(): -- cgit v1.2.3 From 019a3a88f07766f2d32c32fbe8e41625f28ecb5e Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Wed, 19 Oct 2022 17:15:47 +0100 Subject: Update ui.py --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index d2e24880..1573ef82 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1247,7 +1247,7 @@ def create_ui(wrap_gradio_gpu_call): run_preprocess = gr.Button(value="Preprocess", variant='primary') with gr.Tab(label="Train"): - gr.HTML(value="

Train an embedding; must specify a directory with a set of 1:1 ratio images

") + gr.HTML(value="

Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images
Initial learning rates: 0.005 for an Embedding, 0.00001 for Hypernetwork wiki

") with gr.Row(): train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name") -- cgit v1.2.3 From 57eb1a64c85d995cacb4fa3832e87405bf6820b9 Mon Sep 17 00:00:00 2001 From: Alexandre Simard Date: Wed, 19 Oct 2022 12:28:27 -0400 Subject: Update ui.py --- modules/ui.py | 13 +++++++++---- 1 file changed, 9 insertions(+), 4 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index d2e24880..c9a923ab 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -268,8 +268,13 @@ def calc_time_left(progress, threshold, label, force_display): time_since_start = time.time() - shared.state.time_start eta = (time_since_start/progress) eta_relative = eta-time_since_start - if (eta_relative > threshold and progress > 0.02) or force_display: - return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative)) + if (eta_relative > threshold and progress > 0.02) or force_display: + if eta_relative > 3600: + return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative)) + elif eta_relative > 60: + return label + time.strftime('%M:%S', time.gmtime(eta_relative)) + else: + return label + time.strftime('%Ss', time.gmtime(eta_relative)) else: return "" @@ -285,7 +290,7 @@ def check_progress_call(id_part): if shared.state.sampling_steps > 0: progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps - time_left = calc_time_left( progress, 60, " ETA:", shared.state.time_left_force_display ) + time_left = calc_time_left( progress, 1, " ETA: ", shared.state.time_left_force_display ) if time_left != "": shared.state.time_left_force_display = True @@ -293,7 +298,7 @@ def check_progress_call(id_part): progressbar = "" if opts.show_progressbar: - progressbar = f"""
{str(int(progress*100))+"%"+time_left if progress > 0.01 else ""}
""" + progressbar = f"""
{str(int(progress*100))+"%"+time_left if progress > 0.01 else ""}
""" image = gr_show(False) preview_visibility = gr_show(False) -- cgit v1.2.3 From 1e4809b251d478a102fd980dcfc26e21d6d3730b Mon Sep 17 00:00:00 2001 From: Alexandre Simard Date: Wed, 19 Oct 2022 12:53:23 -0400 Subject: Added a bit of padding to the left --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index c9a923ab..a2dbd41e 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -298,7 +298,7 @@ def check_progress_call(id_part): progressbar = "" if opts.show_progressbar: - progressbar = f"""
{str(int(progress*100))+"%"+time_left if progress > 0.01 else ""}
""" + progressbar = f"""
{" " * 2 + str(int(progress*100))+"%" + time_left if progress > 0.01 else ""}
""" image = gr_show(False) preview_visibility = gr_show(False) -- cgit v1.2.3 From 14c1c2b9351f16d43ba4e6b6c9062edad44a6bec Mon Sep 17 00:00:00 2001 From: Alexandre Simard Date: Wed, 19 Oct 2022 13:53:52 -0400 Subject: Show PB texts at same time and earlier For big tasks (1000+ steps), waiting 1 minute to see ETA is long and this changes it so the number of steps done plays a role in showing the text as well. --- modules/ui.py | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index a2dbd41e..0abd177a 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -261,14 +261,14 @@ def wrap_gradio_call(func, extra_outputs=None): return f -def calc_time_left(progress, threshold, label, force_display): +def calc_time_left(progress, threshold, label, force_display, showTime): if progress == 0: return "" else: time_since_start = time.time() - shared.state.time_start eta = (time_since_start/progress) eta_relative = eta-time_since_start - if (eta_relative > threshold and progress > 0.02) or force_display: + if (eta_relative > threshold and showTime) or force_display: if eta_relative > 3600: return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative)) elif eta_relative > 60: @@ -290,7 +290,10 @@ def check_progress_call(id_part): if shared.state.sampling_steps > 0: progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps - time_left = calc_time_left( progress, 1, " ETA: ", shared.state.time_left_force_display ) + # Show progress percentage and time left at the same moment, and base it also on steps done + showPBText = progress >= 0.01 or shared.state.sampling_step >= 10 + + time_left = calc_time_left( progress, 1, " ETA: ", shared.state.time_left_force_display, showPBText ) if time_left != "": shared.state.time_left_force_display = True @@ -298,7 +301,7 @@ def check_progress_call(id_part): progressbar = "" if opts.show_progressbar: - progressbar = f"""
{" " * 2 + str(int(progress*100))+"%" + time_left if progress > 0.01 else ""}
""" + progressbar = f"""
{" " * 2 + str(int(progress*100))+"%" + time_left if showPBText else ""}
""" image = gr_show(False) preview_visibility = gr_show(False) -- cgit v1.2.3 From eb7ba4b713ac2fb960ecf6365b1de0c89451e583 Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Wed, 19 Oct 2022 19:50:46 +0100 Subject: update training header text --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 1573ef82..93c0767c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1247,7 +1247,7 @@ def create_ui(wrap_gradio_gpu_call): run_preprocess = gr.Button(value="Preprocess", variant='primary') with gr.Tab(label="Train"): - gr.HTML(value="

Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images
Initial learning rates: 0.005 for an Embedding, 0.00001 for Hypernetwork wiki

") + gr.HTML(value="

Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images
Initial learning rates: 0.005 for an Embedding, 0.00001 for Hypernetwork [wiki]

") with gr.Row(): train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name") -- cgit v1.2.3 From 4d663055ded968831ec97f047dfa8e94036cf1c1 Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Wed, 19 Oct 2022 20:33:18 +0100 Subject: update ui with extra training options --- modules/ui.py | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 93c0767c..cdb9d335 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1206,6 +1206,7 @@ def create_ui(wrap_gradio_gpu_call): new_embedding_name = gr.Textbox(label="Name") initialization_text = gr.Textbox(label="Initialization text", value="*") nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1) + overwrite_old_embedding = gr.Checkbox(value=False, label="Overwrite Old Embedding") with gr.Row(): with gr.Column(scale=3): @@ -1219,6 +1220,7 @@ def create_ui(wrap_gradio_gpu_call): new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'") new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization") + overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork") with gr.Row(): with gr.Column(scale=3): @@ -1247,14 +1249,17 @@ def create_ui(wrap_gradio_gpu_call): run_preprocess = gr.Button(value="Preprocess", variant='primary') with gr.Tab(label="Train"): - gr.HTML(value="

Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images
Initial learning rates: 0.005 for an Embedding, 0.00001 for Hypernetwork [wiki]

") + gr.HTML(value="

Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images [wiki]

") with gr.Row(): train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name") with gr.Row(): train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=[x for x in shared.hypernetworks.keys()]) create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted([x for x in shared.hypernetworks.keys()])}, "refresh_train_hypernetwork_name") - learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.005") + with gr.Row(): + embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005") + hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001") + batch_size = gr.Number(label='Batch size', value=1, precision=0) dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images") log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion") @@ -1288,6 +1293,7 @@ def create_ui(wrap_gradio_gpu_call): new_embedding_name, initialization_text, nvpt, + overwrite_old_embedding, ], outputs=[ train_embedding_name, @@ -1303,6 +1309,7 @@ def create_ui(wrap_gradio_gpu_call): new_hypernetwork_sizes, new_hypernetwork_layer_structure, new_hypernetwork_add_layer_norm, + overwrite_old_hypernetwork, ], outputs=[ train_hypernetwork_name, -- cgit v1.2.3 From 632e8d660293081cadb145d8062e5aff0a4a8f0d Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Thu, 20 Oct 2022 00:19:40 +0100 Subject: split learn rates --- modules/ui.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index cdb9d335..d07184ee 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1342,7 +1342,7 @@ def create_ui(wrap_gradio_gpu_call): _js="start_training_textual_inversion", inputs=[ train_embedding_name, - learn_rate, + embedding_learn_rate, batch_size, dataset_directory, log_directory, @@ -1367,7 +1367,7 @@ def create_ui(wrap_gradio_gpu_call): _js="start_training_textual_inversion", inputs=[ train_hypernetwork_name, - learn_rate, + hypernetwork_learn_rate, batch_size, dataset_directory, log_directory, -- cgit v1.2.3 From 4d6b9f76a55fd0ac0f72634071032dd9c6efb409 Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Thu, 20 Oct 2022 00:27:16 +0100 Subject: reorder create_hypernetwork params --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index d07184ee..322c082b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1307,9 +1307,9 @@ def create_ui(wrap_gradio_gpu_call): inputs=[ new_hypernetwork_name, new_hypernetwork_sizes, + overwrite_old_hypernetwork, new_hypernetwork_layer_structure, new_hypernetwork_add_layer_norm, - overwrite_old_hypernetwork, ], outputs=[ train_hypernetwork_name, -- cgit v1.2.3 From ab353b141df8eee042b0964bcb645015dabf3459 Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Thu, 20 Oct 2022 00:48:07 +0100 Subject: link existing txt option --- modules/ui.py | 2 ++ 1 file changed, 2 insertions(+) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 322c082b..7f52ac0c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1234,6 +1234,7 @@ def create_ui(wrap_gradio_gpu_call): process_dst = gr.Textbox(label='Destination directory') process_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512) process_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) + preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', choices=['ignore', 'copy', 'prepend', 'append']) with gr.Row(): process_flip = gr.Checkbox(label='Create flipped copies') @@ -1326,6 +1327,7 @@ def create_ui(wrap_gradio_gpu_call): process_dst, process_width, process_height, + preprocess_txt_action, process_flip, process_split, process_caption, -- cgit v1.2.3 From 55d8c6cce6d3aef848b9f194adad2ce53064d8b7 Mon Sep 17 00:00:00 2001 From: DepFA <35278260+dfaker@users.noreply.github.com> Date: Thu, 20 Oct 2022 00:53:29 +0100 Subject: default to ignore existing captions --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 7f52ac0c..bd5f1b05 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1234,7 +1234,7 @@ def create_ui(wrap_gradio_gpu_call): process_dst = gr.Textbox(label='Destination directory') process_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512) process_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) - preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', choices=['ignore', 'copy', 'prepend', 'append']) + preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', value="ignore", choices=["ignore", "copy", "prepend", "append"]) with gr.Row(): process_flip = gr.Checkbox(label='Create flipped copies') -- cgit v1.2.3 From 8b74b9aa9a20e4c5c1f72641f8b9617479eb276b Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Wed, 19 Oct 2022 19:06:14 -0500 Subject: add symbol for clear button and simplify roll_col css selector --- modules/ui.py | 2 ++ style.css | 2 +- 2 files changed, 3 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index a2dbd41e..9f6edc5f 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -83,6 +83,7 @@ folder_symbol = '\U0001f4c2' # 📂 refresh_symbol = '\U0001f504' # 🔄 save_style_symbol = '\U0001f4be' # 💾 apply_style_symbol = '\U0001f4cb' # 📋 +trash_prompt_symbol = '\U0001F5D1' # 🗑🗑🗑 def plaintext_to_html(text): @@ -498,6 +499,7 @@ def create_toprow(is_img2img): paste = gr.Button(value=paste_symbol, elem_id="paste") save_style = gr.Button(value=save_style_symbol, elem_id="style_create") prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply") + trash_prompt = gr.Button(value=trash_prompt_symbol, elem_id="trash_prompt") token_counter = gr.HTML(value="", elem_id=f"{id_part}_token_counter") token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button") diff --git a/style.css b/style.css index 26ae36a5..21a8911f 100644 --- a/style.css +++ b/style.css @@ -114,7 +114,7 @@ padding: 0.4em 0; } -#roll, #paste, #style_create, #style_apply{ +#roll_col > button { min-width: 2em; min-height: 2em; max-width: 2em; -- cgit v1.2.3 From 6f98e89486f55b0e4657e96ce640cf1c4675d187 Mon Sep 17 00:00:00 2001 From: discus0434 Date: Thu, 20 Oct 2022 00:10:45 +0000 Subject: update --- modules/hypernetworks/hypernetwork.py | 29 +++++++++++++++-------- modules/hypernetworks/ui.py | 3 ++- modules/ui.py | 43 +++++++++++++++++++---------------- 3 files changed, 44 insertions(+), 31 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 74300122..7d617680 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -22,16 +22,20 @@ from modules.textual_inversion.learn_schedule import LearnRateScheduler class HypernetworkModule(torch.nn.Module): multiplier = 1.0 - def __init__(self, dim, state_dict=None, layer_structure=None, add_layer_norm=False): + def __init__(self, dim, state_dict=None, layer_structure=None, add_layer_norm=False, activation_func=None): super().__init__() - assert layer_structure is not None, "layer_structure mut not be None" + assert layer_structure is not None, "layer_structure must not be None" assert layer_structure[0] == 1, "Multiplier Sequence should start with size 1!" assert layer_structure[-1] == 1, "Multiplier Sequence should end with size 1!" linears = [] for i in range(len(layer_structure) - 1): linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i+1]))) + if activation_func == "relu": + linears.append(torch.nn.ReLU()) + if activation_func == "leakyrelu": + linears.append(torch.nn.LeakyReLU()) if add_layer_norm: linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1]))) @@ -42,8 +46,9 @@ class HypernetworkModule(torch.nn.Module): self.load_state_dict(state_dict) else: for layer in self.linear: - layer.weight.data.normal_(mean=0.0, std=0.01) - layer.bias.data.zero_() + if not "ReLU" in layer.__str__(): + layer.weight.data.normal_(mean=0.0, std=0.01) + layer.bias.data.zero_() self.to(devices.device) @@ -69,7 +74,8 @@ class HypernetworkModule(torch.nn.Module): def trainables(self): layer_structure = [] for layer in self.linear: - layer_structure += [layer.weight, layer.bias] + if not "ReLU" in layer.__str__(): + layer_structure += [layer.weight, layer.bias] return layer_structure @@ -81,7 +87,7 @@ class Hypernetwork: filename = None name = None - def __init__(self, name=None, enable_sizes=None, layer_structure=None, add_layer_norm=False): + def __init__(self, name=None, enable_sizes=None, layer_structure=None, add_layer_norm=False, activation_func=None): self.filename = None self.name = name self.layers = {} @@ -90,11 +96,12 @@ class Hypernetwork: self.sd_checkpoint_name = None self.layer_structure = layer_structure self.add_layer_norm = add_layer_norm + self.activation_func = activation_func for size in enable_sizes or []: self.layers[size] = ( - HypernetworkModule(size, None, self.layer_structure, self.add_layer_norm), - HypernetworkModule(size, None, self.layer_structure, self.add_layer_norm), + HypernetworkModule(size, None, self.layer_structure, self.add_layer_norm, self.activation_func), + HypernetworkModule(size, None, self.layer_structure, self.add_layer_norm, self.activation_func), ) def weights(self): @@ -117,6 +124,7 @@ class Hypernetwork: state_dict['name'] = self.name state_dict['layer_structure'] = self.layer_structure state_dict['is_layer_norm'] = self.add_layer_norm + state_dict['activation_func'] = self.activation_func state_dict['sd_checkpoint'] = self.sd_checkpoint state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name @@ -131,12 +139,13 @@ class Hypernetwork: self.layer_structure = state_dict.get('layer_structure', [1, 2, 1]) self.add_layer_norm = state_dict.get('is_layer_norm', False) + self.activation_func = state_dict.get('activation_func', None) for size, sd in state_dict.items(): if type(size) == int: self.layers[size] = ( - HypernetworkModule(size, sd[0], self.layer_structure, self.add_layer_norm), - HypernetworkModule(size, sd[1], self.layer_structure, self.add_layer_norm), + HypernetworkModule(size, sd[0], self.layer_structure, self.add_layer_norm, self.activation_func), + HypernetworkModule(size, sd[1], self.layer_structure, self.add_layer_norm, self.activation_func), ) self.name = state_dict.get('name', self.name) diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py index 08f75f15..83f9547b 100644 --- a/modules/hypernetworks/ui.py +++ b/modules/hypernetworks/ui.py @@ -10,7 +10,7 @@ from modules import sd_hijack, shared, devices from modules.hypernetworks import hypernetwork -def create_hypernetwork(name, enable_sizes, layer_structure=None, add_layer_norm=False): +def create_hypernetwork(name, enable_sizes, layer_structure=None, add_layer_norm=False, activation_func=None): fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt") assert not os.path.exists(fn), f"file {fn} already exists" @@ -22,6 +22,7 @@ def create_hypernetwork(name, enable_sizes, layer_structure=None, add_layer_norm enable_sizes=[int(x) for x in enable_sizes], layer_structure=layer_structure, add_layer_norm=add_layer_norm, + activation_func=activation_func, ) hypernet.save(fn) diff --git a/modules/ui.py b/modules/ui.py index d2e24880..8751fa9c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -5,43 +5,44 @@ import json import math import mimetypes import os +import platform import random +import subprocess as sp import sys import tempfile import time import traceback -import platform -import subprocess as sp from functools import partial, reduce +import gradio as gr +import gradio.routes +import gradio.utils import numpy as np +import piexif import torch from PIL import Image, PngImagePlugin -import piexif -import gradio as gr -import gradio.utils -import gradio.routes - -from modules import sd_hijack, sd_models, localization +from modules import localization, sd_hijack, sd_models from modules.paths import script_path -from modules.shared import opts, cmd_opts, restricted_opts +from modules.shared import cmd_opts, opts, restricted_opts + if cmd_opts.deepdanbooru: from modules.deepbooru import get_deepbooru_tags -import modules.shared as shared -from modules.sd_samplers import samplers, samplers_for_img2img -from modules.sd_hijack import model_hijack + +import modules.codeformer_model +import modules.generation_parameters_copypaste +import modules.gfpgan_model +import modules.hypernetworks.ui +import modules.images_history as img_his import modules.ldsr_model import modules.scripts -import modules.gfpgan_model -import modules.codeformer_model +import modules.shared as shared import modules.styles -import modules.generation_parameters_copypaste +import modules.textual_inversion.ui from modules import prompt_parser from modules.images import save_image -import modules.textual_inversion.ui -import modules.hypernetworks.ui -import modules.images_history as img_his +from modules.sd_hijack import model_hijack +from modules.sd_samplers import samplers, samplers_for_img2img # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() @@ -268,8 +269,8 @@ def calc_time_left(progress, threshold, label, force_display): time_since_start = time.time() - shared.state.time_start eta = (time_since_start/progress) eta_relative = eta-time_since_start - if (eta_relative > threshold and progress > 0.02) or force_display: - return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative)) + if (eta_relative > threshold and progress > 0.02) or force_display: + return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative)) else: return "" @@ -1219,6 +1220,7 @@ def create_ui(wrap_gradio_gpu_call): new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'") new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization") + new_hypernetwork_activation_func = gr.Dropdown(value="relu", label="Select activation function of hypernetwork", choices=["relu", "leakyrelu"]) with gr.Row(): with gr.Column(scale=3): @@ -1303,6 +1305,7 @@ def create_ui(wrap_gradio_gpu_call): new_hypernetwork_sizes, new_hypernetwork_layer_structure, new_hypernetwork_add_layer_norm, + new_hypernetwork_activation_func, ], outputs=[ train_hypernetwork_name, -- cgit v1.2.3 From ba469343e6a1c6e23e82acf5feb65c6101dacbb2 Mon Sep 17 00:00:00 2001 From: discus0434 Date: Thu, 20 Oct 2022 00:17:04 +0000 Subject: align ui.py imports with upstream --- modules/ui.py | 37 ++++++++++++++++++------------------- 1 file changed, 18 insertions(+), 19 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 987b1d7d..913b23b4 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -5,44 +5,43 @@ import json import math import mimetypes import os -import platform import random -import subprocess as sp import sys import tempfile import time import traceback +import platform +import subprocess as sp from functools import partial, reduce -import gradio as gr -import gradio.routes -import gradio.utils import numpy as np -import piexif import torch from PIL import Image, PngImagePlugin +import piexif -from modules import localization, sd_hijack, sd_models -from modules.paths import script_path -from modules.shared import cmd_opts, opts, restricted_opts +import gradio as gr +import gradio.utils +import gradio.routes +from modules import sd_hijack, sd_models, localization +from modules.paths import script_path +from modules.shared import opts, cmd_opts, restricted_opts if cmd_opts.deepdanbooru: from modules.deepbooru import get_deepbooru_tags - -import modules.codeformer_model -import modules.generation_parameters_copypaste -import modules.gfpgan_model -import modules.hypernetworks.ui -import modules.images_history as img_his +import modules.shared as shared +from modules.sd_samplers import samplers, samplers_for_img2img +from modules.sd_hijack import model_hijack import modules.ldsr_model import modules.scripts -import modules.shared as shared +import modules.gfpgan_model +import modules.codeformer_model import modules.styles -import modules.textual_inversion.ui +import modules.generation_parameters_copypaste from modules import prompt_parser from modules.images import save_image -from modules.sd_hijack import model_hijack -from modules.sd_samplers import samplers, samplers_for_img2img +import modules.textual_inversion.ui +import modules.hypernetworks.ui +import modules.images_history as img_his # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() -- cgit v1.2.3 From c6345bd445463b7aa41723d6637e80dfa293a890 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Wed, 19 Oct 2022 21:23:57 -0500 Subject: nerf line length --- modules/ui.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 9f6edc5f..cb9a6c6e 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -83,7 +83,7 @@ folder_symbol = '\U0001f4c2' # 📂 refresh_symbol = '\U0001f504' # 🔄 save_style_symbol = '\U0001f4be' # 💾 apply_style_symbol = '\U0001f4cb' # 📋 -trash_prompt_symbol = '\U0001F5D1' # 🗑🗑🗑 +trash_prompt_symbol = '\U0001F5D1' # def plaintext_to_html(text): @@ -617,7 +617,10 @@ def create_ui(wrap_gradio_gpu_call): return refresh_button with gr.Blocks(analytics_enabled=False) as txt2img_interface: - txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False) + txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _,\ + txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter,\ + token_button = create_toprow(is_img2img=False) + dummy_component = gr.Label(visible=False) txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False) -- cgit v1.2.3 From 158d678f596d7fc304a6ce2f0dc31f8abfe62250 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Thu, 20 Oct 2022 01:08:24 -0500 Subject: clear prompt button now works on both relevant tabs. Device detection stuff will be added later. --- javascript/ui.js | 28 ++++++++++++++++++++++++++++ modules/ui.py | 21 ++++++++++++++++++--- 2 files changed, 46 insertions(+), 3 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index cfd0dcd3..165383da 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -151,6 +151,34 @@ function ask_for_style_name(_, prompt_text, negative_prompt_text) { return [name_, prompt_text, negative_prompt_text] } +// returns css id for currently selected tab in ui +function selected_tab_id() { + tabs = gradioApp().querySelectorAll('#tabs div.tabitem') + + for(var tab = 0; tab < tabs.length; tab++) { + if (tabs[tab].style.display != "none") return tabs[tab].id + + } + +} + +function trash_prompt(_,_, is_img2img) { + + if(selected_tab_id() == "tab_txt2img") { + pos_prompt = txt2img_textarea = gradioApp().querySelector("#txt2img_prompt > label > textarea"); + neg_prompt = txt2img_textarea = gradioApp().querySelector("#txt2img_neg_prompt > label > textarea"); + + pos_prompt.value = "" + neg_prompt.value = "" + } else { + pos_prompt = txt2img_textarea = gradioApp().querySelector("#img2img_prompt > label > textarea"); + neg_prompt = txt2img_textarea = gradioApp().querySelector("#img2img_neg_prompt > label > textarea"); + + pos_prompt.value = "" + neg_prompt.value = "" + } +} + opts = {} diff --git a/modules/ui.py b/modules/ui.py index cb9a6c6e..bde546cc 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -424,6 +424,16 @@ def create_seed_inputs(): return seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox +# setup button for clearing prompt input boxes on client side of webui +def connect_trash_prompt(dummy_component, button, is_img2img): + + button.click( + fn=lambda: print("Clearing prompt"), + _js="trash_prompt", + inputs=[], + outputs=[], + ) + def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox, dummy_component, is_subseed): """ Connects a 'reuse (sub)seed' button's click event so that it copies last used (sub)seed value from generation info the to the seed field. If copying subseed and subseed strength @@ -540,7 +550,7 @@ def create_toprow(is_img2img): prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys()))) prompt_style2.save_to_config = True - return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button + return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button, trash_prompt def setup_progressbar(progressbar, preview, id_part, textinfo=None): @@ -619,10 +629,11 @@ def create_ui(wrap_gradio_gpu_call): with gr.Blocks(analytics_enabled=False) as txt2img_interface: txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _,\ txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter,\ - token_button = create_toprow(is_img2img=False) + token_button, trash_prompt_button = create_toprow(is_img2img=False) dummy_component = gr.Label(visible=False) txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False) + connect_trash_prompt(dummy_component, trash_prompt_button, False) with gr.Row(elem_id='txt2img_progress_row'): with gr.Column(scale=1): @@ -807,7 +818,11 @@ def create_ui(wrap_gradio_gpu_call): token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter]) with gr.Blocks(analytics_enabled=False) as img2img_interface: - img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste, token_counter, token_button = create_toprow(is_img2img=True) + img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit,\ + img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,\ + token_counter, token_button, trash_prompt_button = create_toprow(is_img2img=True) + + connect_trash_prompt(dummy_component,trash_prompt_button, True) with gr.Row(elem_id='img2img_progress_row'): img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False) -- cgit v1.2.3 From f8733ad08be08bafb40f4299785590e11f049e96 Mon Sep 17 00:00:00 2001 From: discus0434 Date: Thu, 20 Oct 2022 11:07:37 +0000 Subject: add linear as a act func (option for doin nothing) --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 913b23b4..716f14b8 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1224,7 +1224,7 @@ def create_ui(wrap_gradio_gpu_call): new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'") new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization") - new_hypernetwork_activation_func = gr.Dropdown(value="relu", label="Select activation function of hypernetwork", choices=["relu", "leakyrelu"]) + new_hypernetwork_activation_func = gr.Dropdown(value="relu", label="Select activation function of hypernetwork", choices=["linear", "relu", "leakyrelu"]) with gr.Row(): with gr.Column(scale=3): -- cgit v1.2.3 From 85dd62c4c7635b8e21a75f140d093036069e97a1 Mon Sep 17 00:00:00 2001 From: Milly Date: Thu, 20 Oct 2022 22:56:45 +0900 Subject: train: ui: added `Split image threshold` and `Split image overlap ratio` to preprocess --- modules/textual_inversion/preprocess.py | 10 +++++----- modules/ui.py | 16 ++++++++++++++-- 2 files changed, 19 insertions(+), 7 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index 2743bdeb..c8df8aa0 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -12,7 +12,7 @@ if cmd_opts.deepdanbooru: import modules.deepbooru as deepbooru -def preprocess(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru=False): +def preprocess(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2): try: if process_caption: shared.interrogator.load() @@ -22,7 +22,7 @@ def preprocess(process_src, process_dst, process_width, process_height, process_ db_opts[deepbooru.OPT_INCLUDE_RANKS] = False deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, db_opts) - preprocess_work(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru) + preprocess_work(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru, split_threshold, overlap_ratio) finally: @@ -34,13 +34,13 @@ def preprocess(process_src, process_dst, process_width, process_height, process_ -def preprocess_work(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru=False): +def preprocess_work(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2): width = process_width height = process_height src = os.path.abspath(process_src) dst = os.path.abspath(process_dst) - split_threshold = 0.5 - overlap_ratio = 0.2 + split_threshold = max(0.0, min(1.0, split_threshold)) + overlap_ratio = max(0.0, min(0.9, overlap_ratio)) assert src != dst, 'same directory specified as source and destination' diff --git a/modules/ui.py b/modules/ui.py index a2dbd41e..bc7f3330 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1240,10 +1240,14 @@ def create_ui(wrap_gradio_gpu_call): with gr.Row(): process_flip = gr.Checkbox(label='Create flipped copies') - process_split = gr.Checkbox(label='Split oversized images into two') + process_split = gr.Checkbox(label='Split oversized images') process_caption = gr.Checkbox(label='Use BLIP for caption') process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True if cmd_opts.deepdanbooru else False) + with gr.Row(visible=False) as process_split_extra_row: + process_split_threshold = gr.Slider(label='Split image threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05) + process_overlap_ratio = gr.Slider(label='Split image overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05) + with gr.Row(): with gr.Column(scale=3): gr.HTML(value="") @@ -1251,6 +1255,12 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column(): run_preprocess = gr.Button(value="Preprocess", variant='primary') + process_split.change( + fn=lambda show: gr_show(show), + inputs=[process_split], + outputs=[process_split_extra_row], + ) + with gr.Tab(label="Train"): gr.HTML(value="

Train an embedding; must specify a directory with a set of 1:1 ratio images

") with gr.Row(): @@ -1327,7 +1337,9 @@ def create_ui(wrap_gradio_gpu_call): process_flip, process_split, process_caption, - process_caption_deepbooru + process_caption_deepbooru, + process_split_threshold, + process_overlap_ratio, ], outputs=[ ti_output, -- cgit v1.2.3 From d07cb46f34b3d9fe7a78b102f899ebef352ea56b Mon Sep 17 00:00:00 2001 From: yfszzx Date: Thu, 20 Oct 2022 23:58:52 +0800 Subject: inspiration pull request --- .gitignore | 3 +- javascript/imageviewer.js | 1 - javascript/inspiration.js | 42 ++++++++++++ modules/inspiration.py | 122 +++++++++++++++++++++++++++++++++++ modules/shared.py | 1 + modules/ui.py | 13 ++-- scripts/create_inspiration_images.py | 45 +++++++++++++ webui.py | 5 ++ 8 files changed, 225 insertions(+), 7 deletions(-) create mode 100644 javascript/inspiration.js create mode 100644 modules/inspiration.py create mode 100644 scripts/create_inspiration_images.py (limited to 'modules/ui.py') diff --git a/.gitignore b/.gitignore index f9c3357c..434d50b7 100644 --- a/.gitignore +++ b/.gitignore @@ -27,4 +27,5 @@ __pycache__ notification.mp3 /SwinIR /textual_inversion -.vscode \ No newline at end of file +.vscode +/inspiration \ No newline at end of file diff --git a/javascript/imageviewer.js b/javascript/imageviewer.js index 9e380c65..d4ab6984 100644 --- a/javascript/imageviewer.js +++ b/javascript/imageviewer.js @@ -116,7 +116,6 @@ function showGalleryImage() { e.dataset.modded = true; if(e && e.parentElement.tagName == 'DIV'){ e.style.cursor='pointer' - e.style.userSelect='none' e.addEventListener('click', function (evt) { if(!opts.js_modal_lightbox) return; modalZoomSet(gradioApp().getElementById('modalImage'), opts.js_modal_lightbox_initially_zoomed) diff --git a/javascript/inspiration.js b/javascript/inspiration.js new file mode 100644 index 00000000..e1c0e114 --- /dev/null +++ b/javascript/inspiration.js @@ -0,0 +1,42 @@ +function public_image_index_in_gallery(item, gallery){ + var index; + var i = 0; + gallery.querySelectorAll("img").forEach(function(e){ + if (e == item) + index = i; + i += 1; + }); + return index; +} + +function inspiration_selected(name, types, name_list){ + var btn = gradioApp().getElementById("inspiration_select_button") + return [gradioApp().getElementById("inspiration_select_button").getAttribute("img-index"), types]; +} +var inspiration_image_click = function(){ + var index = public_image_index_in_gallery(this, gradioApp().getElementById("inspiration_gallery")); + var btn = gradioApp().getElementById("inspiration_select_button") + btn.setAttribute("img-index", index) + setTimeout(function(btn){btn.click();}, 10, btn) +} + +document.addEventListener("DOMContentLoaded", function() { + var mutationObserver = new MutationObserver(function(m){ + var gallery = gradioApp().getElementById("inspiration_gallery") + if (gallery) { + var node = gallery.querySelector(".absolute.backdrop-blur.h-full") + if (node) { + node.style.display = "None"; //parentNode.removeChild(node) + } + + gallery.querySelectorAll('img').forEach(function(e){ + e.onclick = inspiration_image_click + }) + + } + + + }); + mutationObserver.observe( gradioApp(), { childList:true, subtree:true }); + +}); diff --git a/modules/inspiration.py b/modules/inspiration.py new file mode 100644 index 00000000..456bfcb5 --- /dev/null +++ b/modules/inspiration.py @@ -0,0 +1,122 @@ +import os +import random +import gradio +inspiration_path = "inspiration" +inspiration_system_path = os.path.join(inspiration_path, "system") +def read_name_list(file): + if not os.path.exists(file): + return [] + f = open(file, "r") + ret = [] + line = f.readline() + while len(line) > 0: + line = line.rstrip("\n") + ret.append(line) + print(ret) + return ret + +def save_name_list(file, name): + print(file) + f = open(file, "a") + f.write(name + "\n") + +def get_inspiration_images(source, types): + path = os.path.join(inspiration_path , types) + if source == "Favorites": + names = read_name_list(os.path.join(inspiration_system_path, types + "_faverites.txt")) + names = random.sample(names, 25) + elif source == "Abandoned": + names = read_name_list(os.path.join(inspiration_system_path, types + "_abondened.txt")) + names = random.sample(names, 25) + elif source == "Exclude abandoned": + abondened = read_name_list(os.path.join(inspiration_system_path, types + "_abondened.txt")) + all_names = os.listdir(path) + names = [] + while len(names) < 25: + name = random.choice(all_names) + if name not in abondened: + names.append(name) + else: + names = random.sample(os.listdir(path), 25) + names = random.sample(names, 25) + image_list = [] + for a in names: + image_path = os.path.join(path, a) + images = os.listdir(image_path) + image_list.append(os.path.join(image_path, random.choice(images))) + return image_list, names + +def select_click(index, types, name_list): + name = name_list[int(index)] + path = os.path.join(inspiration_path, types, name) + images = os.listdir(path) + return name, [os.path.join(path, x) for x in images] + +def give_up_click(name, types): + file = os.path.join(inspiration_system_path, types + "_abandoned.txt") + name_list = read_name_list(file) + if name not in name_list: + save_name_list(file, name) + +def collect_click(name, types): + file = os.path.join(inspiration_system_path, types + "_faverites.txt") + print(file) + name_list = read_name_list(file) + print(name_list) + if name not in name_list: + save_name_list(file, name) + +def moveout_click(name, types): + file = os.path.join(inspiration_system_path, types + "_faverites.txt") + name_list = read_name_list(file) + if name not in name_list: + save_name_list(file, name) + +def source_change(source): + if source == "Abandoned" or source == "Favorites": + return gradio.Button.update(visible=True, value=f"Move out {source}") + else: + return gradio.Button.update(visible=False) + +def ui(gr, opts): + with gr.Blocks(analytics_enabled=False) as inspiration: + flag = os.path.exists(inspiration_path) + if flag: + types = os.listdir(inspiration_path) + types = [x for x in types if x != "system"] + flag = len(types) > 0 + if not flag: + os.mkdir(inspiration_path) + gr.HTML(""" +
" + """) + return inspiration + if not os.path.exists(inspiration_system_path): + os.mkdir(inspiration_system_path) + gallery, names = get_inspiration_images("Exclude abandoned", types[0]) + with gr.Row(): + with gr.Column(scale=2): + inspiration_gallery = gr.Gallery(gallery, show_label=False, elem_id="inspiration_gallery").style(grid=5, height='auto') + with gr.Column(scale=1): + types = gr.Dropdown(choices=types, value=types[0], label="Type", visible=len(types) > 1) + with gr.Row(): + source = gr.Dropdown(choices=["All", "Favorites", "Exclude abandoned", "Abandoned"], value="Exclude abandoned", label="Source") + get_inspiration = gr.Button("Get inspiration") + name = gr.Textbox(show_label=False, interactive=False) + with gr.Row(): + send_to_txt2img = gr.Button('to txt2img') + send_to_img2img = gr.Button('to img2img') + style_gallery = gr.Gallery(show_label=False, elem_id="inspiration_style_gallery").style(grid=2, height='auto') + + collect = gr.Button('Collect') + give_up = gr.Button("Don't show any more") + moveout = gr.Button("Move out", visible=False) + with gr.Row(): + select_button = gr.Button('set button', elem_id="inspiration_select_button") + name_list = gr.State(names) + source.change(source_change, inputs=[source], outputs=[moveout]) + get_inspiration.click(get_inspiration_images, inputs=[source, types], outputs=[inspiration_gallery, name_list]) + select_button.click(select_click, _js="inspiration_selected", inputs=[name, types, name_list], outputs=[name, style_gallery]) + give_up.click(give_up_click, inputs=[name, types], outputs=None) + collect.click(collect_click, inputs=[name, types], outputs=None) + return inspiration diff --git a/modules/shared.py b/modules/shared.py index faede821..ae033710 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -78,6 +78,7 @@ parser.add_argument('--vae-path', type=str, help='Path to Variational Autoencode parser.add_argument("--disable-safe-unpickle", action='store_true', help="disable checking pytorch models for malicious code", default=False) parser.add_argument("--api", action='store_true', help="use api=True to launch the api with the webui") parser.add_argument("--nowebui", action='store_true', help="use api=True to launch the api instead of the webui") +parser.add_argument("--ui-debug-mode", action='store_true', help="Don't load model to quickly launch UI") cmd_opts = parser.parse_args() restricted_opts = [ diff --git a/modules/ui.py b/modules/ui.py index a2dbd41e..6a0a3c3b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -41,7 +41,8 @@ from modules import prompt_parser from modules.images import save_image import modules.textual_inversion.ui import modules.hypernetworks.ui -import modules.images_history as img_his +import modules.images_history as images_history +import modules.inspiration as inspiration # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() @@ -1082,9 +1083,9 @@ def create_ui(wrap_gradio_gpu_call): upscaling_resize_w = gr.Number(label="Width", value=512, precision=0) upscaling_resize_h = gr.Number(label="Height", value=512, precision=0) upscaling_crop = gr.Checkbox(label='Crop to fit', value=True) - + with gr.Group(): - extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") + extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers] , value=shared.sd_upscalers[0].name, type="index") with gr.Group(): extras_upscaler_2 = gr.Radio(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") @@ -1178,7 +1179,8 @@ def create_ui(wrap_gradio_gpu_call): "i2i":img2img_paste_fields } - images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) + browser_interface = images_history.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) + inspiration_interface = inspiration.ui(gr, opts) with gr.Blocks() as modelmerger_interface: with gr.Row().style(equal_height=False): @@ -1595,7 +1597,8 @@ Requested path was: {f} (img2img_interface, "img2img", "img2img"), (extras_interface, "Extras", "extras"), (pnginfo_interface, "PNG Info", "pnginfo"), - (images_history, "History", "images_history"), + (browser_interface, "History", "images_history"), + (inspiration_interface, "Inspiration", "inspiration"), (modelmerger_interface, "Checkpoint Merger", "modelmerger"), (train_interface, "Train", "ti"), (settings_interface, "Settings", "settings"), diff --git a/scripts/create_inspiration_images.py b/scripts/create_inspiration_images.py new file mode 100644 index 00000000..6a20def8 --- /dev/null +++ b/scripts/create_inspiration_images.py @@ -0,0 +1,45 @@ +import csv, os, shutil +import modules.scripts as scripts +from modules import processing, shared, sd_samplers, images +from modules.processing import Processed + + +class Script(scripts.Script): + def title(self): + return "Create artists style image" + + def show(self, is_img2img): + return not is_img2img + + def ui(self, is_img2img): + return [] + def show(self, is_img2img): + return not is_img2img + + def run(self, p): #, max_snapshoots_num): + path = os.path.join("style_snapshoot", "artist") + if not os.path.exists(path): + os.makedirs(path) + p.do_not_save_samples = True + p.do_not_save_grid = True + p.negative_prompt = "portrait photo" + f = open('artists.csv') + f_csv = csv.reader(f) + for row in f_csv: + name = row[0] + artist_path = os.path.join(path, name) + if not os.path.exists(artist_path): + os.mkdir(artist_path) + if len(os.listdir(artist_path)) > 0: + continue + print(name) + p.prompt = name + processed = processing.process_images(p) + for img in processed.images: + i = 0 + filename = os.path.join(artist_path, format(0, "03d") + ".jpg") + while os.path.exists(filename): + i += 1 + filename = os.path.join(artist_path, format(i, "03d") + ".jpg") + img.save(filename, quality=70) + return processed diff --git a/webui.py b/webui.py index 177bef74..5923905f 100644 --- a/webui.py +++ b/webui.py @@ -72,6 +72,11 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs) def initialize(): + if cmd_opts.ui_debug_mode: + class enmpty(): + name = None + shared.sd_upscalers = [enmpty()] + return modelloader.cleanup_models() modules.sd_models.setup_model() codeformer.setup_model(cmd_opts.codeformer_models_path) -- cgit v1.2.3 From a3b047b7c74dc6ca07f40aee778997fc1889d72f Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Thu, 20 Oct 2022 19:28:58 -0500 Subject: add settings option to toggle button visibility --- javascript/ui.js | 1 - modules/shared.py | 1 + modules/ui.py | 2 +- 3 files changed, 2 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index 39eae1f7..f19af550 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -163,7 +163,6 @@ function selected_tab_id() { } function trash_prompt(_,_, is_img2img) { -//txt2img_token_button if(!confirm("Delete prompt?")) return false diff --git a/modules/shared.py b/modules/shared.py index faede821..7e9c2696 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -300,6 +300,7 @@ options_templates.update(options_section(('ui', "User interface"), { "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"), "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"), "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."), + "trash_prompt_visible": OptionInfo(True, "Show trash prompt button"), 'quicksettings': OptionInfo("sd_model_checkpoint", "Quicksettings list"), 'localization': OptionInfo("None", "Localization (requires restart)", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)), })) diff --git a/modules/ui.py b/modules/ui.py index bde546cc..13c0b4ca 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -509,7 +509,7 @@ def create_toprow(is_img2img): paste = gr.Button(value=paste_symbol, elem_id="paste") save_style = gr.Button(value=save_style_symbol, elem_id="style_create") prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply") - trash_prompt = gr.Button(value=trash_prompt_symbol, elem_id="trash_prompt") + trash_prompt = gr.Button(value=trash_prompt_symbol, elem_id="trash_prompt", visible=opts.trash_prompt_visible) token_counter = gr.HTML(value="", elem_id=f"{id_part}_token_counter") token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button") -- cgit v1.2.3 From df5706409386cc2e88718bd9101045587c39f8bb Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 21 Oct 2022 16:10:51 +0300 Subject: do not load aesthetic clip model until it's needed add refresh button for aesthetic embeddings add aesthetic params to images' infotext --- modules/aesthetic_clip.py | 40 +++++++++++++++++++---- modules/generation_parameters_copypaste.py | 18 +++++++++-- modules/img2img.py | 5 +-- modules/processing.py | 4 +-- modules/sd_models.py | 3 -- modules/txt2img.py | 4 +-- modules/ui.py | 52 ++++++++++++++++++++---------- style.css | 2 +- 8 files changed, 89 insertions(+), 39 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/aesthetic_clip.py b/modules/aesthetic_clip.py index 34efa931..8c828541 100644 --- a/modules/aesthetic_clip.py +++ b/modules/aesthetic_clip.py @@ -40,6 +40,8 @@ def iter_to_batched(iterable, n=1): def create_ui(): + import modules.ui + with gr.Group(): with gr.Accordion("Open for Clip Aesthetic!", open=False): with gr.Row(): @@ -55,6 +57,8 @@ def create_ui(): label="Aesthetic imgs embedding", value="None") + modules.ui.create_refresh_button(aesthetic_imgs, shared.update_aesthetic_embeddings, lambda: {"choices": sorted(shared.aesthetic_embeddings.keys())}, "refresh_aesthetic_embeddings") + with gr.Row(): aesthetic_imgs_text = gr.Textbox(label='Aesthetic text for imgs', placeholder="This text is used to rotate the feature space of the imgs embs", @@ -66,11 +70,21 @@ def create_ui(): return aesthetic_weight, aesthetic_steps, aesthetic_lr, aesthetic_slerp, aesthetic_imgs, aesthetic_imgs_text, aesthetic_slerp_angle, aesthetic_text_negative +aesthetic_clip_model = None + + +def aesthetic_clip(): + global aesthetic_clip_model + + if aesthetic_clip_model is None or aesthetic_clip_model.name_or_path != shared.sd_model.cond_stage_model.wrapped.transformer.name_or_path: + aesthetic_clip_model = CLIPModel.from_pretrained(shared.sd_model.cond_stage_model.wrapped.transformer.name_or_path) + aesthetic_clip_model.cpu() + + return aesthetic_clip_model + + def generate_imgs_embd(name, folder, batch_size): - # clipModel = CLIPModel.from_pretrained( - # shared.sd_model.cond_stage_model.clipModel.name_or_path - # ) - model = shared.clip_model.to(device) + model = aesthetic_clip().to(device) processor = CLIPProcessor.from_pretrained(model.name_or_path) with torch.no_grad(): @@ -91,7 +105,7 @@ def generate_imgs_embd(name, folder, batch_size): path = str(Path(shared.cmd_opts.aesthetic_embeddings_dir) / f"{name}.pt") torch.save(embs, path) - model = model.cpu() + model.cpu() del processor del embs gc.collect() @@ -132,7 +146,7 @@ class AestheticCLIP: self.image_embs = None self.load_image_embs(None) - def set_aesthetic_params(self, aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, image_embs_name=None, + def set_aesthetic_params(self, p, aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, image_embs_name=None, aesthetic_slerp=True, aesthetic_imgs_text="", aesthetic_slerp_angle=0.15, aesthetic_text_negative=False): @@ -145,6 +159,18 @@ class AestheticCLIP: self.aesthetic_steps = aesthetic_steps self.load_image_embs(image_embs_name) + if self.image_embs_name is not None: + p.extra_generation_params.update({ + "Aesthetic LR": aesthetic_lr, + "Aesthetic weight": aesthetic_weight, + "Aesthetic steps": aesthetic_steps, + "Aesthetic embedding": self.image_embs_name, + "Aesthetic slerp": aesthetic_slerp, + "Aesthetic text": aesthetic_imgs_text, + "Aesthetic text negative": aesthetic_text_negative, + "Aesthetic slerp angle": aesthetic_slerp_angle, + }) + def set_skip(self, skip): self.skip = skip @@ -168,7 +194,7 @@ class AestheticCLIP: tokens = torch.asarray(remade_batch_tokens).to(device) - model = copy.deepcopy(shared.clip_model).to(device) + model = copy.deepcopy(aesthetic_clip()).to(device) model.requires_grad_(True) if self.aesthetic_imgs_text is not None and len(self.aesthetic_imgs_text) > 0: text_embs_2 = model.get_text_features( diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 0f041449..f73647da 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -4,13 +4,22 @@ import gradio as gr from modules.shared import script_path from modules import shared -re_param_code = r"\s*([\w ]+):\s*([^,]+)(?:,|$)" +re_param_code = r'\s*([\w ]+):\s*("(?:\\|\"|[^\"])+"|[^,]*)(?:,|$)' re_param = re.compile(re_param_code) re_params = re.compile(r"^(?:" + re_param_code + "){3,}$") re_imagesize = re.compile(r"^(\d+)x(\d+)$") type_of_gr_update = type(gr.update()) +def quote(text): + if ',' not in str(text): + return text + + text = str(text) + text = text.replace('\\', '\\\\') + text = text.replace('"', '\\"') + return f'"{text}"' + def parse_generation_parameters(x: str): """parses generation parameters string, the one you see in text field under the picture in UI: ``` @@ -83,7 +92,12 @@ def connect_paste(button, paste_fields, input_comp, js=None): else: try: valtype = type(output.value) - val = valtype(v) + + if valtype == bool and v == "False": + val = False + else: + val = valtype(v) + res.append(gr.update(value=val)) except Exception: res.append(gr.update()) diff --git a/modules/img2img.py b/modules/img2img.py index bc7c66bc..eea5199b 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -109,10 +109,7 @@ def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, pro inpainting_mask_invert=inpainting_mask_invert, ) - shared.aesthetic_clip.set_aesthetic_params(float(aesthetic_lr), float(aesthetic_weight), int(aesthetic_steps), - aesthetic_imgs, aesthetic_slerp, aesthetic_imgs_text, - aesthetic_slerp_angle, - aesthetic_text_negative) + shared.aesthetic_clip.set_aesthetic_params(p, float(aesthetic_lr), float(aesthetic_weight), int(aesthetic_steps), aesthetic_imgs, aesthetic_slerp, aesthetic_imgs_text, aesthetic_slerp_angle, aesthetic_text_negative) if shared.cmd_opts.enable_console_prompts: print(f"\nimg2img: {prompt}", file=shared.progress_print_out) diff --git a/modules/processing.py b/modules/processing.py index d1deffa9..f0852cd5 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -12,7 +12,7 @@ from skimage import exposure from typing import Any, Dict, List, Optional import modules.sd_hijack -from modules import devices, prompt_parser, masking, sd_samplers, lowvram +from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste from modules.sd_hijack import model_hijack from modules.shared import opts, cmd_opts, state import modules.shared as shared @@ -318,7 +318,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration generation_params.update(p.extra_generation_params) - generation_params_text = ", ".join([k if k == v else f'{k}: {v}' for k, v in generation_params.items() if v is not None]) + generation_params_text = ", ".join([k if k == v else f'{k}: {generation_parameters_copypaste.quote(v)}' for k, v in generation_params.items() if v is not None]) negative_prompt_text = "\nNegative prompt: " + p.negative_prompt if p.negative_prompt else "" diff --git a/modules/sd_models.py b/modules/sd_models.py index 05a1df28..b1c91b0d 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -234,9 +234,6 @@ def load_model(checkpoint_info=None): sd_hijack.model_hijack.hijack(sd_model) - if shared.clip_model is None or shared.clip_model.transformer.name_or_path != sd_model.cond_stage_model.wrapped.transformer.name_or_path: - shared.clip_model = CLIPModel.from_pretrained(sd_model.cond_stage_model.wrapped.transformer.name_or_path) - sd_model.eval() print(f"Model loaded.") diff --git a/modules/txt2img.py b/modules/txt2img.py index 32ed1d8d..1761cfa2 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -36,9 +36,7 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: firstphase_height=firstphase_height if enable_hr else None, ) - shared.aesthetic_clip.set_aesthetic_params(float(aesthetic_lr), float(aesthetic_weight), int(aesthetic_steps), - aesthetic_imgs, aesthetic_slerp, aesthetic_imgs_text, aesthetic_slerp_angle, - aesthetic_text_negative) + shared.aesthetic_clip.set_aesthetic_params(p, float(aesthetic_lr), float(aesthetic_weight), int(aesthetic_steps), aesthetic_imgs, aesthetic_slerp, aesthetic_imgs_text, aesthetic_slerp_angle, aesthetic_text_negative) if cmd_opts.enable_console_prompts: print(f"\ntxt2img: {prompt}", file=shared.progress_print_out) diff --git a/modules/ui.py b/modules/ui.py index 381ca925..0d020de6 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -597,27 +597,29 @@ def apply_setting(key, value): return value -def create_ui(wrap_gradio_gpu_call): - import modules.img2img - import modules.txt2img +def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id): + def refresh(): + refresh_method() + args = refreshed_args() if callable(refreshed_args) else refreshed_args - def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id): - def refresh(): - refresh_method() - args = refreshed_args() if callable(refreshed_args) else refreshed_args + for k, v in args.items(): + setattr(refresh_component, k, v) - for k, v in args.items(): - setattr(refresh_component, k, v) + return gr.update(**(args or {})) - return gr.update(**(args or {})) + refresh_button = gr.Button(value=refresh_symbol, elem_id=elem_id) + refresh_button.click( + fn=refresh, + inputs=[], + outputs=[refresh_component] + ) + return refresh_button + + +def create_ui(wrap_gradio_gpu_call): + import modules.img2img + import modules.txt2img - refresh_button = gr.Button(value=refresh_symbol, elem_id=elem_id) - refresh_button.click( - fn = refresh, - inputs = [], - outputs = [refresh_component] - ) - return refresh_button with gr.Blocks(analytics_enabled=False) as txt2img_interface: txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False) @@ -802,6 +804,14 @@ def create_ui(wrap_gradio_gpu_call): (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)), (firstphase_width, "First pass size-1"), (firstphase_height, "First pass size-2"), + (aesthetic_lr, "Aesthetic LR"), + (aesthetic_weight, "Aesthetic weight"), + (aesthetic_steps, "Aesthetic steps"), + (aesthetic_imgs, "Aesthetic embedding"), + (aesthetic_slerp, "Aesthetic slerp"), + (aesthetic_imgs_text, "Aesthetic text"), + (aesthetic_text_negative, "Aesthetic text negative"), + (aesthetic_slerp_angle, "Aesthetic slerp angle"), ] txt2img_preview_params = [ @@ -1077,6 +1087,14 @@ def create_ui(wrap_gradio_gpu_call): (seed_resize_from_w, "Seed resize from-1"), (seed_resize_from_h, "Seed resize from-2"), (denoising_strength, "Denoising strength"), + (aesthetic_lr_im, "Aesthetic LR"), + (aesthetic_weight_im, "Aesthetic weight"), + (aesthetic_steps_im, "Aesthetic steps"), + (aesthetic_imgs_im, "Aesthetic embedding"), + (aesthetic_slerp_im, "Aesthetic slerp"), + (aesthetic_imgs_text_im, "Aesthetic text"), + (aesthetic_text_negative_im, "Aesthetic text negative"), + (aesthetic_slerp_angle_im, "Aesthetic slerp angle"), ] token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter]) diff --git a/style.css b/style.css index 26ae36a5..5d2bacc9 100644 --- a/style.css +++ b/style.css @@ -477,7 +477,7 @@ input[type="range"]{ padding: 0; } -#refresh_sd_model_checkpoint, #refresh_sd_hypernetwork, #refresh_train_hypernetwork_name, #refresh_train_embedding_name, #refresh_localization{ +#refresh_sd_model_checkpoint, #refresh_sd_hypernetwork, #refresh_train_hypernetwork_name, #refresh_train_embedding_name, #refresh_localization, #refresh_aesthetic_embeddings{ max-width: 2.5em; min-width: 2.5em; height: 2.4em; -- cgit v1.2.3 From 704036ff07b71bf86cadcbbff2bcfeebdd1ed3a6 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 21 Oct 2022 17:11:42 +0300 Subject: make aspect ratio overlay work regardless of selected localization --- javascript/aspectRatioOverlay.js | 36 +++++++++++++++++------------------- javascript/dragdrop.js | 2 +- modules/ui.py | 4 ++-- 3 files changed, 20 insertions(+), 22 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/aspectRatioOverlay.js b/javascript/aspectRatioOverlay.js index 96f1c00d..d3ca2781 100644 --- a/javascript/aspectRatioOverlay.js +++ b/javascript/aspectRatioOverlay.js @@ -3,12 +3,12 @@ let currentWidth = null; let currentHeight = null; let arFrameTimeout = setTimeout(function(){},0); -function dimensionChange(e,dimname){ +function dimensionChange(e, is_width, is_height){ - if(dimname == 'Width'){ + if(is_width){ currentWidth = e.target.value*1.0 } - if(dimname == 'Height'){ + if(is_height){ currentHeight = e.target.value*1.0 } @@ -98,22 +98,20 @@ onUiUpdate(function(){ var inImg2img = Boolean(gradioApp().querySelector("button.rounded-t-lg.border-gray-200")) if(inImg2img){ let inputs = gradioApp().querySelectorAll('input'); - inputs.forEach(function(e){ - let parentLabel = e.parentElement.querySelector('label') - if(parentLabel && parentLabel.innerText){ - if(!e.classList.contains('scrollwatch')){ - if(parentLabel.innerText == 'Width' || parentLabel.innerText == 'Height'){ - e.addEventListener('input', function(e){dimensionChange(e,parentLabel.innerText)} ) - e.classList.add('scrollwatch') - } - if(parentLabel.innerText == 'Width'){ - currentWidth = e.value*1.0 - } - if(parentLabel.innerText == 'Height'){ - currentHeight = e.value*1.0 - } - } - } + inputs.forEach(function(e){ + var is_width = e.parentElement.id == "img2img_width" + var is_height = e.parentElement.id == "img2img_height" + + if((is_width || is_height) && !e.classList.contains('scrollwatch')){ + e.addEventListener('input', function(e){dimensionChange(e, is_width, is_height)} ) + e.classList.add('scrollwatch') + } + if(is_width){ + currentWidth = e.value*1.0 + } + if(is_height){ + currentHeight = e.value*1.0 + } }) } }); diff --git a/javascript/dragdrop.js b/javascript/dragdrop.js index 070cf255..3ed1cb3c 100644 --- a/javascript/dragdrop.js +++ b/javascript/dragdrop.js @@ -43,7 +43,7 @@ function dropReplaceImage( imgWrap, files ) { window.document.addEventListener('dragover', e => { const target = e.composedPath()[0]; const imgWrap = target.closest('[data-testid="image"]'); - if ( !imgWrap && target.placeholder.indexOf("Prompt") == -1) { + if ( !imgWrap && target.placeholder && target.placeholder.indexOf("Prompt") == -1) { return; } e.stopPropagation(); diff --git a/modules/ui.py b/modules/ui.py index 0d020de6..85f95792 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -879,8 +879,8 @@ def create_ui(wrap_gradio_gpu_call): sampler_index = gr.Radio(label='Sampling method', choices=[x.name for x in samplers_for_img2img], value=samplers_for_img2img[0].name, type="index") with gr.Group(): - width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512) - height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) + width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512, elem_id="img2img_width") + height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512, elem_id="img2img_height") with gr.Row(): restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1) -- cgit v1.2.3 From bb0f1a2cdae3410a41d06ae878f56e29b8154c41 Mon Sep 17 00:00:00 2001 From: yfszzx Date: Sat, 22 Oct 2022 01:23:00 +0800 Subject: inspiration finished --- javascript/inspiration.js | 27 ++++--- modules/inspiration.py | 192 ++++++++++++++++++++++++++++++---------------- modules/shared.py | 6 ++ modules/ui.py | 2 +- webui.py | 3 +- 5 files changed, 151 insertions(+), 79 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/inspiration.js b/javascript/inspiration.js index e1c0e114..791a80c9 100644 --- a/javascript/inspiration.js +++ b/javascript/inspiration.js @@ -1,25 +1,31 @@ function public_image_index_in_gallery(item, gallery){ + var imgs = gallery.querySelectorAll("img.h-full") var index; var i = 0; - gallery.querySelectorAll("img").forEach(function(e){ + imgs.forEach(function(e){ if (e == item) index = i; i += 1; }); + var num = imgs.length / 2 + index = (index < num) ? index : (index - num) return index; } -function inspiration_selected(name, types, name_list){ +function inspiration_selected(name, name_list){ var btn = gradioApp().getElementById("inspiration_select_button") - return [gradioApp().getElementById("inspiration_select_button").getAttribute("img-index"), types]; -} + return [gradioApp().getElementById("inspiration_select_button").getAttribute("img-index")]; +} +function inspiration_click_get_button(){ + gradioApp().getElementById("inspiration_get_button").click(); +} var inspiration_image_click = function(){ var index = public_image_index_in_gallery(this, gradioApp().getElementById("inspiration_gallery")); - var btn = gradioApp().getElementById("inspiration_select_button") - btn.setAttribute("img-index", index) - setTimeout(function(btn){btn.click();}, 10, btn) + var btn = gradioApp().getElementById("inspiration_select_button"); + btn.setAttribute("img-index", index); + setTimeout(function(btn){btn.click();}, 10, btn); } - + document.addEventListener("DOMContentLoaded", function() { var mutationObserver = new MutationObserver(function(m){ var gallery = gradioApp().getElementById("inspiration_gallery") @@ -27,11 +33,10 @@ document.addEventListener("DOMContentLoaded", function() { var node = gallery.querySelector(".absolute.backdrop-blur.h-full") if (node) { node.style.display = "None"; //parentNode.removeChild(node) - } - + } gallery.querySelectorAll('img').forEach(function(e){ e.onclick = inspiration_image_click - }) + }); } diff --git a/modules/inspiration.py b/modules/inspiration.py index 456bfcb5..f72ebf3a 100644 --- a/modules/inspiration.py +++ b/modules/inspiration.py @@ -1,122 +1,182 @@ import os import random -import gradio -inspiration_path = "inspiration" -inspiration_system_path = os.path.join(inspiration_path, "system") -def read_name_list(file): +import gradio +from modules.shared import opts +inspiration_system_path = os.path.join(opts.inspiration_dir, "system") +def read_name_list(file, types=None, keyword=None): if not os.path.exists(file): return [] - f = open(file, "r") ret = [] + f = open(file, "r") line = f.readline() while len(line) > 0: line = line.rstrip("\n") - ret.append(line) - print(ret) + if types is not None: + dirname = os.path.split(line) + if dirname[0] in types and keyword in dirname[1]: + ret.append(line) + else: + ret.append(line) + line = f.readline() return ret def save_name_list(file, name): - print(file) - f = open(file, "a") - f.write(name + "\n") + with open(file, "a") as f: + f.write(name + "\n") -def get_inspiration_images(source, types): - path = os.path.join(inspiration_path , types) +def get_types_list(): + files = os.listdir(opts.inspiration_dir) + types = [] + for x in files: + path = os.path.join(opts.inspiration_dir, x) + if x[0] == ".": + continue + if not os.path.isdir(path): + continue + if path == inspiration_system_path: + continue + types.append(x) + return types + +def get_inspiration_images(source, types, keyword): + get_num = int(opts.inspiration_rows_num * opts.inspiration_cols_num) if source == "Favorites": - names = read_name_list(os.path.join(inspiration_system_path, types + "_faverites.txt")) - names = random.sample(names, 25) + names = read_name_list(os.path.join(inspiration_system_path, "faverites.txt"), types, keyword) + names = random.sample(names, get_num) if len(names) > get_num else names elif source == "Abandoned": - names = read_name_list(os.path.join(inspiration_system_path, types + "_abondened.txt")) - names = random.sample(names, 25) - elif source == "Exclude abandoned": - abondened = read_name_list(os.path.join(inspiration_system_path, types + "_abondened.txt")) - all_names = os.listdir(path) - names = [] - while len(names) < 25: - name = random.choice(all_names) - if name not in abondened: - names.append(name) + names = read_name_list(os.path.join(inspiration_system_path, "abandoned.txt"), types, keyword) + print(names) + names = random.sample(names, get_num) if len(names) > get_num else names + elif source == "Exclude abandoned": + abandoned = read_name_list(os.path.join(inspiration_system_path, "abandoned.txt"), types, keyword) + all_names = [] + for tp in types: + name_list = os.listdir(os.path.join(opts.inspiration_dir, tp)) + all_names += [os.path.join(tp, x) for x in name_list if keyword in x] + + if len(all_names) > get_num: + names = [] + while len(names) < get_num: + name = random.choice(all_names) + if name not in abandoned: + names.append(name) + else: + names = all_names else: - names = random.sample(os.listdir(path), 25) - names = random.sample(names, 25) + all_names = [] + for tp in types: + name_list = os.listdir(os.path.join(opts.inspiration_dir, tp)) + all_names += [os.path.join(tp, x) for x in name_list if keyword in x] + names = random.sample(all_names, get_num) if len(all_names) > get_num else all_names image_list = [] for a in names: - image_path = os.path.join(path, a) + image_path = os.path.join(opts.inspiration_dir, a) images = os.listdir(image_path) - image_list.append(os.path.join(image_path, random.choice(images))) - return image_list, names + image_list.append((os.path.join(image_path, random.choice(images)), a)) + return image_list, names, "" -def select_click(index, types, name_list): +def select_click(index, name_list): name = name_list[int(index)] - path = os.path.join(inspiration_path, types, name) + path = os.path.join(opts.inspiration_dir, name) images = os.listdir(path) - return name, [os.path.join(path, x) for x in images] + return name, [os.path.join(path, x) for x in images], "" -def give_up_click(name, types): - file = os.path.join(inspiration_system_path, types + "_abandoned.txt") +def give_up_click(name): + file = os.path.join(inspiration_system_path, "abandoned.txt") name_list = read_name_list(file) if name not in name_list: save_name_list(file, name) + return "Added to abandoned list" -def collect_click(name, types): - file = os.path.join(inspiration_system_path, types + "_faverites.txt") - print(file) +def collect_click(name): + file = os.path.join(inspiration_system_path, "faverites.txt") name_list = read_name_list(file) - print(name_list) if name not in name_list: save_name_list(file, name) + return "Added to faverite list" -def moveout_click(name, types): - file = os.path.join(inspiration_system_path, types + "_faverites.txt") +def moveout_click(name, source): + if source == "Abandoned": + file = os.path.join(inspiration_system_path, "abandoned.txt") + if source == "Favorites": + file = os.path.join(inspiration_system_path, "faverites.txt") + else: + return None name_list = read_name_list(file) - if name not in name_list: - save_name_list(file, name) + os.remove(file) + with open(file, "a") as f: + for a in name_list: + if a != name: + f.write(a) + return "Moved out {name} from {source} list" def source_change(source): - if source == "Abandoned" or source == "Favorites": - return gradio.Button.update(visible=True, value=f"Move out {source}") + if source in ["Abandoned", "Favorites"]: + return gradio.update(visible=True), [] else: - return gradio.Button.update(visible=False) + return gradio.update(visible=False), [] +def add_to_prompt(name, prompt): + print(name, prompt) + name = os.path.basename(name) + return prompt + "," + name -def ui(gr, opts): +def ui(gr, opts, txt2img_prompt, img2img_prompt): with gr.Blocks(analytics_enabled=False) as inspiration: - flag = os.path.exists(inspiration_path) + flag = os.path.exists(opts.inspiration_dir) if flag: - types = os.listdir(inspiration_path) - types = [x for x in types if x != "system"] + types = get_types_list() flag = len(types) > 0 - if not flag: - os.mkdir(inspiration_path) + else: + os.makedirs(opts.inspiration_dir) + if not flag: gr.HTML(""" -
" +

To activate inspiration function, you need get "inspiration" images first.


+ You can create these images by run "Create inspiration images" script in txt2img page,
you can get the artists or art styles list from here
+ https://github.com/pharmapsychotic/clip-interrogator/tree/main/data
+ download these files, and select these files in the "Create inspiration images" script UI
+ There about 6000 artists and art styles in these files.
This takes server hours depending on your GPU type and how many pictures you generate for each artist/style +
I suggest at least four images for each


+

You can also download generated pictures from here:


+ https://huggingface.co/datasets/yfszzx/inspiration
+ unzip the file to the project directory of webui
+ and restart webui, and enjoy the joy of creation!
""") return inspiration if not os.path.exists(inspiration_system_path): os.mkdir(inspiration_system_path) - gallery, names = get_inspiration_images("Exclude abandoned", types[0]) with gr.Row(): with gr.Column(scale=2): - inspiration_gallery = gr.Gallery(gallery, show_label=False, elem_id="inspiration_gallery").style(grid=5, height='auto') + inspiration_gallery = gr.Gallery(show_label=False, elem_id="inspiration_gallery").style(grid=opts.inspiration_cols_num, height='auto') with gr.Column(scale=1): - types = gr.Dropdown(choices=types, value=types[0], label="Type", visible=len(types) > 1) + print(types) + types = gr.CheckboxGroup(choices=types, value=types) + keyword = gr.Textbox("", label="Key word") with gr.Row(): source = gr.Dropdown(choices=["All", "Favorites", "Exclude abandoned", "Abandoned"], value="Exclude abandoned", label="Source") - get_inspiration = gr.Button("Get inspiration") + get_inspiration = gr.Button("Get inspiration", elem_id="inspiration_get_button") name = gr.Textbox(show_label=False, interactive=False) with gr.Row(): send_to_txt2img = gr.Button('to txt2img') send_to_img2img = gr.Button('to img2img') - style_gallery = gr.Gallery(show_label=False, elem_id="inspiration_style_gallery").style(grid=2, height='auto') - + style_gallery = gr.Gallery(show_label=False).style(grid=2, height='auto') collect = gr.Button('Collect') - give_up = gr.Button("Don't show any more") + give_up = gr.Button("Don't show again") moveout = gr.Button("Move out", visible=False) - with gr.Row(): + warning = gr.HTML() + with gr.Row(visible=False): select_button = gr.Button('set button', elem_id="inspiration_select_button") - name_list = gr.State(names) - source.change(source_change, inputs=[source], outputs=[moveout]) - get_inspiration.click(get_inspiration_images, inputs=[source, types], outputs=[inspiration_gallery, name_list]) - select_button.click(select_click, _js="inspiration_selected", inputs=[name, types, name_list], outputs=[name, style_gallery]) - give_up.click(give_up_click, inputs=[name, types], outputs=None) - collect.click(collect_click, inputs=[name, types], outputs=None) + name_list = gr.State() + + get_inspiration.click(get_inspiration_images, inputs=[source, types, keyword], outputs=[inspiration_gallery, name_list, keyword]) + source.change(source_change, inputs=[source], outputs=[moveout, style_gallery]) + source.change(fn=None, _js="inspiration_click_get_button", inputs=None, outputs=None) + keyword.submit(fn=None, _js="inspiration_click_get_button", inputs=None, outputs=None) + select_button.click(select_click, _js="inspiration_selected", inputs=[name, name_list], outputs=[name, style_gallery, warning]) + give_up.click(give_up_click, inputs=[name], outputs=[warning]) + collect.click(collect_click, inputs=[name], outputs=[warning]) + moveout.click(moveout_click, inputs=[name, source], outputs=[warning]) + send_to_txt2img.click(add_to_prompt, inputs=[name, txt2img_prompt], outputs=[txt2img_prompt]) + send_to_img2img.click(add_to_prompt, inputs=[name, img2img_prompt], outputs=[img2img_prompt]) + send_to_txt2img.click(None, _js='switch_to_txt2img', inputs=None, outputs=None) + send_to_img2img.click(None, _js="switch_to_img2img_img2img", inputs=None, outputs=None) return inspiration diff --git a/modules/shared.py b/modules/shared.py index ae033710..564b1b8d 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -316,6 +316,12 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}), })) +options_templates.update(options_section(('inspiration', "Inspiration"), { + "inspiration_dir": OptionInfo("inspiration", "Directory of inspiration", component_args=hide_dirs), + "inspiration_max_samples": OptionInfo(4, "Maximum number of samples, used to determine which folders to skip when continue running the create script", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1}), + "inspiration_rows_num": OptionInfo(4, "Rows of inspiration interface frame", gr.Slider, {"minimum": 4, "maximum": 16, "step": 1}), + "inspiration_cols_num": OptionInfo(8, "Columns of inspiration interface frame", gr.Slider, {"minimum": 4, "maximum": 16, "step": 1}), +})) class Options: data = None diff --git a/modules/ui.py b/modules/ui.py index 6a0a3c3b..b651eb9c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1180,7 +1180,7 @@ def create_ui(wrap_gradio_gpu_call): } browser_interface = images_history.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) - inspiration_interface = inspiration.ui(gr, opts) + inspiration_interface = inspiration.ui(gr, opts, txt2img_prompt, img2img_prompt) with gr.Blocks() as modelmerger_interface: with gr.Row().style(equal_height=False): diff --git a/webui.py b/webui.py index 5923905f..5ccae715 100644 --- a/webui.py +++ b/webui.py @@ -72,6 +72,7 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs) def initialize(): + modules.scripts.load_scripts(os.path.join(script_path, "scripts")) if cmd_opts.ui_debug_mode: class enmpty(): name = None @@ -84,7 +85,7 @@ def initialize(): shared.face_restorers.append(modules.face_restoration.FaceRestoration()) modelloader.load_upscalers() - modules.scripts.load_scripts(os.path.join(script_path, "scripts")) + shared.sd_model = modules.sd_models.load_model() shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model))) -- cgit v1.2.3 From 9ba372de90df81c4f1e992d8b33ae17c6630de95 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Fri, 21 Oct 2022 13:55:42 -0500 Subject: initial work on getting prompts cleared on the backend and synchronizing token counter --- javascript/ui.js | 10 +++++++--- modules/ui.py | 29 +++++++++++++++++++---------- 2 files changed, 26 insertions(+), 13 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index f19af550..a0f01d10 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -162,9 +162,13 @@ function selected_tab_id() { } -function trash_prompt(_,_, is_img2img) { +function trash_prompt(_, confirmed) { -if(!confirm("Delete prompt?")) return false +if(confirm("Delete prompt?")) { + confirmed = true +} else { +return [_, confirmed] +} if(selected_tab_id() == "tab_txt2img") { gradioApp().querySelector("#txt2img_prompt > label > textarea").value = ""; @@ -178,7 +182,7 @@ if(!confirm("Delete prompt?")) return false update_token_counter("txt2img_token_button") } - return true + return [_, confirmed] } diff --git a/modules/ui.py b/modules/ui.py index d2cb528e..2748a2e0 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -429,15 +429,16 @@ def create_seed_inputs(): return seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox -# setup button for clearing prompt input boxes on client side of webui -def connect_trash_prompt(dummy_component, button, is_img2img): +def clear_prompt(prompt): + print(f"type: '{prompt}'") + print(prompt) + + # update_token_counter(prompt, steps) + return "" + +def connect_trash_prompt(prompt, confirmed): + if(confirmed): clear_prompt(prompt) - button.click( - fn=lambda: print("Clearing prompt"), - _js="trash_prompt", - inputs=[], - outputs=[], - ) def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox, dummy_component, is_subseed): """ Connects a 'reuse (sub)seed' button's click event so that it copies last used @@ -640,7 +641,16 @@ def create_ui(wrap_gradio_gpu_call): dummy_component = gr.Label(visible=False) txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False) - connect_trash_prompt(dummy_component, trash_prompt_button, False) + + + trash_prompt_button.click( + # fn=lambda: print("Clearing prompt"), + _js="trash_prompt", + fn=lambda: clear_prompt(), + inputs=[txt2img_prompt, dummy_component], + outputs=[txt2img_prompt, dummy_component], + ) + with gr.Row(elem_id='txt2img_progress_row'): with gr.Column(scale=1): @@ -848,7 +858,6 @@ def create_ui(wrap_gradio_gpu_call): img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,\ token_counter, token_button, trash_prompt_button = create_toprow(is_img2img=True) - connect_trash_prompt(dummy_component,trash_prompt_button, True) with gr.Row(elem_id='img2img_progress_row'): img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False) -- cgit v1.2.3 From ee0505dd0092ae7073b77aba93a858bda000dc60 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Fri, 21 Oct 2022 14:24:14 -0500 Subject: only delete prompt on back end and remove client-side deletion --- javascript/ui.js | 6 ------ modules/ui.py | 29 +++++++++++++++-------------- 2 files changed, 15 insertions(+), 20 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index a0f01d10..29306abe 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -171,14 +171,8 @@ return [_, confirmed] } if(selected_tab_id() == "tab_txt2img") { - gradioApp().querySelector("#txt2img_prompt > label > textarea").value = ""; - gradioApp().querySelector("#txt2img_neg_prompt > label > textarea").value = ""; - update_token_counter("img2img_token_button") } else { - gradioApp().querySelector("#img2img_prompt > label > textarea").value = ""; - gradioApp().querySelector("#img2img_neg_prompt > label > textarea").value = ""; - update_token_counter("txt2img_token_button") } diff --git a/modules/ui.py b/modules/ui.py index 2748a2e0..90c338da 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -429,15 +429,21 @@ def create_seed_inputs(): return seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox -def clear_prompt(prompt): - print(f"type: '{prompt}'") - print(prompt) - # update_token_counter(prompt, steps) - return "" +def connect_trash_prompt(_, confirmed): + if(confirmed): + # update_token_counter(prompt, steps) + return ["", confirmed] -def connect_trash_prompt(prompt, confirmed): - if(confirmed): clear_prompt(prompt) +def trash_prompt_click(button, prompt): + dummy_component = gradio.Label(visible=False) + + button.click( + _js="trash_prompt", + fn=connect_trash_prompt, + inputs=[prompt, dummy_component], + outputs=[prompt, dummy_component], + ) def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox, dummy_component, is_subseed): @@ -643,13 +649,7 @@ def create_ui(wrap_gradio_gpu_call): txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False) - trash_prompt_button.click( - # fn=lambda: print("Clearing prompt"), - _js="trash_prompt", - fn=lambda: clear_prompt(), - inputs=[txt2img_prompt, dummy_component], - outputs=[txt2img_prompt, dummy_component], - ) + trash_prompt_click(trash_prompt_button, txt2img_prompt) with gr.Row(elem_id='txt2img_progress_row'): @@ -858,6 +858,7 @@ def create_ui(wrap_gradio_gpu_call): img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,\ token_counter, token_button, trash_prompt_button = create_toprow(is_img2img=True) + trash_prompt_click(trash_prompt_button, img2img_prompt) with gr.Row(elem_id='img2img_progress_row'): img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False) -- cgit v1.2.3 From de70ddaf58fae98c561738a54f574abfa14cd8d1 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Fri, 21 Oct 2022 15:00:35 -0500 Subject: update token counter when clearing prompt --- javascript/ui.js | 4 ++-- modules/ui.py | 17 +++++++---------- 2 files changed, 9 insertions(+), 12 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index 29306abe..acd57565 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -162,7 +162,7 @@ function selected_tab_id() { } -function trash_prompt(_, confirmed) { +function trash_prompt(_, confirmed,_steps) { if(confirm("Delete prompt?")) { confirmed = true @@ -176,7 +176,7 @@ return [_, confirmed] update_token_counter("txt2img_token_button") } - return [_, confirmed] + return [_, confirmed,_steps] } diff --git a/modules/ui.py b/modules/ui.py index 90c338da..d3a89bf7 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -430,19 +430,16 @@ def create_seed_inputs(): -def connect_trash_prompt(_, confirmed): +def connect_trash_prompt(_prompt, confirmed, _token_counter): if(confirmed): - # update_token_counter(prompt, steps) - return ["", confirmed] - -def trash_prompt_click(button, prompt): - dummy_component = gradio.Label(visible=False) + return ["", confirmed, update_token_counter("", 1)] +def trash_prompt_click(button, prompt, _dummy_confirmed, token_counter): button.click( _js="trash_prompt", fn=connect_trash_prompt, - inputs=[prompt, dummy_component], - outputs=[prompt, dummy_component], + inputs=[prompt, _dummy_confirmed, token_counter], + outputs=[prompt, _dummy_confirmed, token_counter], ) @@ -649,7 +646,6 @@ def create_ui(wrap_gradio_gpu_call): txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False) - trash_prompt_click(trash_prompt_button, txt2img_prompt) with gr.Row(elem_id='txt2img_progress_row'): @@ -720,6 +716,7 @@ def create_ui(wrap_gradio_gpu_call): connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) + trash_prompt_click(trash_prompt_button, txt2img_prompt, dummy_component, token_counter) txt2img_args = dict( fn=wrap_gradio_gpu_call(modules.txt2img.txt2img), @@ -858,7 +855,6 @@ def create_ui(wrap_gradio_gpu_call): img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,\ token_counter, token_button, trash_prompt_button = create_toprow(is_img2img=True) - trash_prompt_click(trash_prompt_button, img2img_prompt) with gr.Row(elem_id='img2img_progress_row'): img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False) @@ -958,6 +954,7 @@ def create_ui(wrap_gradio_gpu_call): connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) + trash_prompt_click(trash_prompt_button, img2img_prompt, dummy_component, token_counter) img2img_prompt_img.change( fn=modules.images.image_data, -- cgit v1.2.3 From 9e40520f00d836cfa93187f7f1e81e2a7bd100b9 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Fri, 21 Oct 2022 15:13:12 -0500 Subject: refactor internal terminology to use 'clear' instead of 'trash' like #2728 --- javascript/ui.js | 2 +- modules/shared.py | 2 +- modules/ui.py | 22 +++++++++++----------- 3 files changed, 13 insertions(+), 13 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index acd57565..45d93a5c 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -162,7 +162,7 @@ function selected_tab_id() { } -function trash_prompt(_, confirmed,_steps) { +function clear_prompt(_, confirmed,_steps) { if(confirm("Delete prompt?")) { confirmed = true diff --git a/modules/shared.py b/modules/shared.py index 1585d532..ab5a0e9a 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -317,7 +317,7 @@ options_templates.update(options_section(('ui', "User interface"), { "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"), "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"), "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."), - "trash_prompt_visible": OptionInfo(True, "Show trash prompt button"), + "clear_prompt_visible": OptionInfo(True, "Show clear prompt button"), 'quicksettings': OptionInfo("sd_model_checkpoint", "Quicksettings list"), 'localization': OptionInfo("None", "Localization (requires restart)", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)), })) diff --git a/modules/ui.py b/modules/ui.py index d3a89bf7..31150800 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -88,7 +88,7 @@ folder_symbol = '\U0001f4c2' # 📂 refresh_symbol = '\U0001f504' # 🔄 save_style_symbol = '\U0001f4be' # 💾 apply_style_symbol = '\U0001f4cb' # 📋 -trash_prompt_symbol = '\U0001F5D1' # +clear_prompt_symbol = '\U0001F5D1' # 🗑️ def plaintext_to_html(text): @@ -430,14 +430,14 @@ def create_seed_inputs(): -def connect_trash_prompt(_prompt, confirmed, _token_counter): +def clear_prompt(_prompt, confirmed, _token_counter): if(confirmed): return ["", confirmed, update_token_counter("", 1)] -def trash_prompt_click(button, prompt, _dummy_confirmed, token_counter): +def connect_clear_prompt(button, prompt, _dummy_confirmed, token_counter): button.click( - _js="trash_prompt", - fn=connect_trash_prompt, + _js="clear_prompt", + fn=clear_prompt, inputs=[prompt, _dummy_confirmed, token_counter], outputs=[prompt, _dummy_confirmed, token_counter], ) @@ -518,7 +518,7 @@ def create_toprow(is_img2img): paste = gr.Button(value=paste_symbol, elem_id="paste") save_style = gr.Button(value=save_style_symbol, elem_id="style_create") prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply") - trash_prompt = gr.Button(value=trash_prompt_symbol, elem_id="trash_prompt", visible=opts.trash_prompt_visible) + clear_prompt_button = gr.Button(value=clear_prompt_symbol, elem_id="clear_prompt", visible=opts.clear_prompt_visible) token_counter = gr.HTML(value="", elem_id=f"{id_part}_token_counter") token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button") @@ -559,7 +559,7 @@ def create_toprow(is_img2img): prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys()))) prompt_style2.save_to_config = True - return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button, trash_prompt + return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button, clear_prompt_button def setup_progressbar(progressbar, preview, id_part, textinfo=None): @@ -640,7 +640,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Blocks(analytics_enabled=False) as txt2img_interface: txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _,\ txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter,\ - token_button, trash_prompt_button = create_toprow(is_img2img=False) + token_button, clear_prompt_button = create_toprow(is_img2img=False) dummy_component = gr.Label(visible=False) txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False) @@ -716,7 +716,7 @@ def create_ui(wrap_gradio_gpu_call): connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) - trash_prompt_click(trash_prompt_button, txt2img_prompt, dummy_component, token_counter) + connect_clear_prompt(clear_prompt_button, txt2img_prompt, dummy_component, token_counter) txt2img_args = dict( fn=wrap_gradio_gpu_call(modules.txt2img.txt2img), @@ -853,7 +853,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Blocks(analytics_enabled=False) as img2img_interface: img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit,\ img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,\ - token_counter, token_button, trash_prompt_button = create_toprow(is_img2img=True) + token_counter, token_button, clear_prompt_button = create_toprow(is_img2img=True) with gr.Row(elem_id='img2img_progress_row'): @@ -954,7 +954,7 @@ def create_ui(wrap_gradio_gpu_call): connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) - trash_prompt_click(trash_prompt_button, img2img_prompt, dummy_component, token_counter) + connect_clear_prompt(clear_prompt_button, img2img_prompt, dummy_component, token_counter) img2img_prompt_img.change( fn=modules.images.image_data, -- cgit v1.2.3 From 0c7cf08b3d27a61bab4cd8b16f8be8ae74879423 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Fri, 21 Oct 2022 15:32:26 -0500 Subject: some doc and formatting --- modules/ui.py | 17 ++++++++++++----- 1 file changed, 12 insertions(+), 5 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 31150800..b26cf10a 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -88,7 +88,7 @@ folder_symbol = '\U0001f4c2' # 📂 refresh_symbol = '\U0001f504' # 🔄 save_style_symbol = '\U0001f4be' # 💾 apply_style_symbol = '\U0001f4cb' # 📋 -clear_prompt_symbol = '\U0001F5D1' # 🗑️ +clear_prompt_symbol = '\U0001F5D1' # 🗑️ def plaintext_to_html(text): @@ -429,12 +429,14 @@ def create_seed_inputs(): return seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox - def clear_prompt(_prompt, confirmed, _token_counter): - if(confirmed): - return ["", confirmed, update_token_counter("", 1)] + """Given confirmation from a user on the client-side, go ahead with clearing prompt""" + if confirmed: + return ["", confirmed, update_token_counter("", 1)] + def connect_clear_prompt(button, prompt, _dummy_confirmed, token_counter): + """Given clear button, prompt, and token_counter objects, setup clear prompt button click event""" button.click( _js="clear_prompt", fn=clear_prompt, @@ -518,7 +520,12 @@ def create_toprow(is_img2img): paste = gr.Button(value=paste_symbol, elem_id="paste") save_style = gr.Button(value=save_style_symbol, elem_id="style_create") prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply") - clear_prompt_button = gr.Button(value=clear_prompt_symbol, elem_id="clear_prompt", visible=opts.clear_prompt_visible) + + clear_prompt_button = gr.Button( + value=clear_prompt_symbol, + elem_id="clear_prompt", + visible=opts.clear_prompt_visible + ) token_counter = gr.HTML(value="", elem_id=f"{id_part}_token_counter") token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button") -- cgit v1.2.3 From 700340448baa7412c7cc5ff3d1349ac79ee8ed0c Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Fri, 21 Oct 2022 17:24:04 -0500 Subject: forgot to clear neg prompt after moving to back. Add tooltip to hints --- javascript/hints.js | 1 + javascript/ui.js | 4 ++-- modules/ui.py | 14 +++++++------- 3 files changed, 10 insertions(+), 9 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/hints.js b/javascript/hints.js index a1fcc93b..54c8c238 100644 --- a/javascript/hints.js +++ b/javascript/hints.js @@ -17,6 +17,7 @@ titles = { "\u2199\ufe0f": "Read generation parameters from prompt or last generation if prompt is empty into user interface.", "\u{1f4c2}": "Open images output directory", "\u{1f4be}": "Save style", + "\U0001F5D1": "Clear prompt" "\u{1f4cb}": "Apply selected styles to current prompt", "Inpaint a part of image": "Draw a mask over an image, and the script will regenerate the masked area with content according to prompt", diff --git a/javascript/ui.js b/javascript/ui.js index 45d93a5c..6c99824b 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -162,7 +162,7 @@ function selected_tab_id() { } -function clear_prompt(_, confirmed,_steps) { +function clear_prompt(_, _prompt_neg, confirmed,_steps) { if(confirm("Delete prompt?")) { confirmed = true @@ -176,7 +176,7 @@ return [_, confirmed] update_token_counter("txt2img_token_button") } - return [_, confirmed,_steps] + return [_, _prompt_neg, confirmed,_steps] } diff --git a/modules/ui.py b/modules/ui.py index b26cf10a..25aeba3b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -429,19 +429,19 @@ def create_seed_inputs(): return seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox -def clear_prompt(_prompt, confirmed, _token_counter): +def clear_prompt(_prompt, _prompt_neg, confirmed, _token_counter): """Given confirmation from a user on the client-side, go ahead with clearing prompt""" if confirmed: - return ["", confirmed, update_token_counter("", 1)] + return ["", "", confirmed, update_token_counter("", 1)] -def connect_clear_prompt(button, prompt, _dummy_confirmed, token_counter): +def connect_clear_prompt(button, prompt, prompt_neg, _dummy_confirmed, token_counter): """Given clear button, prompt, and token_counter objects, setup clear prompt button click event""" button.click( _js="clear_prompt", fn=clear_prompt, - inputs=[prompt, _dummy_confirmed, token_counter], - outputs=[prompt, _dummy_confirmed, token_counter], + inputs=[prompt, prompt_neg, _dummy_confirmed, token_counter], + outputs=[prompt, prompt_neg, _dummy_confirmed, token_counter], ) @@ -723,7 +723,7 @@ def create_ui(wrap_gradio_gpu_call): connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) - connect_clear_prompt(clear_prompt_button, txt2img_prompt, dummy_component, token_counter) + connect_clear_prompt(clear_prompt_button, txt2img_prompt, txt2img_negative_prompt, dummy_component, token_counter) txt2img_args = dict( fn=wrap_gradio_gpu_call(modules.txt2img.txt2img), @@ -961,7 +961,7 @@ def create_ui(wrap_gradio_gpu_call): connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) - connect_clear_prompt(clear_prompt_button, img2img_prompt, dummy_component, token_counter) + connect_clear_prompt(clear_prompt_button, img2img_prompt, img2img_negative_prompt, dummy_component, token_counter) img2img_prompt_img.change( fn=modules.images.image_data, -- cgit v1.2.3 From 2b91251637078e04472c91a06a8d9c4db9c1dcf0 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 22 Oct 2022 12:23:45 +0300 Subject: removed aesthetic gradients as built-in added support for extensions --- .gitignore | 2 +- extensions/put extension here.txt | 0 modules/aesthetic_clip.py | 241 -------------------------------------- modules/images_history.py | 2 +- modules/img2img.py | 5 +- modules/processing.py | 35 ++++-- modules/script_callbacks.py | 42 +++++++ modules/scripts.py | 210 ++++++++++++++++++++++++--------- modules/sd_hijack.py | 1 - modules/sd_models.py | 7 +- modules/shared.py | 19 --- modules/txt2img.py | 5 +- modules/ui.py | 83 ++----------- webui.py | 7 +- 14 files changed, 249 insertions(+), 410 deletions(-) create mode 100644 extensions/put extension here.txt delete mode 100644 modules/aesthetic_clip.py create mode 100644 modules/script_callbacks.py (limited to 'modules/ui.py') diff --git a/.gitignore b/.gitignore index f9c3357c..2f1e08ed 100644 --- a/.gitignore +++ b/.gitignore @@ -27,4 +27,4 @@ __pycache__ notification.mp3 /SwinIR /textual_inversion -.vscode \ No newline at end of file +.vscode diff --git a/extensions/put extension here.txt b/extensions/put extension here.txt new file mode 100644 index 00000000..e69de29b diff --git a/modules/aesthetic_clip.py b/modules/aesthetic_clip.py deleted file mode 100644 index 8c828541..00000000 --- a/modules/aesthetic_clip.py +++ /dev/null @@ -1,241 +0,0 @@ -import copy -import itertools -import os -from pathlib import Path -import html -import gc - -import gradio as gr -import torch -from PIL import Image -from torch import optim - -from modules import shared -from transformers import CLIPModel, CLIPProcessor, CLIPTokenizer -from tqdm.auto import tqdm, trange -from modules.shared import opts, device - - -def get_all_images_in_folder(folder): - return [os.path.join(folder, f) for f in os.listdir(folder) if - os.path.isfile(os.path.join(folder, f)) and check_is_valid_image_file(f)] - - -def check_is_valid_image_file(filename): - return filename.lower().endswith(('.png', '.jpg', '.jpeg', ".gif", ".tiff", ".webp")) - - -def batched(dataset, total, n=1): - for ndx in range(0, total, n): - yield [dataset.__getitem__(i) for i in range(ndx, min(ndx + n, total))] - - -def iter_to_batched(iterable, n=1): - it = iter(iterable) - while True: - chunk = tuple(itertools.islice(it, n)) - if not chunk: - return - yield chunk - - -def create_ui(): - import modules.ui - - with gr.Group(): - with gr.Accordion("Open for Clip Aesthetic!", open=False): - with gr.Row(): - aesthetic_weight = gr.Slider(minimum=0, maximum=1, step=0.01, label="Aesthetic weight", - value=0.9) - aesthetic_steps = gr.Slider(minimum=0, maximum=50, step=1, label="Aesthetic steps", value=5) - - with gr.Row(): - aesthetic_lr = gr.Textbox(label='Aesthetic learning rate', - placeholder="Aesthetic learning rate", value="0.0001") - aesthetic_slerp = gr.Checkbox(label="Slerp interpolation", value=False) - aesthetic_imgs = gr.Dropdown(sorted(shared.aesthetic_embeddings.keys()), - label="Aesthetic imgs embedding", - value="None") - - modules.ui.create_refresh_button(aesthetic_imgs, shared.update_aesthetic_embeddings, lambda: {"choices": sorted(shared.aesthetic_embeddings.keys())}, "refresh_aesthetic_embeddings") - - with gr.Row(): - aesthetic_imgs_text = gr.Textbox(label='Aesthetic text for imgs', - placeholder="This text is used to rotate the feature space of the imgs embs", - value="") - aesthetic_slerp_angle = gr.Slider(label='Slerp angle', minimum=0, maximum=1, step=0.01, - value=0.1) - aesthetic_text_negative = gr.Checkbox(label="Is negative text", value=False) - - return aesthetic_weight, aesthetic_steps, aesthetic_lr, aesthetic_slerp, aesthetic_imgs, aesthetic_imgs_text, aesthetic_slerp_angle, aesthetic_text_negative - - -aesthetic_clip_model = None - - -def aesthetic_clip(): - global aesthetic_clip_model - - if aesthetic_clip_model is None or aesthetic_clip_model.name_or_path != shared.sd_model.cond_stage_model.wrapped.transformer.name_or_path: - aesthetic_clip_model = CLIPModel.from_pretrained(shared.sd_model.cond_stage_model.wrapped.transformer.name_or_path) - aesthetic_clip_model.cpu() - - return aesthetic_clip_model - - -def generate_imgs_embd(name, folder, batch_size): - model = aesthetic_clip().to(device) - processor = CLIPProcessor.from_pretrained(model.name_or_path) - - with torch.no_grad(): - embs = [] - for paths in tqdm(iter_to_batched(get_all_images_in_folder(folder), batch_size), - desc=f"Generating embeddings for {name}"): - if shared.state.interrupted: - break - inputs = processor(images=[Image.open(path) for path in paths], return_tensors="pt").to(device) - outputs = model.get_image_features(**inputs).cpu() - embs.append(torch.clone(outputs)) - inputs.to("cpu") - del inputs, outputs - - embs = torch.cat(embs, dim=0).mean(dim=0, keepdim=True) - - # The generated embedding will be located here - path = str(Path(shared.cmd_opts.aesthetic_embeddings_dir) / f"{name}.pt") - torch.save(embs, path) - - model.cpu() - del processor - del embs - gc.collect() - torch.cuda.empty_cache() - res = f""" - Done generating embedding for {name}! - Aesthetic embedding saved to {html.escape(path)} - """ - shared.update_aesthetic_embeddings() - return gr.Dropdown.update(choices=sorted(shared.aesthetic_embeddings.keys()), label="Imgs embedding", - value="None"), \ - gr.Dropdown.update(choices=sorted(shared.aesthetic_embeddings.keys()), - label="Imgs embedding", - value="None"), res, "" - - -def slerp(low, high, val): - low_norm = low / torch.norm(low, dim=1, keepdim=True) - high_norm = high / torch.norm(high, dim=1, keepdim=True) - omega = torch.acos((low_norm * high_norm).sum(1)) - so = torch.sin(omega) - res = (torch.sin((1.0 - val) * omega) / so).unsqueeze(1) * low + (torch.sin(val * omega) / so).unsqueeze(1) * high - return res - - -class AestheticCLIP: - def __init__(self): - self.skip = False - self.aesthetic_steps = 0 - self.aesthetic_weight = 0 - self.aesthetic_lr = 0 - self.slerp = False - self.aesthetic_text_negative = "" - self.aesthetic_slerp_angle = 0 - self.aesthetic_imgs_text = "" - - self.image_embs_name = None - self.image_embs = None - self.load_image_embs(None) - - def set_aesthetic_params(self, p, aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, image_embs_name=None, - aesthetic_slerp=True, aesthetic_imgs_text="", - aesthetic_slerp_angle=0.15, - aesthetic_text_negative=False): - self.aesthetic_imgs_text = aesthetic_imgs_text - self.aesthetic_slerp_angle = aesthetic_slerp_angle - self.aesthetic_text_negative = aesthetic_text_negative - self.slerp = aesthetic_slerp - self.aesthetic_lr = aesthetic_lr - self.aesthetic_weight = aesthetic_weight - self.aesthetic_steps = aesthetic_steps - self.load_image_embs(image_embs_name) - - if self.image_embs_name is not None: - p.extra_generation_params.update({ - "Aesthetic LR": aesthetic_lr, - "Aesthetic weight": aesthetic_weight, - "Aesthetic steps": aesthetic_steps, - "Aesthetic embedding": self.image_embs_name, - "Aesthetic slerp": aesthetic_slerp, - "Aesthetic text": aesthetic_imgs_text, - "Aesthetic text negative": aesthetic_text_negative, - "Aesthetic slerp angle": aesthetic_slerp_angle, - }) - - def set_skip(self, skip): - self.skip = skip - - def load_image_embs(self, image_embs_name): - if image_embs_name is None or len(image_embs_name) == 0 or image_embs_name == "None": - image_embs_name = None - self.image_embs_name = None - if image_embs_name is not None and self.image_embs_name != image_embs_name: - self.image_embs_name = image_embs_name - self.image_embs = torch.load(shared.aesthetic_embeddings[self.image_embs_name], map_location=device) - self.image_embs /= self.image_embs.norm(dim=-1, keepdim=True) - self.image_embs.requires_grad_(False) - - def __call__(self, z, remade_batch_tokens): - if not self.skip and self.aesthetic_steps != 0 and self.aesthetic_lr != 0 and self.aesthetic_weight != 0 and self.image_embs_name is not None: - tokenizer = shared.sd_model.cond_stage_model.tokenizer - if not opts.use_old_emphasis_implementation: - remade_batch_tokens = [ - [tokenizer.bos_token_id] + x[:75] + [tokenizer.eos_token_id] for x in - remade_batch_tokens] - - tokens = torch.asarray(remade_batch_tokens).to(device) - - model = copy.deepcopy(aesthetic_clip()).to(device) - model.requires_grad_(True) - if self.aesthetic_imgs_text is not None and len(self.aesthetic_imgs_text) > 0: - text_embs_2 = model.get_text_features( - **tokenizer([self.aesthetic_imgs_text], padding=True, return_tensors="pt").to(device)) - if self.aesthetic_text_negative: - text_embs_2 = self.image_embs - text_embs_2 - text_embs_2 /= text_embs_2.norm(dim=-1, keepdim=True) - img_embs = slerp(self.image_embs, text_embs_2, self.aesthetic_slerp_angle) - else: - img_embs = self.image_embs - - with torch.enable_grad(): - - # We optimize the model to maximize the similarity - optimizer = optim.Adam( - model.text_model.parameters(), lr=self.aesthetic_lr - ) - - for _ in trange(self.aesthetic_steps, desc="Aesthetic optimization"): - text_embs = model.get_text_features(input_ids=tokens) - text_embs = text_embs / text_embs.norm(dim=-1, keepdim=True) - sim = text_embs @ img_embs.T - loss = -sim - optimizer.zero_grad() - loss.mean().backward() - optimizer.step() - - zn = model.text_model(input_ids=tokens, output_hidden_states=-opts.CLIP_stop_at_last_layers) - if opts.CLIP_stop_at_last_layers > 1: - zn = zn.hidden_states[-opts.CLIP_stop_at_last_layers] - zn = model.text_model.final_layer_norm(zn) - else: - zn = zn.last_hidden_state - model.cpu() - del model - gc.collect() - torch.cuda.empty_cache() - zn = torch.concat([zn[77 * i:77 * (i + 1)] for i in range(max(z.shape[1] // 77, 1))], 1) - if self.slerp: - z = slerp(z, zn, self.aesthetic_weight) - else: - z = z * (1 - self.aesthetic_weight) + zn * self.aesthetic_weight - - return z diff --git a/modules/images_history.py b/modules/images_history.py index 78fd0543..bc5cf11f 100644 --- a/modules/images_history.py +++ b/modules/images_history.py @@ -310,7 +310,7 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): forward = gr.Button('Prev batch') backward = gr.Button('Next batch') with gr.Column(scale=3): - load_info = gr.HTML(visible=not custom_dir) + load_info = gr.HTML(visible=not custom_dir) with gr.Row(visible=False) as warning: warning_box = gr.Textbox("Message", interactive=False) diff --git a/modules/img2img.py b/modules/img2img.py index eea5199b..8d9f7cf9 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -56,7 +56,7 @@ def process_batch(p, input_dir, output_dir, args): processed_image.save(os.path.join(output_dir, filename)) -def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, init_img_with_mask, init_img_inpaint, init_mask_inpaint, mask_mode, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, aesthetic_imgs=None, aesthetic_slerp=False, aesthetic_imgs_text="", aesthetic_slerp_angle=0.15, aesthetic_text_negative=False, *args): +def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, init_img_with_mask, init_img_inpaint, init_mask_inpaint, mask_mode, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args): is_inpaint = mode == 1 is_batch = mode == 2 @@ -109,7 +109,8 @@ def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, pro inpainting_mask_invert=inpainting_mask_invert, ) - shared.aesthetic_clip.set_aesthetic_params(p, float(aesthetic_lr), float(aesthetic_weight), int(aesthetic_steps), aesthetic_imgs, aesthetic_slerp, aesthetic_imgs_text, aesthetic_slerp_angle, aesthetic_text_negative) + p.scripts = modules.scripts.scripts_txt2img + p.script_args = args if shared.cmd_opts.enable_console_prompts: print(f"\nimg2img: {prompt}", file=shared.progress_print_out) diff --git a/modules/processing.py b/modules/processing.py index ff1ec4c9..372489f7 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -104,6 +104,12 @@ class StableDiffusionProcessing(): self.seed_resize_from_h = 0 self.seed_resize_from_w = 0 + self.scripts = None + self.script_args = None + self.all_prompts = None + self.all_seeds = None + self.all_subseeds = None + def init(self, all_prompts, all_seeds, all_subseeds): pass @@ -350,32 +356,35 @@ def process_images(p: StableDiffusionProcessing) -> Processed: shared.prompt_styles.apply_styles(p) if type(p.prompt) == list: - all_prompts = p.prompt + p.all_prompts = p.prompt else: - all_prompts = p.batch_size * p.n_iter * [p.prompt] + p.all_prompts = p.batch_size * p.n_iter * [p.prompt] if type(seed) == list: - all_seeds = seed + p.all_seeds = seed else: - all_seeds = [int(seed) + (x if p.subseed_strength == 0 else 0) for x in range(len(all_prompts))] + p.all_seeds = [int(seed) + (x if p.subseed_strength == 0 else 0) for x in range(len(p.all_prompts))] if type(subseed) == list: - all_subseeds = subseed + p.all_subseeds = subseed else: - all_subseeds = [int(subseed) + x for x in range(len(all_prompts))] + p.all_subseeds = [int(subseed) + x for x in range(len(p.all_prompts))] def infotext(iteration=0, position_in_batch=0): - return create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration, position_in_batch) + return create_infotext(p, p.all_prompts, p.all_seeds, p.all_subseeds, comments, iteration, position_in_batch) if os.path.exists(cmd_opts.embeddings_dir) and not p.do_not_reload_embeddings: model_hijack.embedding_db.load_textual_inversion_embeddings() + if p.scripts is not None: + p.scripts.run_alwayson_scripts(p) + infotexts = [] output_images = [] with torch.no_grad(), p.sd_model.ema_scope(): with devices.autocast(): - p.init(all_prompts, all_seeds, all_subseeds) + p.init(p.all_prompts, p.all_seeds, p.all_subseeds) if state.job_count == -1: state.job_count = p.n_iter @@ -387,9 +396,9 @@ def process_images(p: StableDiffusionProcessing) -> Processed: if state.interrupted: break - prompts = all_prompts[n * p.batch_size:(n + 1) * p.batch_size] - seeds = all_seeds[n * p.batch_size:(n + 1) * p.batch_size] - subseeds = all_subseeds[n * p.batch_size:(n + 1) * p.batch_size] + prompts = p.all_prompts[n * p.batch_size:(n + 1) * p.batch_size] + seeds = p.all_seeds[n * p.batch_size:(n + 1) * p.batch_size] + subseeds = p.all_subseeds[n * p.batch_size:(n + 1) * p.batch_size] if (len(prompts) == 0): break @@ -490,10 +499,10 @@ def process_images(p: StableDiffusionProcessing) -> Processed: index_of_first_image = 1 if opts.grid_save: - images.save_image(grid, p.outpath_grids, "grid", all_seeds[0], all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True) + images.save_image(grid, p.outpath_grids, "grid", p.all_seeds[0], p.all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True) devices.torch_gc() - return Processed(p, output_images, all_seeds[0], infotext() + "".join(["\n\n" + x for x in comments]), subseed=all_subseeds[0], all_prompts=all_prompts, all_seeds=all_seeds, all_subseeds=all_subseeds, index_of_first_image=index_of_first_image, infotexts=infotexts) + return Processed(p, output_images, p.all_seeds[0], infotext() + "".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], all_prompts=p.all_prompts, all_seeds=p.all_seeds, all_subseeds=p.all_subseeds, index_of_first_image=index_of_first_image, infotexts=infotexts) class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py new file mode 100644 index 00000000..866b7acd --- /dev/null +++ b/modules/script_callbacks.py @@ -0,0 +1,42 @@ + +callbacks_model_loaded = [] +callbacks_ui_tabs = [] + + +def clear_callbacks(): + callbacks_model_loaded.clear() + callbacks_ui_tabs.clear() + + +def model_loaded_callback(sd_model): + for callback in callbacks_model_loaded: + callback(sd_model) + + +def ui_tabs_callback(): + res = [] + + for callback in callbacks_ui_tabs: + res += callback() or [] + + return res + + +def on_model_loaded(callback): + """register a function to be called when the stable diffusion model is created; the model is + passed as an argument""" + callbacks_model_loaded.append(callback) + + +def on_ui_tabs(callback): + """register a function to be called when the UI is creating new tabs. + The function must either return a None, which means no new tabs to be added, or a list, where + each element is a tuple: + (gradio_component, title, elem_id) + + gradio_component is a gradio component to be used for contents of the tab (usually gr.Blocks) + title is tab text displayed to user in the UI + elem_id is HTML id for the tab + """ + callbacks_ui_tabs.append(callback) + diff --git a/modules/scripts.py b/modules/scripts.py index 1039fa9c..65f25f49 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -1,86 +1,153 @@ import os import sys import traceback +from collections import namedtuple import modules.ui as ui import gradio as gr from modules.processing import StableDiffusionProcessing -from modules import shared +from modules import shared, paths, script_callbacks + +AlwaysVisible = object() + class Script: filename = None args_from = None args_to = None + alwayson = False + + infotext_fields = None + """if set in ui(), this is a list of pairs of gradio component + text; the text will be used when + parsing infotext to set the value for the component; see ui.py's txt2img_paste_fields for an example + """ - # The title of the script. This is what will be displayed in the dropdown menu. def title(self): + """this function should return the title of the script. This is what will be displayed in the dropdown menu.""" + raise NotImplementedError() - # How the script is displayed in the UI. See https://gradio.app/docs/#components - # for the different UI components you can use and how to create them. - # Most UI components can return a value, such as a boolean for a checkbox. - # The returned values are passed to the run method as parameters. def ui(self, is_img2img): + """this function should create gradio UI elements. See https://gradio.app/docs/#components + The return value should be an array of all components that are used in processing. + Values of those returned componenbts will be passed to run() and process() functions. + """ + pass - # Determines when the script should be shown in the dropdown menu via the - # returned value. As an example: - # is_img2img is True if the current tab is img2img, and False if it is txt2img. - # Thus, return is_img2img to only show the script on the img2img tab. def show(self, is_img2img): + """ + is_img2img is True if this function is called for the img2img interface, and Fasle otherwise + + This function should return: + - False if the script should not be shown in UI at all + - True if the script should be shown in UI if it's scelected in the scripts drowpdown + - script.AlwaysVisible if the script should be shown in UI at all times + """ + return True - # This is where the additional processing is implemented. The parameters include - # self, the model object "p" (a StableDiffusionProcessing class, see - # processing.py), and the parameters returned by the ui method. - # Custom functions can be defined here, and additional libraries can be imported - # to be used in processing. The return value should be a Processed object, which is - # what is returned by the process_images method. - def run(self, *args): + def run(self, p, *args): + """ + This function is called if the script has been selected in the script dropdown. + It must do all processing and return the Processed object with results, same as + one returned by processing.process_images. + + Usually the processing is done by calling the processing.process_images function. + + args contains all values returned by components from ui() + """ + raise NotImplementedError() - # The description method is currently unused. - # To add a description that appears when hovering over the title, amend the "titles" - # dict in script.js to include the script title (returned by title) as a key, and - # your description as the value. + def process(self, p, *args): + """ + This function is called before processing begins for AlwaysVisible scripts. + scripts. You can modify the processing object (p) here, inject hooks, etc. + """ + + pass + def describe(self): + """unused""" return "" +current_basedir = paths.script_path + + +def basedir(): + """returns the base directory for the current script. For scripts in the main scripts directory, + this is the main directory (where webui.py resides), and for scripts in extensions directory + (ie extensions/aesthetic/script/aesthetic.py), this is extension's directory (extensions/aesthetic) + """ + return current_basedir + + scripts_data = [] +ScriptFile = namedtuple("ScriptFile", ["basedir", "filename", "path"]) +ScriptClassData = namedtuple("ScriptClassData", ["script_class", "path", "basedir"]) + + +def list_scripts(scriptdirname, extension): + scripts_list = [] + + basedir = os.path.join(paths.script_path, scriptdirname) + if os.path.exists(basedir): + for filename in sorted(os.listdir(basedir)): + scripts_list.append(ScriptFile(paths.script_path, filename, os.path.join(basedir, filename))) + + extdir = os.path.join(paths.script_path, "extensions") + if os.path.exists(extdir): + for dirname in sorted(os.listdir(extdir)): + dirpath = os.path.join(extdir, dirname) + if not os.path.isdir(dirpath): + continue + for filename in sorted(os.listdir(os.path.join(dirpath, scriptdirname))): + scripts_list.append(ScriptFile(dirpath, filename, os.path.join(dirpath, scriptdirname, filename))) -def load_scripts(basedir): - if not os.path.exists(basedir): - return + scripts_list = [x for x in scripts_list if os.path.splitext(x.path)[1].lower() == extension and os.path.isfile(x.path)] - for filename in sorted(os.listdir(basedir)): - path = os.path.join(basedir, filename) + return scripts_list - if os.path.splitext(path)[1].lower() != '.py': - continue - if not os.path.isfile(path): - continue +def load_scripts(): + global current_basedir + scripts_data.clear() + script_callbacks.clear_callbacks() + + scripts_list = list_scripts("scripts", ".py") + + syspath = sys.path + for scriptfile in sorted(scripts_list): try: - with open(path, "r", encoding="utf8") as file: + if scriptfile.basedir != paths.script_path: + sys.path = [scriptfile.basedir] + sys.path + current_basedir = scriptfile.basedir + + with open(scriptfile.path, "r", encoding="utf8") as file: text = file.read() from types import ModuleType - compiled = compile(text, path, 'exec') - module = ModuleType(filename) + compiled = compile(text, scriptfile.path, 'exec') + module = ModuleType(scriptfile.filename) exec(compiled, module.__dict__) for key, script_class in module.__dict__.items(): if type(script_class) == type and issubclass(script_class, Script): - scripts_data.append((script_class, path)) + scripts_data.append(ScriptClassData(script_class, scriptfile.path, scriptfile.basedir)) except Exception: - print(f"Error loading script: {filename}", file=sys.stderr) + print(f"Error loading script: {scriptfile.filename}", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) + finally: + sys.path = syspath + current_basedir = paths.script_path + def wrap_call(func, filename, funcname, *args, default=None, **kwargs): try: @@ -96,56 +163,80 @@ def wrap_call(func, filename, funcname, *args, default=None, **kwargs): class ScriptRunner: def __init__(self): self.scripts = [] + self.selectable_scripts = [] + self.alwayson_scripts = [] self.titles = [] + self.infotext_fields = [] def setup_ui(self, is_img2img): - for script_class, path in scripts_data: + for script_class, path, basedir in scripts_data: script = script_class() script.filename = path - if not script.show(is_img2img): - continue + visibility = script.show(is_img2img) - self.scripts.append(script) + if visibility == AlwaysVisible: + self.scripts.append(script) + self.alwayson_scripts.append(script) + script.alwayson = True - self.titles = [wrap_call(script.title, script.filename, "title") or f"{script.filename} [error]" for script in self.scripts] + elif visibility: + self.scripts.append(script) + self.selectable_scripts.append(script) - dropdown = gr.Dropdown(label="Script", choices=["None"] + self.titles, value="None", type="index") - dropdown.save_to_config = True - inputs = [dropdown] + self.titles = [wrap_call(script.title, script.filename, "title") or f"{script.filename} [error]" for script in self.selectable_scripts] + + inputs = [None] + inputs_alwayson = [True] - for script in self.scripts: + def create_script_ui(script, inputs, inputs_alwayson): script.args_from = len(inputs) script.args_to = len(inputs) controls = wrap_call(script.ui, script.filename, "ui", is_img2img) if controls is None: - continue + return for control in controls: control.custom_script_source = os.path.basename(script.filename) - control.visible = False + if not script.alwayson: + control.visible = False + + if script.infotext_fields is not None: + self.infotext_fields += script.infotext_fields inputs += controls + inputs_alwayson += [script.alwayson for _ in controls] script.args_to = len(inputs) + for script in self.alwayson_scripts: + with gr.Group(): + create_script_ui(script, inputs, inputs_alwayson) + + dropdown = gr.Dropdown(label="Script", choices=["None"] + self.titles, value="None", type="index") + dropdown.save_to_config = True + inputs[0] = dropdown + + for script in self.selectable_scripts: + create_script_ui(script, inputs, inputs_alwayson) + def select_script(script_index): - if 0 < script_index <= len(self.scripts): - script = self.scripts[script_index-1] + if 0 < script_index <= len(self.selectable_scripts): + script = self.selectable_scripts[script_index-1] args_from = script.args_from args_to = script.args_to else: args_from = 0 args_to = 0 - return [ui.gr_show(True if i == 0 else args_from <= i < args_to) for i in range(len(inputs))] + return [ui.gr_show(True if i == 0 else args_from <= i < args_to or is_alwayson) for i, is_alwayson in enumerate(inputs_alwayson)] def init_field(title): if title == 'None': return script_index = self.titles.index(title) - script = self.scripts[script_index] + script = self.selectable_scripts[script_index] for i in range(script.args_from, script.args_to): inputs[i].visible = True @@ -164,7 +255,7 @@ class ScriptRunner: if script_index == 0: return None - script = self.scripts[script_index-1] + script = self.selectable_scripts[script_index-1] if script is None: return None @@ -176,6 +267,15 @@ class ScriptRunner: return processed + def run_alwayson_scripts(self, p): + for script in self.alwayson_scripts: + try: + script_args = p.script_args[script.args_from:script.args_to] + script.process(p, *script_args) + except Exception: + print(f"Error running alwayson script: {script.filename}", file=sys.stderr) + print(traceback.format_exc(), file=sys.stderr) + def reload_sources(self): for si, script in list(enumerate(self.scripts)): with open(script.filename, "r", encoding="utf8") as file: @@ -197,19 +297,21 @@ class ScriptRunner: self.scripts[si].args_from = args_from self.scripts[si].args_to = args_to + scripts_txt2img = ScriptRunner() scripts_img2img = ScriptRunner() + def reload_script_body_only(): scripts_txt2img.reload_sources() scripts_img2img.reload_sources() -def reload_scripts(basedir): +def reload_scripts(): global scripts_txt2img, scripts_img2img - scripts_data.clear() - load_scripts(basedir) + load_scripts() scripts_txt2img = ScriptRunner() scripts_img2img = ScriptRunner() + diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index 1f8587d1..0f10828e 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -332,7 +332,6 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): multipliers.append([1.0] * 75) z1 = self.process_tokens(tokens, multipliers) - z1 = shared.aesthetic_clip(z1, remade_batch_tokens) z = z1 if z is None else torch.cat((z, z1), axis=-2) remade_batch_tokens = rem_tokens diff --git a/modules/sd_models.py b/modules/sd_models.py index d99dbce8..f9b3063d 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -7,7 +7,7 @@ from omegaconf import OmegaConf from ldm.util import instantiate_from_config -from modules import shared, modelloader, devices +from modules import shared, modelloader, devices, script_callbacks from modules.paths import models_path from modules.sd_hijack_inpainting import do_inpainting_hijack, should_hijack_inpainting @@ -238,6 +238,9 @@ def load_model(checkpoint_info=None): sd_hijack.model_hijack.hijack(sd_model) sd_model.eval() + shared.sd_model = sd_model + + script_callbacks.model_loaded_callback(sd_model) print(f"Model loaded.") return sd_model @@ -252,7 +255,7 @@ def reload_model_weights(sd_model, info=None): if sd_model.sd_checkpoint_info.config != checkpoint_info.config or should_hijack_inpainting(checkpoint_info) != should_hijack_inpainting(sd_model.sd_checkpoint_info): checkpoints_loaded.clear() - shared.sd_model = load_model(checkpoint_info) + load_model(checkpoint_info) return shared.sd_model if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: diff --git a/modules/shared.py b/modules/shared.py index 0dbe360d..7d786f07 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -31,7 +31,6 @@ parser.add_argument("--no-half-vae", action='store_true', help="do not switch th parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)") parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI") parser.add_argument("--embeddings-dir", type=str, default=os.path.join(script_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)") -parser.add_argument("--aesthetic_embeddings-dir", type=str, default=os.path.join(models_path, 'aesthetic_embeddings'), help="aesthetic_embeddings directory(default: aesthetic_embeddings)") parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory") parser.add_argument("--localizations-dir", type=str, default=os.path.join(script_path, 'localizations'), help="localizations directory") parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui") @@ -109,21 +108,6 @@ os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True) hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) loaded_hypernetwork = None - -os.makedirs(cmd_opts.aesthetic_embeddings_dir, exist_ok=True) -aesthetic_embeddings = {} - - -def update_aesthetic_embeddings(): - global aesthetic_embeddings - aesthetic_embeddings = {f.replace(".pt", ""): os.path.join(cmd_opts.aesthetic_embeddings_dir, f) for f in - os.listdir(cmd_opts.aesthetic_embeddings_dir) if f.endswith(".pt")} - aesthetic_embeddings = OrderedDict(**{"None": None}, **aesthetic_embeddings) - - -update_aesthetic_embeddings() - - def reload_hypernetworks(): global hypernetworks @@ -415,9 +399,6 @@ sd_model = None clip_model = None -from modules.aesthetic_clip import AestheticCLIP -aesthetic_clip = AestheticCLIP() - progress_print_out = sys.stdout diff --git a/modules/txt2img.py b/modules/txt2img.py index 1761cfa2..c9d5a090 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -7,7 +7,7 @@ import modules.processing as processing from modules.ui import plaintext_to_html -def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, firstphase_width: int, firstphase_height: int, aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, aesthetic_imgs=None, aesthetic_slerp=False, aesthetic_imgs_text="", aesthetic_slerp_angle=0.15, aesthetic_text_negative=False, *args): +def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, firstphase_width: int, firstphase_height: int, *args): p = StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples, @@ -36,7 +36,8 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: firstphase_height=firstphase_height if enable_hr else None, ) - shared.aesthetic_clip.set_aesthetic_params(p, float(aesthetic_lr), float(aesthetic_weight), int(aesthetic_steps), aesthetic_imgs, aesthetic_slerp, aesthetic_imgs_text, aesthetic_slerp_angle, aesthetic_text_negative) + p.scripts = modules.scripts.scripts_txt2img + p.script_args = args if cmd_opts.enable_console_prompts: print(f"\ntxt2img: {prompt}", file=shared.progress_print_out) diff --git a/modules/ui.py b/modules/ui.py index 70a9cf10..c977482c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -23,10 +23,10 @@ import gradio as gr import gradio.utils import gradio.routes -from modules import sd_hijack, sd_models, localization +from modules import sd_hijack, sd_models, localization, script_callbacks from modules.paths import script_path -from modules.shared import opts, cmd_opts, restricted_opts, aesthetic_embeddings +from modules.shared import opts, cmd_opts, restricted_opts if cmd_opts.deepdanbooru: from modules.deepbooru import get_deepbooru_tags @@ -44,7 +44,6 @@ from modules.images import save_image import modules.textual_inversion.ui import modules.hypernetworks.ui -import modules.aesthetic_clip as aesthetic_clip import modules.images_history as img_his @@ -662,8 +661,6 @@ def create_ui(wrap_gradio_gpu_call): seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs() - aesthetic_weight, aesthetic_steps, aesthetic_lr, aesthetic_slerp, aesthetic_imgs, aesthetic_imgs_text, aesthetic_slerp_angle, aesthetic_text_negative = aesthetic_clip.create_ui() - with gr.Group(): custom_inputs = modules.scripts.scripts_txt2img.setup_ui(is_img2img=False) @@ -718,14 +715,6 @@ def create_ui(wrap_gradio_gpu_call): denoising_strength, firstphase_width, firstphase_height, - aesthetic_lr, - aesthetic_weight, - aesthetic_steps, - aesthetic_imgs, - aesthetic_slerp, - aesthetic_imgs_text, - aesthetic_slerp_angle, - aesthetic_text_negative ] + custom_inputs, outputs=[ @@ -804,14 +793,7 @@ def create_ui(wrap_gradio_gpu_call): (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)), (firstphase_width, "First pass size-1"), (firstphase_height, "First pass size-2"), - (aesthetic_lr, "Aesthetic LR"), - (aesthetic_weight, "Aesthetic weight"), - (aesthetic_steps, "Aesthetic steps"), - (aesthetic_imgs, "Aesthetic embedding"), - (aesthetic_slerp, "Aesthetic slerp"), - (aesthetic_imgs_text, "Aesthetic text"), - (aesthetic_text_negative, "Aesthetic text negative"), - (aesthetic_slerp_angle, "Aesthetic slerp angle"), + *modules.scripts.scripts_txt2img.infotext_fields ] txt2img_preview_params = [ @@ -896,8 +878,6 @@ def create_ui(wrap_gradio_gpu_call): seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs() - aesthetic_weight_im, aesthetic_steps_im, aesthetic_lr_im, aesthetic_slerp_im, aesthetic_imgs_im, aesthetic_imgs_text_im, aesthetic_slerp_angle_im, aesthetic_text_negative_im = aesthetic_clip.create_ui() - with gr.Group(): custom_inputs = modules.scripts.scripts_img2img.setup_ui(is_img2img=True) @@ -988,14 +968,6 @@ def create_ui(wrap_gradio_gpu_call): inpainting_mask_invert, img2img_batch_input_dir, img2img_batch_output_dir, - aesthetic_lr_im, - aesthetic_weight_im, - aesthetic_steps_im, - aesthetic_imgs_im, - aesthetic_slerp_im, - aesthetic_imgs_text_im, - aesthetic_slerp_angle_im, - aesthetic_text_negative_im, ] + custom_inputs, outputs=[ img2img_gallery, @@ -1087,14 +1059,7 @@ def create_ui(wrap_gradio_gpu_call): (seed_resize_from_w, "Seed resize from-1"), (seed_resize_from_h, "Seed resize from-2"), (denoising_strength, "Denoising strength"), - (aesthetic_lr_im, "Aesthetic LR"), - (aesthetic_weight_im, "Aesthetic weight"), - (aesthetic_steps_im, "Aesthetic steps"), - (aesthetic_imgs_im, "Aesthetic embedding"), - (aesthetic_slerp_im, "Aesthetic slerp"), - (aesthetic_imgs_text_im, "Aesthetic text"), - (aesthetic_text_negative_im, "Aesthetic text negative"), - (aesthetic_slerp_angle_im, "Aesthetic slerp angle"), + *modules.scripts.scripts_img2img.infotext_fields ] token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter]) @@ -1217,9 +1182,9 @@ def create_ui(wrap_gradio_gpu_call): ) #images history images_history_switch_dict = { - "fn":modules.generation_parameters_copypaste.connect_paste, - "t2i":txt2img_paste_fields, - "i2i":img2img_paste_fields + "fn": modules.generation_parameters_copypaste.connect_paste, + "t2i": txt2img_paste_fields, + "i2i": img2img_paste_fields } images_history = img_his.create_history_tabs(gr, opts, cmd_opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) @@ -1264,18 +1229,6 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column(): create_embedding = gr.Button(value="Create embedding", variant='primary') - with gr.Tab(label="Create aesthetic images embedding"): - - new_embedding_name_ae = gr.Textbox(label="Name") - process_src_ae = gr.Textbox(label='Source directory') - batch_ae = gr.Slider(minimum=1, maximum=1024, step=1, label="Batch size", value=256) - with gr.Row(): - with gr.Column(scale=3): - gr.HTML(value="") - - with gr.Column(): - create_embedding_ae = gr.Button(value="Create images embedding", variant='primary') - with gr.Tab(label="Create hypernetwork"): new_hypernetwork_name = gr.Textbox(label="Name") new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) @@ -1375,21 +1328,6 @@ def create_ui(wrap_gradio_gpu_call): ] ) - create_embedding_ae.click( - fn=aesthetic_clip.generate_imgs_embd, - inputs=[ - new_embedding_name_ae, - process_src_ae, - batch_ae - ], - outputs=[ - aesthetic_imgs, - aesthetic_imgs_im, - ti_output, - ti_outcome, - ] - ) - create_hypernetwork.click( fn=modules.hypernetworks.ui.create_hypernetwork, inputs=[ @@ -1580,10 +1518,10 @@ Requested path was: {f} if not opts.same_type(value, opts.data_labels[key].default): return gr.update(visible=True), opts.dumpjson() + oldval = opts.data.get(key, None) if cmd_opts.hide_ui_dir_config and key in restricted_opts: return gr.update(value=oldval), opts.dumpjson() - oldval = opts.data.get(key, None) opts.data[key] = value if oldval != value: @@ -1692,9 +1630,12 @@ Requested path was: {f} (images_history, "Image Browser", "images_history"), (modelmerger_interface, "Checkpoint Merger", "modelmerger"), (train_interface, "Train", "ti"), - (settings_interface, "Settings", "settings"), ] + interfaces += script_callbacks.ui_tabs_callback() + + interfaces += [(settings_interface, "Settings", "settings")] + with open(os.path.join(script_path, "style.css"), "r", encoding="utf8") as file: css = file.read() diff --git a/webui.py b/webui.py index 87589064..b1deca1b 100644 --- a/webui.py +++ b/webui.py @@ -71,6 +71,7 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs) + def initialize(): modelloader.cleanup_models() modules.sd_models.setup_model() @@ -79,9 +80,9 @@ def initialize(): shared.face_restorers.append(modules.face_restoration.FaceRestoration()) modelloader.load_upscalers() - modules.scripts.load_scripts(os.path.join(script_path, "scripts")) + modules.scripts.load_scripts() - shared.sd_model = modules.sd_models.load_model() + modules.sd_models.load_model() shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model))) shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork))) shared.opts.onchange("sd_hypernetwork_strength", modules.hypernetworks.hypernetwork.apply_strength) @@ -145,7 +146,7 @@ def webui(): sd_samplers.set_samplers() print('Reloading Custom Scripts') - modules.scripts.reload_scripts(os.path.join(script_path, "scripts")) + modules.scripts.reload_scripts() print('Reloading modules: modules.ui') importlib.reload(modules.ui) print('Refreshing Model List') -- cgit v1.2.3 From 6398dc9b1049f242576ca309f95a3fb1e654951c Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 22 Oct 2022 13:34:49 +0300 Subject: further support for extensions --- .gitignore | 1 + README.md | 3 +-- modules/scripts.py | 44 +++++++++++++++++++++++++++++++++++--------- modules/ui.py | 19 ++++++++++--------- style.css | 2 +- 5 files changed, 48 insertions(+), 21 deletions(-) (limited to 'modules/ui.py') diff --git a/.gitignore b/.gitignore index 2f1e08ed..8fa05852 100644 --- a/.gitignore +++ b/.gitignore @@ -28,3 +28,4 @@ notification.mp3 /SwinIR /textual_inversion .vscode +/extensions diff --git a/README.md b/README.md index 5b5dc8ba..6853aea0 100644 --- a/README.md +++ b/README.md @@ -83,8 +83,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web - Estimated completion time in progress bar - API - Support for dedicated [inpainting model](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion) by RunwayML. -- Aesthetic Gradients, a way to generate images with a specific aesthetic by using clip images embds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients)) - +- via extension: [Aesthetic Gradients](https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients), a way to generate images with a specific aesthetic by using clip images embds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients)) ## Installation and Running Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs. diff --git a/modules/scripts.py b/modules/scripts.py index 65f25f49..9323af3e 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -102,17 +102,39 @@ def list_scripts(scriptdirname, extension): if os.path.exists(extdir): for dirname in sorted(os.listdir(extdir)): dirpath = os.path.join(extdir, dirname) - if not os.path.isdir(dirpath): + scriptdirpath = os.path.join(dirpath, scriptdirname) + + if not os.path.isdir(scriptdirpath): continue - for filename in sorted(os.listdir(os.path.join(dirpath, scriptdirname))): - scripts_list.append(ScriptFile(dirpath, filename, os.path.join(dirpath, scriptdirname, filename))) + for filename in sorted(os.listdir(scriptdirpath)): + scripts_list.append(ScriptFile(dirpath, filename, os.path.join(scriptdirpath, filename))) scripts_list = [x for x in scripts_list if os.path.splitext(x.path)[1].lower() == extension and os.path.isfile(x.path)] return scripts_list +def list_files_with_name(filename): + res = [] + + dirs = [paths.script_path] + + extdir = os.path.join(paths.script_path, "extensions") + if os.path.exists(extdir): + dirs += [os.path.join(extdir, d) for d in sorted(os.listdir(extdir))] + + for dirpath in dirs: + if not os.path.isdir(dirpath): + continue + + path = os.path.join(dirpath, filename) + if os.path.isfile(filename): + res.append(path) + + return res + + def load_scripts(): global current_basedir scripts_data.clear() @@ -276,7 +298,7 @@ class ScriptRunner: print(f"Error running alwayson script: {script.filename}", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) - def reload_sources(self): + def reload_sources(self, cache): for si, script in list(enumerate(self.scripts)): with open(script.filename, "r", encoding="utf8") as file: args_from = script.args_from @@ -286,9 +308,12 @@ class ScriptRunner: from types import ModuleType - compiled = compile(text, filename, 'exec') - module = ModuleType(script.filename) - exec(compiled, module.__dict__) + module = cache.get(filename, None) + if module is None: + compiled = compile(text, filename, 'exec') + module = ModuleType(script.filename) + exec(compiled, module.__dict__) + cache[filename] = module for key, script_class in module.__dict__.items(): if type(script_class) == type and issubclass(script_class, Script): @@ -303,8 +328,9 @@ scripts_img2img = ScriptRunner() def reload_script_body_only(): - scripts_txt2img.reload_sources() - scripts_img2img.reload_sources() + cache = {} + scripts_txt2img.reload_sources(cache) + scripts_img2img.reload_sources(cache) def reload_scripts(): diff --git a/modules/ui.py b/modules/ui.py index c977482c..29986124 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1636,13 +1636,15 @@ Requested path was: {f} interfaces += [(settings_interface, "Settings", "settings")] - with open(os.path.join(script_path, "style.css"), "r", encoding="utf8") as file: - css = file.read() + css = "" + + for cssfile in modules.scripts.list_files_with_name("style.css"): + with open(cssfile, "r", encoding="utf8") as file: + css += file.read() + "\n" if os.path.exists(os.path.join(script_path, "user.css")): with open(os.path.join(script_path, "user.css"), "r", encoding="utf8") as file: - usercss = file.read() - css += usercss + css += file.read() + "\n" if not cmd_opts.no_progressbar_hiding: css += css_hide_progressbar @@ -1865,9 +1867,9 @@ def load_javascript(raw_response): with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile: javascript = f'' - jsdir = os.path.join(script_path, "javascript") - for filename in sorted(os.listdir(jsdir)): - with open(os.path.join(jsdir, filename), "r", encoding="utf8") as jsfile: + scripts_list = modules.scripts.list_scripts("javascript", ".js") + for basedir, filename, path in scripts_list: + with open(path, "r", encoding="utf8") as jsfile: javascript += f"\n" if cmd_opts.theme is not None: @@ -1885,6 +1887,5 @@ def load_javascript(raw_response): gradio.routes.templates.TemplateResponse = template_response -reload_javascript = partial(load_javascript, - gradio.routes.templates.TemplateResponse) +reload_javascript = partial(load_javascript, gradio.routes.templates.TemplateResponse) reload_javascript() diff --git a/style.css b/style.css index 5d2bacc9..26ae36a5 100644 --- a/style.css +++ b/style.css @@ -477,7 +477,7 @@ input[type="range"]{ padding: 0; } -#refresh_sd_model_checkpoint, #refresh_sd_hypernetwork, #refresh_train_hypernetwork_name, #refresh_train_embedding_name, #refresh_localization, #refresh_aesthetic_embeddings{ +#refresh_sd_model_checkpoint, #refresh_sd_hypernetwork, #refresh_train_hypernetwork_name, #refresh_train_embedding_name, #refresh_localization{ max-width: 2.5em; min-width: 2.5em; height: 2.4em; -- cgit v1.2.3 From 0e8ca8e7af05be22d7d2c07a47c3c7febe0f0ab6 Mon Sep 17 00:00:00 2001 From: discus0434 Date: Sat, 22 Oct 2022 11:07:00 +0000 Subject: add dropout --- modules/hypernetworks/hypernetwork.py | 68 +++++++++++++++++++++-------------- modules/hypernetworks/ui.py | 10 +++--- modules/ui.py | 43 +++++++++++----------- 3 files changed, 70 insertions(+), 51 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 905cbeef..e493f366 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -1,47 +1,60 @@ +import csv import datetime import glob import html import os import sys import traceback -import tqdm -import csv +import modules.textual_inversion.dataset import torch - -from ldm.util import default -from modules import devices, shared, processing, sd_models -import torch -from torch import einsum +import tqdm from einops import rearrange, repeat -import modules.textual_inversion.dataset +from ldm.util import default +from modules import devices, processing, sd_models, shared from modules.textual_inversion import textual_inversion from modules.textual_inversion.learn_schedule import LearnRateScheduler +from torch import einsum class HypernetworkModule(torch.nn.Module): multiplier = 1.0 - activation_dict = {"relu": torch.nn.ReLU, "leakyrelu": torch.nn.LeakyReLU, "elu": torch.nn.ELU, - "swish": torch.nn.Hardswish} - - def __init__(self, dim, state_dict=None, layer_structure=None, add_layer_norm=False, activation_func=None): + activation_dict = { + "relu": torch.nn.ReLU, + "leakyrelu": torch.nn.LeakyReLU, + "elu": torch.nn.ELU, + "swish": torch.nn.Hardswish, + } + + def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, add_layer_norm=False, use_dropout=False): super().__init__() assert layer_structure is not None, "layer_structure must not be None" assert layer_structure[0] == 1, "Multiplier Sequence should start with size 1!" assert layer_structure[-1] == 1, "Multiplier Sequence should end with size 1!" - + assert activation_func not in self.activation_dict.keys() + "linear", f"Valid activation funcs: 'linear', 'relu', 'leakyrelu', 'elu', 'swish'" + linears = [] for i in range(len(layer_structure) - 1): + + # Add a fully-connected layer linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i+1]))) - # if skip_first_layer because first parameters potentially contain negative values - # if i < 1: continue - if activation_func in HypernetworkModule.activation_dict: - linears.append(HypernetworkModule.activation_dict[activation_func]()) + + # Add an activation func + if activation_func == "linear": + pass + elif activation_func in self.activation_dict: + linears.append(self.activation_dict[activation_func]()) else: - print("Invalid key {} encountered as activation function!".format(activation_func)) - # if use_dropout: - # linears.append(torch.nn.Dropout(p=0.3)) + raise NotImplementedError( + "Valid activation funcs: 'linear', 'relu', 'leakyrelu', 'elu', 'swish'" + ) + + # Add dropout + if use_dropout: + linears.append(torch.nn.Dropout(p=0.3)) + + # Add layer normalization if add_layer_norm: linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1]))) @@ -93,7 +106,7 @@ class Hypernetwork: filename = None name = None - def __init__(self, name=None, enable_sizes=None, layer_structure=None, add_layer_norm=False, activation_func=None): + def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, add_layer_norm=False, use_dropout=False): self.filename = None self.name = name self.layers = {} @@ -101,13 +114,14 @@ class Hypernetwork: self.sd_checkpoint = None self.sd_checkpoint_name = None self.layer_structure = layer_structure - self.add_layer_norm = add_layer_norm self.activation_func = activation_func + self.add_layer_norm = add_layer_norm + self.use_dropout = use_dropout for size in enable_sizes or []: self.layers[size] = ( - HypernetworkModule(size, None, self.layer_structure, self.add_layer_norm, self.activation_func), - HypernetworkModule(size, None, self.layer_structure, self.add_layer_norm, self.activation_func), + HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout), + HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout), ) def weights(self): @@ -129,8 +143,9 @@ class Hypernetwork: state_dict['step'] = self.step state_dict['name'] = self.name state_dict['layer_structure'] = self.layer_structure - state_dict['is_layer_norm'] = self.add_layer_norm state_dict['activation_func'] = self.activation_func + state_dict['is_layer_norm'] = self.add_layer_norm + state_dict['use_dropout'] = self.use_dropout state_dict['sd_checkpoint'] = self.sd_checkpoint state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name @@ -144,8 +159,9 @@ class Hypernetwork: state_dict = torch.load(filename, map_location='cpu') self.layer_structure = state_dict.get('layer_structure', [1, 2, 1]) - self.add_layer_norm = state_dict.get('is_layer_norm', False) self.activation_func = state_dict.get('activation_func', None) + self.add_layer_norm = state_dict.get('is_layer_norm', False) + self.use_dropout = state_dict.get('use_dropout', False) for size, sd in state_dict.items(): if type(size) == int: diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py index 1a5a27d8..5f6f17b6 100644 --- a/modules/hypernetworks/ui.py +++ b/modules/hypernetworks/ui.py @@ -3,14 +3,13 @@ import os import re import gradio as gr - -import modules.textual_inversion.textual_inversion import modules.textual_inversion.preprocess -from modules import sd_hijack, shared, devices +import modules.textual_inversion.textual_inversion +from modules import devices, sd_hijack, shared from modules.hypernetworks import hypernetwork -def create_hypernetwork(name, enable_sizes, layer_structure=None, add_layer_norm=False, activation_func=None): +def create_hypernetwork(name, enable_sizes, layer_structure=None, activation_func=None, add_layer_norm=False, use_dropout=False): fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt") assert not os.path.exists(fn), f"file {fn} already exists" @@ -21,8 +20,9 @@ def create_hypernetwork(name, enable_sizes, layer_structure=None, add_layer_norm name=name, enable_sizes=[int(x) for x in enable_sizes], layer_structure=layer_structure, - add_layer_norm=add_layer_norm, activation_func=activation_func, + add_layer_norm=add_layer_norm, + use_dropout=use_dropout, ) hypernet.save(fn) diff --git a/modules/ui.py b/modules/ui.py index 716f14b8..d4b32c05 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -5,43 +5,44 @@ import json import math import mimetypes import os +import platform import random +import subprocess as sp import sys import tempfile import time import traceback -import platform -import subprocess as sp from functools import partial, reduce +import gradio as gr +import gradio.routes +import gradio.utils import numpy as np +import piexif import torch from PIL import Image, PngImagePlugin -import piexif -import gradio as gr -import gradio.utils -import gradio.routes - -from modules import sd_hijack, sd_models, localization +from modules import localization, sd_hijack, sd_models from modules.paths import script_path -from modules.shared import opts, cmd_opts, restricted_opts +from modules.shared import cmd_opts, opts, restricted_opts + if cmd_opts.deepdanbooru: from modules.deepbooru import get_deepbooru_tags -import modules.shared as shared -from modules.sd_samplers import samplers, samplers_for_img2img -from modules.sd_hijack import model_hijack + +import modules.codeformer_model +import modules.generation_parameters_copypaste +import modules.gfpgan_model +import modules.hypernetworks.ui +import modules.images_history as img_his import modules.ldsr_model import modules.scripts -import modules.gfpgan_model -import modules.codeformer_model +import modules.shared as shared import modules.styles -import modules.generation_parameters_copypaste +import modules.textual_inversion.ui from modules import prompt_parser from modules.images import save_image -import modules.textual_inversion.ui -import modules.hypernetworks.ui -import modules.images_history as img_his +from modules.sd_hijack import model_hijack +from modules.sd_samplers import samplers, samplers_for_img2img # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() @@ -1223,8 +1224,9 @@ def create_ui(wrap_gradio_gpu_call): new_hypernetwork_name = gr.Textbox(label="Name") new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'") + new_hypernetwork_activation_func = gr.Dropdown(value="relu", label="Select activation function of hypernetwork", choices=["linear", "relu", "leakyrelu", "elu", "swish"]) new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization") - new_hypernetwork_activation_func = gr.Dropdown(value="relu", label="Select activation function of hypernetwork", choices=["linear", "relu", "leakyrelu"]) + new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout") with gr.Row(): with gr.Column(scale=3): @@ -1308,8 +1310,9 @@ def create_ui(wrap_gradio_gpu_call): new_hypernetwork_name, new_hypernetwork_sizes, new_hypernetwork_layer_structure, - new_hypernetwork_add_layer_norm, new_hypernetwork_activation_func, + new_hypernetwork_add_layer_norm, + new_hypernetwork_use_dropout ], outputs=[ train_hypernetwork_name, -- cgit v1.2.3 From 1cd3ed7def40198f46d30f74dd37d2906ebdbaa6 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 22 Oct 2022 14:28:56 +0300 Subject: fix for extensions without style.css --- modules/ui.py | 3 +++ 1 file changed, 3 insertions(+) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 29986124..d8d52db1 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1639,6 +1639,9 @@ Requested path was: {f} css = "" for cssfile in modules.scripts.list_files_with_name("style.css"): + if not os.path.isfile(cssfile): + continue + with open(cssfile, "r", encoding="utf8") as file: css += file.read() + "\n" -- cgit v1.2.3 From 7912acef725832debef58c4c7bf8ec22fb446c0b Mon Sep 17 00:00:00 2001 From: discus0434 Date: Sat, 22 Oct 2022 13:00:44 +0000 Subject: small fix --- modules/hypernetworks/hypernetwork.py | 12 +++++------- modules/ui.py | 1 - 2 files changed, 5 insertions(+), 8 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 3132a56c..7d12e0ff 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -42,22 +42,20 @@ class HypernetworkModule(torch.nn.Module): # Add an activation func if activation_func == "linear" or activation_func is None: pass - # If ReLU, Skip adding it to the first layer to avoid dying ReLU - elif activation_func == "relu" and i < 1: - pass elif activation_func in self.activation_dict: linears.append(self.activation_dict[activation_func]()) else: raise RuntimeError(f'hypernetwork uses an unsupported activation function: {activation_func}') - # Add dropout - if use_dropout: - linears.append(torch.nn.Dropout(p=0.3)) - # Add layer normalization if add_layer_norm: linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1]))) + # Add dropout + if use_dropout: + p = 0.5 if 0 <= i <= len(layer_structure) - 3 else 0.2 + linears.append(torch.nn.Dropout(p=p)) + self.linear = torch.nn.Sequential(*linears) if state_dict is not None: diff --git a/modules/ui.py b/modules/ui.py index cd118552..eca887ca 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1244,7 +1244,6 @@ def create_ui(wrap_gradio_gpu_call): new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization") new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout") overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork") - new_hypernetwork_activation_func = gr.Dropdown(value="relu", label="Select activation function of hypernetwork", choices=["linear", "relu", "leakyrelu"]) with gr.Row(): with gr.Column(scale=3): -- cgit v1.2.3 From d37cfffd537cd29309afbcb192c4f979995c6a34 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 22 Oct 2022 19:18:56 +0300 Subject: added callback for creating new settings in extensions --- modules/script_callbacks.py | 11 +++++++++++ modules/shared.py | 19 +++++++++++++++++-- modules/ui.py | 6 +++++- 3 files changed, 33 insertions(+), 3 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index 866b7acd..1270e50f 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -1,6 +1,7 @@ callbacks_model_loaded = [] callbacks_ui_tabs = [] +callbacks_ui_settings = [] def clear_callbacks(): @@ -22,6 +23,11 @@ def ui_tabs_callback(): return res +def ui_settings_callback(): + for callback in callbacks_ui_settings: + callback() + + def on_model_loaded(callback): """register a function to be called when the stable diffusion model is created; the model is passed as an argument""" @@ -40,3 +46,8 @@ def on_ui_tabs(callback): """ callbacks_ui_tabs.append(callback) + +def on_ui_settings(callback): + """register a function to be called before UI settingsare populated; add your settings + by using shared.opts.add_option(shared.OptionInfo(...)) """ + callbacks_ui_settings.append(callback) diff --git a/modules/shared.py b/modules/shared.py index 5d83971e..d9cb65ef 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -165,13 +165,13 @@ def realesrgan_models_names(): class OptionInfo: - def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, show_on_main_page=False, refresh=None): + def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, section=None, refresh=None): self.default = default self.label = label self.component = component self.component_args = component_args self.onchange = onchange - self.section = None + self.section = section self.refresh = refresh @@ -327,6 +327,7 @@ options_templates.update(options_section(('images-history', "Images Browser"), { })) + class Options: data = None data_labels = options_templates @@ -389,6 +390,20 @@ class Options: d = {k: self.data.get(k, self.data_labels.get(k).default) for k in self.data_labels.keys()} return json.dumps(d) + def add_option(self, key, info): + self.data_labels[key] = info + + def reorder(self): + """reorder settings so that all items related to section always go together""" + + section_ids = {} + settings_items = self.data_labels.items() + for k, item in settings_items: + if item.section not in section_ids: + section_ids[item.section] = len(section_ids) + + self.data_labels = {k: v for k, v in sorted(settings_items, key=lambda x: section_ids[x[1].section])} + opts = Options() if os.path.exists(config_filename): diff --git a/modules/ui.py b/modules/ui.py index d8d52db1..2849b111 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1461,6 +1461,9 @@ def create_ui(wrap_gradio_gpu_call): components = [] component_dict = {} + script_callbacks.ui_settings_callback() + opts.reorder() + def open_folder(f): if not os.path.exists(f): print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.') @@ -1564,7 +1567,8 @@ Requested path was: {f} previous_section = item.section - gr.HTML(elem_id="settings_header_text_{}".format(item.section[0]), value='

{}

'.format(item.section[1])) + elem_id, text = item.section + gr.HTML(elem_id="settings_header_text_{}".format(elem_id), value='

{}

'.format(text)) if k in quicksettings_names: quicksettings_list.append((i, k, item)) -- cgit v1.2.3 From 4fdb53c1e9962507fc8336dad9a0fabfe6c418c0 Mon Sep 17 00:00:00 2001 From: Unnoen Date: Wed, 19 Oct 2022 21:38:10 +1100 Subject: Generate grid preview for progress image --- modules/sd_samplers.py | 26 +++++++++++++++++++++++++- modules/shared.py | 1 + modules/ui.py | 5 ++++- 3 files changed, 30 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index f58a29b9..74a480e5 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -7,7 +7,7 @@ import inspect import k_diffusion.sampling import ldm.models.diffusion.ddim import ldm.models.diffusion.plms -from modules import prompt_parser, devices, processing +from modules import prompt_parser, devices, processing, images from modules.shared import opts, cmd_opts, state import modules.shared as shared @@ -89,6 +89,30 @@ def sample_to_image(samples): x_sample = x_sample.astype(np.uint8) return Image.fromarray(x_sample) +def samples_to_image_grid(samples): + progress_images = [] + for i in range(len(samples)): + # Decode the samples individually to reduce VRAM usage at the cost of a bit of speed. + x_sample = processing.decode_first_stage(shared.sd_model, samples[i:i+1])[0] + x_sample = torch.clamp((x_sample + 1.0) / 2.0, min=0.0, max=1.0) + x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) + x_sample = x_sample.astype(np.uint8) + progress_images.append(Image.fromarray(x_sample)) + + return images.image_grid(progress_images) + +def samples_to_image_grid_combined(samples): + progress_images = [] + # Decode all samples at once to increase speed at the cost of VRAM usage. + x_samples = processing.decode_first_stage(shared.sd_model, samples) + x_samples = torch.clamp((x_samples + 1.0) / 2.0, min=0.0, max=1.0) + + for x_sample in x_samples: + x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) + x_sample = x_sample.astype(np.uint8) + progress_images.append(Image.fromarray(x_sample)) + + return images.image_grid(progress_images) def store_latent(decoded): state.current_latent = decoded diff --git a/modules/shared.py b/modules/shared.py index d9cb65ef..95d6e225 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -294,6 +294,7 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"), options_templates.update(options_section(('ui', "User interface"), { "show_progressbar": OptionInfo(True, "Show progressbar"), "show_progress_every_n_steps": OptionInfo(0, "Show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}), + "progress_decode_combined": OptionInfo(False, "Decode all progress images at once. (Slighty speeds up progress generation but consumes significantly more VRAM with large batches.)"), "return_grid": OptionInfo(True, "Show grid in results for web"), "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"), "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"), diff --git a/modules/ui.py b/modules/ui.py index 56c233ab..de0abc7e 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -318,7 +318,10 @@ def check_progress_call(id_part): if shared.parallel_processing_allowed: if shared.state.sampling_step - shared.state.current_image_sampling_step >= opts.show_progress_every_n_steps and shared.state.current_latent is not None: - shared.state.current_image = modules.sd_samplers.sample_to_image(shared.state.current_latent) + if opts.progress_decode_combined: + shared.state.current_image = modules.sd_samplers.samples_to_image_grid_combined(shared.state.current_latent) + else: + shared.state.current_image = modules.sd_samplers.samples_to_image_grid(shared.state.current_latent) shared.state.current_image_sampling_step = shared.state.sampling_step image = shared.state.current_image -- cgit v1.2.3 From d213d6ca6f90094cb45c11e2f3cb37d25a8d1f94 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 22 Oct 2022 20:48:13 +0300 Subject: removed the option to use 2x more memory when generating previews added an option to always only show one image in previews removed duplicate code --- modules/sd_samplers.py | 35 ++++++++++------------------------- modules/shared.py | 2 +- modules/ui.py | 6 +++--- 3 files changed, 14 insertions(+), 29 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index 74a480e5..0b408a70 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -71,6 +71,7 @@ sampler_extra_params = { 'sample_dpm_2': ['s_churn', 's_tmin', 's_tmax', 's_noise'], } + def setup_img2img_steps(p, steps=None): if opts.img2img_fix_steps or steps is not None: steps = int((steps or p.steps) / min(p.denoising_strength, 0.999)) if p.denoising_strength > 0 else 0 @@ -82,37 +83,21 @@ def setup_img2img_steps(p, steps=None): return steps, t_enc -def sample_to_image(samples): - x_sample = processing.decode_first_stage(shared.sd_model, samples[0:1])[0] +def single_sample_to_image(sample): + x_sample = processing.decode_first_stage(shared.sd_model, sample.unsqueeze(0))[0] x_sample = torch.clamp((x_sample + 1.0) / 2.0, min=0.0, max=1.0) x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) x_sample = x_sample.astype(np.uint8) return Image.fromarray(x_sample) + +def sample_to_image(samples): + return single_sample_to_image(samples[0]) + + def samples_to_image_grid(samples): - progress_images = [] - for i in range(len(samples)): - # Decode the samples individually to reduce VRAM usage at the cost of a bit of speed. - x_sample = processing.decode_first_stage(shared.sd_model, samples[i:i+1])[0] - x_sample = torch.clamp((x_sample + 1.0) / 2.0, min=0.0, max=1.0) - x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) - x_sample = x_sample.astype(np.uint8) - progress_images.append(Image.fromarray(x_sample)) - - return images.image_grid(progress_images) - -def samples_to_image_grid_combined(samples): - progress_images = [] - # Decode all samples at once to increase speed at the cost of VRAM usage. - x_samples = processing.decode_first_stage(shared.sd_model, samples) - x_samples = torch.clamp((x_samples + 1.0) / 2.0, min=0.0, max=1.0) - - for x_sample in x_samples: - x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) - x_sample = x_sample.astype(np.uint8) - progress_images.append(Image.fromarray(x_sample)) - - return images.image_grid(progress_images) + return images.image_grid([single_sample_to_image(sample) for sample in samples]) + def store_latent(decoded): state.current_latent = decoded diff --git a/modules/shared.py b/modules/shared.py index 95d6e225..25bfc895 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -294,7 +294,7 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"), options_templates.update(options_section(('ui', "User interface"), { "show_progressbar": OptionInfo(True, "Show progressbar"), "show_progress_every_n_steps": OptionInfo(0, "Show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}), - "progress_decode_combined": OptionInfo(False, "Decode all progress images at once. (Slighty speeds up progress generation but consumes significantly more VRAM with large batches.)"), + "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"), "return_grid": OptionInfo(True, "Show grid in results for web"), "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"), "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"), diff --git a/modules/ui.py b/modules/ui.py index de0abc7e..ffa14cac 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -318,10 +318,10 @@ def check_progress_call(id_part): if shared.parallel_processing_allowed: if shared.state.sampling_step - shared.state.current_image_sampling_step >= opts.show_progress_every_n_steps and shared.state.current_latent is not None: - if opts.progress_decode_combined: - shared.state.current_image = modules.sd_samplers.samples_to_image_grid_combined(shared.state.current_latent) - else: + if opts.show_progress_grid: shared.state.current_image = modules.sd_samplers.samples_to_image_grid(shared.state.current_latent) + else: + shared.state.current_image = modules.sd_samplers.sample_to_image(shared.state.current_latent) shared.state.current_image_sampling_step = shared.state.sampling_step image = shared.state.current_image -- cgit v1.2.3 From be748e8b086bd9834d08bdd9160649a5e7700af7 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 22 Oct 2022 22:05:22 +0300 Subject: add --freeze-settings commandline argument to disable changing settings --- modules/shared.py | 1 + modules/ui.py | 11 +++++++++-- 2 files changed, 10 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/shared.py b/modules/shared.py index 25bfc895..b55371d3 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -64,6 +64,7 @@ parser.add_argument("--port", type=int, help="launch gradio with given server po parser.add_argument("--show-negative-prompt", action='store_true', help="does not do anything", default=False) parser.add_argument("--ui-config-file", type=str, help="filename to use for ui configuration", default=os.path.join(script_path, 'ui-config.json')) parser.add_argument("--hide-ui-dir-config", action='store_true', help="hide directory configuration from webui", default=False) +parser.add_argument("--freeze-settings", action='store_true', help="disable editing settings", default=False) parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(script_path, 'config.json')) parser.add_argument("--gradio-debug", action='store_true', help="launch gradio with --debug option") parser.add_argument("--gradio-auth", type=str, help='set gradio authentication like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3"', default=None) diff --git a/modules/ui.py b/modules/ui.py index ffa14cac..2311572c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -580,6 +580,9 @@ def apply_setting(key, value): if value is None: return gr.update() + if shared.cmd_opts.freeze_settings: + return gr.update() + # dont allow model to be swapped when model hash exists in prompt if key == "sd_model_checkpoint" and opts.disable_weights_auto_swap: return gr.update() @@ -1501,6 +1504,8 @@ Requested path was: {f} def run_settings(*args): changed = 0 + assert not shared.cmd_opts.freeze_settings, "changing settings is disabled" + for key, value, comp in zip(opts.data_labels.keys(), args, components): if comp != dummy_component and not opts.same_type(value, opts.data_labels[key].default): return f"Bad value for setting {key}: {value}; expecting {type(opts.data_labels[key].default).__name__}", opts.dumpjson() @@ -1530,6 +1535,8 @@ Requested path was: {f} return f'{changed} settings changed.', opts.dumpjson() def run_settings_single(value, key): + assert not shared.cmd_opts.freeze_settings, "changing settings is disabled" + if not opts.same_type(value, opts.data_labels[key].default): return gr.update(visible=True), opts.dumpjson() @@ -1582,7 +1589,7 @@ Requested path was: {f} elem_id, text = item.section gr.HTML(elem_id="settings_header_text_{}".format(elem_id), value='

{}

'.format(text)) - if k in quicksettings_names: + if k in quicksettings_names and not shared.cmd_opts.freeze_settings: quicksettings_list.append((i, k, item)) components.append(dummy_component) else: @@ -1615,7 +1622,7 @@ Requested path was: {f} def reload_scripts(): modules.scripts.reload_script_body_only() - reload_javascript() # need to refresh the html page + reload_javascript() # need to refresh the html page reload_script_bodies.click( fn=reload_scripts, -- cgit v1.2.3 From ce42879438bf2dbd76b5b346be656292e42ffb2b Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Sat, 22 Oct 2022 14:53:37 -0500 Subject: fix js func signature and not forget to initialize confirmation var to prevent exception upon cancelling confirmation --- javascript/ui.js | 7 ++++--- modules/ui.py | 4 +++- 2 files changed, 7 insertions(+), 4 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index 6c99824b..39011079 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -162,12 +162,13 @@ function selected_tab_id() { } -function clear_prompt(_, _prompt_neg, confirmed,_steps) { +function clear_prompt(_, _prompt_neg, confirmed, _token_counter) { +confirmed = false if(confirm("Delete prompt?")) { confirmed = true } else { -return [_, confirmed] +return [_, _prompt_neg, confirmed, _token_counter] } if(selected_tab_id() == "tab_txt2img") { @@ -176,7 +177,7 @@ return [_, confirmed] update_token_counter("txt2img_token_button") } - return [_, _prompt_neg, confirmed,_steps] + return [_, _prompt_neg, confirmed, _token_counter] } diff --git a/modules/ui.py b/modules/ui.py index 25aeba3b..e58f040e 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -429,10 +429,12 @@ def create_seed_inputs(): return seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox -def clear_prompt(_prompt, _prompt_neg, confirmed, _token_counter): +def clear_prompt(prompt, _prompt_neg, confirmed, _token_counter): """Given confirmation from a user on the client-side, go ahead with clearing prompt""" if confirmed: return ["", "", confirmed, update_token_counter("", 1)] + else: + return [prompt, _prompt_neg, confirmed, _token_counter] def connect_clear_prompt(button, prompt, prompt_neg, _dummy_confirmed, token_counter): -- cgit v1.2.3 From 124e44cf1eed1edc68954f63a2a9bc428aabbcec Mon Sep 17 00:00:00 2001 From: yfszzx Date: Mon, 24 Oct 2022 09:51:56 +0800 Subject: remove browser to extension --- .gitignore | 1 - javascript/images_history.js | 200 -------------------- javascript/inspiration.js | 48 ----- modules/images_history.py | 424 ------------------------------------------- modules/inspiration.py | 193 -------------------- modules/script_callbacks.py | 2 - modules/shared.py | 15 -- modules/ui.py | 20 +- 8 files changed, 4 insertions(+), 899 deletions(-) delete mode 100644 javascript/images_history.js delete mode 100644 javascript/inspiration.js delete mode 100644 modules/images_history.py delete mode 100644 modules/inspiration.py (limited to 'modules/ui.py') diff --git a/.gitignore b/.gitignore index 8d01bc6a..70660c51 100644 --- a/.gitignore +++ b/.gitignore @@ -29,5 +29,4 @@ notification.mp3 /textual_inversion .vscode /extensions - /inspiration diff --git a/javascript/images_history.js b/javascript/images_history.js deleted file mode 100644 index c9aa76f8..00000000 --- a/javascript/images_history.js +++ /dev/null @@ -1,200 +0,0 @@ -var images_history_click_image = function(){ - if (!this.classList.contains("transform")){ - var gallery = images_history_get_parent_by_class(this, "images_history_cantainor"); - var buttons = gallery.querySelectorAll(".gallery-item"); - var i = 0; - var hidden_list = []; - buttons.forEach(function(e){ - if (e.style.display == "none"){ - hidden_list.push(i); - } - i += 1; - }) - if (hidden_list.length > 0){ - setTimeout(images_history_hide_buttons, 10, hidden_list, gallery); - } - } - images_history_set_image_info(this); -} - -function images_history_disabled_del(){ - gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){ - btn.setAttribute('disabled','disabled'); - }); -} - -function images_history_get_parent_by_class(item, class_name){ - var parent = item.parentElement; - while(!parent.classList.contains(class_name)){ - parent = parent.parentElement; - } - return parent; -} - -function images_history_get_parent_by_tagname(item, tagname){ - var parent = item.parentElement; - tagname = tagname.toUpperCase() - while(parent.tagName != tagname){ - parent = parent.parentElement; - } - return parent; -} - -function images_history_hide_buttons(hidden_list, gallery){ - var buttons = gallery.querySelectorAll(".gallery-item"); - var num = 0; - buttons.forEach(function(e){ - if (e.style.display == "none"){ - num += 1; - } - }); - if (num == hidden_list.length){ - setTimeout(images_history_hide_buttons, 10, hidden_list, gallery); - } - for( i in hidden_list){ - buttons[hidden_list[i]].style.display = "none"; - } -} - -function images_history_set_image_info(button){ - var buttons = images_history_get_parent_by_tagname(button, "DIV").querySelectorAll(".gallery-item"); - var index = -1; - var i = 0; - buttons.forEach(function(e){ - if(e == button){ - index = i; - } - if(e.style.display != "none"){ - i += 1; - } - }); - var gallery = images_history_get_parent_by_class(button, "images_history_cantainor"); - var set_btn = gallery.querySelector(".images_history_set_index"); - var curr_idx = set_btn.getAttribute("img_index", index); - if (curr_idx != index) { - set_btn.setAttribute("img_index", index); - images_history_disabled_del(); - } - set_btn.click(); - -} - -function images_history_get_current_img(tabname, img_index, files){ - return [ - tabname, - gradioApp().getElementById(tabname + '_images_history_set_index').getAttribute("img_index"), - files - ]; -} - -function images_history_delete(del_num, tabname, image_index){ - image_index = parseInt(image_index); - var tab = gradioApp().getElementById(tabname + '_images_history'); - var set_btn = tab.querySelector(".images_history_set_index"); - var buttons = []; - tab.querySelectorAll(".gallery-item").forEach(function(e){ - if (e.style.display != 'none'){ - buttons.push(e); - } - }); - var img_num = buttons.length / 2; - del_num = Math.min(img_num - image_index, del_num) - if (img_num <= del_num){ - setTimeout(function(tabname){ - gradioApp().getElementById(tabname + '_images_history_renew_page').click(); - }, 30, tabname); - } else { - var next_img - for (var i = 0; i < del_num; i++){ - buttons[image_index + i].style.display = 'none'; - buttons[image_index + i + img_num].style.display = 'none'; - next_img = image_index + i + 1 - } - var bnt; - if (next_img >= img_num){ - btn = buttons[image_index - 1]; - } else { - btn = buttons[next_img]; - } - setTimeout(function(btn){btn.click()}, 30, btn); - } - images_history_disabled_del(); - -} - -function images_history_turnpage(tabname){ - gradioApp().getElementById(tabname + '_images_history_del_button').setAttribute('disabled','disabled'); - var buttons = gradioApp().getElementById(tabname + '_images_history').querySelectorAll(".gallery-item"); - buttons.forEach(function(elem) { - elem.style.display = 'block'; - }) -} - -function images_history_enable_del_buttons(){ - gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){ - btn.removeAttribute('disabled'); - }) -} - -function images_history_init(){ - var tabnames = gradioApp().getElementById("images_history_tabnames_list") - if (tabnames){ - images_history_tab_list = tabnames.querySelector("textarea").value.split(",") - for (var i in images_history_tab_list ){ - var tab = images_history_tab_list[i]; - gradioApp().getElementById(tab + '_images_history').classList.add("images_history_cantainor"); - gradioApp().getElementById(tab + '_images_history_set_index').classList.add("images_history_set_index"); - gradioApp().getElementById(tab + '_images_history_del_button').classList.add("images_history_del_button"); - gradioApp().getElementById(tab + '_images_history_gallery').classList.add("images_history_gallery"); - gradioApp().getElementById(tab + "_images_history_start").setAttribute("style","padding:20px;font-size:25px"); - } - - //preload - if (gradioApp().getElementById("images_history_preload").querySelector("input").checked ){ - var tabs_box = gradioApp().getElementById("tab_images_history").querySelector("div").querySelector("div").querySelector("div"); - tabs_box.setAttribute("id", "images_history_tab"); - var tab_btns = tabs_box.querySelectorAll("button"); - for (var i in images_history_tab_list){ - var tabname = images_history_tab_list[i] - tab_btns[i].setAttribute("tabname", tabname); - tab_btns[i].addEventListener('click', function(){ - var tabs_box = gradioApp().getElementById("images_history_tab"); - if (!tabs_box.classList.contains(this.getAttribute("tabname"))) { - gradioApp().getElementById(this.getAttribute("tabname") + "_images_history_start").click(); - tabs_box.classList.add(this.getAttribute("tabname")) - } - }); - } - tab_btns[0].click() - } - } else { - setTimeout(images_history_init, 500); - } -} - -var images_history_tab_list = ""; -setTimeout(images_history_init, 500); -document.addEventListener("DOMContentLoaded", function() { - var mutationObserver = new MutationObserver(function(m){ - if (images_history_tab_list != ""){ - for (var i in images_history_tab_list ){ - let tabname = images_history_tab_list[i] - var buttons = gradioApp().querySelectorAll('#' + tabname + '_images_history .gallery-item'); - buttons.forEach(function(bnt){ - bnt.addEventListener('click', images_history_click_image, true); - }); - - var cls_btn = gradioApp().getElementById(tabname + '_images_history_gallery').querySelector("svg"); - if (cls_btn){ - cls_btn.addEventListener('click', function(){ - gradioApp().getElementById(tabname + '_images_history_renew_page').click(); - }, false); - } - - } - } - }); - mutationObserver.observe(gradioApp(), { childList:true, subtree:true }); -}); - - diff --git a/javascript/inspiration.js b/javascript/inspiration.js deleted file mode 100644 index 39844544..00000000 --- a/javascript/inspiration.js +++ /dev/null @@ -1,48 +0,0 @@ -function public_image_index_in_gallery(item, gallery){ - var imgs = gallery.querySelectorAll("img.h-full") - var index; - var i = 0; - imgs.forEach(function(e){ - if (e == item) - index = i; - i += 1; - }); - var all_imgs = gallery.querySelectorAll("img") - if (all_imgs.length > imgs.length){ - var num = imgs.length / 2 - index = (index < num) ? index : (index - num) - } - return index; -} - -function inspiration_selected(name, name_list){ - var btn = gradioApp().getElementById("inspiration_select_button") - return [gradioApp().getElementById("inspiration_select_button").getAttribute("img-index")]; -} - -function inspiration_click_get_button(){ - gradioApp().getElementById("inspiration_get_button").click(); -} - -var inspiration_image_click = function(){ - var index = public_image_index_in_gallery(this, gradioApp().getElementById("inspiration_gallery")); - var btn = gradioApp().getElementById("inspiration_select_button"); - btn.setAttribute("img-index", index); - setTimeout(function(btn){btn.click();}, 10, btn); -} - -document.addEventListener("DOMContentLoaded", function() { - var mutationObserver = new MutationObserver(function(m){ - var gallery = gradioApp().getElementById("inspiration_gallery") - if (gallery) { - var node = gallery.querySelector(".absolute.backdrop-blur.h-full") - if (node) { - node.style.display = "None"; - } - gallery.querySelectorAll('img').forEach(function(e){ - e.onclick = inspiration_image_click - }); - } - }); - mutationObserver.observe( gradioApp(), { childList:true, subtree:true }); -}); diff --git a/modules/images_history.py b/modules/images_history.py deleted file mode 100644 index bc5cf11f..00000000 --- a/modules/images_history.py +++ /dev/null @@ -1,424 +0,0 @@ -import os -import shutil -import time -import hashlib -import gradio -system_bak_path = "webui_log_and_bak" -custom_tab_name = "custom fold" -faverate_tab_name = "favorites" -tabs_list = ["txt2img", "img2img", "extras", faverate_tab_name] -def is_valid_date(date): - try: - time.strptime(date, "%Y%m%d") - return True - except: - return False - -def reduplicative_file_move(src, dst): - def same_name_file(basename, path): - name, ext = os.path.splitext(basename) - f_list = os.listdir(path) - max_num = 0 - for f in f_list: - if len(f) <= len(basename): - continue - f_ext = f[-len(ext):] if len(ext) > 0 else "" - if f[:len(name)] == name and f_ext == ext: - if f[len(name)] == "(" and f[-len(ext)-1] == ")": - number = f[len(name)+1:-len(ext)-1] - if number.isdigit(): - if int(number) > max_num: - max_num = int(number) - return f"{name}({max_num + 1}){ext}" - name = os.path.basename(src) - save_name = os.path.join(dst, name) - if not os.path.exists(save_name): - shutil.move(src, dst) - else: - name = same_name_file(name, dst) - shutil.move(src, os.path.join(dst, name)) - -def traverse_all_files(curr_path, image_list, all_type=False): - try: - f_list = os.listdir(curr_path) - except: - if all_type or (curr_path[-10:].rfind(".") > 0 and curr_path[-4:] != ".txt" and curr_path[-4:] != ".csv"): - image_list.append(curr_path) - return image_list - for file in f_list: - file = os.path.join(curr_path, file) - if (not all_type) and (file[-4:] == ".txt" or file[-4:] == ".csv"): - pass - elif os.path.isfile(file) and file[-10:].rfind(".") > 0: - image_list.append(file) - else: - image_list = traverse_all_files(file, image_list) - return image_list - -def auto_sorting(dir_name): - bak_path = os.path.join(dir_name, system_bak_path) - if not os.path.exists(bak_path): - os.mkdir(bak_path) - log_file = None - files_list = [] - f_list = os.listdir(dir_name) - for file in f_list: - if file == system_bak_path: - continue - file_path = os.path.join(dir_name, file) - if not is_valid_date(file): - if file[-10:].rfind(".") > 0: - files_list.append(file_path) - else: - files_list = traverse_all_files(file_path, files_list, all_type=True) - - for file in files_list: - date_str = time.strftime("%Y%m%d",time.localtime(os.path.getmtime(file))) - file_path = os.path.dirname(file) - hash_path = hashlib.md5(file_path.encode()).hexdigest() - path = os.path.join(dir_name, date_str, hash_path) - if not os.path.exists(path): - os.makedirs(path) - if log_file is None: - log_file = open(os.path.join(bak_path,"path_mapping.csv"),"a") - log_file.write(f"{hash_path},{file_path}\n") - reduplicative_file_move(file, path) - - date_list = [] - f_list = os.listdir(dir_name) - for f in f_list: - if is_valid_date(f): - date_list.append(f) - elif f == system_bak_path: - continue - else: - try: - reduplicative_file_move(os.path.join(dir_name, f), bak_path) - except: - pass - - today = time.strftime("%Y%m%d",time.localtime(time.time())) - if today not in date_list: - date_list.append(today) - return sorted(date_list, reverse=True) - -def archive_images(dir_name, date_to): - filenames = [] - batch_size =int(opts.images_history_num_per_page * opts.images_history_pages_num) - if batch_size <= 0: - batch_size = opts.images_history_num_per_page * 6 - today = time.strftime("%Y%m%d",time.localtime(time.time())) - date_to = today if date_to is None or date_to == "" else date_to - date_to_bak = date_to - if False: #opts.images_history_reconstruct_directory: - date_list = auto_sorting(dir_name) - for date in date_list: - if date <= date_to: - path = os.path.join(dir_name, date) - if date == today and not os.path.exists(path): - continue - filenames = traverse_all_files(path, filenames) - if len(filenames) > batch_size: - break - filenames = sorted(filenames, key=lambda file: -os.path.getmtime(file)) - else: - filenames = traverse_all_files(dir_name, filenames) - total_num = len(filenames) - tmparray = [(os.path.getmtime(file), file) for file in filenames ] - date_stamp = time.mktime(time.strptime(date_to, "%Y%m%d")) + 86400 - filenames = [] - date_list = {date_to:None} - date = time.strftime("%Y%m%d",time.localtime(time.time())) - for t, f in tmparray: - date = time.strftime("%Y%m%d",time.localtime(t)) - date_list[date] = None - if t <= date_stamp: - filenames.append((t, f ,date)) - date_list = sorted(list(date_list.keys()), reverse=True) - sort_array = sorted(filenames, key=lambda x:-x[0]) - if len(sort_array) > batch_size: - date = sort_array[batch_size][2] - filenames = [x[1] for x in sort_array] - else: - date = date_to if len(sort_array) == 0 else sort_array[-1][2] - filenames = [x[1] for x in sort_array] - filenames = [x[1] for x in sort_array if x[2]>= date] - num = len(filenames) - last_date_from = date_to_bak if num == 0 else time.strftime("%Y%m%d", time.localtime(time.mktime(time.strptime(date, "%Y%m%d")) - 1000)) - date = date[:4] + "/" + date[4:6] + "/" + date[6:8] - date_to_bak = date_to_bak[:4] + "/" + date_to_bak[4:6] + "/" + date_to_bak[6:8] - load_info = "
" - load_info += f"{total_num} images in this directory. Loaded {num} images during {date} - {date_to_bak}, divided into {int((num + 1) // opts.images_history_num_per_page + 1)} pages" - load_info += "
" - _, image_list, _, _, visible_num = get_recent_images(1, 0, filenames) - return ( - date_to, - load_info, - filenames, - 1, - image_list, - "", - "", - visible_num, - last_date_from, - gradio.update(visible=total_num > num) - ) - -def delete_image(delete_num, name, filenames, image_index, visible_num): - if name == "": - return filenames, delete_num - else: - delete_num = int(delete_num) - visible_num = int(visible_num) - image_index = int(image_index) - index = list(filenames).index(name) - i = 0 - new_file_list = [] - for name in filenames: - if i >= index and i < index + delete_num: - if os.path.exists(name): - if visible_num == image_index: - new_file_list.append(name) - i += 1 - continue - print(f"Delete file {name}") - os.remove(name) - visible_num -= 1 - txt_file = os.path.splitext(name)[0] + ".txt" - if os.path.exists(txt_file): - os.remove(txt_file) - else: - print(f"Not exists file {name}") - else: - new_file_list.append(name) - i += 1 - return new_file_list, 1, visible_num - -def save_image(file_name): - if file_name is not None and os.path.exists(file_name): - shutil.copy(file_name, opts.outdir_save) - -def get_recent_images(page_index, step, filenames): - page_index = int(page_index) - num_of_imgs_per_page = int(opts.images_history_num_per_page) - max_page_index = len(filenames) // num_of_imgs_per_page + 1 - page_index = max_page_index if page_index == -1 else page_index + step - page_index = 1 if page_index < 1 else page_index - page_index = max_page_index if page_index > max_page_index else page_index - idx_frm = (page_index - 1) * num_of_imgs_per_page - image_list = filenames[idx_frm:idx_frm + num_of_imgs_per_page] - length = len(filenames) - visible_num = num_of_imgs_per_page if idx_frm + num_of_imgs_per_page <= length else length % num_of_imgs_per_page - visible_num = num_of_imgs_per_page if visible_num == 0 else visible_num - return page_index, image_list, "", "", visible_num - -def loac_batch_click(date_to): - if date_to is None: - return time.strftime("%Y%m%d",time.localtime(time.time())), [] - else: - return None, [] -def forward_click(last_date_from, date_to_recorder): - if len(date_to_recorder) == 0: - return None, [] - if last_date_from == date_to_recorder[-1]: - date_to_recorder = date_to_recorder[:-1] - if len(date_to_recorder) == 0: - return None, [] - return date_to_recorder[-1], date_to_recorder[:-1] - -def backward_click(last_date_from, date_to_recorder): - if last_date_from is None or last_date_from == "": - return time.strftime("%Y%m%d",time.localtime(time.time())), [] - if len(date_to_recorder) == 0 or last_date_from != date_to_recorder[-1]: - date_to_recorder.append(last_date_from) - return last_date_from, date_to_recorder - - -def first_page_click(page_index, filenames): - return get_recent_images(1, 0, filenames) - -def end_page_click(page_index, filenames): - return get_recent_images(-1, 0, filenames) - -def prev_page_click(page_index, filenames): - return get_recent_images(page_index, -1, filenames) - -def next_page_click(page_index, filenames): - return get_recent_images(page_index, 1, filenames) - -def page_index_change(page_index, filenames): - return get_recent_images(page_index, 0, filenames) - -def show_image_info(tabname_box, num, page_index, filenames): - file = filenames[int(num) + int((page_index - 1) * int(opts.images_history_num_per_page))] - tm = "
" + time.strftime("%Y-%m-%d %H:%M:%S",time.localtime(os.path.getmtime(file))) + "
" - return file, tm, num, file - -def enable_page_buttons(): - return gradio.update(visible=True) - -def change_dir(img_dir, date_to): - warning = None - try: - if os.path.exists(img_dir): - try: - f = os.listdir(img_dir) - except: - warning = f"'{img_dir} is not a directory" - else: - warning = "The directory is not exist" - except: - warning = "The format of the directory is incorrect" - if warning is None: - today = time.strftime("%Y%m%d",time.localtime(time.time())) - return gradio.update(visible=False), gradio.update(visible=True), None, None if date_to != today else today, gradio.update(visible=True), gradio.update(visible=True) - else: - return gradio.update(visible=True), gradio.update(visible=False), warning, date_to, gradio.update(visible=False), gradio.update(visible=False) - -def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): - custom_dir = False - if tabname == "txt2img": - dir_name = opts.outdir_txt2img_samples - elif tabname == "img2img": - dir_name = opts.outdir_img2img_samples - elif tabname == "extras": - dir_name = opts.outdir_extras_samples - elif tabname == faverate_tab_name: - dir_name = opts.outdir_save - else: - custom_dir = True - dir_name = None - - if not custom_dir: - d = dir_name.split("/") - dir_name = d[0] - for p in d[1:]: - dir_name = os.path.join(dir_name, p) - if not os.path.exists(dir_name): - os.makedirs(dir_name) - - with gr.Column() as page_panel: - with gr.Row(): - with gr.Column(scale=1, visible=not custom_dir) as load_batch_box: - load_batch = gr.Button('Load', elem_id=tabname + "_images_history_start", full_width=True) - with gr.Column(scale=4): - with gr.Row(): - img_path = gr.Textbox(dir_name, label="Images directory", placeholder="Input images directory", interactive=custom_dir) - with gr.Row(): - with gr.Column(visible=False, scale=1) as batch_panel: - with gr.Row(): - forward = gr.Button('Prev batch') - backward = gr.Button('Next batch') - with gr.Column(scale=3): - load_info = gr.HTML(visible=not custom_dir) - with gr.Row(visible=False) as warning: - warning_box = gr.Textbox("Message", interactive=False) - - with gr.Row(visible=not custom_dir, elem_id=tabname + "_images_history") as main_panel: - with gr.Column(scale=2): - with gr.Row(visible=True) as turn_page_buttons: - #date_to = gr.Dropdown(label="Date to") - first_page = gr.Button('First Page') - prev_page = gr.Button('Prev Page') - page_index = gr.Number(value=1, label="Page Index") - next_page = gr.Button('Next Page') - end_page = gr.Button('End Page') - - history_gallery = gr.Gallery(show_label=False, elem_id=tabname + "_images_history_gallery").style(grid=opts.images_history_grid_num) - with gr.Row(): - delete_num = gr.Number(value=1, interactive=True, label="number of images to delete consecutively next") - delete = gr.Button('Delete', elem_id=tabname + "_images_history_del_button") - - with gr.Column(): - with gr.Row(): - with gr.Column(): - img_file_info = gr.Textbox(label="Generate Info", interactive=False, lines=6) - gr.HTML("
") - img_file_name = gr.Textbox(value="", label="File Name", interactive=False) - img_file_time= gr.HTML() - with gr.Row(): - if tabname != faverate_tab_name: - save_btn = gr.Button('Collect') - pnginfo_send_to_txt2img = gr.Button('Send to txt2img') - pnginfo_send_to_img2img = gr.Button('Send to img2img') - - - # hiden items - with gr.Row(visible=False): - renew_page = gr.Button('Refresh page', elem_id=tabname + "_images_history_renew_page") - batch_date_to = gr.Textbox(label="Date to") - visible_img_num = gr.Number() - date_to_recorder = gr.State([]) - last_date_from = gr.Textbox() - tabname_box = gr.Textbox(tabname) - image_index = gr.Textbox(value=-1) - set_index = gr.Button('set_index', elem_id=tabname + "_images_history_set_index") - filenames = gr.State() - all_images_list = gr.State() - hidden = gr.Image(type="pil") - info1 = gr.Textbox() - info2 = gr.Textbox() - - img_path.submit(change_dir, inputs=[img_path, batch_date_to], outputs=[warning, main_panel, warning_box, batch_date_to, load_batch_box, load_info]) - - #change batch - change_date_output = [batch_date_to, load_info, filenames, page_index, history_gallery, img_file_name, img_file_time, visible_img_num, last_date_from, batch_panel] - - batch_date_to.change(archive_images, inputs=[img_path, batch_date_to], outputs=change_date_output) - batch_date_to.change(enable_page_buttons, inputs=None, outputs=[turn_page_buttons]) - batch_date_to.change(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") - - load_batch.click(loac_batch_click, inputs=[batch_date_to], outputs=[batch_date_to, date_to_recorder]) - forward.click(forward_click, inputs=[last_date_from, date_to_recorder], outputs=[batch_date_to, date_to_recorder]) - backward.click(backward_click, inputs=[last_date_from, date_to_recorder], outputs=[batch_date_to, date_to_recorder]) - - - #delete - delete.click(delete_image, inputs=[delete_num, img_file_name, filenames, image_index, visible_img_num], outputs=[filenames, delete_num, visible_img_num]) - delete.click(fn=None, _js="images_history_delete", inputs=[delete_num, tabname_box, image_index], outputs=None) - if tabname != faverate_tab_name: - save_btn.click(save_image, inputs=[img_file_name], outputs=None) - - #turn page - gallery_inputs = [page_index, filenames] - gallery_outputs = [page_index, history_gallery, img_file_name, img_file_time, visible_img_num] - first_page.click(first_page_click, inputs=gallery_inputs, outputs=gallery_outputs) - next_page.click(next_page_click, inputs=gallery_inputs, outputs=gallery_outputs) - prev_page.click(prev_page_click, inputs=gallery_inputs, outputs=gallery_outputs) - end_page.click(end_page_click, inputs=gallery_inputs, outputs=gallery_outputs) - page_index.submit(page_index_change, inputs=gallery_inputs, outputs=gallery_outputs) - renew_page.click(page_index_change, inputs=gallery_inputs, outputs=gallery_outputs) - - first_page.click(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") - next_page.click(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") - prev_page.click(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") - end_page.click(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") - page_index.submit(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") - renew_page.click(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") - - # other funcitons - set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[tabname_box, image_index, page_index, filenames], outputs=[img_file_name, img_file_time, image_index, hidden]) - img_file_name.change(fn=None, _js="images_history_enable_del_buttons", inputs=None, outputs=None) - hidden.change(fn=run_pnginfo, inputs=[hidden], outputs=[info1, img_file_info, info2]) - switch_dict["fn"](pnginfo_send_to_txt2img, switch_dict["t2i"], img_file_info, 'switch_to_txt2img') - switch_dict["fn"](pnginfo_send_to_img2img, switch_dict["i2i"], img_file_info, 'switch_to_img2img_img2img') - - - -def create_history_tabs(gr, sys_opts, cmp_ops, run_pnginfo, switch_dict): - global opts; - opts = sys_opts - loads_files_num = int(opts.images_history_num_per_page) - num_of_imgs_per_page = int(opts.images_history_num_per_page * opts.images_history_pages_num) - if cmp_ops.browse_all_images: - tabs_list.append(custom_tab_name) - with gr.Blocks(analytics_enabled=False) as images_history: - with gr.Tabs() as tabs: - for tab in tabs_list: - with gr.Tab(tab): - with gr.Blocks(analytics_enabled=False) : - show_images_history(gr, opts, tab, run_pnginfo, switch_dict) - gradio.Checkbox(opts.images_history_preload, elem_id="images_history_preload", visible=False) - gradio.Textbox(",".join(tabs_list), elem_id="images_history_tabnames_list", visible=False) - - return images_history diff --git a/modules/inspiration.py b/modules/inspiration.py deleted file mode 100644 index 29cf8297..00000000 --- a/modules/inspiration.py +++ /dev/null @@ -1,193 +0,0 @@ -import os -import random -import gradio -from modules.shared import opts -inspiration_system_path = os.path.join(opts.inspiration_dir, "system") -def read_name_list(file, types=None, keyword=None): - if not os.path.exists(file): - return [] - ret = [] - f = open(file, "r") - line = f.readline() - while len(line) > 0: - line = line.rstrip("\n") - if types is not None: - dirname = os.path.split(line) - if dirname[0] in types and keyword in dirname[1].lower(): - ret.append(line) - else: - ret.append(line) - line = f.readline() - return ret - -def save_name_list(file, name): - name_list = read_name_list(file) - if name not in name_list: - with open(file, "a") as f: - f.write(name + "\n") - -def get_types_list(): - files = os.listdir(opts.inspiration_dir) - types = [] - for x in files: - path = os.path.join(opts.inspiration_dir, x) - if x[0] == ".": - continue - if not os.path.isdir(path): - continue - if path == inspiration_system_path: - continue - types.append(x) - return types - -def get_inspiration_images(source, types, keyword): - keyword = keyword.strip(" ").lower() - get_num = int(opts.inspiration_rows_num * opts.inspiration_cols_num) - if source == "Favorites": - names = read_name_list(os.path.join(inspiration_system_path, "faverites.txt"), types, keyword) - names = random.sample(names, get_num) if len(names) > get_num else names - elif source == "Abandoned": - names = read_name_list(os.path.join(inspiration_system_path, "abandoned.txt"), types, keyword) - names = random.sample(names, get_num) if len(names) > get_num else names - elif source == "Exclude abandoned": - abandoned = read_name_list(os.path.join(inspiration_system_path, "abandoned.txt"), types, keyword) - all_names = [] - for tp in types: - name_list = os.listdir(os.path.join(opts.inspiration_dir, tp)) - all_names += [os.path.join(tp, x) for x in name_list if keyword in x.lower()] - - if len(all_names) > get_num: - names = [] - while len(names) < get_num: - name = random.choice(all_names) - if name not in abandoned: - names.append(name) - else: - names = all_names - else: - all_names = [] - for tp in types: - name_list = os.listdir(os.path.join(opts.inspiration_dir, tp)) - all_names += [os.path.join(tp, x) for x in name_list if keyword in x.lower()] - names = random.sample(all_names, get_num) if len(all_names) > get_num else all_names - image_list = [] - for a in names: - image_path = os.path.join(opts.inspiration_dir, a) - images = os.listdir(image_path) - if len(images) > 0: - image_list.append((os.path.join(image_path, random.choice(images)), a)) - else: - print(image_path) - return image_list, names - -def select_click(index, name_list): - name = name_list[int(index)] - path = os.path.join(opts.inspiration_dir, name) - images = os.listdir(path) - return name, [os.path.join(path, x) for x in images], "" - -def give_up_click(name): - file = os.path.join(inspiration_system_path, "abandoned.txt") - save_name_list(file, name) - return "Added to abandoned list" - -def collect_click(name): - file = os.path.join(inspiration_system_path, "faverites.txt") - save_name_list(file, name) - return "Added to faverite list" - -def moveout_click(name, source): - if source == "Abandoned": - file = os.path.join(inspiration_system_path, "abandoned.txt") - elif source == "Favorites": - file = os.path.join(inspiration_system_path, "faverites.txt") - else: - return None - name_list = read_name_list(file) - os.remove(file) - with open(file, "a") as f: - for a in name_list: - if a != name: - f.write(a + "\n") - return f"Moved out {name} from {source} list" - -def source_change(source): - if source in ["Abandoned", "Favorites"]: - return gradio.update(visible=True), [] - else: - return gradio.update(visible=False), [] -def add_to_prompt(name, prompt): - name = os.path.basename(name) - return prompt + "," + name - -def clear_keyword(): - return "" - -def ui(gr, opts, txt2img_prompt, img2img_prompt): - with gr.Blocks(analytics_enabled=False) as inspiration: - flag = os.path.exists(opts.inspiration_dir) - if flag: - types = get_types_list() - flag = len(types) > 0 - else: - os.makedirs(opts.inspiration_dir) - if not flag: - gr.HTML(""" -

To activate inspiration function, you need get "inspiration" images first.


- You can create these images by run "Create inspiration images" script in txt2img page,
you can get the artists or art styles list from here
- https://github.com/pharmapsychotic/clip-interrogator/tree/main/data
- download these files, and select these files in the "Create inspiration images" script UI
- There about 6000 artists and art styles in these files.
This takes server hours depending on your GPU type and how many pictures you generate for each artist/style -
I suggest at least four images for each


-

You can also download generated pictures from here:


- https://huggingface.co/datasets/yfszzx/inspiration
- unzip the file to the project directory of webui
- and restart webui, and enjoy the joy of creation!
- """) - return inspiration - if not os.path.exists(inspiration_system_path): - os.mkdir(inspiration_system_path) - with gr.Row(): - with gr.Column(scale=2): - inspiration_gallery = gr.Gallery(show_label=False, elem_id="inspiration_gallery").style(grid=opts.inspiration_cols_num, height='auto') - with gr.Column(scale=1): - types = gr.CheckboxGroup(choices=types, value=types) - with gr.Row(): - source = gr.Dropdown(choices=["All", "Favorites", "Exclude abandoned", "Abandoned"], value="Exclude abandoned", label="Source") - keyword = gr.Textbox("", label="Key word") - get_inspiration = gr.Button("Get inspiration", elem_id="inspiration_get_button") - name = gr.Textbox(show_label=False, interactive=False) - with gr.Row(): - send_to_txt2img = gr.Button('to txt2img') - send_to_img2img = gr.Button('to img2img') - collect = gr.Button('Collect') - give_up = gr.Button("Don't show again") - moveout = gr.Button("Move out", visible=False) - warning = gr.HTML() - style_gallery = gr.Gallery(show_label=False).style(grid=2, height='auto') - - - - with gr.Row(visible=False): - select_button = gr.Button('set button', elem_id="inspiration_select_button") - name_list = gr.State() - - get_inspiration.click(get_inspiration_images, inputs=[source, types, keyword], outputs=[inspiration_gallery, name_list]) - keyword.submit(fn=None, _js="inspiration_click_get_button", inputs=None, outputs=None) - source.change(source_change, inputs=[source], outputs=[moveout, style_gallery]) - source.change(fn=clear_keyword, _js="inspiration_click_get_button", inputs=None, outputs=[keyword]) - types.change(fn=clear_keyword, _js="inspiration_click_get_button", inputs=None, outputs=[keyword]) - - select_button.click(select_click, _js="inspiration_selected", inputs=[name, name_list], outputs=[name, style_gallery, warning]) - give_up.click(give_up_click, inputs=[name], outputs=[warning]) - collect.click(collect_click, inputs=[name], outputs=[warning]) - moveout.click(moveout_click, inputs=[name, source], outputs=[warning]) - moveout.click(fn=None, _js="inspiration_click_get_button", inputs=None, outputs=None) - - send_to_txt2img.click(add_to_prompt, inputs=[name, txt2img_prompt], outputs=[txt2img_prompt]) - send_to_img2img.click(add_to_prompt, inputs=[name, img2img_prompt], outputs=[img2img_prompt]) - send_to_txt2img.click(collect_click, inputs=[name], outputs=[warning]) - send_to_img2img.click(collect_click, inputs=[name], outputs=[warning]) - send_to_txt2img.click(None, _js='switch_to_txt2img', inputs=None, outputs=None) - send_to_img2img.click(None, _js="switch_to_img2img_img2img", inputs=None, outputs=None) - return inspiration diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index 5bcccd67..66666a56 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -1,4 +1,3 @@ - callbacks_model_loaded = [] callbacks_ui_tabs = [] callbacks_ui_settings = [] @@ -16,7 +15,6 @@ def model_loaded_callback(sd_model): def ui_tabs_callback(): res = [] - for callback in callbacks_ui_tabs: res += callback() or [] diff --git a/modules/shared.py b/modules/shared.py index 0aaaadac..5dfd7927 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -321,21 +321,6 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}), })) -options_templates.update(options_section(('inspiration', "Inspiration"), { - "inspiration_dir": OptionInfo("inspiration", "Directory of inspiration", component_args=hide_dirs), - "inspiration_max_samples": OptionInfo(4, "Maximum number of samples, used to determine which folders to skip when continue running the create script", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1}), - "inspiration_rows_num": OptionInfo(4, "Rows of inspiration interface frame", gr.Slider, {"minimum": 4, "maximum": 16, "step": 1}), - "inspiration_cols_num": OptionInfo(8, "Columns of inspiration interface frame", gr.Slider, {"minimum": 4, "maximum": 16, "step": 1}), -})) - -options_templates.update(options_section(('images-history', "Images Browser"), { - #"images_history_reconstruct_directory": OptionInfo(False, "Reconstruct output directory structure.This can greatly improve the speed of loading , but will change the original output directory structure"), - "images_history_preload": OptionInfo(False, "Preload images at startup"), - "images_history_num_per_page": OptionInfo(36, "Number of pictures displayed on each page"), - "images_history_pages_num": OptionInfo(6, "Minimum number of pages per load "), - "images_history_grid_num": OptionInfo(6, "Number of grids in each row"), - -})) class Options: data = None diff --git a/modules/ui.py b/modules/ui.py index a73175f5..fa42712e 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -49,14 +49,12 @@ from modules.sd_hijack import model_hijack from modules.sd_samplers import samplers, samplers_for_img2img import modules.textual_inversion.ui import modules.hypernetworks.ui -import modules.images_history as images_history -import modules.inspiration as inspiration - - # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() mimetypes.add_type('application/javascript', '.js') +txt2img_paste_fields = [] +img2img_paste_fields = [] if not cmd_opts.share and not cmd_opts.listen: @@ -1193,16 +1191,7 @@ def create_ui(wrap_gradio_gpu_call): inputs=[image], outputs=[html, generation_info, html2], ) - #images history - images_history_switch_dict = { - "fn": modules.generation_parameters_copypaste.connect_paste, - "t2i": txt2img_paste_fields, - "i2i": img2img_paste_fields - } - - browser_interface = images_history.create_history_tabs(gr, opts, cmd_opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) - inspiration_interface = inspiration.ui(gr, opts, txt2img_prompt, img2img_prompt) - + with gr.Blocks() as modelmerger_interface: with gr.Row().style(equal_height=False): with gr.Column(variant='panel'): @@ -1651,8 +1640,6 @@ Requested path was: {f} (img2img_interface, "img2img", "img2img"), (extras_interface, "Extras", "extras"), (pnginfo_interface, "PNG Info", "pnginfo"), - (inspiration_interface, "Inspiration", "inspiration"), - (browser_interface , "Image Browser", "images_history"), (modelmerger_interface, "Checkpoint Merger", "modelmerger"), (train_interface, "Train", "ti"), ] @@ -1896,6 +1883,7 @@ def load_javascript(raw_response): javascript = f'' scripts_list = modules.scripts.list_scripts("javascript", ".js") + scripts_list += modules.scripts.list_scripts("scripts", ".js") for basedir, filename, path in scripts_list: with open(path, "r", encoding="utf8") as jsfile: javascript += f"\n" -- cgit v1.2.3 From cef1b89aa2e6c7647db7e93a4cd4ec020da3f2da Mon Sep 17 00:00:00 2001 From: yfszzx Date: Mon, 24 Oct 2022 10:10:33 +0800 Subject: remove browser to extension --- modules/script_callbacks.py | 2 ++ modules/shared.py | 1 - modules/ui.py | 2 +- scripts/create_inspiration_images.py | 57 ------------------------------------ 4 files changed, 3 insertions(+), 59 deletions(-) delete mode 100644 scripts/create_inspiration_images.py (limited to 'modules/ui.py') diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index 66666a56..f46d3d9a 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -1,3 +1,4 @@ + callbacks_model_loaded = [] callbacks_ui_tabs = [] callbacks_ui_settings = [] @@ -15,6 +16,7 @@ def model_loaded_callback(sd_model): def ui_tabs_callback(): res = [] + for callback in callbacks_ui_tabs: res += callback() or [] diff --git a/modules/shared.py b/modules/shared.py index 5dfd7927..6541e679 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -82,7 +82,6 @@ parser.add_argument("--api", action='store_true', help="use api=True to launch t parser.add_argument("--nowebui", action='store_true', help="use api=True to launch the api instead of the webui") parser.add_argument("--ui-debug-mode", action='store_true', help="Don't load model to quickly launch UI") parser.add_argument("--device-id", type=str, help="Select the default CUDA device to use (export CUDA_VISIBLE_DEVICES=0,1,etc might be needed before)", default=None) -parser.add_argument("--browse-all-images", action='store_true', help="Allow browsing all images by Image Browser", default=False) cmd_opts = parser.parse_args() restricted_opts = [ diff --git a/modules/ui.py b/modules/ui.py index fa42712e..a32f7259 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1104,7 +1104,7 @@ def create_ui(wrap_gradio_gpu_call): upscaling_crop = gr.Checkbox(label='Crop to fit', value=True) with gr.Group(): - extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers] , value=shared.sd_upscalers[0].name, type="index") + extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") with gr.Group(): extras_upscaler_2 = gr.Radio(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") diff --git a/scripts/create_inspiration_images.py b/scripts/create_inspiration_images.py deleted file mode 100644 index 2fd30578..00000000 --- a/scripts/create_inspiration_images.py +++ /dev/null @@ -1,57 +0,0 @@ -import csv, os, shutil -import modules.scripts as scripts -from modules import processing, shared, sd_samplers, images -from modules.processing import Processed -from modules.shared import opts -import gradio -class Script(scripts.Script): - def title(self): - return "Create inspiration images" - - def show(self, is_img2img): - return True - - def ui(self, is_img2img): - file = gradio.Files(label="Artist or styles name list. '.txt' files with one name per line",) - with gradio.Row(): - prefix = gradio.Textbox("a painting in", label="Prompt words before artist or style name", file_count="multiple") - suffix= gradio.Textbox("style", label="Prompt words after artist or style name") - negative_prompt = gradio.Textbox("picture frame, portrait photo", label="Negative Prompt") - with gradio.Row(): - batch_size = gradio.Number(1, label="Batch size") - batch_count = gradio.Number(2, label="Batch count") - return [batch_size, batch_count, prefix, suffix, negative_prompt, file] - - def run(self, p, batch_size, batch_count, prefix, suffix, negative_prompt, files): - p.batch_size = int(batch_size) - p.n_iterint = int(batch_count) - p.negative_prompt = negative_prompt - p.do_not_save_samples = True - p.do_not_save_grid = True - for file in files: - tp = file.orig_name.split(".")[0] - print(tp) - path = os.path.join(opts.inspiration_dir, tp) - if not os.path.exists(path): - os.makedirs(path) - f = open(file.name, "r") - line = f.readline() - while len(line) > 0: - name = line.rstrip("\n").split(",")[0] - line = f.readline() - artist_path = os.path.join(path, name) - if not os.path.exists(artist_path): - os.mkdir(artist_path) - if len(os.listdir(artist_path)) >= opts.inspiration_max_samples: - continue - p.prompt = f"{prefix} {name} {suffix}" - print(p.prompt) - processed = processing.process_images(p) - for img in processed.images: - i = 0 - filename = os.path.join(artist_path, format(0, "03d") + ".jpg") - while os.path.exists(filename): - i += 1 - filename = os.path.join(artist_path, format(i, "03d") + ".jpg") - img.save(filename, quality=80) - return processed -- cgit v1.2.3 From a889c93f23f1e80d0dac4e5ddbc3a26207e8cdf1 Mon Sep 17 00:00:00 2001 From: yfszzx Date: Mon, 24 Oct 2022 11:13:16 +0800 Subject: paste_fields add to public --- modules/ui.py | 2 ++ 1 file changed, 2 insertions(+) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index a32f7259..a73b9ff0 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -784,6 +784,7 @@ def create_ui(wrap_gradio_gpu_call): ] ) + global txt2img_paste_fields txt2img_paste_fields = [ (txt2img_prompt, "Prompt"), (txt2img_negative_prompt, "Negative prompt"), @@ -1054,6 +1055,7 @@ def create_ui(wrap_gradio_gpu_call): outputs=[prompt, negative_prompt, style1, style2], ) + global img2img_paste_fields img2img_paste_fields = [ (img2img_prompt, "Prompt"), (img2img_negative_prompt, "Negative prompt"), -- cgit v1.2.3 From 876a96f0f9843382ebc8984db3de5d8af0e9ce4c Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Mon, 24 Oct 2022 09:39:46 +0300 Subject: remove erroneous dir in the extension directory remove loading .js files from scripts dir (they go into javascript) load scripts after models, for scripts that depend on loaded models --- extensions/stable-diffusion-webui-inspiration | 1 - modules/ui.py | 2 +- webui.py | 11 ++++++----- 3 files changed, 7 insertions(+), 7 deletions(-) delete mode 160000 extensions/stable-diffusion-webui-inspiration (limited to 'modules/ui.py') diff --git a/extensions/stable-diffusion-webui-inspiration b/extensions/stable-diffusion-webui-inspiration deleted file mode 160000 index a0b96664..00000000 --- a/extensions/stable-diffusion-webui-inspiration +++ /dev/null @@ -1 +0,0 @@ -Subproject commit a0b96664d2524b87916ae463fbb65411b13a569b diff --git a/modules/ui.py b/modules/ui.py index a73b9ff0..03528968 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1885,7 +1885,7 @@ def load_javascript(raw_response): javascript = f'' scripts_list = modules.scripts.list_scripts("javascript", ".js") - scripts_list += modules.scripts.list_scripts("scripts", ".js") + for basedir, filename, path in scripts_list: with open(path, "r", encoding="utf8") as jsfile: javascript += f"\n" diff --git a/webui.py b/webui.py index a0f3757f..ade7334b 100644 --- a/webui.py +++ b/webui.py @@ -9,7 +9,7 @@ from fastapi.middleware.gzip import GZipMiddleware from modules.paths import script_path -from modules import devices, sd_samplers +from modules import devices, sd_samplers, upscaler import modules.codeformer_model as codeformer import modules.extras import modules.face_restoration @@ -73,12 +73,11 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): def initialize(): - modules.scripts.load_scripts() if cmd_opts.ui_debug_mode: - class enmpty(): - name = None - shared.sd_upscalers = [enmpty()] + shared.sd_upscalers = upscaler.UpscalerLanczos().scalers + modules.scripts.load_scripts() return + modelloader.cleanup_models() modules.sd_models.setup_model() codeformer.setup_model(cmd_opts.codeformer_models_path) @@ -86,6 +85,8 @@ def initialize(): shared.face_restorers.append(modules.face_restoration.FaceRestoration()) modelloader.load_upscalers() + modules.scripts.load_scripts() + modules.sd_models.load_model() shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model))) shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork))) -- cgit v1.2.3 From 994aaadf0861366b9e6f219e1a3c25a233fbb63c Mon Sep 17 00:00:00 2001 From: yfszzx Date: Mon, 24 Oct 2022 16:44:36 +0800 Subject: a strange bug --- extensions/stable-diffusion-webui-inspiration | 2 +- modules/ui.py | 4 ++++ 2 files changed, 5 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/extensions/stable-diffusion-webui-inspiration b/extensions/stable-diffusion-webui-inspiration index a0b96664..c50c03ac 160000 --- a/extensions/stable-diffusion-webui-inspiration +++ b/extensions/stable-diffusion-webui-inspiration @@ -1 +1 @@ -Subproject commit a0b96664d2524b87916ae463fbb65411b13a569b +Subproject commit c50c03ac8fd2f6317d17d0c8c7c1ce26e6fe5cd7 diff --git a/modules/ui.py b/modules/ui.py index a73b9ff0..8c6dc026 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -55,6 +55,7 @@ mimetypes.init() mimetypes.add_type('application/javascript', '.js') txt2img_paste_fields = [] img2img_paste_fields = [] +init_img_components = {} if not cmd_opts.share and not cmd_opts.listen: @@ -1174,6 +1175,9 @@ def create_ui(wrap_gradio_gpu_call): outputs=[init_img_with_mask], ) + global init_img_components + init_img_components = {"img2img":init_img, "inpaint":init_img_with_mask, "extras":extras_image} + with gr.Blocks(analytics_enabled=False) as pnginfo_interface: with gr.Row().style(equal_height=False): with gr.Column(variant='panel'): -- cgit v1.2.3 From db8ed5fe5cd6e967d12d43d96b7f83083e58626c Mon Sep 17 00:00:00 2001 From: captin411 Date: Tue, 25 Oct 2022 15:22:29 -0700 Subject: Focal crop UI elements --- modules/textual_inversion/preprocess.py | 26 +++++++++++++------------- modules/ui.py | 20 ++++++++++++++++++-- 2 files changed, 31 insertions(+), 15 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index a8c17c6f..1e4d4de8 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -13,7 +13,7 @@ if cmd_opts.deepdanbooru: import modules.deepbooru as deepbooru -def preprocess(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_entropy_focus=False): +def preprocess(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False): try: if process_caption: shared.interrogator.load() @@ -23,7 +23,7 @@ def preprocess(process_src, process_dst, process_width, process_height, preproce db_opts[deepbooru.OPT_INCLUDE_RANKS] = False deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, db_opts) - preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru, split_threshold, overlap_ratio, process_entropy_focus) + preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru, split_threshold, overlap_ratio, process_focal_crop, process_focal_crop_face_weight, process_focal_crop_entropy_weight, process_focal_crop_edges_weight, process_focal_crop_debug) finally: @@ -35,7 +35,7 @@ def preprocess(process_src, process_dst, process_width, process_height, preproce -def preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_entropy_focus=False): +def preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False): width = process_width height = process_height src = os.path.abspath(process_src) @@ -139,27 +139,27 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre ratio = (img.height * width) / (img.width * height) inverse_xy = True - processing_option_ran = False + process_default_resize = True if process_split and ratio < 1.0 and ratio <= split_threshold: for splitted in split_pic(img, inverse_xy): save_pic(splitted, index, existing_caption=existing_caption) - processing_option_ran = True + process_default_resize = False if process_entropy_focus and img.height != img.width: autocrop_settings = autocrop.Settings( crop_width = width, crop_height = height, - face_points_weight = 0.9, - entropy_points_weight = 0.7, - corner_points_weight = 0.5, - annotate_image = False + face_points_weight = process_focal_crop_face_weight, + entropy_points_weight = process_focal_crop_entropy_weight, + corner_points_weight = process_focal_crop_edges_weight, + annotate_image = process_focal_crop_debug ) - focal = autocrop.crop_image(img, autocrop_settings) - save_pic(focal, index, existing_caption=existing_caption) - processing_option_ran = True + for focal in autocrop.crop_image(img, autocrop_settings): + save_pic(focal, index, existing_caption=existing_caption) + process_default_resize = False - if not processing_option_ran: + if process_default_resize: img = images.resize_image(1, img, width, height) save_pic(img, index, existing_caption=existing_caption) diff --git a/modules/ui.py b/modules/ui.py index 028eb4e5..95b9c703 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1260,7 +1260,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Row(): process_flip = gr.Checkbox(label='Create flipped copies') process_split = gr.Checkbox(label='Split oversized images') - process_entropy_focus = gr.Checkbox(label='Create auto focal point crop') + process_focal_crop = gr.Checkbox(label='Auto focal point crop') process_caption = gr.Checkbox(label='Use BLIP for caption') process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True if cmd_opts.deepdanbooru else False) @@ -1268,6 +1268,12 @@ def create_ui(wrap_gradio_gpu_call): process_split_threshold = gr.Slider(label='Split image threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05) process_overlap_ratio = gr.Slider(label='Split image overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05) + with gr.Row(visible=False) as process_focal_crop_row: + process_focal_crop_face_weight = gr.Slider(label='Focal point face weight', value=0.9, minimum=0.0, maximum=1.0, step=0.05) + process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.3, minimum=0.0, maximum=1.0, step=0.05) + process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05) + process_focal_crop_debug = gr.Checkbox(label='Create debug image') + with gr.Row(): with gr.Column(scale=3): gr.HTML(value="") @@ -1281,6 +1287,12 @@ def create_ui(wrap_gradio_gpu_call): outputs=[process_split_extra_row], ) + process_focal_crop.change( + fn=lambda show: gr_show(show), + inputs=[process_focal_crop], + outputs=[process_focal_crop_row], + ) + with gr.Tab(label="Train"): gr.HTML(value="

Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images [wiki]

") with gr.Row(): @@ -1368,7 +1380,11 @@ def create_ui(wrap_gradio_gpu_call): process_caption_deepbooru, process_split_threshold, process_overlap_ratio, - process_entropy_focus, + process_focal_crop, + process_focal_crop_face_weight, + process_focal_crop_entropy_weight, + process_focal_crop_edges_weight, + process_focal_crop_debug, ], outputs=[ ti_output, -- cgit v1.2.3 From df0c5ea29d7f0c682ac81f184f3e482a6450d018 Mon Sep 17 00:00:00 2001 From: captin411 Date: Tue, 25 Oct 2022 17:06:59 -0700 Subject: update default weights --- modules/textual_inversion/autocrop.py | 16 ++++++++-------- modules/ui.py | 2 +- 2 files changed, 9 insertions(+), 9 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py index 01a92b12..9859974a 100644 --- a/modules/textual_inversion/autocrop.py +++ b/modules/textual_inversion/autocrop.py @@ -71,9 +71,9 @@ def crop_image(im, settings): return results def focal_point(im, settings): - corner_points = image_corner_points(im, settings) - entropy_points = image_entropy_points(im, settings) - face_points = image_face_points(im, settings) + corner_points = image_corner_points(im, settings) if settings.corner_points_weight > 0 else [] + entropy_points = image_entropy_points(im, settings) if settings.entropy_points_weight > 0 else [] + face_points = image_face_points(im, settings) if settings.face_points_weight > 0 else [] pois = [] @@ -144,7 +144,7 @@ def image_face_points(im, settings): settings.dnn_model_path, "", (im.width, im.height), - 0.8, # score threshold + 0.9, # score threshold 0.3, # nms threshold 5000 # keep top k before nms ) @@ -159,7 +159,7 @@ def image_face_points(im, settings): results.append( PointOfInterest( int(x + (w * 0.5)), # face focus left/right is center - int(y + (h * 0)), # face focus up/down is close to the top of the head + int(y + (h * 0.33)), # face focus up/down is close to the top of the head size = w, weight = 1/len(faces[1]) ) @@ -207,7 +207,7 @@ def image_corner_points(im, settings): np_im, maxCorners=100, qualityLevel=0.04, - minDistance=min(grayscale.width, grayscale.height)*0.03, + minDistance=min(grayscale.width, grayscale.height)*0.06, useHarrisDetector=False, ) @@ -256,8 +256,8 @@ def image_entropy_points(im, settings): def image_entropy(im): # greyscale image entropy - band = np.asarray(im.convert("L")) - # band = np.asarray(im.convert("1"), dtype=np.uint8) + # band = np.asarray(im.convert("L")) + band = np.asarray(im.convert("1"), dtype=np.uint8) hist, _ = np.histogram(band, bins=range(0, 256)) hist = hist[hist > 0] return -np.log2(hist / hist.sum()).sum() diff --git a/modules/ui.py b/modules/ui.py index 95b9c703..095200a8 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1270,7 +1270,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Row(visible=False) as process_focal_crop_row: process_focal_crop_face_weight = gr.Slider(label='Focal point face weight', value=0.9, minimum=0.0, maximum=1.0, step=0.05) - process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.3, minimum=0.0, maximum=1.0, step=0.05) + process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05) process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05) process_focal_crop_debug = gr.Checkbox(label='Create debug image') -- cgit v1.2.3 From de096d0ce752c96e45508dcc7b9e84f7dbe10cca Mon Sep 17 00:00:00 2001 From: AngelBottomless <35677394+aria1th@users.noreply.github.com> Date: Tue, 25 Oct 2022 14:48:49 +0900 Subject: Weight initialization and More activation func add weight init add weight init option in create_hypernetwork fstringify hypernet info save weight initialization info for further debugging fill bias with zero for He/Xavier initialize LayerNorm with Normal fix loading weight_init --- modules/hypernetworks/hypernetwork.py | 47 ++++++++++++++++++++++++++++------- modules/hypernetworks/ui.py | 4 ++- modules/ui.py | 4 ++- 3 files changed, 44 insertions(+), 11 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index d647ea55..afbcdff8 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -5,6 +5,7 @@ import html import os import sys import traceback +import inspect import modules.textual_inversion.dataset import torch @@ -15,10 +16,12 @@ from modules import devices, processing, sd_models, shared from modules.textual_inversion import textual_inversion from modules.textual_inversion.learn_schedule import LearnRateScheduler from torch import einsum +from torch.nn.init import normal_, xavier_normal_, xavier_uniform_, kaiming_normal_, kaiming_uniform_, zeros_ from collections import defaultdict, deque from statistics import stdev, mean + class HypernetworkModule(torch.nn.Module): multiplier = 1.0 activation_dict = { @@ -26,9 +29,12 @@ class HypernetworkModule(torch.nn.Module): "leakyrelu": torch.nn.LeakyReLU, "elu": torch.nn.ELU, "swish": torch.nn.Hardswish, + "tanh": torch.nn.Tanh, + "sigmoid": torch.nn.Sigmoid, } + activation_dict.update({cls_name: cls_obj for cls_name, cls_obj in inspect.getmembers(torch.nn.modules.activation) if inspect.isclass(cls_obj) and cls_obj.__module__ == 'torch.nn.modules.activation'}) - def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, add_layer_norm=False, use_dropout=False): + def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, weight_init='Normal', add_layer_norm=False, use_dropout=False): super().__init__() assert layer_structure is not None, "layer_structure must not be None" @@ -65,9 +71,24 @@ class HypernetworkModule(torch.nn.Module): else: for layer in self.linear: if type(layer) == torch.nn.Linear or type(layer) == torch.nn.LayerNorm: - layer.weight.data.normal_(mean=0.0, std=0.01) - layer.bias.data.zero_() - + w, b = layer.weight.data, layer.bias.data + if weight_init == "Normal" or type(layer) == torch.nn.LayerNorm: + normal_(w, mean=0.0, std=0.01) + normal_(b, mean=0.0, std=0.005) + elif weight_init == 'XavierUniform': + xavier_uniform_(w) + zeros_(b) + elif weight_init == 'XavierNormal': + xavier_normal_(w) + zeros_(b) + elif weight_init == 'KaimingUniform': + kaiming_uniform_(w, nonlinearity='leaky_relu' if 'leakyrelu' == activation_func else 'relu') + zeros_(b) + elif weight_init == 'KaimingNormal': + kaiming_normal_(w, nonlinearity='leaky_relu' if 'leakyrelu' == activation_func else 'relu') + zeros_(b) + else: + raise KeyError(f"Key {weight_init} is not defined as initialization!") self.to(devices.device) def fix_old_state_dict(self, state_dict): @@ -105,7 +126,7 @@ class Hypernetwork: filename = None name = None - def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, add_layer_norm=False, use_dropout=False): + def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False): self.filename = None self.name = name self.layers = {} @@ -114,13 +135,14 @@ class Hypernetwork: self.sd_checkpoint_name = None self.layer_structure = layer_structure self.activation_func = activation_func + self.weight_init = weight_init self.add_layer_norm = add_layer_norm self.use_dropout = use_dropout for size in enable_sizes or []: self.layers[size] = ( - HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout), - HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout), + HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout), + HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout), ) def weights(self): @@ -144,6 +166,7 @@ class Hypernetwork: state_dict['layer_structure'] = self.layer_structure state_dict['activation_func'] = self.activation_func state_dict['is_layer_norm'] = self.add_layer_norm + state_dict['weight_initialization'] = self.weight_init state_dict['use_dropout'] = self.use_dropout state_dict['sd_checkpoint'] = self.sd_checkpoint state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name @@ -158,15 +181,21 @@ class Hypernetwork: state_dict = torch.load(filename, map_location='cpu') self.layer_structure = state_dict.get('layer_structure', [1, 2, 1]) + print(self.layer_structure) self.activation_func = state_dict.get('activation_func', None) + print(f"Activation function is {self.activation_func}") + self.weight_init = state_dict.get('weight_initialization', 'Normal') + print(f"Weight initialization is {self.weight_init}") self.add_layer_norm = state_dict.get('is_layer_norm', False) + print(f"Layer norm is set to {self.add_layer_norm}") self.use_dropout = state_dict.get('use_dropout', False) + print(f"Dropout usage is set to {self.use_dropout}" ) for size, sd in state_dict.items(): if type(size) == int: self.layers[size] = ( - HypernetworkModule(size, sd[0], self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout), - HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout), + HypernetworkModule(size, sd[0], self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout), + HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout), ) self.name = state_dict.get('name', self.name) diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py index 2b472d87..2c6c0470 100644 --- a/modules/hypernetworks/ui.py +++ b/modules/hypernetworks/ui.py @@ -8,8 +8,9 @@ import modules.textual_inversion.textual_inversion from modules import devices, sd_hijack, shared from modules.hypernetworks import hypernetwork +keys = list(hypernetwork.HypernetworkModule.activation_dict.keys()) -def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, add_layer_norm=False, use_dropout=False): +def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False): # Remove illegal characters from name. name = "".join( x for x in name if (x.isalnum() or x in "._- ")) @@ -25,6 +26,7 @@ def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, enable_sizes=[int(x) for x in enable_sizes], layer_structure=layer_structure, activation_func=activation_func, + weight_init=weight_init, add_layer_norm=add_layer_norm, use_dropout=use_dropout, ) diff --git a/modules/ui.py b/modules/ui.py index 03528968..8e343258 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1238,7 +1238,8 @@ def create_ui(wrap_gradio_gpu_call): new_hypernetwork_name = gr.Textbox(label="Name") new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'") - new_hypernetwork_activation_func = gr.Dropdown(value="relu", label="Select activation function of hypernetwork", choices=["linear", "relu", "leakyrelu", "elu", "swish"]) + new_hypernetwork_activation_func = gr.Dropdown(value="relu", label="Select activation function of hypernetwork", choices=modules.hypernetworks.ui.keys) + new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. relu-like - Kaiming, sigmoid-like - Xavier is recommended", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"]) new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization") new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout") overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork") @@ -1342,6 +1343,7 @@ def create_ui(wrap_gradio_gpu_call): overwrite_old_hypernetwork, new_hypernetwork_layer_structure, new_hypernetwork_activation_func, + new_hypernetwork_initialization_option, new_hypernetwork_add_layer_norm, new_hypernetwork_use_dropout ], -- cgit v1.2.3 From 4a4647e0dfc812783db7fa993d486b031f098ef8 Mon Sep 17 00:00:00 2001 From: yfszzx Date: Thu, 27 Oct 2022 13:36:11 +0800 Subject: create send to buttons in one module --- javascript/ui.js | 24 +- modules/generation_parameters_copypaste.py | 86 +++++++- modules/shared.py | 1 + modules/ui.py | 344 +++++++++-------------------- webui-user.bat | 2 +- 5 files changed, 187 insertions(+), 270 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index cfd0dcd3..7e116465 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -45,14 +45,14 @@ function switch_to_txt2img(){ return args_to_array(arguments); } -function switch_to_img2img_img2img(){ +function switch_to_img2img(){ gradioApp().querySelector('#tabs').querySelectorAll('button')[1].click(); gradioApp().getElementById('mode_img2img').querySelectorAll('button')[0].click(); return args_to_array(arguments); } -function switch_to_img2img_inpaint(){ +function switch_to_inpaint(){ gradioApp().querySelector('#tabs').querySelectorAll('button')[1].click(); gradioApp().getElementById('mode_img2img').querySelectorAll('button')[1].click(); @@ -65,26 +65,6 @@ function switch_to_extras(){ return args_to_array(arguments); } -function extract_image_from_gallery_txt2img(gallery){ - switch_to_txt2img() - return extract_image_from_gallery(gallery); -} - -function extract_image_from_gallery_img2img(gallery){ - switch_to_img2img_img2img() - return extract_image_from_gallery(gallery); -} - -function extract_image_from_gallery_inpaint(gallery){ - switch_to_img2img_inpaint() - return extract_image_from_gallery(gallery); -} - -function extract_image_from_gallery_extras(gallery){ - switch_to_extras() - return extract_image_from_gallery(gallery); -} - function get_tab_index(tabId){ var res = 0 diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index f73647da..2b80737a 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -3,13 +3,16 @@ import re import gradio as gr from modules.shared import script_path from modules import shared +import tempfile +from PIL import Image, PngImagePlugin re_param_code = r'\s*([\w ]+):\s*("(?:\\|\"|[^\"])+"|[^,]*)(?:,|$)' re_param = re.compile(re_param_code) re_params = re.compile(r"^(?:" + re_param_code + "){3,}$") re_imagesize = re.compile(r"^(\d+)x(\d+)$") type_of_gr_update = type(gr.update()) - +paste_fields = {} +bind_list = [] def quote(text): if ',' not in str(text): @@ -20,6 +23,81 @@ def quote(text): text = text.replace('"', '\\"') return f'"{text}"' +def image_from_url_text(filedata): + if type(filedata) == dict and filedata["is_file"]: + filename = filedata["name"] + tempdir = os.path.normpath(tempfile.gettempdir()) + normfn = os.path.normpath(filename) + assert normfn.startswith(tempdir), 'trying to open image file not in temporary directory' + + return Image.open(filename) + + if type(filedata) == list: + if len(filedata) == 0: + return None + + filedata = filedata[0] + + if filedata.startswith("data:image/png;base64,"): + filedata = filedata[len("data:image/png;base64,"):] + + filedata = base64.decodebytes(filedata.encode('utf-8')) + image = Image.open(io.BytesIO(filedata)) + return image + +def add_paste_fields(tabname, init_img, fields): + paste_fields[tabname] = {"init_img":init_img, "fields": fields} + +def create_buttons(tabs_list): + buttons = {} + for tab in tabs_list: + buttons[tab] = gr.Button(f"Send to {tab}") + return buttons + +#if send_generate_info is a tab name, mean generate_info comes from the params fields of the tab +def bind_buttons(buttons, send_image, send_generate_info): + bind_list.append([buttons, send_image, send_generate_info]) + +def run_bind(): + for buttons, send_image, send_generate_info in bind_list: + for tab in buttons: + button = buttons[tab] + if send_image and paste_fields[tab]["init_img"]: + if type(send_image) == gr.Gallery: + button.click( + fn=lambda x: image_from_url_text(x), + _js="extract_image_from_gallery", + inputs=[send_image], + outputs=[paste_fields[tab]["init_img"]], + ) + else: + button.click( + fn=lambda x:x, + inputs=[send_image], + outputs=[paste_fields[tab]["init_img"]], + ) + + if send_generate_info and paste_fields[tab]["fields"] is not None: + paste_field_names = ['Prompt', 'Negative prompt', 'Steps', 'Face restoration', 'Size-1', 'Size-2'] + if shared.opts.send_seed: + paste_field_names += ["Seed"] + if send_generate_info in paste_fields: + button.click( + fn=lambda *x:x, + inputs=[field for field,name in paste_fields[send_generate_info]["fields"] if name in paste_field_names], + outputs=[field for field,name in paste_fields[tab]["fields"] if name in paste_field_names], + ) + + else: + connect_paste(button, [(field, name) for field, name in paste_fields[tab]["fields"] if name in paste_field_names], send_generate_info) + + button.click( + fn=None, + _js=f"switch_to_{tab}", + inputs=None, + outputs=None, + ) + def parse_generation_parameters(x: str): """parses generation parameters string, the one you see in text field under the picture in UI: ``` @@ -67,8 +145,7 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model return res - -def connect_paste(button, paste_fields, input_comp, js=None): +def connect_paste(button, paste_fields, input_comp): def paste_func(prompt): if not prompt and not shared.cmd_opts.hide_ui_dir_config: filename = os.path.join(script_path, "params.txt") @@ -106,7 +183,8 @@ def connect_paste(button, paste_fields, input_comp, js=None): button.click( fn=paste_func, - _js=js, inputs=[input_comp], outputs=[x[0] for x in paste_fields], ) + + diff --git a/modules/shared.py b/modules/shared.py index f8b13b06..3ade2afa 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -279,6 +279,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "filter_nsfw": OptionInfo(False, "Filter NSFW content"), 'CLIP_stop_at_last_layers': OptionInfo(1, "Stop At last layers of CLIP model", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}), "random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}), + "send_seed": OptionInfo(False, "Send seed when sending prompt or image to other interface"), })) options_templates.update(options_section(('interrogate', "Interrogate Options"), { diff --git a/modules/ui.py b/modules/ui.py index 3e5b84d2..ccba14b6 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -35,7 +35,7 @@ if cmd_opts.deepdanbooru: from modules.deepbooru import get_deepbooru_tags import modules.codeformer_model -import modules.generation_parameters_copypaste +import modules.generation_parameters_copypaste as parameters_copypaste import modules.gfpgan_model import modules.hypernetworks.ui import modules.ldsr_model @@ -49,14 +49,11 @@ from modules.sd_hijack import model_hijack from modules.sd_samplers import samplers, samplers_for_img2img import modules.textual_inversion.ui import modules.hypernetworks.ui +from modules.generation_parameters_copypaste import image_from_url_text # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() mimetypes.add_type('application/javascript', '.js') -txt2img_paste_fields = [] -img2img_paste_fields = [] -init_img_components = {} - if not cmd_opts.share and not cmd_opts.listen: # fix gradio phoning home @@ -99,37 +96,11 @@ def plaintext_to_html(text): text = "

" + "
\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "

" return text - -def image_from_url_text(filedata): - if type(filedata) == dict and filedata["is_file"]: - filename = filedata["name"] - tempdir = os.path.normpath(tempfile.gettempdir()) - normfn = os.path.normpath(filename) - assert normfn.startswith(tempdir), 'trying to open image file not in temporary directory' - - return Image.open(filename) - - if type(filedata) == list: - if len(filedata) == 0: - return None - - filedata = filedata[0] - - if filedata.startswith("data:image/png;base64,"): - filedata = filedata[len("data:image/png;base64,"):] - - filedata = base64.decodebytes(filedata.encode('utf-8')) - image = Image.open(io.BytesIO(filedata)) - return image - - def send_gradio_gallery_to_image(x): if len(x) == 0: return None - return image_from_url_text(x[0]) - def save_files(js_data, images, do_make_zip, index): import csv filenames = [] @@ -193,7 +164,6 @@ def save_files(js_data, images, do_make_zip, index): return gr.File.update(value=fullfns, visible=True), '', '', plaintext_to_html(f"Saved: {filenames[0]}") - def save_pil_to_file(pil_image, dir=None): use_metadata = False metadata = PngImagePlugin.PngInfo() @@ -626,6 +596,83 @@ def create_refresh_button(refresh_component, refresh_method, refreshed_args, ele ) return refresh_button +def create_output_panel(tabname, outdir): + def open_folder(f): + if not os.path.exists(f): + print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.') + return + elif not os.path.isdir(f): + print(f""" +WARNING +An open_folder request was made with an argument that is not a folder. +This could be an error or a malicious attempt to run code on your computer. +Requested path was: {f} +""", file=sys.stderr) + return + + if not shared.cmd_opts.hide_ui_dir_config: + path = os.path.normpath(f) + if platform.system() == "Windows": + os.startfile(path) + elif platform.system() == "Darwin": + sp.Popen(["open", path]) + else: + sp.Popen(["xdg-open", path]) + + with gr.Column(variant='panel'): + with gr.Group(): + result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(grid=4) + + generation_info = None + with gr.Column(): + with gr.Row(): + if tabname != "extras": + save = gr.Button('Save') + + buttons = parameters_copypaste.create_buttons(["img2img", "inpaint", "extras"]) + button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder' + open_folder = gr.Button(folder_symbol, elem_id=button_id) + + open_folder.click( + fn=lambda: open_folder(opts.outdir_samples or outdir), + inputs=[], + outputs=[], + ) + + if tabname != "extras": + with gr.Row(): + do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False) + + with gr.Row(): + download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False) + + with gr.Group(): + html_info = gr.HTML() + generation_info = gr.Textbox(visible=False) + + save.click( + fn=wrap_gradio_call(save_files), + _js="(x, y, z, w) => [x, y, z, selected_gallery_index()]", + inputs=[ + generation_info, + result_gallery, + do_make_zip, + html_info, + ], + outputs=[ + download_files, + html_info, + html_info, + html_info, + ] + ) + else: + html_info_x = gr.HTML() + html_info = gr.HTML() + parameters_copypaste.bind_buttons(buttons, result_gallery, "txt2img" if tabname == "txt2img" else None) + return result_gallery, generation_info if tabname != "extras" else html_info_x, html_info + + def create_ui(wrap_gradio_gpu_call): import modules.img2img @@ -676,31 +723,10 @@ def create_ui(wrap_gradio_gpu_call): with gr.Group(): custom_inputs = modules.scripts.scripts_txt2img.setup_ui(is_img2img=False) - with gr.Column(variant='panel'): - - with gr.Group(): - txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False) - txt2img_gallery = gr.Gallery(label='Output', show_label=False, elem_id='txt2img_gallery').style(grid=4) - - with gr.Column(): - with gr.Row(): - save = gr.Button('Save') - send_to_img2img = gr.Button('Send to img2img') - send_to_inpaint = gr.Button('Send to inpaint') - send_to_extras = gr.Button('Send to extras') - button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder' - open_txt2img_folder = gr.Button(folder_symbol, elem_id=button_id) - - with gr.Row(): - do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False) - - with gr.Row(): - download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False) - - with gr.Group(): - html_info = gr.HTML() - generation_info = gr.Textbox(visible=False) + + txt2img_gallery, generation_info, html_info = create_output_panel("txt2img", opts.outdir_txt2img_samples) + connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) @@ -755,24 +781,7 @@ def create_ui(wrap_gradio_gpu_call): fn=lambda x: gr_show(x), inputs=[enable_hr], outputs=[hr_options], - ) - - save.click( - fn=wrap_gradio_call(save_files), - _js="(x, y, z, w) => [x, y, z, selected_gallery_index()]", - inputs=[ - generation_info, - txt2img_gallery, - do_make_zip, - html_info, - ], - outputs=[ - download_files, - html_info, - html_info, - html_info, - ] - ) + ) roll.click( fn=roll_artist, @@ -785,8 +794,7 @@ def create_ui(wrap_gradio_gpu_call): ] ) - global txt2img_paste_fields - txt2img_paste_fields = [ + parameters_copypaste.add_paste_fields("txt2img", None, [ (txt2img_prompt, "Prompt"), (txt2img_negative_prompt, "Negative prompt"), (steps, "Steps"), @@ -807,7 +815,7 @@ def create_ui(wrap_gradio_gpu_call): (firstphase_width, "First pass size-1"), (firstphase_height, "First pass size-2"), *modules.scripts.scripts_txt2img.infotext_fields - ] + ]) txt2img_preview_params = [ txt2img_prompt, @@ -894,30 +902,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Group(): custom_inputs = modules.scripts.scripts_img2img.setup_ui(is_img2img=True) - with gr.Column(variant='panel'): - - with gr.Group(): - img2img_preview = gr.Image(elem_id='img2img_preview', visible=False) - img2img_gallery = gr.Gallery(label='Output', show_label=False, elem_id='img2img_gallery').style(grid=4) - - with gr.Column(): - with gr.Row(): - save = gr.Button('Save') - img2img_send_to_img2img = gr.Button('Send to img2img') - img2img_send_to_inpaint = gr.Button('Send to inpaint') - img2img_send_to_extras = gr.Button('Send to extras') - button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder' - open_img2img_folder = gr.Button(folder_symbol, elem_id=button_id) - - with gr.Row(): - do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False) - - with gr.Row(): - download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False) - - with gr.Group(): - html_info = gr.HTML() - generation_info = gr.Textbox(visible=False) + img2img_gallery, generation_info, html_info = create_output_panel("img2img", opts.outdir_img2img_samples) connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) @@ -1004,24 +989,8 @@ def create_ui(wrap_gradio_gpu_call): fn=interrogate_deepbooru, inputs=[init_img], outputs=[img2img_prompt], - ) - - save.click( - fn=wrap_gradio_call(save_files), - _js="(x, y, z, w) => [x, y, z, selected_gallery_index()]", - inputs=[ - generation_info, - img2img_gallery, - do_make_zip, - html_info, - ], - outputs=[ - download_files, - html_info, - html_info, - html_info, - ] ) + roll.click( fn=roll_artist, @@ -1056,7 +1025,8 @@ def create_ui(wrap_gradio_gpu_call): outputs=[prompt, negative_prompt, style1, style2], ) - global img2img_paste_fields + token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter]) + img2img_paste_fields = [ (img2img_prompt, "Prompt"), (img2img_negative_prompt, "Negative prompt"), @@ -1075,7 +1045,9 @@ def create_ui(wrap_gradio_gpu_call): (denoising_strength, "Denoising strength"), *modules.scripts.scripts_img2img.infotext_fields ] - token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter]) + parameters_copypaste.add_paste_fields("img2img", init_img, img2img_paste_fields) + parameters_copypaste.add_paste_fields("inpaint", init_img_with_mask, img2img_paste_fields) + with gr.Blocks(analytics_enabled=False) as extras_interface: with gr.Row().style(equal_height=False): @@ -1122,15 +1094,8 @@ def create_ui(wrap_gradio_gpu_call): submit = gr.Button('Generate', elem_id="extras_generate", variant='primary') - with gr.Column(variant='panel'): - result_images = gr.Gallery(label="Result", show_label=False) - html_info_x = gr.HTML() - html_info = gr.HTML() - extras_send_to_img2img = gr.Button('Send to img2img') - extras_send_to_inpaint = gr.Button('Send to inpaint') - button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else '' - open_extras_folder = gr.Button('Open output directory', elem_id=button_id) + result_images, html_info_x, html_info = create_output_panel("extras", opts.outdir_extras_samples) submit.click( fn=wrap_gradio_gpu_call(modules.extras.run_extras), @@ -1160,23 +1125,8 @@ def create_ui(wrap_gradio_gpu_call): html_info, ] ) + parameters_copypaste.add_paste_fields("extras", extras_image, None) - extras_send_to_img2img.click( - fn=lambda x: image_from_url_text(x), - _js="extract_image_from_gallery_img2img", - inputs=[result_images], - outputs=[init_img], - ) - - extras_send_to_inpaint.click( - fn=lambda x: image_from_url_text(x), - _js="extract_image_from_gallery_inpaint", - inputs=[result_images], - outputs=[init_img_with_mask], - ) - - global init_img_components - init_img_components = {"img2img":init_img, "inpaint":init_img_with_mask, "extras":extras_image} with gr.Blocks(analytics_enabled=False) as pnginfo_interface: with gr.Row().style(equal_height=False): @@ -1187,11 +1137,10 @@ def create_ui(wrap_gradio_gpu_call): html = gr.HTML() generation_info = gr.Textbox(visible=False) html2 = gr.HTML() - with gr.Row(): - pnginfo_send_to_txt2img = gr.Button('Send to txt2img') - pnginfo_send_to_img2img = gr.Button('Send to img2img') - + buttons = parameters_copypaste.create_buttons(["txt2img", "img2img", "inpaint", "extras"]) + parameters_copypaste.bind_buttons(buttons, image, generation_info) + image.change( fn=wrap_gradio_call(modules.extras.run_pnginfo), inputs=[image], @@ -1475,28 +1424,6 @@ def create_ui(wrap_gradio_gpu_call): script_callbacks.ui_settings_callback() opts.reorder() - def open_folder(f): - if not os.path.exists(f): - print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.') - return - elif not os.path.isdir(f): - print(f""" -WARNING -An open_folder request was made with an argument that is not a folder. -This could be an error or a malicious attempt to run code on your computer. -Requested path was: {f} -""", file=sys.stderr) - return - - if not shared.cmd_opts.hide_ui_dir_config: - path = os.path.normpath(f) - if platform.system() == "Windows": - os.startfile(path) - elif platform.system() == "Darwin": - sp.Popen(["open", path]) - else: - sp.Popen(["xdg-open", path]) - def run_settings(*args): changed = 0 @@ -1641,6 +1568,8 @@ Requested path was: {f} if column is not None: column.__exit__() + parameters_copypaste.run_bind() + interfaces = [ (txt2img_interface, "txt2img", "txt2img"), (img2img_interface, "img2img", "img2img"), @@ -1731,85 +1660,14 @@ Requested path was: {f} component_dict['sd_model_checkpoint'], ] ) - paste_field_names = ['Prompt', 'Negative prompt', 'Steps', 'Face restoration', 'Seed', 'Size-1', 'Size-2'] - txt2img_fields = [field for field,name in txt2img_paste_fields if name in paste_field_names] - img2img_fields = [field for field,name in img2img_paste_fields if name in paste_field_names] - send_to_img2img.click( - fn=lambda img, *args: (image_from_url_text(img),*args), - _js="(gallery, ...args) => [extract_image_from_gallery_img2img(gallery), ...args]", - inputs=[txt2img_gallery] + txt2img_fields, - outputs=[init_img] + img2img_fields, - ) - - send_to_inpaint.click( - fn=lambda x, *args: (image_from_url_text(x), *args), - _js="(gallery, ...args) => [extract_image_from_gallery_inpaint(gallery), ...args]", - inputs=[txt2img_gallery] + txt2img_fields, - outputs=[init_img_with_mask] + img2img_fields, - ) - - img2img_send_to_img2img.click( - fn=lambda x: image_from_url_text(x), - _js="extract_image_from_gallery_img2img", - inputs=[img2img_gallery], - outputs=[init_img], - ) - - img2img_send_to_inpaint.click( - fn=lambda x: image_from_url_text(x), - _js="extract_image_from_gallery_inpaint", - inputs=[img2img_gallery], - outputs=[init_img_with_mask], - ) - - send_to_extras.click( - fn=lambda x: image_from_url_text(x), - _js="extract_image_from_gallery_extras", - inputs=[txt2img_gallery], - outputs=[extras_image], - ) - - open_txt2img_folder.click( - fn=lambda: open_folder(opts.outdir_samples or opts.outdir_txt2img_samples), - inputs=[], - outputs=[], - ) - - open_img2img_folder.click( - fn=lambda: open_folder(opts.outdir_samples or opts.outdir_img2img_samples), - inputs=[], - outputs=[], - ) - - open_extras_folder.click( - fn=lambda: open_folder(opts.outdir_samples or opts.outdir_extras_samples), - inputs=[], - outputs=[], - ) - - img2img_send_to_extras.click( - fn=lambda x: image_from_url_text(x), - _js="extract_image_from_gallery_extras", - inputs=[img2img_gallery], - outputs=[extras_image], - ) + settings_map = { 'sd_hypernetwork': 'Hypernet', 'CLIP_stop_at_last_layers': 'Clip skip', 'sd_model_checkpoint': 'Model hash', } - - settings_paste_fields = [ - (component_dict[k], lambda d, k=k, v=v: apply_setting(k, d.get(v, None))) - for k, v in settings_map.items() - ] - - modules.generation_parameters_copypaste.connect_paste(txt2img_paste, txt2img_paste_fields + settings_paste_fields, txt2img_prompt) - modules.generation_parameters_copypaste.connect_paste(img2img_paste, img2img_paste_fields + settings_paste_fields, img2img_prompt) - - modules.generation_parameters_copypaste.connect_paste(pnginfo_send_to_txt2img, txt2img_paste_fields + settings_paste_fields, generation_info, 'switch_to_txt2img') - modules.generation_parameters_copypaste.connect_paste(pnginfo_send_to_img2img, img2img_paste_fields + settings_paste_fields, generation_info, 'switch_to_img2img_img2img') + ui_config_file = cmd_opts.ui_config_file ui_settings = {} diff --git a/webui-user.bat b/webui-user.bat index e5a257be..fcd0f1fb 100644 --- a/webui-user.bat +++ b/webui-user.bat @@ -3,6 +3,6 @@ set PYTHON= set GIT= set VENV_DIR= -set COMMANDLINE_ARGS= +set COMMANDLINE_ARGS=--ui-debug-mode call webui.bat -- cgit v1.2.3 From 85fcccc105aa50f1d78de559233eaa9f384608b5 Mon Sep 17 00:00:00 2001 From: AngelBottomless <35677394+aria1th@users.noreply.github.com> Date: Wed, 26 Oct 2022 22:24:33 +0900 Subject: Squashed commit of fixing dropout silently fix dropouts for future hypernetworks add kwargs for Hypernetwork class hypernet UI for gradio input add recommended options remove as options revert adding options in ui --- modules/hypernetworks/hypernetwork.py | 25 +++++++++++++++++-------- modules/ui.py | 4 ++-- 2 files changed, 19 insertions(+), 10 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 2997cead..dd921153 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -34,7 +34,8 @@ class HypernetworkModule(torch.nn.Module): } activation_dict.update({cls_name.lower(): cls_obj for cls_name, cls_obj in inspect.getmembers(torch.nn.modules.activation) if inspect.isclass(cls_obj) and cls_obj.__module__ == 'torch.nn.modules.activation'}) - def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, weight_init='Normal', add_layer_norm=False, use_dropout=False, activate_output=False): + def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, weight_init='Normal', + add_layer_norm=False, use_dropout=False, activate_output=False, **kwargs): super().__init__() assert layer_structure is not None, "layer_structure must not be None" @@ -60,7 +61,7 @@ class HypernetworkModule(torch.nn.Module): linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1]))) # Add dropout except last layer - if use_dropout and i < len(layer_structure) - 3: + if 'last_layer_dropout' in kwargs and kwargs['last_layer_dropout'] and use_dropout and i < len(layer_structure) - 2: linears.append(torch.nn.Dropout(p=0.3)) self.linear = torch.nn.Sequential(*linears) @@ -126,7 +127,7 @@ class Hypernetwork: filename = None name = None - def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, activate_output=False): + def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, activate_output=False, **kwargs): self.filename = None self.name = name self.layers = {} @@ -139,11 +140,14 @@ class Hypernetwork: self.add_layer_norm = add_layer_norm self.use_dropout = use_dropout self.activate_output = activate_output + self.last_layer_dropout = kwargs['last_layer_dropout'] if 'last_layer_dropout' in kwargs else True for size in enable_sizes or []: self.layers[size] = ( - HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout, self.activate_output), - HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout, self.activate_output), + HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init, + self.add_layer_norm, self.use_dropout, self.activate_output, last_layer_dropout=self.last_layer_dropout), + HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init, + self.add_layer_norm, self.use_dropout, self.activate_output, last_layer_dropout=self.last_layer_dropout), ) def weights(self): @@ -172,7 +176,8 @@ class Hypernetwork: state_dict['sd_checkpoint'] = self.sd_checkpoint state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name state_dict['activate_output'] = self.activate_output - + state_dict['last_layer_dropout'] = self.last_layer_dropout + torch.save(state_dict, filename) def load(self, filename): @@ -193,12 +198,16 @@ class Hypernetwork: self.use_dropout = state_dict.get('use_dropout', False) print(f"Dropout usage is set to {self.use_dropout}" ) self.activate_output = state_dict.get('activate_output', True) + print(f"Activate last layer is set to {self.activate_output}") + self.last_layer_dropout = state_dict.get('last_layer_dropout', False) for size, sd in state_dict.items(): if type(size) == int: self.layers[size] = ( - HypernetworkModule(size, sd[0], self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout, self.activate_output), - HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout, self.activate_output), + HypernetworkModule(size, sd[0], self.layer_structure, self.activation_func, self.weight_init, + self.add_layer_norm, self.use_dropout, self.activate_output, last_layer_dropout=self.last_layer_dropout), + HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.weight_init, + self.add_layer_norm, self.use_dropout, self.activate_output, last_layer_dropout=self.last_layer_dropout), ) self.name = state_dict.get('name', self.name) diff --git a/modules/ui.py b/modules/ui.py index 0a63e357..55cbe859 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1238,8 +1238,8 @@ def create_ui(wrap_gradio_gpu_call): new_hypernetwork_name = gr.Textbox(label="Name") new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'") - new_hypernetwork_activation_func = gr.Dropdown(value="relu", label="Select activation function of hypernetwork", choices=modules.hypernetworks.ui.keys) - new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. relu-like - Kaiming, sigmoid-like - Xavier is recommended", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"]) + new_hypernetwork_activation_func = gr.Dropdown(value="relu", label="Select activation function of hypernetwork. Recommended : Swish / Linear(none)", choices=modules.hypernetworks.ui.keys) + new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. Normal is default, for experiments, relu-like - Kaiming, sigmoid-like - Xavier is recommended", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"]) new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization") new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout") overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork") -- cgit v1.2.3 From e0cbf53f451f45ea73dafab654eb6596cbd67ec2 Mon Sep 17 00:00:00 2001 From: yfszzx Date: Thu, 27 Oct 2022 18:00:51 +0800 Subject: create send to buttons by extensions --- modules/ui.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index ccba14b6..922a2163 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1568,7 +1568,8 @@ def create_ui(wrap_gradio_gpu_call): if column is not None: column.__exit__() - parameters_copypaste.run_bind() + + interfaces = [ (txt2img_interface, "txt2img", "txt2img"), @@ -1581,7 +1582,7 @@ def create_ui(wrap_gradio_gpu_call): interfaces += script_callbacks.ui_tabs_callback() - interfaces += [(settings_interface, "Settings", "settings")] + interfaces += [(settings_interface, "Settings", "settings")] css = "" @@ -1667,7 +1668,8 @@ def create_ui(wrap_gradio_gpu_call): 'CLIP_stop_at_last_layers': 'Clip skip', 'sd_model_checkpoint': 'Model hash', } - + + parameters_copypaste.run_bind() ui_config_file = cmd_opts.ui_config_file ui_settings = {} -- cgit v1.2.3 From 0995e879cea8ce871489ea8e393bb0eba6edc09c Mon Sep 17 00:00:00 2001 From: Florian Horn Date: Thu, 27 Oct 2022 16:20:01 +0200 Subject: added save button and shortcut (s) to Modal View --- javascript/imageviewer.js | 29 +++++++++++++++++++++++++++++ modules/ui.py | 8 +++++--- style.css | 18 ++++++++++++++++-- 3 files changed, 50 insertions(+), 5 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/imageviewer.js b/javascript/imageviewer.js index 9e380c65..3aa3b29e 100644 --- a/javascript/imageviewer.js +++ b/javascript/imageviewer.js @@ -81,6 +81,25 @@ function modalImageSwitch(offset) { } } +function saveImage(){ + const tabTxt2Img = gradioApp().getElementById("tab_txt2img") + const tabImg2Img = gradioApp().getElementById("tab_img2img") + const saveTxt2Img = "save_txt2img" + const saveImg2Img = "save_img2img" + if (tabTxt2Img.style["display"] != "none") { + gradioApp().getElementById(saveTxt2Img).click() + } else if (tabImg2Img.style["display"] != "none") { + gradioApp().getElementById(saveImg2Img).click() + } else { + console.error("missing implementation for saving modal of this type") + } +} + +function modalSaveImage(event) { + saveImage() + event.stopPropagation() +} + function modalNextImage(event) { modalImageSwitch(1) event.stopPropagation() @@ -93,6 +112,9 @@ function modalPrevImage(event) { function modalKeyHandler(event) { switch (event.key) { + case "s": + saveImage() + break; case "ArrowLeft": modalPrevImage(event) break; @@ -198,6 +220,13 @@ document.addEventListener("DOMContentLoaded", function() { modalTileImage.title = "Preview tiling"; modalControls.appendChild(modalTileImage) + const modalSave = document.createElement("span") + modalSave.className = "modalSave cursor" + modalSave.innerHTML = "🖫" + modalSave.addEventListener("click", modalSaveImage, true) + modalSave.title = "Save Image(s)" + modalControls.appendChild(modalSave) + const modalClose = document.createElement('span') modalClose.className = 'modalClose cursor'; modalClose.innerHTML = '×' diff --git a/modules/ui.py b/modules/ui.py index 0a63e357..1332e265 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -630,7 +630,7 @@ def create_ui(wrap_gradio_gpu_call): import modules.img2img import modules.txt2img - + with gr.Blocks(analytics_enabled=False) as txt2img_interface: txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False) dummy_component = gr.Label(visible=False) @@ -683,7 +683,8 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column(): with gr.Row(): - save = gr.Button('Save') + saveButtonId = 'save_txt2img' + save = gr.Button('Save', elem_id=saveButtonId) send_to_img2img = gr.Button('Send to img2img') send_to_inpaint = gr.Button('Send to inpaint') send_to_extras = gr.Button('Send to extras') @@ -901,7 +902,8 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column(): with gr.Row(): - save = gr.Button('Save') + saveButtonId = 'save_img2img' + save = gr.Button('Save', elem_id=saveButtonId) img2img_send_to_img2img = gr.Button('Send to img2img') img2img_send_to_inpaint = gr.Button('Send to inpaint') img2img_send_to_extras = gr.Button('Send to extras') diff --git a/style.css b/style.css index 13a9fb07..fa357a49 100644 --- a/style.css +++ b/style.css @@ -314,8 +314,8 @@ input[type="range"]{ .modalControls { display: grid; - grid-template-columns: 32px auto 1fr 32px; - grid-template-areas: "zoom tile space close"; + grid-template-columns: 32px auto 32px 1fr 32px; + grid-template-areas: "zoom tile save space close"; position: absolute; top: 0; left: 0; @@ -333,6 +333,10 @@ input[type="range"]{ grid-area: zoom; } +.modalSave { + grid-area: save; +} + .modalTileImage { grid-area: tile; } @@ -346,8 +350,18 @@ input[type="range"]{ cursor: pointer; } +.modalSave { + color: white; + font-size: 30px; + margin-top: 6px; + font-weight: bold; + cursor: pointer; +} + .modalClose:hover, .modalClose:focus, +.modalSave:hover, +.modalSave:focus, .modalZoom:hover, .modalZoom:focus { color: #999; -- cgit v1.2.3 From 268159cfe3231743c554a1a9bf15d090c758f920 Mon Sep 17 00:00:00 2001 From: Florian Horn Date: Thu, 27 Oct 2022 16:32:10 +0200 Subject: fixed indentation --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 1332e265..d49b10b2 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -630,7 +630,7 @@ def create_ui(wrap_gradio_gpu_call): import modules.img2img import modules.txt2img - + with gr.Blocks(analytics_enabled=False) as txt2img_interface: txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False) dummy_component = gr.Label(visible=False) -- cgit v1.2.3 From 26d08193848568b06105a1ee7b76f338ebf0f0ee Mon Sep 17 00:00:00 2001 From: Chris OBryan <13701027+cobryan05@users.noreply.github.com> Date: Fri, 28 Oct 2022 13:24:11 -0500 Subject: extras: Add option to run upscaling before face fixing Face restoration can look much better if ran after upscaling, as it allows the restoration to fix upscaling artifacts. This patch adds an option to choose which order to run upscaling/face fixing in. --- modules/extras.py | 145 +++++++++++++++++++++++++++++++++++------------------- modules/ui.py | 4 ++ 2 files changed, 99 insertions(+), 50 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/extras.py b/modules/extras.py index 22c5a1c1..79047f3a 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -7,6 +7,10 @@ from PIL import Image import torch import tqdm +from typing import Callable, List, Tuple +from functools import partial +from dataclasses import dataclass + from modules import processing, shared, images, devices, sd_models from modules.shared import opts import modules.gfpgan_model @@ -20,7 +24,7 @@ import gradio as gr cached_images = {} -def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_dir, show_extras_results, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility): +def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_dir, show_extras_results, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, upscale_first: bool ): devices.torch_gc() imageArr = [] @@ -56,68 +60,109 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_ else: outpath = opts.outdir_samples or opts.outdir_extras_samples - - for image, image_name in zip(imageArr, imageNameArr): - if image is None: - return outputs, "Please select an input image.", '' - existing_pnginfo = image.info or {} - image = image.convert("RGB") - info = "" + # Extra operation definitions + def run_gfpgan(image: Image.Image, info: str) -> Tuple[Image.Image, str]: + restored_img = modules.gfpgan_model.gfpgan_fix_faces(np.array(image, dtype=np.uint8)) + res = Image.fromarray(restored_img) + + if gfpgan_visibility < 1.0: + res = Image.blend(image, res, gfpgan_visibility) + + info += f"GFPGAN visibility:{round(gfpgan_visibility, 2)}\n" + return (res, info) - if gfpgan_visibility > 0: - restored_img = modules.gfpgan_model.gfpgan_fix_faces(np.array(image, dtype=np.uint8)) - res = Image.fromarray(restored_img) + def run_codeformer(image: Image.Image, info: str) -> Tuple[Image.Image, str]: + restored_img = modules.codeformer_model.codeformer.restore(np.array(image, dtype=np.uint8), w=codeformer_weight) + res = Image.fromarray(restored_img) - if gfpgan_visibility < 1.0: - res = Image.blend(image, res, gfpgan_visibility) + if codeformer_visibility < 1.0: + res = Image.blend(image, res, codeformer_visibility) - info += f"GFPGAN visibility:{round(gfpgan_visibility, 2)}\n" - image = res + info += f"CodeFormer w: {round(codeformer_weight, 2)}, CodeFormer visibility:{round(codeformer_visibility, 2)}\n" + return (res, info) - if codeformer_visibility > 0: - restored_img = modules.codeformer_model.codeformer.restore(np.array(image, dtype=np.uint8), w=codeformer_weight) - res = Image.fromarray(restored_img) - if codeformer_visibility < 1.0: - res = Image.blend(image, res, codeformer_visibility) + def upscale(image, scaler_index, resize, mode, resize_w, resize_h, crop): + small = image.crop((image.width // 2, image.height // 2, image.width // 2 + 10, image.height // 2 + 10)) + pixels = tuple(np.array(small).flatten().tolist()) + key = (resize, scaler_index, image.width, image.height, gfpgan_visibility, codeformer_visibility, codeformer_weight, + resize_mode, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop) + pixels - info += f"CodeFormer w: {round(codeformer_weight, 2)}, CodeFormer visibility:{round(codeformer_visibility, 2)}\n" - image = res + c = cached_images.get(key) + if c is None: + upscaler = shared.sd_upscalers[scaler_index] + c = upscaler.scaler.upscale(image, resize, upscaler.data_path) + if mode == 1 and crop: + cropped = Image.new("RGB", (resize_w, resize_h)) + cropped.paste(c, box=(resize_w // 2 - c.width // 2, resize_h // 2 - c.height // 2)) + c = cropped + cached_images[key] = c + return c + + def run_prepare_crop(image: Image.Image, info: str) -> Tuple[Image.Image, str]: + # Actual crop happens in run_upscalers_blend, this just sets upscaling_resize and adds info text + nonlocal upscaling_resize if resize_mode == 1: upscaling_resize = max(upscaling_resize_w/image.width, upscaling_resize_h/image.height) crop_info = " (crop)" if upscaling_crop else "" info += f"Resize to: {upscaling_resize_w:g}x{upscaling_resize_h:g}{crop_info}\n" + return (image, info) + + @dataclass + class UpscaleParams: + upscaler_idx: int + blend_alpha: float + + def run_upscalers_blend( params: List[UpscaleParams], image: Image.Image, info: str) -> Tuple[Image.Image, str]: + blended_result: Image.Image = None + for upscaler in params: + res = upscale(image, upscaler.upscaler_idx, upscaling_resize, resize_mode, upscaling_resize_w, upscaling_resize_h, upscaling_crop) + info += f"Upscale: {round(upscaling_resize, 3)}, visibility: {upscaler.blend_alpha}, model:{shared.sd_upscalers[upscaler.upscaler_idx].name}\n" + if blended_result is None: + blended_result = res + else: + blended_result = Image.blend(blended_result, res, upscaler.blend_alpha) + return (blended_result, info) + + # Build a list of operations to run + facefix_ops: List[Callable] = [] + if gfpgan_visibility > 0: + facefix_ops.append(run_gfpgan) + if codeformer_visibility > 0: + facefix_ops.append(run_codeformer) + + upscale_ops: List[Callable] = [] + if resize_mode == 1: + upscale_ops.append(run_prepare_crop) + + if upscaling_resize != 0: + step_params: List[UpscaleParams] = [] + step_params.append( UpscaleParams( upscaler_idx=extras_upscaler_1, blend_alpha=1.0 )) + if extras_upscaler_2 != 0 and extras_upscaler_2_visibility > 0: + step_params.append( UpscaleParams( upscaler_idx=extras_upscaler_2, blend_alpha=extras_upscaler_2_visibility ) ) + + upscale_ops.append( partial(run_upscalers_blend, step_params) ) + + + extras_ops: List[Callable] = [] + if upscale_first: + extras_ops = upscale_ops + facefix_ops + else: + extras_ops = facefix_ops + upscale_ops + + + for image, image_name in zip(imageArr, imageNameArr): + if image is None: + return outputs, "Please select an input image.", '' + existing_pnginfo = image.info or {} - if upscaling_resize != 1.0: - def upscale(image, scaler_index, resize, mode, resize_w, resize_h, crop): - small = image.crop((image.width // 2, image.height // 2, image.width // 2 + 10, image.height // 2 + 10)) - pixels = tuple(np.array(small).flatten().tolist()) - key = (resize, scaler_index, image.width, image.height, gfpgan_visibility, codeformer_visibility, codeformer_weight, - resize_mode, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop) + pixels - - c = cached_images.get(key) - if c is None: - upscaler = shared.sd_upscalers[scaler_index] - c = upscaler.scaler.upscale(image, resize, upscaler.data_path) - if mode == 1 and crop: - cropped = Image.new("RGB", (resize_w, resize_h)) - cropped.paste(c, box=(resize_w // 2 - c.width // 2, resize_h // 2 - c.height // 2)) - c = cropped - cached_images[key] = c - - return c - - info += f"Upscale: {round(upscaling_resize, 3)}, model:{shared.sd_upscalers[extras_upscaler_1].name}\n" - res = upscale(image, extras_upscaler_1, upscaling_resize, resize_mode, upscaling_resize_w, upscaling_resize_h, upscaling_crop) - - if extras_upscaler_2 != 0 and extras_upscaler_2_visibility > 0: - res2 = upscale(image, extras_upscaler_2, upscaling_resize, resize_mode, upscaling_resize_w, upscaling_resize_h, upscaling_crop) - info += f"Upscale: {round(upscaling_resize, 3)}, visibility: {round(extras_upscaler_2_visibility, 3)}, model:{shared.sd_upscalers[extras_upscaler_2].name}\n" - res = Image.blend(res, res2, extras_upscaler_2_visibility) - - image = res + image = image.convert("RGB") + info = "" + # Run each operation on each image + for op in extras_ops: + image, info = op(image, info) while len(cached_images) > 2: del cached_images[next(iter(cached_images.keys()))] diff --git a/modules/ui.py b/modules/ui.py index 0a63e357..16b6ac49 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1119,6 +1119,9 @@ def create_ui(wrap_gradio_gpu_call): codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer visibility", value=0, interactive=modules.codeformer_model.have_codeformer) codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer weight (0 = maximum effect, 1 = minimum effect)", value=0, interactive=modules.codeformer_model.have_codeformer) + with gr.Group(): + upscale_before_face_fix = gr.Checkbox(label='Upscale Before Restoring Faces', value=False) + submit = gr.Button('Generate', elem_id="extras_generate", variant='primary') with gr.Column(variant='panel'): @@ -1152,6 +1155,7 @@ def create_ui(wrap_gradio_gpu_call): extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, + upscale_before_face_fix, ], outputs=[ result_images, -- cgit v1.2.3 From 1f1b327959b546b5e6f995905a1699c5fe4a0c35 Mon Sep 17 00:00:00 2001 From: Chris OBryan <13701027+cobryan05@users.noreply.github.com> Date: Fri, 28 Oct 2022 16:11:16 -0500 Subject: extras: Make image cache LRU This changes the extras image cache into a Least-Recently-Used cache. This allows more experimentation with different upscalers without missing the cache. Max cache size is increased to 5 and is cleared on source image update. --- modules/extras.py | 67 +++++++++++++++++++++++++++++++------------------------ modules/ui.py | 5 +++++ 2 files changed, 43 insertions(+), 29 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/extras.py b/modules/extras.py index cffe0381..72cc6d1d 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -1,3 +1,4 @@ +from __future__ import annotations import math import os @@ -7,7 +8,7 @@ from PIL import Image import torch import tqdm -from typing import Callable, Dict, List, Tuple +from typing import Callable, List, OrderedDict, Tuple from functools import partial from dataclasses import dataclass @@ -21,18 +22,34 @@ import piexif.helper import gradio as gr -@dataclass(frozen=True) -class CacheKey: - image_hash: int - info_hash: int - args_hash: int +class LruCache(OrderedDict): + @dataclass(frozen=True) + class Key: + image_hash: int + info_hash: int + args_hash: int -@dataclass -class CacheEntry: - image: Image.Image - info: str + @dataclass + class Value: + image: Image.Image + info: str + + def __init__(self, max_size:int = 5, *args, **kwargs): + super().__init__(*args, **kwargs) + self._max_size = max_size + + def get(self, key: LruCache.Key) -> LruCache.Value: + ret = super().get(key) + if ret is not None: + self.move_to_end(key) # Move to end of eviction list + return ret + + def put(self, key: LruCache.Key, value: LruCache.Value) -> None: + self[key] = value + while len(self) > self._max_size: + self.popitem(last=False) -cached_images: Dict[CacheKey, CacheEntry] = {} +cached_images: LruCache = LruCache(max_size = 5) def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_dir, show_extras_results, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, upscale_first: bool ): @@ -121,14 +138,14 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_ blended_result: Image.Image = None for upscaler in params: upscale_args = (upscaler.upscaler_idx, upscaling_resize, resize_mode, upscaling_resize_w, upscaling_resize_h, upscaling_crop) - cache_key = CacheKey( image_hash = hash(np.array(image.getdata()).tobytes()), + cache_key = LruCache.Key( image_hash = hash(np.array(image.getdata()).tobytes()), info_hash = hash(info), - args_hash = hash(upscale_args) ) + args_hash = hash(upscale_args + (upscaler.blend_alpha,)) ) cached_entry = cached_images.get(cache_key) if cached_entry is None: res = upscale(image, *upscale_args) info += f"Upscale: {round(upscaling_resize, 3)}, visibility: {upscaler.blend_alpha}, model:{shared.sd_upscalers[upscaler.upscaler_idx].name}\n" - cached_images[cache_key] = CacheEntry(image=res, info=info) + cached_images.put(cache_key, LruCache.Value(image=res, info=info)) else: res, info = cached_entry.image, cached_entry.info @@ -140,14 +157,11 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_ # Build a list of operations to run facefix_ops: List[Callable] = [] - if gfpgan_visibility > 0: - facefix_ops.append(run_gfpgan) - if codeformer_visibility > 0: - facefix_ops.append(run_codeformer) + facefix_ops += [run_gfpgan] if gfpgan_visibility > 0 else [] + facefix_ops += [run_codeformer] if codeformer_visibility > 0 else [] upscale_ops: List[Callable] = [] - if resize_mode == 1: - upscale_ops.append(run_prepare_crop) + upscale_ops += [run_prepare_crop] if resize_mode == 1 else [] if upscaling_resize != 0: step_params: List[UpscaleParams] = [] @@ -157,12 +171,7 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_ upscale_ops.append( partial(run_upscalers_blend, step_params) ) - - extras_ops: List[Callable] = [] - if upscale_first: - extras_ops = upscale_ops + facefix_ops - else: - extras_ops = facefix_ops + upscale_ops + extras_ops: List[Callable] = (upscale_ops + facefix_ops) if upscale_first else (facefix_ops + upscale_ops) for image, image_name in zip(imageArr, imageNameArr): @@ -176,9 +185,6 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_ for op in extras_ops: image, info = op(image, info) - while len(cached_images) > 2: - del cached_images[next(iter(cached_images.keys()))] - if opts.use_original_name_batch and image_name != None: basename = os.path.splitext(os.path.basename(image_name))[0] else: @@ -198,6 +204,9 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_ return outputs, plaintext_to_html(info), '' +def clear_cache(): + cached_images.clear() + def run_pnginfo(image): if image is None: diff --git a/modules/ui.py b/modules/ui.py index 16b6ac49..b7c36c55 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1178,6 +1178,11 @@ def create_ui(wrap_gradio_gpu_call): outputs=[init_img_with_mask], ) + extras_image.change( + fn=modules.extras.clear_cache, + inputs=[], outputs=[] + ) + with gr.Blocks(analytics_enabled=False) as pnginfo_interface: with gr.Row().style(equal_height=False): with gr.Column(variant='panel'): -- cgit v1.2.3 From bce5adcd6de1ad608df8d813a92e1167b7a1d3f2 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 29 Oct 2022 07:37:06 +0300 Subject: change default hypernet activation function to linear --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 0a63e357..2541970d 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1238,7 +1238,7 @@ def create_ui(wrap_gradio_gpu_call): new_hypernetwork_name = gr.Textbox(label="Name") new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'") - new_hypernetwork_activation_func = gr.Dropdown(value="relu", label="Select activation function of hypernetwork", choices=modules.hypernetworks.ui.keys) + new_hypernetwork_activation_func = gr.Dropdown(value="linear", label="Select activation function of hypernetwork", choices=modules.hypernetworks.ui.keys) new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. relu-like - Kaiming, sigmoid-like - Xavier is recommended", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"]) new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization") new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout") -- cgit v1.2.3 From 2d220afb24bd9812d5124814f670ec2a1ff5b0fe Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 29 Oct 2022 08:26:12 +0300 Subject: fix open folder button not working --- modules/ui.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 922a2163..20cc10cf 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -631,9 +631,9 @@ Requested path was: {f} buttons = parameters_copypaste.create_buttons(["img2img", "inpaint", "extras"]) button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder' - open_folder = gr.Button(folder_symbol, elem_id=button_id) + open_folder_button = gr.Button(folder_symbol, elem_id=button_id) - open_folder.click( + open_folder_button.click( fn=lambda: open_folder(opts.outdir_samples or outdir), inputs=[], outputs=[], -- cgit v1.2.3 From a33d0a9a65189be35038be5765f2b4d1b19bab0f Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 29 Oct 2022 08:28:48 +0300 Subject: remove weird spaces added to ui.py over time --- modules/ui.py | 51 +++++++++++++++++++++++++-------------------------- 1 file changed, 25 insertions(+), 26 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 20cc10cf..46657dd4 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -596,7 +596,7 @@ def create_refresh_button(refresh_component, refresh_method, refreshed_args, ele ) return refresh_button -def create_output_panel(tabname, outdir): +def create_output_panel(tabname, outdir): def open_folder(f): if not os.path.exists(f): print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.') @@ -618,11 +618,11 @@ Requested path was: {f} sp.Popen(["open", path]) else: sp.Popen(["xdg-open", path]) - - with gr.Column(variant='panel'): - with gr.Group(): + + with gr.Column(variant='panel'): + with gr.Group(): result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(grid=4) - + generation_info = None with gr.Column(): with gr.Row(): @@ -639,7 +639,7 @@ Requested path was: {f} outputs=[], ) - if tabname != "extras": + if tabname != "extras": with gr.Row(): do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False) @@ -671,8 +671,7 @@ Requested path was: {f} html_info = gr.HTML() parameters_copypaste.bind_buttons(buttons, result_gallery, "txt2img" if tabname == "txt2img" else None) return result_gallery, generation_info if tabname != "extras" else html_info_x, html_info - - + def create_ui(wrap_gradio_gpu_call): import modules.img2img @@ -723,10 +722,10 @@ def create_ui(wrap_gradio_gpu_call): with gr.Group(): custom_inputs = modules.scripts.scripts_txt2img.setup_ui(is_img2img=False) - - txt2img_gallery, generation_info, html_info = create_output_panel("txt2img", opts.outdir_txt2img_samples) - + + txt2img_gallery, generation_info, html_info = create_output_panel("txt2img", opts.outdir_txt2img_samples) + connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) @@ -781,7 +780,7 @@ def create_ui(wrap_gradio_gpu_call): fn=lambda x: gr_show(x), inputs=[enable_hr], outputs=[hr_options], - ) + ) roll.click( fn=roll_artist, @@ -902,7 +901,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Group(): custom_inputs = modules.scripts.scripts_img2img.setup_ui(is_img2img=True) - img2img_gallery, generation_info, html_info = create_output_panel("img2img", opts.outdir_img2img_samples) + img2img_gallery, generation_info, html_info = create_output_panel("img2img", opts.outdir_img2img_samples) connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) @@ -990,7 +989,7 @@ def create_ui(wrap_gradio_gpu_call): inputs=[init_img], outputs=[img2img_prompt], ) - + roll.click( fn=roll_artist, @@ -1045,7 +1044,7 @@ def create_ui(wrap_gradio_gpu_call): (denoising_strength, "Denoising strength"), *modules.scripts.scripts_img2img.infotext_fields ] - parameters_copypaste.add_paste_fields("img2img", init_img, img2img_paste_fields) + parameters_copypaste.add_paste_fields("img2img", init_img, img2img_paste_fields) parameters_copypaste.add_paste_fields("inpaint", init_img_with_mask, img2img_paste_fields) @@ -1077,9 +1076,9 @@ def create_ui(wrap_gradio_gpu_call): upscaling_resize_w = gr.Number(label="Width", value=512, precision=0) upscaling_resize_h = gr.Number(label="Height", value=512, precision=0) upscaling_crop = gr.Checkbox(label='Crop to fit', value=True) - + with gr.Group(): - extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") + extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") with gr.Group(): extras_upscaler_2 = gr.Radio(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") @@ -1125,7 +1124,7 @@ def create_ui(wrap_gradio_gpu_call): html_info, ] ) - parameters_copypaste.add_paste_fields("extras", extras_image, None) + parameters_copypaste.add_paste_fields("extras", extras_image, None) with gr.Blocks(analytics_enabled=False) as pnginfo_interface: @@ -1139,14 +1138,14 @@ def create_ui(wrap_gradio_gpu_call): html2 = gr.HTML() with gr.Row(): buttons = parameters_copypaste.create_buttons(["txt2img", "img2img", "inpaint", "extras"]) - parameters_copypaste.bind_buttons(buttons, image, generation_info) - + parameters_copypaste.bind_buttons(buttons, image, generation_info) + image.change( fn=wrap_gradio_call(modules.extras.run_pnginfo), inputs=[image], outputs=[html, generation_info, html2], ) - + with gr.Blocks() as modelmerger_interface: with gr.Row().style(equal_height=False): with gr.Column(variant='panel'): @@ -1569,7 +1568,7 @@ def create_ui(wrap_gradio_gpu_call): column.__exit__() - + interfaces = [ (txt2img_interface, "txt2img", "txt2img"), @@ -1582,7 +1581,7 @@ def create_ui(wrap_gradio_gpu_call): interfaces += script_callbacks.ui_tabs_callback() - interfaces += [(settings_interface, "Settings", "settings")] + interfaces += [(settings_interface, "Settings", "settings")] css = "" @@ -1661,7 +1660,7 @@ def create_ui(wrap_gradio_gpu_call): component_dict['sd_model_checkpoint'], ] ) - + settings_map = { 'sd_hypernetwork': 'Hypernet', @@ -1669,7 +1668,7 @@ def create_ui(wrap_gradio_gpu_call): 'sd_model_checkpoint': 'Model hash', } - parameters_copypaste.run_bind() + parameters_copypaste.run_bind() ui_config_file = cmd_opts.ui_config_file ui_settings = {} @@ -1749,7 +1748,7 @@ def load_javascript(raw_response): javascript = f'' scripts_list = modules.scripts.list_scripts("javascript", ".js") - + for basedir, filename, path in scripts_list: with open(path, "r", encoding="utf8") as jsfile: javascript += f"\n" -- cgit v1.2.3 From 3c207ca68483b3406faf519bde2743b578dac222 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 29 Oct 2022 08:42:34 +0300 Subject: add needed imports fr new code in copypaste.py --- modules/generation_parameters_copypaste.py | 9 +++++++++ modules/ui.py | 7 ------- 2 files changed, 9 insertions(+), 7 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 2b80737a..224a17ea 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -1,3 +1,5 @@ +import base64 +import io import os import re import gradio as gr @@ -14,6 +16,7 @@ type_of_gr_update = type(gr.update()) paste_fields = {} bind_list = [] + def quote(text): if ',' not in str(text): return text @@ -23,6 +26,7 @@ def quote(text): text = text.replace('"', '\\"') return f'"{text}"' + def image_from_url_text(filedata): if type(filedata) == dict and filedata["is_file"]: filename = filedata["name"] @@ -45,19 +49,23 @@ def image_from_url_text(filedata): image = Image.open(io.BytesIO(filedata)) return image + def add_paste_fields(tabname, init_img, fields): paste_fields[tabname] = {"init_img":init_img, "fields": fields} + def create_buttons(tabs_list): buttons = {} for tab in tabs_list: buttons[tab] = gr.Button(f"Send to {tab}") return buttons + #if send_generate_info is a tab name, mean generate_info comes from the params fields of the tab def bind_buttons(buttons, send_image, send_generate_info): bind_list.append([buttons, send_image, send_generate_info]) + def run_bind(): for buttons, send_image, send_generate_info in bind_list: for tab in buttons: @@ -98,6 +106,7 @@ def run_bind(): outputs=None, ) + def parse_generation_parameters(x: str): """parses generation parameters string, the one you see in text field under the picture in UI: ``` diff --git a/modules/ui.py b/modules/ui.py index 46657dd4..280910d0 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1,6 +1,4 @@ -import base64 import html -import io import json import math import mimetypes @@ -18,13 +16,8 @@ import gradio as gr import gradio.routes import gradio.utils import numpy as np -import piexif -import torch from PIL import Image, PngImagePlugin -import gradio as gr -import gradio.utils -import gradio.routes from modules import sd_hijack, sd_models, localization, script_callbacks from modules.paths import script_path -- cgit v1.2.3 From 28e6d4a54ea1fa1e34ad1ea0742ab2003ed7fa7f Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 29 Oct 2022 09:13:36 +0300 Subject: add element ids for save buttons for #3798 --- modules/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 66b743f5..3c34eca0 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -620,7 +620,7 @@ Requested path was: {f} with gr.Column(): with gr.Row(): if tabname != "extras": - save = gr.Button('Save') + save = gr.Button('Save', elem_id=f'save_{tabname}') buttons = parameters_copypaste.create_buttons(["img2img", "inpaint", "extras"]) button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder' -- cgit v1.2.3 From 35c45df28b303a05d56a13cb56d4046f08cf8c25 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 29 Oct 2022 10:56:19 +0300 Subject: fix broken ↙ button, fix field paste ignoring most of useful fields for for #3768 MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- modules/generation_parameters_copypaste.py | 36 ++++++++++++++++++------- modules/ui.py | 43 +++++++++++------------------- 2 files changed, 41 insertions(+), 38 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index d590e9ee..bbaad42e 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -6,7 +6,7 @@ import gradio as gr from modules.shared import script_path from modules import shared import tempfile -from PIL import Image, PngImagePlugin +from PIL import Image re_param_code = r'\s*([\w ]+):\s*("(?:\\|\"|[^\"])+"|[^,]*)(?:,|$)' re_param = re.compile(re_param_code) @@ -61,6 +61,24 @@ def add_paste_fields(tabname, init_img, fields): modules.ui.img2img_paste_fields = fields +def integrate_settings_paste_fields(component_dict): + from modules import ui + + settings_map = { + 'sd_hypernetwork': 'Hypernet', + 'CLIP_stop_at_last_layers': 'Clip skip', + 'sd_model_checkpoint': 'Model hash', + } + settings_paste_fields = [ + (component_dict[k], lambda d, k=k, v=v: ui.apply_setting(k, d.get(v, None))) + for k, v in settings_map.items() + ] + + for tabname, info in paste_fields.items(): + if info["fields"] is not None: + info["fields"] += settings_paste_fields + + def create_buttons(tabs_list): buttons = {} for tab in tabs_list: @@ -87,24 +105,22 @@ def run_bind(): ) else: button.click( - fn=lambda x:x, + fn=lambda x: x, inputs=[send_image], outputs=[paste_fields[tab]["init_img"]], ) if send_generate_info and paste_fields[tab]["fields"] is not None: - paste_field_names = ['Prompt', 'Negative prompt', 'Steps', 'Face restoration', 'Size-1', 'Size-2'] - if shared.opts.send_seed: - paste_field_names += ["Seed"] if send_generate_info in paste_fields: + paste_field_names = ['Prompt', 'Negative prompt', 'Steps', 'Face restoration', 'Size-1', 'Size-2'] + (["Seed"] if shared.opts.send_seed else []) + button.click( - fn=lambda *x:x, - inputs=[field for field,name in paste_fields[send_generate_info]["fields"] if name in paste_field_names], - outputs=[field for field,name in paste_fields[tab]["fields"] if name in paste_field_names], + fn=lambda *x: x, + inputs=[field for field, name in paste_fields[send_generate_info]["fields"] if name in paste_field_names], + outputs=[field for field, name in paste_fields[tab]["fields"] if name in paste_field_names], ) - else: - connect_paste(button, [(field, name) for field, name in paste_fields[tab]["fields"] if name in paste_field_names], send_generate_info) + connect_paste(button, paste_fields[tab]["fields"], send_generate_info) button.click( fn=None, diff --git a/modules/ui.py b/modules/ui.py index 3c34eca0..5055ca64 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -589,6 +589,7 @@ def create_refresh_button(refresh_component, refresh_method, refreshed_args, ele ) return refresh_button + def create_output_panel(tabname, outdir): def open_folder(f): if not os.path.exists(f): @@ -716,6 +717,7 @@ def create_ui(wrap_gradio_gpu_call): custom_inputs = modules.scripts.scripts_txt2img.setup_ui(is_img2img=False) txt2img_gallery, generation_info, html_info = create_output_panel("txt2img", opts.outdir_txt2img_samples) + parameters_copypaste.bind_buttons({"txt2img": txt2img_paste}, None, txt2img_prompt) connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) @@ -784,7 +786,7 @@ def create_ui(wrap_gradio_gpu_call): ] ) - parameters_copypaste.add_paste_fields("txt2img", None, [ + txt2img_paste_fields = [ (txt2img_prompt, "Prompt"), (txt2img_negative_prompt, "Negative prompt"), (steps, "Steps"), @@ -805,7 +807,8 @@ def create_ui(wrap_gradio_gpu_call): (firstphase_width, "First pass size-1"), (firstphase_height, "First pass size-2"), *modules.scripts.scripts_txt2img.infotext_fields - ]) + ] + parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields) txt2img_preview_params = [ txt2img_prompt, @@ -893,6 +896,7 @@ def create_ui(wrap_gradio_gpu_call): custom_inputs = modules.scripts.scripts_img2img.setup_ui(is_img2img=True) img2img_gallery, generation_info, html_info = create_output_panel("img2img", opts.outdir_img2img_samples) + parameters_copypaste.bind_buttons({"img2img": img2img_paste}, None, img2img_prompt) connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) @@ -1038,7 +1042,6 @@ def create_ui(wrap_gradio_gpu_call): parameters_copypaste.add_paste_fields("img2img", init_img, img2img_paste_fields) parameters_copypaste.add_paste_fields("inpaint", init_img_with_mask, img2img_paste_fields) - with gr.Blocks(analytics_enabled=False) as extras_interface: with gr.Row().style(equal_height=False): with gr.Column(variant='panel'): @@ -1050,12 +1053,8 @@ def create_ui(wrap_gradio_gpu_call): image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file") with gr.TabItem('Batch from Directory'): - extras_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, - placeholder="A directory on the same machine where the server is running." - ) - extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, - placeholder="Leave blank to save images to the default path." - ) + extras_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, placeholder="A directory on the same machine where the server is running.") + extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, placeholder="Leave blank to save images to the default path.") show_extras_results = gr.Checkbox(label='Show result images', value=True) with gr.Tabs(elem_id="extras_resize_mode"): @@ -1087,7 +1086,6 @@ def create_ui(wrap_gradio_gpu_call): submit = gr.Button('Generate', elem_id="extras_generate", variant='primary') - result_images, html_info_x, html_info = create_output_panel("extras", opts.outdir_extras_samples) submit.click( @@ -1121,7 +1119,6 @@ def create_ui(wrap_gradio_gpu_call): ) parameters_copypaste.add_paste_fields("extras", extras_image, None) - extras_image.change( fn=modules.extras.clear_cache, inputs=[], outputs=[] @@ -1587,9 +1584,6 @@ def create_ui(wrap_gradio_gpu_call): if column is not None: column.__exit__() - - - interfaces = [ (txt2img_interface, "txt2img", "txt2img"), (img2img_interface, "img2img", "img2img"), @@ -1599,10 +1593,6 @@ def create_ui(wrap_gradio_gpu_call): (train_interface, "Train", "ti"), ] - interfaces += script_callbacks.ui_tabs_callback() - - interfaces += [(settings_interface, "Settings", "settings")] - css = "" for cssfile in modules.scripts.list_files_with_name("style.css"): @@ -1619,6 +1609,9 @@ def create_ui(wrap_gradio_gpu_call): if not cmd_opts.no_progressbar_hiding: css += css_hide_progressbar + interfaces += script_callbacks.ui_tabs_callback() + interfaces += [(settings_interface, "Settings", "settings")] + with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo: with gr.Row(elem_id="quicksettings"): for i, k, item in quicksettings_list: @@ -1627,6 +1620,9 @@ def create_ui(wrap_gradio_gpu_call): settings_interface.gradio_ref = demo + parameters_copypaste.integrate_settings_paste_fields(component_dict) + parameters_copypaste.run_bind() + with gr.Tabs(elem_id="tabs") as tabs: for interface, label, ifid in interfaces: with gr.TabItem(label, id=ifid, elem_id='tab_' + ifid): @@ -1681,15 +1677,6 @@ def create_ui(wrap_gradio_gpu_call): ] ) - - settings_map = { - 'sd_hypernetwork': 'Hypernet', - 'CLIP_stop_at_last_layers': 'Clip skip', - 'sd_model_checkpoint': 'Model hash', - } - - parameters_copypaste.run_bind() - ui_config_file = cmd_opts.ui_config_file ui_settings = {} settings_count = len(ui_settings) @@ -1708,7 +1695,7 @@ def create_ui(wrap_gradio_gpu_call): def apply_field(obj, field, condition=None, init_field=None): key = path + "/" + field - if getattr(obj,'custom_script_source',None) is not None: + if getattr(obj, 'custom_script_source', None) is not None: key = 'customscript/' + obj.custom_script_source + '/' + key if getattr(obj, 'do_not_save_to_config', False): -- cgit v1.2.3 From c9bb33dd43dbb9479ff1b70351df14508c89ac60 Mon Sep 17 00:00:00 2001 From: victorca25 Date: Sun, 30 Oct 2022 12:52:50 +0100 Subject: add resrgan 8x, allow use 1x and up to 8x extra models, move BSRGAN model, add nearest --- modules/esrgan_model.py | 17 +++++++++++++---- modules/modelloader.py | 3 +++ modules/ui.py | 2 +- modules/upscaler.py | 17 ++++++++++++++++- 4 files changed, 33 insertions(+), 6 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py index a13cf6ac..c61669b4 100644 --- a/modules/esrgan_model.py +++ b/modules/esrgan_model.py @@ -50,6 +50,7 @@ def mod2normal(state_dict): def resrgan2normal(state_dict, nb=23): # this code is copied from https://github.com/victorca25/iNNfer if "conv_first.weight" in state_dict and "body.0.rdb1.conv1.weight" in state_dict: + re8x = 0 crt_net = {} items = [] for k, v in state_dict.items(): @@ -75,10 +76,18 @@ def resrgan2normal(state_dict, nb=23): crt_net['model.3.bias'] = state_dict['conv_up1.bias'] crt_net['model.6.weight'] = state_dict['conv_up2.weight'] crt_net['model.6.bias'] = state_dict['conv_up2.bias'] - crt_net['model.8.weight'] = state_dict['conv_hr.weight'] - crt_net['model.8.bias'] = state_dict['conv_hr.bias'] - crt_net['model.10.weight'] = state_dict['conv_last.weight'] - crt_net['model.10.bias'] = state_dict['conv_last.bias'] + + if 'conv_up3.weight' in state_dict: + # modification supporting: https://github.com/ai-forever/Real-ESRGAN/blob/main/RealESRGAN/rrdbnet_arch.py + re8x = 3 + crt_net['model.9.weight'] = state_dict['conv_up3.weight'] + crt_net['model.9.bias'] = state_dict['conv_up3.bias'] + + crt_net[f'model.{8+re8x}.weight'] = state_dict['conv_hr.weight'] + crt_net[f'model.{8+re8x}.bias'] = state_dict['conv_hr.bias'] + crt_net[f'model.{10+re8x}.weight'] = state_dict['conv_last.weight'] + crt_net[f'model.{10+re8x}.bias'] = state_dict['conv_last.bias'] + state_dict = crt_net return state_dict diff --git a/modules/modelloader.py b/modules/modelloader.py index b0f2f33d..e4a6f8ac 100644 --- a/modules/modelloader.py +++ b/modules/modelloader.py @@ -85,6 +85,9 @@ def cleanup_models(): src_path = os.path.join(root_path, "ESRGAN") dest_path = os.path.join(models_path, "ESRGAN") move_files(src_path, dest_path) + src_path = os.path.join(models_path, "BSRGAN") + dest_path = os.path.join(models_path, "ESRGAN") + move_files(src_path, dest_path, ".pth") src_path = os.path.join(root_path, "gfpgan") dest_path = os.path.join(models_path, "GFPGAN") move_files(src_path, dest_path) diff --git a/modules/ui.py b/modules/ui.py index 5055ca64..47610f5c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1059,7 +1059,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Tabs(elem_id="extras_resize_mode"): with gr.TabItem('Scale by'): - upscaling_resize = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Resize", value=2) + upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4) with gr.TabItem('Scale to'): with gr.Group(): with gr.Row(): diff --git a/modules/upscaler.py b/modules/upscaler.py index 6ab2fb40..83fde7ca 100644 --- a/modules/upscaler.py +++ b/modules/upscaler.py @@ -10,6 +10,7 @@ import modules.shared from modules import modelloader, shared LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS) +NEAREST = (Image.Resampling.NEAREST if hasattr(Image, 'Resampling') else Image.NEAREST) from modules.paths import models_path @@ -57,7 +58,7 @@ class Upscaler: dest_w = img.width * scale dest_h = img.height * scale for i in range(3): - if img.width >= dest_w and img.height >= dest_h: + if img.width > dest_w and img.height > dest_h: break img = self.do_upscale(img, selected_model) if img.width != dest_w or img.height != dest_h: @@ -120,3 +121,17 @@ class UpscalerLanczos(Upscaler): self.name = "Lanczos" self.scalers = [UpscalerData("Lanczos", None, self)] + +class UpscalerNearest(Upscaler): + scalers = [] + + def do_upscale(self, img, selected_model=None): + return img.resize((int(img.width * self.scale), int(img.height * self.scale)), resample=NEAREST) + + def load_model(self, _): + pass + + def __init__(self, dirname=None): + super().__init__(False) + self.name = "Nearest" + self.scalers = [UpscalerData("Nearest", None, self)] \ No newline at end of file -- cgit v1.2.3 From 910a097ae2ed78a62101951f1b87137f9e1baaea Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Mon, 31 Oct 2022 17:36:45 +0300 Subject: add initial version of the extensions tab fix broken Restart Gradio button --- javascript/extensions.js | 24 +++++ modules/extensions.py | 83 +++++++++++++++ modules/generation_parameters_copypaste.py | 5 + modules/scripts.py | 21 +--- modules/shared.py | 10 +- modules/ui.py | 16 ++- modules/ui_extensions.py | 162 +++++++++++++++++++++++++++++ style.css | 22 +++- webui.py | 20 ++-- 9 files changed, 333 insertions(+), 30 deletions(-) create mode 100644 javascript/extensions.js create mode 100644 modules/extensions.py create mode 100644 modules/ui_extensions.py (limited to 'modules/ui.py') diff --git a/javascript/extensions.js b/javascript/extensions.js new file mode 100644 index 00000000..86f5336d --- /dev/null +++ b/javascript/extensions.js @@ -0,0 +1,24 @@ + +function extensions_apply(_, _){ + disable = [] + update = [] + gradioApp().querySelectorAll('#extensions input[type="checkbox"]').forEach(function(x){ + if(x.name.startsWith("enable_") && ! x.checked) + disable.push(x.name.substr(7)) + + if(x.name.startsWith("update_") && x.checked) + update.push(x.name.substr(7)) + }) + + restart_reload() + + return [JSON.stringify(disable), JSON.stringify(update)] +} + +function extensions_check(){ + gradioApp().querySelectorAll('#extensions .extension_status').forEach(function(x){ + x.innerHTML = "Loading..." + }) + + return [] +} \ No newline at end of file diff --git a/modules/extensions.py b/modules/extensions.py new file mode 100644 index 00000000..8d6ae848 --- /dev/null +++ b/modules/extensions.py @@ -0,0 +1,83 @@ +import os +import sys +import traceback + +import git + +from modules import paths, shared + + +extensions = [] +extensions_dir = os.path.join(paths.script_path, "extensions") + + +def active(): + return [x for x in extensions if x.enabled] + + +class Extension: + def __init__(self, name, path, enabled=True): + self.name = name + self.path = path + self.enabled = enabled + self.status = '' + self.can_update = False + + repo = None + try: + if os.path.exists(os.path.join(path, ".git")): + repo = git.Repo(path) + except Exception: + print(f"Error reading github repository info from {path}:", file=sys.stderr) + print(traceback.format_exc(), file=sys.stderr) + + if repo is None or repo.bare: + self.remote = None + else: + self.remote = next(repo.remote().urls, None) + self.status = 'unknown' + + def list_files(self, subdir, extension): + from modules import scripts + + dirpath = os.path.join(self.path, subdir) + if not os.path.isdir(dirpath): + return [] + + res = [] + for filename in sorted(os.listdir(dirpath)): + res.append(scripts.ScriptFile(dirpath, filename, os.path.join(dirpath, filename))) + + res = [x for x in res if os.path.splitext(x.path)[1].lower() == extension and os.path.isfile(x.path)] + + return res + + def check_updates(self): + repo = git.Repo(self.path) + for fetch in repo.remote().fetch("--dry-run"): + if fetch.flags != fetch.HEAD_UPTODATE: + self.can_update = True + self.status = "behind" + return + + self.can_update = False + self.status = "latest" + + def pull(self): + repo = git.Repo(self.path) + repo.remotes.origin.pull() + + +def list_extensions(): + extensions.clear() + + if not os.path.isdir(extensions_dir): + return + + for dirname in sorted(os.listdir(extensions_dir)): + path = os.path.join(extensions_dir, dirname) + if not os.path.isdir(path): + continue + + extension = Extension(name=dirname, path=path, enabled=dirname not in shared.opts.disabled_extensions) + extensions.append(extension) diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index df70c728..985ec95e 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -17,6 +17,11 @@ paste_fields = {} bind_list = [] +def reset(): + paste_fields.clear() + bind_list.clear() + + def quote(text): if ',' not in str(text): return text diff --git a/modules/scripts.py b/modules/scripts.py index 96e44bfd..533db45c 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -7,7 +7,7 @@ import modules.ui as ui import gradio as gr from modules.processing import StableDiffusionProcessing -from modules import shared, paths, script_callbacks +from modules import shared, paths, script_callbacks, extensions AlwaysVisible = object() @@ -107,17 +107,8 @@ def list_scripts(scriptdirname, extension): for filename in sorted(os.listdir(basedir)): scripts_list.append(ScriptFile(paths.script_path, filename, os.path.join(basedir, filename))) - extdir = os.path.join(paths.script_path, "extensions") - if os.path.exists(extdir): - for dirname in sorted(os.listdir(extdir)): - dirpath = os.path.join(extdir, dirname) - scriptdirpath = os.path.join(dirpath, scriptdirname) - - if not os.path.isdir(scriptdirpath): - continue - - for filename in sorted(os.listdir(scriptdirpath)): - scripts_list.append(ScriptFile(dirpath, filename, os.path.join(scriptdirpath, filename))) + for ext in extensions.active(): + scripts_list += ext.list_files(scriptdirname, extension) scripts_list = [x for x in scripts_list if os.path.splitext(x.path)[1].lower() == extension and os.path.isfile(x.path)] @@ -127,11 +118,7 @@ def list_scripts(scriptdirname, extension): def list_files_with_name(filename): res = [] - dirs = [paths.script_path] - - extdir = os.path.join(paths.script_path, "extensions") - if os.path.exists(extdir): - dirs += [os.path.join(extdir, d) for d in sorted(os.listdir(extdir))] + dirs = [paths.script_path] + [ext.path for ext in extensions.active()] for dirpath in dirs: if not os.path.isdir(dirpath): diff --git a/modules/shared.py b/modules/shared.py index e4f163c1..cce87081 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -132,6 +132,7 @@ class State: current_image = None current_image_sampling_step = 0 textinfo = None + need_restart = False def skip(self): self.skipped = True @@ -354,6 +355,12 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}), })) +options_templates.update(options_section((None, "Hidden options"), { + "disabled_extensions": OptionInfo([], "Disable those extensions"), +})) + +options_templates.update() + class Options: data = None @@ -365,8 +372,9 @@ class Options: def __setattr__(self, key, value): if self.data is not None: - if key in self.data: + if key in self.data or key in self.data_labels: self.data[key] = value + return return super(Options, self).__setattr__(key, value) diff --git a/modules/ui.py b/modules/ui.py index 5055ca64..2c15abb7 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -19,7 +19,7 @@ import numpy as np from PIL import Image, PngImagePlugin -from modules import sd_hijack, sd_models, localization, script_callbacks +from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions from modules.paths import script_path from modules.shared import opts, cmd_opts, restricted_opts @@ -671,6 +671,7 @@ def create_ui(wrap_gradio_gpu_call): import modules.img2img import modules.txt2img + parameters_copypaste.reset() with gr.Blocks(analytics_enabled=False) as txt2img_interface: txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False) @@ -1511,8 +1512,9 @@ def create_ui(wrap_gradio_gpu_call): column = None with gr.Row(elem_id="settings").style(equal_height=False): for i, (k, item) in enumerate(opts.data_labels.items()): + section_must_be_skipped = item.section[0] is None - if previous_section != item.section: + if previous_section != item.section and not section_must_be_skipped: if cols_displayed < settings_cols and (items_displayed >= items_per_col or previous_section is None): if column is not None: column.__exit__() @@ -1531,6 +1533,8 @@ def create_ui(wrap_gradio_gpu_call): if k in quicksettings_names and not shared.cmd_opts.freeze_settings: quicksettings_list.append((i, k, item)) components.append(dummy_component) + elif section_must_be_skipped: + components.append(dummy_component) else: component = create_setting_component(k) component_dict[k] = component @@ -1572,9 +1576,10 @@ def create_ui(wrap_gradio_gpu_call): def request_restart(): shared.state.interrupt() - settings_interface.gradio_ref.do_restart = True + shared.state.need_restart = True restart_gradio.click( + fn=request_restart, inputs=[], outputs=[], @@ -1612,14 +1617,15 @@ def create_ui(wrap_gradio_gpu_call): interfaces += script_callbacks.ui_tabs_callback() interfaces += [(settings_interface, "Settings", "settings")] + extensions_interface = ui_extensions.create_ui() + interfaces += [(extensions_interface, "Extensions", "extensions")] + with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo: with gr.Row(elem_id="quicksettings"): for i, k, item in quicksettings_list: component = create_setting_component(k, is_quicksettings=True) component_dict[k] = component - settings_interface.gradio_ref = demo - parameters_copypaste.integrate_settings_paste_fields(component_dict) parameters_copypaste.run_bind() diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py new file mode 100644 index 00000000..b7d747dc --- /dev/null +++ b/modules/ui_extensions.py @@ -0,0 +1,162 @@ +import json +import os.path +import shutil +import sys +import time +import traceback + +import git + +import gradio as gr +import html + +from modules import extensions, shared, paths + + +def apply_and_restart(disable_list, update_list): + disabled = json.loads(disable_list) + assert type(disabled) == list, f"wrong disable_list data for apply_and_restart: {disable_list}" + + update = json.loads(update_list) + assert type(update) == list, f"wrong update_list data for apply_and_restart: {update_list}" + + update = set(update) + + for ext in extensions.extensions: + if ext.name not in update: + continue + + try: + ext.pull() + except Exception: + print(f"Error pulling updates for {ext.name}:", file=sys.stderr) + print(traceback.format_exc(), file=sys.stderr) + + shared.opts.disabled_extensions = disabled + shared.opts.save(shared.config_filename) + + shared.state.interrupt() + shared.state.need_restart = True + + +def check_updates(): + for ext in extensions.extensions: + if ext.remote is None: + continue + + try: + ext.check_updates() + except Exception: + print(f"Error checking updates for {ext.name}:", file=sys.stderr) + print(traceback.format_exc(), file=sys.stderr) + + return extension_table() + + +def extension_table(): + code = f""" + + + + + + + + + + """ + + for ext in extensions.extensions: + if ext.can_update: + ext_status = f"""""" + else: + ext_status = ext.status + + code += f""" + + + + {ext_status} + + """ + + code += """ + +
ExtensionURLUpdate
{html.escape(ext.remote or '')}
+ """ + + return code + + +def install_extension_from_url(dirname, url): + assert url, 'No URL specified' + + if dirname is None or dirname == "": + *parts, last_part = url.split('/') + last_part = last_part.replace(".git", "") + + dirname = last_part + + target_dir = os.path.join(extensions.extensions_dir, dirname) + assert not os.path.exists(target_dir), f'Extension directory already exists: {target_dir}' + + assert len([x for x in extensions.extensions if x.remote == url]) == 0, 'Extension with this URL is already installed' + + tmpdir = os.path.join(paths.script_path, "tmp", dirname) + + try: + shutil.rmtree(tmpdir, True) + + repo = git.Repo.clone_from(url, tmpdir) + repo.remote().fetch() + + os.rename(tmpdir, target_dir) + + extensions.list_extensions() + return [extension_table(), html.escape(f"Installed into {target_dir}. Use Installed tab to restart.")] + finally: + shutil.rmtree(tmpdir, True) + + +def create_ui(): + import modules.ui + + with gr.Blocks(analytics_enabled=False) as ui: + with gr.Tabs(elem_id="tabs_extensions") as tabs: + with gr.TabItem("Installed"): + extensions_disabled_list = gr.Text(elem_id="extensions_disabled_list", visible=False) + extensions_update_list = gr.Text(elem_id="extensions_update_list", visible=False) + + with gr.Row(): + apply = gr.Button(value="Apply and restart UI", variant="primary") + check = gr.Button(value="Check for updates") + + extensions_table = gr.HTML(lambda: extension_table()) + + apply.click( + fn=apply_and_restart, + _js="extensions_apply", + inputs=[extensions_disabled_list, extensions_update_list], + outputs=[], + ) + + check.click( + fn=check_updates, + _js="extensions_check", + inputs=[], + outputs=[extensions_table], + ) + + with gr.TabItem("Install from URL"): + install_url = gr.Text(label="URL for extension's git repository") + install_dirname = gr.Text(label="Local directory name", placeholder="Leave empty for auto") + intall_button = gr.Button(value="Install", variant="primary") + intall_result = gr.HTML(elem_id="extension_install_result") + + intall_button.click( + fn=modules.ui.wrap_gradio_call(install_extension_from_url, extra_outputs=[gr.update()]), + inputs=[install_dirname, install_url], + outputs=[extensions_table, intall_result], + ) + + return ui diff --git a/style.css b/style.css index 8b2211b1..859c3933 100644 --- a/style.css +++ b/style.css @@ -530,6 +530,26 @@ img2maskimg, #img2maskimg > .h-60, #img2maskimg > .h-60 > div, #img2maskimg > .h min-height: 480px !important; } +/* Extensions */ + +#extensions{ + border-collapse: collapse; +} + +#extensions td, #extensions th{ + border: 1px solid #ccc; + padding: 0.25em 0.5em; +} + +#extensions input[type="checkbox"]{ + margin-right: 0.5em; +} + +#tab_extensions button{ + max-width: 16em; +} + + /* The following handles localization for right-to-left (RTL) languages like Arabic. The rtl media type will only be activated by the logic in javascript/localization.js. If you change anything above, you need to make sure it is RTL compliant by just running @@ -607,4 +627,4 @@ Then, you will need to add the RTL counterpart only if needed in the rtl section right: unset; left: 0.5em; } -} +} \ No newline at end of file diff --git a/webui.py b/webui.py index 29530872..ad2eb236 100644 --- a/webui.py +++ b/webui.py @@ -9,7 +9,7 @@ from fastapi.middleware.gzip import GZipMiddleware from modules.paths import script_path -from modules import devices, sd_samplers, upscaler +from modules import devices, sd_samplers, upscaler, extensions import modules.codeformer_model as codeformer import modules.extras import modules.face_restoration @@ -60,6 +60,11 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): def initialize(): + extensions.list_extensions() + #for ext in extensions.extensions: + # print(ext.name, ext.path, ext.enabled, ext.remote) + #exit() + if cmd_opts.ui_debug_mode: shared.sd_upscalers = upscaler.UpscalerLanczos().scalers modules.scripts.load_scripts() @@ -92,15 +97,18 @@ def create_api(app): api = Api(app, queue_lock) return api + def wait_on_server(demo=None): while 1: time.sleep(0.5) - if demo and getattr(demo, 'do_restart', False): + if shared.state.need_restart: + shared.state.need_restart = False time.sleep(0.5) demo.close() time.sleep(0.5) break + def api_only(): initialize() @@ -132,14 +140,16 @@ def webui(): app.add_middleware(GZipMiddleware, minimum_size=1000) - if (launch_api): + if launch_api: create_api(app) wait_on_server(demo) sd_samplers.set_samplers() - print('Reloading Custom Scripts') + print('Reloading extensions') + extensions.list_extensions() + print('Reloading custom scripts') modules.scripts.reload_scripts() print('Reloading modules: modules.ui') importlib.reload(modules.ui) @@ -148,8 +158,6 @@ def webui(): print('Restarting Gradio') - -task = [] if __name__ == "__main__": if cmd_opts.nowebui: api_only() -- cgit v1.2.3 From 401350cd59555439570ba5bc95f0ac5698e372e4 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Tue, 1 Nov 2022 14:03:56 -0500 Subject: clear on the client-side again --- javascript/ui.js | 31 +++++++++++++++++++++---------- modules/ui.py | 9 +-------- 2 files changed, 22 insertions(+), 18 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index be47ec64..00e80fd6 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -142,22 +142,33 @@ function selected_tab_id() { } -function clear_prompt(_, _prompt_neg, confirmed, _token_counter) { -confirmed = false +function clear_prompt() { if(confirm("Delete prompt?")) { - confirmed = true -} else { -return [_, _prompt_neg, confirmed, _token_counter] -} - if(selected_tab_id() == "tab_txt2img") { - update_token_counter("img2img_token_button") + let pos_prompt = gradioApp().querySelector("#txt2img_prompt > label > textarea"); + let neg_prompt = gradioApp().querySelector("#txt2img_neg_prompt > label > textarea"); + + if (selected_tab_id() == "tab_txt2img") { } else { - update_token_counter("txt2img_token_button") + pos_prompt = gradioApp().querySelector("#img2img_prompt > label > textarea"); + neg_prompt = gradioApp().querySelector("#img2img_neg_prompt > label > textarea"); } - return [_, _prompt_neg, confirmed, _token_counter] + pos_prompt.value = "" + neg_prompt.value = "" + + //update prompt values on server-side + pos_prompt.dispatchEvent( + new Event("input", {bubbles: true}) + ) + neg_prompt.dispatchEvent( + new Event("input", {bubbles: true}) + ) + + return true +} else return false + } diff --git a/modules/ui.py b/modules/ui.py index 447722cd..f43e79ab 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -400,19 +400,12 @@ def create_seed_inputs(): return seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox -def clear_prompt(prompt, _prompt_neg, confirmed, _token_counter): - """Given confirmation from a user on the client-side, go ahead with clearing prompt""" - if confirmed: - return ["", "", confirmed, update_token_counter("", 1)] - else: - return [prompt, _prompt_neg, confirmed, _token_counter] - def connect_clear_prompt(button, prompt, prompt_neg, _dummy_confirmed, token_counter): """Given clear button, prompt, and token_counter objects, setup clear prompt button click event""" button.click( _js="clear_prompt", - fn=clear_prompt, + fn=None, inputs=[prompt, prompt_neg, _dummy_confirmed, token_counter], outputs=[prompt, prompt_neg, _dummy_confirmed, token_counter], ) -- cgit v1.2.3 From 1dd5d6bafad7575f347056a29636cbab71c1c468 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Tue, 1 Nov 2022 14:33:55 -0500 Subject: clean py func defs --- modules/ui.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index f43e79ab..8a1f3887 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -401,13 +401,13 @@ def create_seed_inputs(): -def connect_clear_prompt(button, prompt, prompt_neg, _dummy_confirmed, token_counter): +def connect_clear_prompt(button): """Given clear button, prompt, and token_counter objects, setup clear prompt button click event""" button.click( _js="clear_prompt", fn=None, - inputs=[prompt, prompt_neg, _dummy_confirmed, token_counter], - outputs=[prompt, prompt_neg, _dummy_confirmed, token_counter], + inputs=[], + outputs=[], ) @@ -746,7 +746,7 @@ def create_ui(wrap_gradio_gpu_call): connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) - connect_clear_prompt(clear_prompt_button, txt2img_prompt, txt2img_negative_prompt, dummy_component, token_counter) + connect_clear_prompt(clear_prompt_button) txt2img_args = dict( fn=wrap_gradio_gpu_call(modules.txt2img.txt2img), @@ -929,7 +929,7 @@ def create_ui(wrap_gradio_gpu_call): connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) - connect_clear_prompt(clear_prompt_button, img2img_prompt, img2img_negative_prompt, dummy_component, token_counter) + connect_clear_prompt(clear_prompt_button) img2img_prompt_img.change( fn=modules.images.image_data, -- cgit v1.2.3 From 86d35526a13a0e2432ab71d1d40b191615d3e343 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Tue, 1 Nov 2022 14:53:40 -0500 Subject: make line evil again --- modules/ui.py | 8 ++------ 1 file changed, 2 insertions(+), 6 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 8a1f3887..bd67c1bd 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -692,9 +692,7 @@ def create_ui(wrap_gradio_gpu_call): parameters_copypaste.reset() with gr.Blocks(analytics_enabled=False) as txt2img_interface: - txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _,\ - txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter,\ - token_button, clear_prompt_button = create_toprow(is_img2img=False) + txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _,txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button, clear_prompt_button = create_toprow(is_img2img=False) dummy_component = gr.Label(visible=False) txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False) @@ -850,9 +848,7 @@ def create_ui(wrap_gradio_gpu_call): token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter]) with gr.Blocks(analytics_enabled=False) as img2img_interface: - img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit,\ - img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,\ - token_counter, token_button, clear_prompt_button = create_toprow(is_img2img=True) + img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button, clear_prompt_button = create_toprow(is_img2img=True) with gr.Row(elem_id='img2img_progress_row'): -- cgit v1.2.3 From 5510c282b1f1974005790066b5e444f74a5178fb Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 2 Nov 2022 07:26:31 +0300 Subject: fix for extensions' javascript not loading --- modules/ui.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 2c15abb7..a94f46ea 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -671,6 +671,8 @@ def create_ui(wrap_gradio_gpu_call): import modules.img2img import modules.txt2img + reload_javascript() + parameters_copypaste.reset() with gr.Blocks(analytics_enabled=False) as txt2img_interface: @@ -1782,4 +1784,3 @@ def load_javascript(raw_response): reload_javascript = partial(load_javascript, gradio.routes.templates.TemplateResponse) -reload_javascript() -- cgit v1.2.3 From 95c6308ccd2e075d1fb804f5b98a4f0b07b87b7d Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 2 Nov 2022 09:47:53 +0300 Subject: switch to gradio 3.8 --- javascript/progressbar.js | 30 ++++++++++++++++++++++++------ modules/ui.py | 5 ++--- requirements.txt | 2 +- requirements_versions.txt | 2 +- style.css | 10 ++++++++++ 5 files changed, 38 insertions(+), 11 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/progressbar.js b/javascript/progressbar.js index 7a05726e..671fde34 100644 --- a/javascript/progressbar.js +++ b/javascript/progressbar.js @@ -3,8 +3,21 @@ global_progressbars = {} galleries = {} galleryObservers = {} +// this tracks laumnches of window.setTimeout for progressbar to prevent starting a new timeout when the previous is still running +timeoutIds = {} + function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_skip, id_interrupt, id_preview, id_gallery){ - var progressbar = gradioApp().getElementById(id_progressbar) + // gradio 3.8's enlightened approach allows them to create two nested div elements inside each other with same id + // every time you use gr.HTML(elem_id='xxx'), so we handle this here + var progressbar = gradioApp().querySelector("#"+id_progressbar+" #"+id_progressbar) + var progressbarParent + if(progressbar){ + progressbarParent = gradioApp().querySelector("#"+id_progressbar) + } else{ + progressbar = gradioApp().getElementById(id_progressbar) + progressbarParent = null + } + var skip = id_skip ? gradioApp().getElementById(id_skip) : null var interrupt = gradioApp().getElementById(id_interrupt) @@ -26,18 +39,26 @@ function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_skip global_progressbars[id_progressbar] = progressbar var mutationObserver = new MutationObserver(function(m){ + if(timeoutIds[id_part]) return; + preview = gradioApp().getElementById(id_preview) gallery = gradioApp().getElementById(id_gallery) if(preview != null && gallery != null){ preview.style.width = gallery.clientWidth + "px" preview.style.height = gallery.clientHeight + "px" + if(progressbarParent) progressbar.style.width = progressbarParent.clientWidth + "px" //only watch gallery if there is a generation process going on check_gallery(id_gallery); var progressDiv = gradioApp().querySelectorAll('#' + id_progressbar_span).length > 0; - if(!progressDiv){ + if(progressDiv){ + timeoutIds[id_part] = window.setTimeout(function() { + timeoutIds[id_part] = null + requestMoreProgress(id_part, id_progressbar_span, id_skip, id_interrupt) + }, 500) + } else{ if (skip) { skip.style.display = "none" } @@ -47,13 +68,10 @@ function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_skip if (galleryObservers[id_gallery]) { galleryObservers[id_gallery].disconnect(); galleries[id_gallery] = null; - } + } } - - } - window.setTimeout(function() { requestMoreProgress(id_part, id_progressbar_span, id_skip, id_interrupt) }, 500) }); mutationObserver.observe( progressbar, { childList:true, subtree:true }) } diff --git a/modules/ui.py b/modules/ui.py index a94f46ea..45cd8c3f 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1572,8 +1572,7 @@ def create_ui(wrap_gradio_gpu_call): reload_script_bodies.click( fn=reload_scripts, inputs=[], - outputs=[], - _js='function(){}' + outputs=[] ) def request_restart(): @@ -1585,7 +1584,7 @@ def create_ui(wrap_gradio_gpu_call): fn=request_restart, inputs=[], outputs=[], - _js='function(){restart_reload()}' + _js='restart_reload' ) if column is not None: diff --git a/requirements.txt b/requirements.txt index a53522f3..79e8b7c6 100644 --- a/requirements.txt +++ b/requirements.txt @@ -4,7 +4,7 @@ fairscale==0.4.4 fonts font-roboto gfpgan -gradio==3.5 +gradio==3.8 invisible-watermark numpy omegaconf diff --git a/requirements_versions.txt b/requirements_versions.txt index 41f2501f..7bd16712 100644 --- a/requirements_versions.txt +++ b/requirements_versions.txt @@ -2,7 +2,7 @@ transformers==4.19.2 diffusers==0.3.0 basicsr==1.4.2 gfpgan==1.3.8 -gradio==3.5 +gradio==3.8 numpy==1.23.3 Pillow==9.2.0 realesrgan==0.3.0 diff --git a/style.css b/style.css index dfef0dc5..e53079e0 100644 --- a/style.css +++ b/style.css @@ -260,6 +260,16 @@ input[type="range"]{ #txt2img_negative_prompt, #img2img_negative_prompt{ } +/* gradio 3.8 adds opacity to progressbar which makes it blink; disable it here */ +.transition.opacity-20 { + opacity: 1 !important; +} + +/* more gradio's garbage cleanup */ +.min-h-\[4rem\] { + min-height: unset !important; +} + #txt2img_progressbar, #img2img_progressbar, #ti_progressbar{ position: absolute; z-index: 1000; -- cgit v1.2.3 From 4a8cf01f6f7f072cc9c67d6b31662384b212dd9c Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 2 Nov 2022 12:12:32 +0300 Subject: remove duplicate code from #3970 --- modules/api/api.py | 10 +--------- modules/shared.py | 14 ++++++++++++++ modules/ui.py | 10 +--------- 3 files changed, 16 insertions(+), 18 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/api/api.py b/modules/api/api.py index b3d85e46..71c9c160 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -178,15 +178,7 @@ class Api: progress = min(progress, 1) - # copy from check_progress_call of ui.py - - if shared.parallel_processing_allowed: - if shared.state.sampling_step - shared.state.current_image_sampling_step >= shared.opts.show_progress_every_n_steps and shared.state.current_latent is not None: - if shared.opts.show_progress_grid: - shared.state.current_image = samples_to_image_grid(shared.state.current_latent) - else: - shared.state.current_image = sample_to_image(shared.state.current_latent) - shared.state.current_image_sampling_step = shared.state.sampling_step + shared.state.set_current_image() current_image = None if shared.state.current_image and not req.skip_current_image: diff --git a/modules/shared.py b/modules/shared.py index 04aaa648..e65f6080 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -184,6 +184,20 @@ class State: devices.torch_gc() + """sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this""" + def set_current_image(self): + if not parallel_processing_allowed: + return + + if self.sampling_step - self.current_image_sampling_step >= opts.show_progress_every_n_steps and self.current_latent is not None: + if opts.show_progress_grid: + self.current_image = sd_samplers.samples_to_image_grid(self.current_latent) + else: + self.current_image = sd_samplers.sample_to_image(self.current_latent) + + self.current_image_sampling_step = self.sampling_step + + state = State() artist_db = modules.artists.ArtistsDatabase(os.path.join(script_path, 'artists.csv')) diff --git a/modules/ui.py b/modules/ui.py index 45cd8c3f..784439ba 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -277,15 +277,7 @@ def check_progress_call(id_part): preview_visibility = gr_show(False) if opts.show_progress_every_n_steps > 0: - if shared.parallel_processing_allowed: - - if shared.state.sampling_step - shared.state.current_image_sampling_step >= opts.show_progress_every_n_steps and shared.state.current_latent is not None: - if opts.show_progress_grid: - shared.state.current_image = modules.sd_samplers.samples_to_image_grid(shared.state.current_latent) - else: - shared.state.current_image = modules.sd_samplers.sample_to_image(shared.state.current_latent) - shared.state.current_image_sampling_step = shared.state.sampling_step - + shared.state.set_current_image() image = shared.state.current_image if image is None: -- cgit v1.2.3 From f1b6ac64e451036fb4dfabe66d79488c56c06776 Mon Sep 17 00:00:00 2001 From: Kyu♥ <3ad4gum@gmail.com> Date: Wed, 2 Nov 2022 17:24:42 +0100 Subject: Added option to preview Created images on batch completion. --- modules/shared.py | 25 ++++++++++++++++--------- modules/ui.py | 2 +- 2 files changed, 17 insertions(+), 10 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/shared.py b/modules/shared.py index d8e99f85..d4cf32a4 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -146,6 +146,9 @@ class State: self.interrupted = True def nextjob(self): + if opts.show_progress_every_n_steps == -1: + self.do_set_current_image() + self.job_no += 1 self.sampling_step = 0 self.current_image_sampling_step = 0 @@ -186,17 +189,21 @@ class State: """sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this""" def set_current_image(self): + if self.sampling_step - self.current_image_sampling_step >= opts.show_progress_every_n_steps and opts.show_progress_every_n_steps > 0: + self.do_set_current_image() + + def do_set_current_image(self): if not parallel_processing_allowed: return + if self.current_latent is None: + return + + if opts.show_progress_grid: + self.current_image = sd_samplers.samples_to_image_grid(self.current_latent) + else: + self.current_image = sd_samplers.sample_to_image(self.current_latent) - if self.sampling_step - self.current_image_sampling_step >= opts.show_progress_every_n_steps and self.current_latent is not None: - if opts.show_progress_grid: - self.current_image = sd_samplers.samples_to_image_grid(self.current_latent) - else: - self.current_image = sd_samplers.sample_to_image(self.current_latent) - - self.current_image_sampling_step = self.sampling_step - + self.current_image_sampling_step = self.sampling_step state = State() @@ -351,7 +358,7 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"), options_templates.update(options_section(('ui', "User interface"), { "show_progressbar": OptionInfo(True, "Show progressbar"), - "show_progress_every_n_steps": OptionInfo(0, "Show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}), + "show_progress_every_n_steps": OptionInfo(0, "Show image creation progress every N sampling steps. Set to 0 to disable. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}), "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"), "return_grid": OptionInfo(True, "Show grid in results for web"), "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"), diff --git a/modules/ui.py b/modules/ui.py index 2609857e..29de1e10 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -276,7 +276,7 @@ def check_progress_call(id_part): image = gr_show(False) preview_visibility = gr_show(False) - if opts.show_progress_every_n_steps > 0: + if opts.show_progress_every_n_steps != 0: shared.state.set_current_image() image = shared.state.current_image -- cgit v1.2.3 From e533ff61c1baa4ad047f9c8dc05c17b64ee89ddf Mon Sep 17 00:00:00 2001 From: timntorres Date: Thu, 3 Nov 2022 22:28:22 -0700 Subject: Lift extras generate button a la #4246. --- modules/ui.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 2609857e..6461002a 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1052,6 +1052,8 @@ def create_ui(wrap_gradio_gpu_call): extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, placeholder="Leave blank to save images to the default path.") show_extras_results = gr.Checkbox(label='Show result images', value=True) + submit = gr.Button('Generate', elem_id="extras_generate", variant='primary') + with gr.Tabs(elem_id="extras_resize_mode"): with gr.TabItem('Scale by'): upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4) @@ -1079,8 +1081,6 @@ def create_ui(wrap_gradio_gpu_call): with gr.Group(): upscale_before_face_fix = gr.Checkbox(label='Upscale Before Restoring Faces', value=False) - submit = gr.Button('Generate', elem_id="extras_generate", variant='primary') - result_images, html_info_x, html_info = create_output_panel("extras", opts.outdir_extras_samples) submit.click( -- cgit v1.2.3 From f2b69709eaff88fc3a2bd49585556ec0883bf5ea Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 4 Nov 2022 09:42:25 +0300 Subject: move option access checking to options class out of various places scattered through code --- modules/processing.py | 4 ++-- modules/shared.py | 11 +++++++++++ modules/ui.py | 20 +++++--------------- 3 files changed, 18 insertions(+), 17 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/processing.py b/modules/processing.py index 2168208c..a46e592d 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -418,13 +418,13 @@ def process_images(p: StableDiffusionProcessing) -> Processed: try: for k, v in p.override_settings.items(): - opts.data[k] = v # we don't call onchange for simplicity which makes changing model, hypernet impossible + setattr(opts, k, v) # we don't call onchange for simplicity which makes changing model, hypernet impossible res = process_images_inner(p) finally: for k, v in stored_opts.items(): - opts.data[k] = v + setattr(opts, k, v) return res diff --git a/modules/shared.py b/modules/shared.py index d8e99f85..024c771a 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -396,6 +396,15 @@ class Options: def __setattr__(self, key, value): if self.data is not None: if key in self.data or key in self.data_labels: + assert not cmd_opts.freeze_settings, "changing settings is disabled" + + comp_args = opts.data_labels[key].component_args + if isinstance(comp_args, dict) and comp_args.get('visible', True) is False: + raise RuntimeError(f"not possible to set {key} because it is restricted") + + if cmd_opts.hide_ui_dir_config and key in restricted_opts: + raise RuntimeError(f"not possible to set {key} because it is restricted") + self.data[key] = value return @@ -412,6 +421,8 @@ class Options: return super(Options, self).__getattribute__(item) def save(self, filename): + assert not cmd_opts.freeze_settings, "saving settings is disabled" + with open(filename, "w", encoding="utf8") as file: json.dump(self.data, file, indent=4) diff --git a/modules/ui.py b/modules/ui.py index b2b1c854..633b56ef 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1438,8 +1438,6 @@ def create_ui(wrap_gradio_gpu_call): def run_settings(*args): changed = 0 - assert not shared.cmd_opts.freeze_settings, "changing settings is disabled" - for key, value, comp in zip(opts.data_labels.keys(), args, components): if comp != dummy_component and not opts.same_type(value, opts.data_labels[key].default): return f"Bad value for setting {key}: {value}; expecting {type(opts.data_labels[key].default).__name__}", opts.dumpjson() @@ -1448,15 +1446,9 @@ def create_ui(wrap_gradio_gpu_call): if comp == dummy_component: continue - comp_args = opts.data_labels[key].component_args - if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False: - continue - - if cmd_opts.hide_ui_dir_config and key in restricted_opts: - continue - oldval = opts.data.get(key, None) - opts.data[key] = value + + setattr(opts, key, value) if oldval != value: if opts.data_labels[key].onchange is not None: @@ -1469,17 +1461,15 @@ def create_ui(wrap_gradio_gpu_call): return f'{changed} settings changed.', opts.dumpjson() def run_settings_single(value, key): - assert not shared.cmd_opts.freeze_settings, "changing settings is disabled" - if not opts.same_type(value, opts.data_labels[key].default): return gr.update(visible=True), opts.dumpjson() oldval = opts.data.get(key, None) - if cmd_opts.hide_ui_dir_config and key in restricted_opts: + try: + setattr(opts, key, value) + except Exception: return gr.update(value=oldval), opts.dumpjson() - opts.data[key] = value - if oldval != value: if opts.data_labels[key].onchange is not None: opts.data_labels[key].onchange() -- cgit v1.2.3 From 321e13ca176b256177c4a752d1f2bbee79b5532e Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 4 Nov 2022 10:35:30 +0300 Subject: produce a readable error message when setting an option fails on the settings screen --- modules/ui.py | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 633b56ef..3ac7540c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1439,8 +1439,7 @@ def create_ui(wrap_gradio_gpu_call): changed = 0 for key, value, comp in zip(opts.data_labels.keys(), args, components): - if comp != dummy_component and not opts.same_type(value, opts.data_labels[key].default): - return f"Bad value for setting {key}: {value}; expecting {type(opts.data_labels[key].default).__name__}", opts.dumpjson() + assert comp == dummy_component or opts.same_type(value, opts.data_labels[key].default), f"Bad value for setting {key}: {value}; expecting {type(opts.data_labels[key].default).__name__}" for key, value, comp in zip(opts.data_labels.keys(), args, components): if comp == dummy_component: @@ -1458,7 +1457,7 @@ def create_ui(wrap_gradio_gpu_call): opts.save(shared.config_filename) - return f'{changed} settings changed.', opts.dumpjson() + return opts.dumpjson(), f'{changed} settings changed.' def run_settings_single(value, key): if not opts.same_type(value, opts.data_labels[key].default): @@ -1622,9 +1621,9 @@ def create_ui(wrap_gradio_gpu_call): text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False) settings_submit.click( - fn=run_settings, + fn=wrap_gradio_call(run_settings, extra_outputs=[gr.update()]), inputs=components, - outputs=[result, text_settings], + outputs=[text_settings, result], ) for i, k, item in quicksettings_list: -- cgit v1.2.3 From 467d8b967b5d1b1984ab113bec3fff217736e7ac Mon Sep 17 00:00:00 2001 From: AngelBottomless <35677394+aria1th@users.noreply.github.com> Date: Sat, 5 Nov 2022 04:24:42 +0900 Subject: Fix errors from commit f2b697 with --hide-ui-dir-config https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/f2b69709eaff88fc3a2bd49585556ec0883bf5ea --- modules/ui.py | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 4c2829af..76ca9b07 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1446,17 +1446,19 @@ def create_ui(wrap_gradio_gpu_call): continue oldval = opts.data.get(key, None) - - setattr(opts, key, value) - + try: + setattr(opts, key, value) + except RuntimeError: + continue if oldval != value: if opts.data_labels[key].onchange is not None: opts.data_labels[key].onchange() changed += 1 - - opts.save(shared.config_filename) - + try: + opts.save(shared.config_filename) + except RuntimeError: + return opts.dumpjson(), f'{changed} settings changed without save.' return opts.dumpjson(), f'{changed} settings changed.' def run_settings_single(value, key): -- cgit v1.2.3 From a2a1a2f7270a865175f64475229838a8d64509ea Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 6 Nov 2022 09:02:25 +0300 Subject: add ability to create extensions that add localizations --- javascript/ui.js | 2 ++ modules/localization.py | 6 ++++++ modules/scripts.py | 1 - modules/shared.py | 2 -- modules/ui.py | 3 +-- webui.py | 9 +++++---- 6 files changed, 14 insertions(+), 9 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index 7e116465..95cfd106 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -208,4 +208,6 @@ function update_token_counter(button_id) { function restart_reload(){ document.body.innerHTML='

Reloading...

'; setTimeout(function(){location.reload()},2000) + + return [] } diff --git a/modules/localization.py b/modules/localization.py index b1810cda..f6a6f2fb 100644 --- a/modules/localization.py +++ b/modules/localization.py @@ -3,6 +3,7 @@ import os import sys import traceback + localizations = {} @@ -16,6 +17,11 @@ def list_localizations(dirname): localizations[fn] = os.path.join(dirname, file) + from modules import scripts + for file in scripts.list_scripts("localizations", ".json"): + fn, ext = os.path.splitext(file.filename) + localizations[fn] = file.path + def localization_js(current_localization_name): fn = localizations.get(current_localization_name, None) diff --git a/modules/scripts.py b/modules/scripts.py index 366c90d7..637b2329 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -3,7 +3,6 @@ import sys import traceback from collections import namedtuple -import modules.ui as ui import gradio as gr from modules.processing import StableDiffusionProcessing diff --git a/modules/shared.py b/modules/shared.py index 70b998ff..e8bacd3c 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -221,8 +221,6 @@ interrogator = modules.interrogate.InterrogateModels("interrogate") face_restorers = [] -localization.list_localizations(cmd_opts.localizations_dir) - def realesrgan_models_names(): import modules.realesrgan_model diff --git a/modules/ui.py b/modules/ui.py index 76ca9b07..23643c22 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1563,11 +1563,10 @@ def create_ui(wrap_gradio_gpu_call): shared.state.need_restart = True restart_gradio.click( - fn=request_restart, + _js='restart_reload', inputs=[], outputs=[], - _js='restart_reload' ) if column is not None: diff --git a/webui.py b/webui.py index a5a520f0..4342a962 100644 --- a/webui.py +++ b/webui.py @@ -10,7 +10,7 @@ from fastapi.middleware.gzip import GZipMiddleware from modules.paths import script_path -from modules import devices, sd_samplers, upscaler, extensions +from modules import devices, sd_samplers, upscaler, extensions, localization import modules.codeformer_model as codeformer import modules.extras import modules.face_restoration @@ -28,9 +28,7 @@ import modules.txt2img import modules.script_callbacks import modules.ui -from modules import devices from modules import modelloader -from modules.paths import script_path from modules.shared import cmd_opts import modules.hypernetworks.hypernetwork @@ -64,6 +62,7 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): def initialize(): extensions.list_extensions() + localization.list_localizations(cmd_opts.localizations_dir) if cmd_opts.ui_debug_mode: shared.sd_upscalers = upscaler.UpscalerLanczos().scalers @@ -99,7 +98,6 @@ def initialize(): else: print("Running with TLS") - # make the program just exit at ctrl+c without waiting for anything def sigint_handler(sig, frame): print(f'Interrupted with signal {sig} in {frame}') @@ -185,6 +183,9 @@ def webui(): print('Reloading extensions') extensions.list_extensions() + + localization.list_localizations(cmd_opts.localizations_dir) + print('Reloading custom scripts') modules.scripts.reload_scripts() print('Reloading modules: modules.ui') -- cgit v1.2.3 From e5b4e3f820cd09e751f1d168ab05d606d078a0d9 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 6 Nov 2022 10:12:53 +0300 Subject: add tags to extensions, and ability to filter out tags list changed Settings keys in UI do not print VRAM/etc stats everywhere but in calls that use GPU --- modules/ui.py | 25 ++++++++++++---------- modules/ui_extensions.py | 55 ++++++++++++++++++++++++++++++++++++++---------- style.css | 5 +++++ webui.py | 2 +- 4 files changed, 64 insertions(+), 23 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 23643c22..c946ad59 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -174,9 +174,9 @@ def save_pil_to_file(pil_image, dir=None): gr.processing_utils.save_pil_to_file = save_pil_to_file -def wrap_gradio_call(func, extra_outputs=None): +def wrap_gradio_call(func, extra_outputs=None, add_stats=False): def f(*args, extra_outputs_array=extra_outputs, **kwargs): - run_memmon = opts.memmon_poll_rate > 0 and not shared.mem_mon.disabled + run_memmon = opts.memmon_poll_rate > 0 and not shared.mem_mon.disabled and add_stats if run_memmon: shared.mem_mon.monitor() t = time.perf_counter() @@ -203,11 +203,18 @@ def wrap_gradio_call(func, extra_outputs=None): res = extra_outputs_array + [f"
{plaintext_to_html(type(e).__name__+': '+str(e))}
"] + shared.state.skipped = False + shared.state.interrupted = False + shared.state.job_count = 0 + + if not add_stats: + return tuple(res) + elapsed = time.perf_counter() - t elapsed_m = int(elapsed // 60) elapsed_s = elapsed % 60 elapsed_text = f"{elapsed_s:.2f}s" - if (elapsed_m > 0): + if elapsed_m > 0: elapsed_text = f"{elapsed_m}m "+elapsed_text if run_memmon: @@ -225,10 +232,6 @@ def wrap_gradio_call(func, extra_outputs=None): # last item is always HTML res[-1] += f"

Time taken: {elapsed_text}

{vram_html}
" - shared.state.skipped = False - shared.state.interrupted = False - shared.state.job_count = 0 - return tuple(res) return f @@ -1436,7 +1439,7 @@ def create_ui(wrap_gradio_gpu_call): opts.reorder() def run_settings(*args): - changed = 0 + changed = [] for key, value, comp in zip(opts.data_labels.keys(), args, components): assert comp == dummy_component or opts.same_type(value, opts.data_labels[key].default), f"Bad value for setting {key}: {value}; expecting {type(opts.data_labels[key].default).__name__}" @@ -1454,12 +1457,12 @@ def create_ui(wrap_gradio_gpu_call): if opts.data_labels[key].onchange is not None: opts.data_labels[key].onchange() - changed += 1 + changed.append(key) try: opts.save(shared.config_filename) except RuntimeError: - return opts.dumpjson(), f'{changed} settings changed without save.' - return opts.dumpjson(), f'{changed} settings changed.' + return opts.dumpjson(), f'{len(changed)} settings changed without save: {", ".join(changed)}.' + return opts.dumpjson(), f'{len(changed)} settings changed: {", ".join(changed)}.' def run_settings_single(value, key): if not opts.same_type(value, opts.data_labels[key].default): diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index 8e0d41d5..02ab9643 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -140,13 +140,15 @@ def install_extension_from_url(dirname, url): shutil.rmtree(tmpdir, True) -def install_extension_from_index(url): +def install_extension_from_index(url, hide_tags): ext_table, message = install_extension_from_url(None, url) - return refresh_available_extensions_from_data(), ext_table, message + code, _ = refresh_available_extensions_from_data(hide_tags) + return code, ext_table, message -def refresh_available_extensions(url): + +def refresh_available_extensions(url, hide_tags): global available_extensions import urllib.request @@ -155,13 +157,25 @@ def refresh_available_extensions(url): available_extensions = json.loads(text) - return url, refresh_available_extensions_from_data(), '' + code, tags = refresh_available_extensions_from_data(hide_tags) + + return url, code, gr.CheckboxGroup.update(choices=tags), '' + + +def refresh_available_extensions_for_tags(hide_tags): + code, _ = refresh_available_extensions_from_data(hide_tags) + return code, '' -def refresh_available_extensions_from_data(): + +def refresh_available_extensions_from_data(hide_tags): extlist = available_extensions["extensions"] installed_extension_urls = {normalize_git_url(extension.remote): extension.name for extension in extensions.extensions} + tags = available_extensions.get("tags", {}) + tags_to_hide = set(hide_tags) + hidden = 0 + code = f""" @@ -178,17 +192,24 @@ def refresh_available_extensions_from_data(): name = ext.get("name", "noname") url = ext.get("url", None) description = ext.get("description", "") + extension_tags = ext.get("tags", []) if url is None: continue + if len([x for x in extension_tags if x in tags_to_hide]) > 0: + hidden += 1 + continue + existing = installed_extension_urls.get(normalize_git_url(url), None) install_code = f"""""" + tags_text = ", ".join([f"{x}" for x in extension_tags]) + code += f""" - + @@ -199,7 +220,10 @@ def refresh_available_extensions_from_data():
{html.escape(name)}{html.escape(name)}
{tags_text}		 {html.escape(description)} {install_code}
""" - return code + if hidden > 0: + code += f"

Extension hidden: {hidden}

" + + return code, list(tags) def create_ui(): @@ -238,21 +262,30 @@ def create_ui(): extension_to_install = gr.Text(elem_id="extension_to_install", visible=False) install_extension_button = gr.Button(elem_id="install_extension_button", visible=False) + with gr.Row(): + hide_tags = gr.CheckboxGroup(value=["ads", "localization"], label="Hide extensions with tags", choices=["script", "ads", "localization"]) + install_result = gr.HTML() available_extensions_table = gr.HTML() refresh_available_extensions_button.click( - fn=modules.ui.wrap_gradio_call(refresh_available_extensions, extra_outputs=[gr.update(), gr.update()]), - inputs=[available_extensions_index], - outputs=[available_extensions_index, available_extensions_table, install_result], + fn=modules.ui.wrap_gradio_call(refresh_available_extensions, extra_outputs=[gr.update(), gr.update(), gr.update()]), + inputs=[available_extensions_index, hide_tags], + outputs=[available_extensions_index, available_extensions_table, hide_tags, install_result], ) install_extension_button.click( fn=modules.ui.wrap_gradio_call(install_extension_from_index, extra_outputs=[gr.update(), gr.update()]), - inputs=[extension_to_install], + inputs=[extension_to_install, hide_tags], outputs=[available_extensions_table, extensions_table, install_result], ) + hide_tags.change( + fn=modules.ui.wrap_gradio_call(refresh_available_extensions_for_tags, extra_outputs=[gr.update()]), + inputs=[hide_tags], + outputs=[available_extensions_table, install_result] + ) + with gr.TabItem("Install from URL"): install_url = gr.Text(label="URL for extension's git repository") install_dirname = gr.Text(label="Local directory name", placeholder="Leave empty for auto") diff --git a/style.css b/style.css index a0382a8c..e2b71f25 100644 --- a/style.css +++ b/style.css @@ -563,6 +563,11 @@ img2maskimg, #img2maskimg > .h-60, #img2maskimg > .h-60 > div, #img2maskimg > .h opacity: 0.5; } +.extension-tag{ + font-weight: bold; + font-size: 95%; +} + /* The following handles localization for right-to-left (RTL) languages like Arabic. The rtl media type will only be activated by the logic in javascript/localization.js. If you change anything above, you need to make sure it is RTL compliant by just running diff --git a/webui.py b/webui.py index 4342a962..f4f1d74d 100644 --- a/webui.py +++ b/webui.py @@ -57,7 +57,7 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): return res - return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs) + return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs, add_stats=True) def initialize(): -- cgit v1.2.3 From 32c0eab89538ba3900bf499291720f80ae4b43e5 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 6 Nov 2022 14:39:41 +0300 Subject: load all settings in one call instead of one by one when the page loads --- modules/ui.py | 22 ++++++++++++++++------ 1 file changed, 16 insertions(+), 6 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index c946ad59..34c31ef1 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1141,7 +1141,7 @@ def create_ui(wrap_gradio_gpu_call): outputs=[html, generation_info, html2], ) - with gr.Blocks() as modelmerger_interface: + with gr.Blocks(analytics_enabled=False) as modelmerger_interface: with gr.Row().style(equal_height=False): with gr.Column(variant='panel'): gr.HTML(value="

A merger of the two checkpoints will be generated in your checkpoint directory.

") @@ -1161,7 +1161,7 @@ def create_ui(wrap_gradio_gpu_call): sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings() - with gr.Blocks() as train_interface: + with gr.Blocks(analytics_enabled=False) as train_interface: with gr.Row().style(equal_height=False): gr.HTML(value="

See wiki for detailed explanation.

") @@ -1420,15 +1420,14 @@ def create_ui(wrap_gradio_gpu_call): if info.refresh is not None: if is_quicksettings: - res = comp(label=info.label, value=fun, elem_id=elem_id, **(args or {})) + res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {})) create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key) else: with gr.Row(variant="compact"): - res = comp(label=info.label, value=fun, elem_id=elem_id, **(args or {})) + res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {})) create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key) else: - res = comp(label=info.label, value=fun, elem_id=elem_id, **(args or {})) - + res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {})) return res @@ -1639,6 +1638,17 @@ def create_ui(wrap_gradio_gpu_call): outputs=[component, text_settings], ) + component_keys = [k for k in opts.data_labels.keys() if k in component_dict] + + def get_settings_values(): + return [getattr(opts, key) for key in component_keys] + + demo.load( + fn=get_settings_values, + inputs=[], + outputs=[component_dict[k] for k in component_keys], + ) + def modelmerger(*args): try: results = modules.extras.run_modelmerger(*args) -- cgit v1.2.3 From 9ed4a126bd6421f91bf4a9bdd348b6aef0a378c6 Mon Sep 17 00:00:00 2001 From: kavorite Date: Mon, 7 Nov 2022 19:58:49 -0500 Subject: add gradio-inpaint-tool; color-sketch --- modules/img2img.py | 19 +++++++++++++------ modules/shared.py | 1 + modules/ui.py | 11 ++++++++++- 3 files changed, 24 insertions(+), 7 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/img2img.py b/modules/img2img.py index be9f3653..00c6f827 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -59,18 +59,25 @@ def process_batch(p, input_dir, output_dir, args): processed_image.save(os.path.join(output_dir, filename)) -def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, init_img_with_mask, init_img_inpaint, init_mask_inpaint, mask_mode, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args): +def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, init_img_with_mask, init_img_with_mask_orig, init_img_inpaint, init_mask_inpaint, mask_mode, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args): is_inpaint = mode == 1 is_batch = mode == 2 if is_inpaint: # Drawn mask if mask_mode == 0: - image = init_img_with_mask['image'] - mask = init_img_with_mask['mask'] - alpha_mask = ImageOps.invert(image.split()[-1]).convert('L').point(lambda x: 255 if x > 0 else 0, mode='1') - mask = ImageChops.lighter(alpha_mask, mask.convert('L')).convert('L') - image = image.convert('RGB') + image = init_img_with_mask + is_mask_sketch = isinstance(image, dict) + if is_mask_sketch: + # Sketch: mask iff. not transparent + image, mask = image["image"], image["mask"] + mask = np.array(mask)[..., -1] > 0 + else: + # Color-sketch: mask iff. painted over + orig = init_img_with_mask_orig or image + mask = np.any(np.array(image) != np.array(orig), axis=-1) + mask = Image.fromarray(mask.astype(np.uint8) * 255, "L") + image = image.convert("RGB") # Uploaded mask else: image = init_img_inpaint diff --git a/modules/shared.py b/modules/shared.py index d8e99f85..325e37d9 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -71,6 +71,7 @@ parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui parser.add_argument("--gradio-debug", action='store_true', help="launch gradio with --debug option") parser.add_argument("--gradio-auth", type=str, help='set gradio authentication like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3"', default=None) parser.add_argument("--gradio-img2img-tool", type=str, help='gradio image uploader tool: can be either editor for ctopping, or color-sketch for drawing', choices=["color-sketch", "editor"], default="editor") +parser.add_argument("--gradio-inpaint-tool", type=str, choices=["sketch", "color-sketch"], default="sketch", help="gradio inpainting editor: can be either sketch to only blur/noise the input, or color-sketch to paint over it") parser.add_argument("--opt-channelslast", action='store_true', help="change memory type for stable diffusion to channels last") parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(script_path, 'styles.csv')) parser.add_argument("--autolaunch", action='store_true', help="open the webui URL in the system's default browser upon launch", default=False) diff --git a/modules/ui.py b/modules/ui.py index 2609857e..db323e9c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -840,8 +840,17 @@ def create_ui(wrap_gradio_gpu_call): init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_img2img_tool).style(height=480) with gr.TabItem('Inpaint', id='inpaint'): - init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA").style(height=480) + init_img_with_mask_orig = gr.State(None) + init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_inpaint_tool, image_mode="RGBA").style(height=480) + def update_orig(image, state): + if image is not None: + same_size = state is not None and state.size == image.size + has_exact_match = np.any(np.all(np.array(image) == np.array(state), axis=-1)) + edited = same_size and has_exact_match + return image if not edited or state is None else state + + init_img_with_mask.change(update_orig, [init_img_with_mask, init_img_with_mask_orig], init_img_with_mask_orig) init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_base") init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_mask") -- cgit v1.2.3 From c5334fc56b3d44976425da2e6d0a303ae96836a1 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 8 Nov 2022 08:35:01 +0300 Subject: fix javascript duplication bug after pressing the restart UI button --- modules/ui.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 34c31ef1..67cf1d6a 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1752,7 +1752,7 @@ def create_ui(wrap_gradio_gpu_call): return demo -def load_javascript(raw_response): +def reload_javascript(): with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile: javascript = f'' @@ -1768,7 +1768,7 @@ def load_javascript(raw_response): javascript += f"\n" def template_response(*args, **kwargs): - res = raw_response(*args, **kwargs) + res = shared.GradioTemplateResponseOriginal(*args, **kwargs) res.body = res.body.replace( b'', f'{javascript}'.encode("utf8")) res.init_headers() @@ -1777,4 +1777,5 @@ def load_javascript(raw_response): gradio.routes.templates.TemplateResponse = template_response -reload_javascript = partial(load_javascript, gradio.routes.templates.TemplateResponse) +if not hasattr(shared, 'GradioTemplateResponseOriginal'): + shared.GradioTemplateResponseOriginal = gradio.routes.templates.TemplateResponse -- cgit v1.2.3 From 1610b3258458025025e9c4faae57d290e4519745 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 8 Nov 2022 08:38:10 +0300 Subject: add callback for creating a tab in train UI --- modules/script_callbacks.py | 27 +++++++++++++++++++++++++-- modules/ui.py | 4 ++++ 2 files changed, 29 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index 74dfb880..f19e164c 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -7,6 +7,7 @@ from typing import Optional from fastapi import FastAPI from gradio import Blocks + def report_exception(c, job): print(f"Error executing callback {job} for {c.script}", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) @@ -45,15 +46,21 @@ class CFGDenoiserParams: """Total number of sampling steps planned""" +class UiTrainTabParams: + def __init__(self, txt2img_preview_params): + self.txt2img_preview_params = txt2img_preview_params + + ScriptCallback = namedtuple("ScriptCallback", ["script", "callback"]) callback_map = dict( callbacks_app_started=[], callbacks_model_loaded=[], callbacks_ui_tabs=[], + callbacks_ui_train_tabs=[], callbacks_ui_settings=[], callbacks_before_image_saved=[], callbacks_image_saved=[], - callbacks_cfg_denoiser=[] + callbacks_cfg_denoiser=[], ) @@ -61,6 +68,7 @@ def clear_callbacks(): for callback_list in callback_map.values(): callback_list.clear() + def app_started_callback(demo: Optional[Blocks], app: FastAPI): for c in callback_map['callbacks_app_started']: try: @@ -79,7 +87,7 @@ def model_loaded_callback(sd_model): def ui_tabs_callback(): res = [] - + for c in callback_map['callbacks_ui_tabs']: try: res += c.callback() or [] @@ -89,6 +97,14 @@ def ui_tabs_callback(): return res +def ui_train_tabs_callback(params: UiTrainTabParams): + for c in callback_map['callbacks_ui_train_tabs']: + try: + c.callback(params) + except Exception: + report_exception(c, 'callbacks_ui_train_tabs') + + def ui_settings_callback(): for c in callback_map['callbacks_ui_settings']: try: @@ -169,6 +185,13 @@ def on_ui_tabs(callback): add_callback(callback_map['callbacks_ui_tabs'], callback) +def on_ui_train_tabs(callback): + """register a function to be called when the UI is creating new tabs for the train tab. + Create your new tabs with gr.Tab. + """ + add_callback(callback_map['callbacks_ui_train_tabs'], callback) + + def on_ui_settings(callback): """register a function to be called before UI settings are populated; add your settings by using shared.opts.add_option(shared.OptionInfo(...)) """ diff --git a/modules/ui.py b/modules/ui.py index 67cf1d6a..7ea1177f 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1270,6 +1270,10 @@ def create_ui(wrap_gradio_gpu_call): train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary') train_embedding = gr.Button(value="Train Embedding", variant='primary') + params = script_callbacks.UiTrainTabParams(txt2img_preview_params) + + script_callbacks.ui_train_tabs_callback(params) + with gr.Column(): progressbar = gr.HTML(elem_id="ti_progressbar") ti_output = gr.Text(elem_id="ti_output", value="", show_label=False) -- cgit v1.2.3 From c34542a48376e4972de955aab00ffc8359f7d792 Mon Sep 17 00:00:00 2001 From: kavorite Date: Tue, 8 Nov 2022 03:25:59 -0500 Subject: add new color-sketch state to img2img invocation --- modules/ui.py | 1 + 1 file changed, 1 insertion(+) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index db323e9c..29954f2a 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -941,6 +941,7 @@ def create_ui(wrap_gradio_gpu_call): img2img_prompt_style2, init_img, init_img_with_mask, + init_img_with_mask_orig, init_img_inpaint, init_mask_inpaint, mask_mode, -- cgit v1.2.3 From 59bb1d36ea69db449cfe23be4988ab4f6711bf4b Mon Sep 17 00:00:00 2001 From: kavorite Date: Tue, 8 Nov 2022 22:06:29 -0500 Subject: blur mask with color-sketch + add paint transparency slider --- modules/img2img.py | 21 +++++++++++++-------- modules/ui.py | 3 +++ 2 files changed, 16 insertions(+), 8 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/img2img.py b/modules/img2img.py index 00c6f827..644297da 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -4,7 +4,7 @@ import sys import traceback import numpy as np -from PIL import Image, ImageOps, ImageChops +from PIL import Image, ImageOps, ImageFilter, ImageEnhance from modules import devices from modules.processing import Processed, StableDiffusionProcessingImg2Img, process_images @@ -40,7 +40,7 @@ def process_batch(p, input_dir, output_dir, args): img = Image.open(image) # Use the EXIF orientation of photos taken by smartphones. - img = ImageOps.exif_transpose(img) + img = ImageOps.exif_transpose(img) p.init_images = [img] * p.batch_size proc = modules.scripts.scripts_img2img.run(p, *args) @@ -59,7 +59,7 @@ def process_batch(p, input_dir, output_dir, args): processed_image.save(os.path.join(output_dir, filename)) -def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, init_img_with_mask, init_img_with_mask_orig, init_img_inpaint, init_mask_inpaint, mask_mode, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args): +def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, init_img_with_mask, init_img_with_mask_orig, init_img_inpaint, init_mask_inpaint, mask_mode, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args): is_inpaint = mode == 1 is_batch = mode == 2 @@ -68,15 +68,20 @@ def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, pro if mask_mode == 0: image = init_img_with_mask is_mask_sketch = isinstance(image, dict) - if is_mask_sketch: + is_mask_paint = not is_mask_sketch + if is_mask_sketch: # Sketch: mask iff. not transparent image, mask = image["image"], image["mask"] - mask = np.array(mask)[..., -1] > 0 + pred = np.array(mask)[..., -1] > 0 else: # Color-sketch: mask iff. painted over orig = init_img_with_mask_orig or image - mask = np.any(np.array(image) != np.array(orig), axis=-1) - mask = Image.fromarray(mask.astype(np.uint8) * 255, "L") + pred = np.any(np.array(image) != np.array(orig), axis=-1) + mask = Image.fromarray(pred.astype(np.uint8) * 255, "L") + if is_mask_paint: + mask = ImageEnhance.Brightness(mask).enhance(1 - mask_alpha / 100) + blur = ImageFilter.GaussianBlur(mask_blur) + image = Image.composite(image.filter(blur), orig, mask.filter(blur)) image = image.convert("RGB") # Uploaded mask else: @@ -89,7 +94,7 @@ def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, pro # Use the EXIF orientation of photos taken by smartphones. if image is not None: - image = ImageOps.exif_transpose(image) + image = ImageOps.exif_transpose(image) assert 0. <= denoising_strength <= 1., 'can only work with strength in [0.0, 1.0]' diff --git a/modules/ui.py b/modules/ui.py index 29954f2a..16982abf 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -854,6 +854,8 @@ def create_ui(wrap_gradio_gpu_call): init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_base") init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_mask") + show_mask_alpha = cmd_opts.gradio_inpaint_tool == "color-sketch" + mask_alpha = gr.Slider(label="Mask transparency", interactive=show_mask_alpha, visible=show_mask_alpha) mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4) with gr.Row(): @@ -948,6 +950,7 @@ def create_ui(wrap_gradio_gpu_call): steps, sampler_index, mask_blur, + mask_alpha, inpainting_fill, restore_faces, tiling, -- cgit v1.2.3 From 81f2575df91a50e4aa9ca816e02e3f77342eedc8 Mon Sep 17 00:00:00 2001 From: Liam Date: Wed, 9 Nov 2022 15:24:31 -0500 Subject: updating the displayed generation info when user clicks images in the gallery. feature request 4415 --- javascript/ui.js | 10 +++++++++- modules/ui.py | 20 ++++++++++++++++++++ scripts/prompt_matrix.py | 2 ++ scripts/prompts_from_file.py | 6 +++++- 4 files changed, 36 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/javascript/ui.js b/javascript/ui.js index 95cfd106..443d1642 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -179,9 +179,17 @@ onUiUpdate(function(){ img2img_textarea = gradioApp().querySelector("#img2img_prompt > label > textarea"); img2img_textarea?.addEventListener("input", () => update_token_counter("img2img_token_button")); } + if (!txt2img_gallery) { + txt2img_gallery = gradioApp().querySelector('#txt2img_gallery') + txt2img_gallery?.addEventListener('click', () => gradioApp().getElementById("txt2img_generation_info_button").click()); + } + if (!img2img_gallery) { + img2img_gallery = gradioApp().querySelector('#img2img_gallery') + img2img_gallery?.addEventListener('click', () => gradioApp().getElementById("img2img_generation_info_button").click()); + } }) -let txt2img_textarea, img2img_textarea = undefined; +let txt2img_textarea, img2img_textarea, txt2img_gallery, img2img_gallery = undefined; let wait_time = 800 let token_timeout; diff --git a/modules/ui.py b/modules/ui.py index 7ea1177f..756499d1 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -566,6 +566,17 @@ def apply_setting(key, value): return value +def update_generation_info(args): + generation_info, html_info, img_index = args + try: + generation_info = json.loads(generation_info) + return plaintext_to_html(generation_info["infotexts"][img_index]) + except Exception: + pass + # if the json parse or anything else fails, just return the old html_info + return html_info + + def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id): def refresh(): refresh_method() @@ -638,6 +649,15 @@ Requested path was: {f} with gr.Group(): html_info = gr.HTML() generation_info = gr.Textbox(visible=False) + if tabname == 'txt2img' or tabname == 'img2img': + generation_info_button = gr.Button(visible=False, elem_id=f"{tabname}_generation_info_button") + generation_info_button.click( + fn=update_generation_info, + _js="(x, y) => [x, y, selected_gallery_index()]", + inputs=[generation_info, html_info], + outputs=[html_info], + preprocess=False + ) save.click( fn=wrap_gradio_call(save_files), diff --git a/scripts/prompt_matrix.py b/scripts/prompt_matrix.py index e49c9b20..4d1e152d 100644 --- a/scripts/prompt_matrix.py +++ b/scripts/prompt_matrix.py @@ -80,6 +80,8 @@ class Script(scripts.Script): grid = images.image_grid(processed.images, p.batch_size, rows=1 << ((len(prompt_matrix_parts) - 1) // 2)) grid = images.draw_prompt_matrix(grid, p.width, p.height, prompt_matrix_parts) processed.images.insert(0, grid) + processed.index_of_first_image = 1 + processed.infotexts.insert(0, processed.infotexts[0]) if opts.grid_save: images.save_image(processed.images[0], p.outpath_grids, "prompt_matrix", prompt=original_prompt, seed=processed.seed, grid=True, p=p) diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py index 3388bc77..32fe6bdb 100644 --- a/scripts/prompts_from_file.py +++ b/scripts/prompts_from_file.py @@ -145,6 +145,8 @@ class Script(scripts.Script): state.job_count = job_count images = [] + all_prompts = [] + infotexts = [] for n, args in enumerate(jobs): state.job = f"{state.job_no + 1} out of {state.job_count}" @@ -157,5 +159,7 @@ class Script(scripts.Script): if checkbox_iterate: p.seed = p.seed + (p.batch_size * p.n_iter) + all_prompts += proc.all_prompts + infotexts += proc.infotexts - return Processed(p, images, p.seed, "") + return Processed(p, images, p.seed, "", all_prompts=all_prompts, infotexts=infotexts) -- cgit v1.2.3 From b98740129c435f04a060369bd071fc4bafe021f5 Mon Sep 17 00:00:00 2001 From: Liam Date: Thu, 10 Nov 2022 13:07:41 -0500 Subject: added event listener for the image gallery modal; moved js to separate file --- javascript/generationParams.js | 33 +++++++++++++++++++++++++++++++++ javascript/ui.js | 10 +--------- modules/ui.py | 2 ++ 3 files changed, 36 insertions(+), 9 deletions(-) create mode 100644 javascript/generationParams.js (limited to 'modules/ui.py') diff --git a/javascript/generationParams.js b/javascript/generationParams.js new file mode 100644 index 00000000..95f05093 --- /dev/null +++ b/javascript/generationParams.js @@ -0,0 +1,33 @@ +// attaches listeners to the txt2img and img2img galleries to update displayed generation param text when the image changes + +let txt2img_gallery, img2img_gallery, modal = undefined; +onUiUpdate(function(){ + if (!txt2img_gallery) { + txt2img_gallery = attachGalleryListeners("txt2img") + } + if (!img2img_gallery) { + img2img_gallery = attachGalleryListeners("img2img") + } + if (!modal) { + modal = gradioApp().getElementById('lightboxModal') + modalObserver.observe(modal, { attributes : true, attributeFilter : ['style'] }); + } +}); + +let modalObserver = new MutationObserver(function(mutations) { + mutations.forEach(function(mutationRecord) { + let selectedTab = gradioApp().querySelector('#tabs div button.bg-white')?.innerText + if (mutationRecord.target.style.display === 'none' && selectedTab === 'txt2img' || selectedTab === 'img2img') + gradioApp().getElementById(selectedTab+"_generation_info_button").click() + }); +}); + +function attachGalleryListeners(tab_name) { + gallery = gradioApp().querySelector('#'+tab_name+'_gallery') + gallery?.addEventListener('click', () => gradioApp().getElementById(tab_name+"_generation_info_button").click()); + gallery?.addEventListener('keydown', (e) => { + if (e.keyCode == 37 || e.keyCode == 39) // left or right arrow + gradioApp().getElementById(tab_name+"_generation_info_button").click() + }); + return gallery; +} diff --git a/javascript/ui.js b/javascript/ui.js index 443d1642..95cfd106 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -179,17 +179,9 @@ onUiUpdate(function(){ img2img_textarea = gradioApp().querySelector("#img2img_prompt > label > textarea"); img2img_textarea?.addEventListener("input", () => update_token_counter("img2img_token_button")); } - if (!txt2img_gallery) { - txt2img_gallery = gradioApp().querySelector('#txt2img_gallery') - txt2img_gallery?.addEventListener('click', () => gradioApp().getElementById("txt2img_generation_info_button").click()); - } - if (!img2img_gallery) { - img2img_gallery = gradioApp().querySelector('#img2img_gallery') - img2img_gallery?.addEventListener('click', () => gradioApp().getElementById("img2img_generation_info_button").click()); - } }) -let txt2img_textarea, img2img_textarea, txt2img_gallery, img2img_gallery = undefined; +let txt2img_textarea, img2img_textarea = undefined; let wait_time = 800 let token_timeout; diff --git a/modules/ui.py b/modules/ui.py index 756499d1..5dce7f3b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -570,6 +570,8 @@ def update_generation_info(args): generation_info, html_info, img_index = args try: generation_info = json.loads(generation_info) + if img_index < 0 or img_index >= len(generation_info["infotexts"]): + return html_info return plaintext_to_html(generation_info["infotexts"][img_index]) except Exception: pass -- cgit v1.2.3 From 72b52fbb77360f848cfa296b0c79d2bc0a1060f2 Mon Sep 17 00:00:00 2001 From: dtlnor Date: Wed, 16 Nov 2022 13:08:03 +0900 Subject: add css override --- modules/ui.py | 3 +++ 1 file changed, 3 insertions(+) (limited to 'modules/ui.py') diff --git a/modules/ui.py b/modules/ui.py index 5dce7f3b..5e2a992f 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -69,8 +69,11 @@ sample_img2img = sample_img2img if os.path.exists(sample_img2img) else None css_hide_progressbar = """ .wrap .m-12 svg { display:none!important; } .wrap .m-12::before { content:"Loading..." } +.wrap .z-20 svg { display:none!important; } +.wrap .z-20::before { content:"Loading..." } .progress-bar { display:none!important; } .meta-text { display:none!important; } +.meta-text-center { display:none!important; } """ # Using constants for these since the variation selector isn't visible. -- cgit v1.2.3 From c8c40c8a643f2d20e3475e4d9ae7aae6d36c7e85 Mon Sep 17 00:00:00 2001 From: space-nuko <24979496+space-nuko@users.noreply.github.com> Date: Thu, 17 Nov 2022 18:03:57 -0800 Subject: Add interrupt button to preprocessing --- modules/textual_inversion/ui.py | 2 +- modules/ui.py | 10 +++++++++- 2 files changed, 10 insertions(+), 2 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py index d679e6f4..35c4feef 100644 --- a/modules/textual_inversion/ui.py +++ b/modules/textual_inversion/ui.py @@ -18,7 +18,7 @@ def create_embedding(name, initialization_text, nvpt, overwrite_old): def preprocess(*args): modules.textual_inversion.preprocess.preprocess(*args) - return "Preprocessing finished.", "" + return f"Preprocessing {'interrupted' if shared.state.interrupted else 'finished'}.", "" def train_embedding(*args): diff --git a/modules/ui.py b/modules/ui.py index 5dce7f3b..88e3c827 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1249,7 +1249,9 @@ def create_ui(wrap_gradio_gpu_call): gr.HTML(value="") with gr.Column(): - run_preprocess = gr.Button(value="Preprocess", variant='primary') + with gr.Row(): + interrupt_preprocessing = gr.Button("Interrupt") + run_preprocess = gr.Button(value="Preprocess", variant='primary') process_split.change( fn=lambda show: gr_show(show), @@ -1422,6 +1424,12 @@ def create_ui(wrap_gradio_gpu_call): outputs=[], ) + interrupt_preprocessing.click( + fn=lambda: shared.state.interrupt(), + inputs=[], + outputs=[], + ) + def create_setting_component(key, is_quicksettings=False): def fun(): return opts.data[key] if key in opts.data else opts.data_labels[key].default -- cgit v1.2.3 From cdc8020d13c5eef099c609b0a911ccf3568afc0d Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 19 Nov 2022 12:01:51 +0300 Subject: change StableDiffusionProcessing to internally use sampler name instead of sampler index --- modules/api/api.py | 26 ++++++++--------------- modules/hypernetworks/hypernetwork.py | 4 ++-- modules/images.py | 2 +- modules/img2img.py | 4 ++-- modules/processing.py | 29 +++++++++++--------------- modules/sd_samplers.py | 13 +++++++++--- modules/textual_inversion/textual_inversion.py | 4 ++-- modules/txt2img.py | 3 ++- modules/ui.py | 2 +- scripts/img2imgalt.py | 4 ++-- scripts/xy_grid.py | 12 +++++------ 11 files changed, 49 insertions(+), 54 deletions(-) (limited to 'modules/ui.py') diff --git a/modules/api/api.py b/modules/api/api.py index 596a6616..0eccccbb 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -6,9 +6,9 @@ from threading import Lock from gradio.processing_utils import encode_pil_to_base64, decode_base64_to_file, decode_base64_to_image from fastapi import APIRouter, Depends, FastAPI, HTTPException import modules.shared as shared +from modules import sd_samplers from modules.api.models import * from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images -from modules.sd_samplers import all_samplers from modules.extras import run_extras, run_pnginfo from PIL import PngImagePlugin from modules.sd_models import checkpoints_list @@ -25,8 +25,12 @@ def upscaler_to_index(name: str): raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be on of these: {' , '.join([x.name for x in sd_upscalers])}") -sampler_to_index = lambda name: next(filter(lambda row: name.lower() == row[1].name.lower(), enumerate(all_samplers)), None) +def validate_sampler_name(name): + config = sd_samplers.all_samplers_map.get(name, None) + if config is None: + raise HTTPException(status_code=404, detail="Sampler not found") + return name def setUpscalers(req: dict): reqDict = vars(req) @@ -82,14 +86,9 @@ class Api: self.app.add_api_route("/sdapi/v1/artists", self.get_artists, methods=["GET"], response_model=List[ArtistItem]) def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI): - sampler_index = sampler_to_index(txt2imgreq.sampler_index) - - if sampler_index is None: - raise HTTPException(status_code=404, detail="Sampler not found") - populate = txt2imgreq.copy(update={ # Override __init__ params "sd_model": shared.sd_model, - "sampler_index": sampler_index[0], + "sampler_name": validate_sampler_name(txt2imgreq.sampler_index), "do_not_save_samples": True, "do_not_save_grid": True } @@ -109,12 +108,6 @@ class Api: return TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js()) def img2imgapi(self, img2imgreq: StableDiffusionImg2ImgProcessingAPI): - sampler_index = sampler_to_index(img2imgreq.sampler_index) - - if sampler_index is None: - raise HTTPException(status_code=404, detail="Sampler not found") - - init_images = img2imgreq.init_images if init_images is None: raise HTTPException(status_code=404, detail="Init image not found") @@ -123,10 +116,9 @@ class Api: if mask: mask = decode_base64_to_image(mask) - populate = img2imgreq.copy(update={ # Override __init__ params "sd_model": shared.sd_model, - "sampler_index": sampler_index[0], + "sampler_name": validate_sampler_name(img2imgreq.sampler_index), "do_not_save_samples": True, "do_not_save_grid": True, "mask": mask @@ -272,7 +264,7 @@ class Api: return vars(shared.cmd_opts) def get_samplers(self): - return [{"name":sampler[0], "aliases":sampler[2], "options":sampler[3]} for sampler in all_samplers] + return [{"name":sampler[0], "aliases":sampler[2], "options":sampler[3]} for sampler in sd_samplers.all_samplers] def get_upscalers(self): upscalers = [] diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 7f182712..fbb87dd1 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -12,7 +12,7 @@ import torch import tqdm from einops import rearrange, repeat from ldm.util import default -from modules import devices, processing, sd_models, shared +from modules import devices, processing, sd_models, shared, sd_samplers from modules.textual_inversion import textual_inversion from modules.textual_inversion.learn_schedule import LearnRateScheduler from torch import einsum @@ -535,7 +535,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log p.prompt = preview_prompt p.negative_prompt = preview_negative_prompt p.steps = preview_steps - p.sampler_index = preview_sampler_index + p.sampler_name = sd_samplers.samplers[preview_sampler_index].name p.cfg_scale = preview_cfg_scale p.seed = preview_seed p.width = preview_width diff --git a/modules/images.py b/modules/images.py index ae705cbd..26d5b7a9 100644 --- a/modules/images.py +++ b/modules/images.py @@ -303,7 +303,7 @@ class FilenameGenerator: 'width': lambda self: self.image.width, 'height': lambda self: self.image.height, 'styles': lambda self: self.p and sanitize_filename_part(", ".join([style for style in self.p.styles if not style == "None"]) or "None", replace_spaces=False), - 'sampler': lambda self: self.p and sanitize_filename_part(sd_samplers.samplers[self.p.sampler_index].name, replace_spaces=False), + 'sampler': lambda self: self.p and sanitize_filename_part(self.p.sampler_name, replace_spaces=False), 'model_hash': lambda self: getattr(self.p, "sd_model_hash", shared.sd_model.sd_model_hash), 'date': lambda self: datetime.datetime.now().strftime('%Y-%m-%d'), 'datetime': lambda self, *args: self.datetime(*args), # accepts formats: [datetime], [datetime], [datetime