diff options
Diffstat (limited to 'modules/ui.py')
| -rw-r--r-- | modules/ui.py | 205 |
1 files changed, 166 insertions, 39 deletions
diff --git a/modules/ui.py b/modules/ui.py index 2a7f64f9..0d020de6 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
@@ -25,7 +25,9 @@ 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
+
+from modules.shared import opts, cmd_opts, restricted_opts, aesthetic_embeddings
+
if cmd_opts.deepdanbooru:
from modules.deepbooru import get_deepbooru_tags
import modules.shared as shared
@@ -41,8 +43,11 @@ from modules import prompt_parser 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
+
# 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')
@@ -261,6 +266,24 @@ def wrap_gradio_call(func, extra_outputs=None): return f
+def calc_time_left(progress, threshold, label, force_display):
+ 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 > 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 ""
+
+
def check_progress_call(id_part):
if shared.state.job_count == 0:
return "", gr_show(False), gr_show(False), gr_show(False)
@@ -272,11 +295,15 @@ 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, 1, " 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"""<div class='progressDiv'><div class='progress' style="width:{progress * 100}%">{str(int(progress*100))+"%" if progress > 0.01 else ""}</div></div>"""
+ progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{" " * 2 + str(int(progress*100))+"%" + time_left if progress > 0.01 else ""}</div></div>"""
image = gr_show(False)
preview_visibility = gr_show(False)
@@ -308,6 +335,8 @@ 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()
+ shared.state.time_left_force_display = False
return check_progress_call(id_part)
@@ -458,14 +487,14 @@ 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)"
)
@@ -542,6 +571,10 @@ 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)
@@ -564,27 +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)
@@ -627,6 +662,8 @@ 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)
@@ -681,7 +718,16 @@ 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=[
txt2img_gallery,
generation_info,
@@ -758,6 +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 = [
@@ -842,6 +896,8 @@ 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)
@@ -932,6 +988,14 @@ 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,
@@ -1023,6 +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])
@@ -1183,6 +1255,7 @@ 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):
@@ -1191,9 +1264,25 @@ 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"])
+ 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")
+ 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):
@@ -1207,6 +1296,7 @@ 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', value="ignore", choices=["ignore", "copy", "prepend", "append"])
with gr.Row():
process_flip = gr.Checkbox(label='Create flipped copies')
@@ -1222,14 +1312,17 @@ def create_ui(wrap_gradio_gpu_call): run_preprocess = gr.Button(value="Preprocess", variant='primary')
with gr.Tab(label="Train"):
- gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 1:1 ratio images</p>")
+ gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images <a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\" style=\"font-weight:bold;\">[wiki]</a></p>")
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")
@@ -1263,6 +1356,7 @@ def create_ui(wrap_gradio_gpu_call): new_embedding_name,
initialization_text,
nvpt,
+ overwrite_old_embedding,
],
outputs=[
train_embedding_name,
@@ -1271,11 +1365,30 @@ 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=[
new_hypernetwork_name,
new_hypernetwork_sizes,
+ overwrite_old_hypernetwork,
+ new_hypernetwork_layer_structure,
+ new_hypernetwork_add_layer_norm,
+ new_hypernetwork_activation_func,
],
outputs=[
train_hypernetwork_name,
@@ -1292,6 +1405,7 @@ def create_ui(wrap_gradio_gpu_call): process_dst,
process_width,
process_height,
+ preprocess_txt_action,
process_flip,
process_split,
process_caption,
@@ -1308,7 +1422,7 @@ 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,
@@ -1333,10 +1447,12 @@ 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,
+ training_width,
+ training_height,
steps,
create_image_every,
save_embedding_every,
@@ -1533,6 +1649,7 @@ 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,
@@ -1733,7 +1850,7 @@ 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:
@@ -1749,6 +1866,8 @@ 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 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')
@@ -1774,7 +1893,8 @@ 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")
@@ -1788,23 +1908,30 @@ Requested path was: {f} return demo
-with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:
- javascript = f'<script>{jsfile.read()}</script>'
+def load_javascript(raw_response):
+ with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:
+ javascript = f'<script>{jsfile.read()}</script>'
+
+ 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<!-- {filename} --><script>{jsfile.read()}</script>"
-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<script>{jsfile.read()}</script>"
+ if cmd_opts.theme is not None:
+ javascript += f"\n<script>set_theme('{cmd_opts.theme}');</script>\n"
-javascript += f"\n<script>{localization.localization_js(shared.opts.localization)}</script>"
+ javascript += f"\n<script>{localization.localization_js(shared.opts.localization)}</script>"
-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'</head>', f'{javascript}</head>'.encode("utf8"))
+ res = raw_response(*args, **kwargs)
+ res.body = res.body.replace(
+ b'</head>', f'{javascript}</head>'.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()
|