diff options
| -rw-r--r-- | javascript/ui.js | 52 | ||||
| -rw-r--r-- | modules/extras.py | 18 | ||||
| -rw-r--r-- | modules/img2img.py | 116 | ||||
| -rw-r--r-- | modules/processing.py | 5 | ||||
| -rw-r--r-- | modules/scripts.py | 1 | ||||
| -rw-r--r-- | modules/shared.py | 3 | ||||
| -rw-r--r-- | modules/ui.py | 132 | ||||
| -rw-r--r-- | scripts/batch.py | 59 | ||||
| -rw-r--r-- | scripts/sd_upscale.py | 93 | ||||
| -rw-r--r-- | style.css | 8 |
10 files changed, 261 insertions, 226 deletions
diff --git a/javascript/ui.js b/javascript/ui.js index f3860d2e..4944800b 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -35,13 +35,36 @@ function extract_image_from_gallery_extras(gallery){ return extract_image_from_gallery(gallery); } -function submit(){ - // this calls a function from progressbar.js - requestProgress() +function get_tab_index(tabId){ + var res = 0 + + gradioApp().getElementById(tabId).querySelector('div').querySelectorAll('button').forEach(function(button, i){ + if(button.className.indexOf('bg-white') != -1) + res = i + }) + + return res +} + +function create_tab_index_args(tabId, args){ + var res = [] + for(var i=0; i<args.length; i++){ + res.push(args[i]) + } + res[0] = get_tab_index(tabId) + + return res +} + +function get_extras_tab_index(){ + return create_tab_index_args('mode_extras', arguments) +} + +function create_submit_args(args){ res = [] - for(var i=0;i<arguments.length;i++){ - res.push(arguments[i]) + for(var i=0;i<args.length;i++){ + res.push(args[i]) } // As it is currently, txt2img and img2img send back the previous output args (txt2img_gallery, generation_info, html_info) whenever you generate a new image. @@ -55,11 +78,30 @@ function submit(){ return res } +function submit(){ + requestProgress() + + return create_submit_args(arguments) +} + +function submit_img2img(){ + requestProgress() + + res = create_submit_args(arguments) + + res[0] = get_tab_index('mode_img2img') + + return res +} + + 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] } + + opts = {} function apply_settings(jsdata){ console.log(jsdata) diff --git a/modules/extras.py b/modules/extras.py index 96bd2118..92569cff 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -15,30 +15,22 @@ import piexif.helper cached_images = {}
-def run_extras(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, image, image_folder, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility):
devices.torch_gc()
imageArr = []
# Also keep track of original file names
imageNameArr = []
- if image_folder is not None:
- if image is not None:
- print("Batch detected and single image detected, please only use one of the two. Aborting.")
- return None
+ if extras_mode == 1:
#convert file to pillow image
for img in image_folder:
image = Image.fromarray(np.array(Image.open(img)))
imageArr.append(image)
imageNameArr.append(os.path.splitext(img.orig_name)[0])
-
- elif image is not None:
- if image_folder is not None:
- print("Batch detected and single image detected, please only use one of the two. Aborting.")
- return None
- else:
- imageArr.append(image)
- imageNameArr.append(None)
+ else:
+ imageArr.append(image)
+ imageNameArr.append(None)
outpath = opts.outdir_samples or opts.outdir_extras_samples
diff --git a/modules/img2img.py b/modules/img2img.py index 6328f9d6..91689232 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -1,4 +1,8 @@ import math
+import os
+import sys
+import traceback
+
import numpy as np
from PIL import Image, ImageOps, ImageChops
@@ -11,9 +15,45 @@ from modules.ui import plaintext_to_html import modules.images as images
import modules.scripts
-def img2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, init_img_with_mask, init_mask, mask_mode, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, restore_faces: bool, tiling: bool, mode: int, 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, upscaler_index: str, upscale_overlap: int, inpaint_full_res: bool, inpainting_mask_invert: int, *args):
+
+def process_batch(p, input_dir, output_dir, args):
+ processing.fix_seed(p)
+
+ images = [file for file in [os.path.join(input_dir, x) for x in os.listdir(input_dir)] if os.path.isfile(file)]
+
+ print(f"Will process {len(images)} images, creating {p.n_iter * p.batch_size} new images for each.")
+
+ p.do_not_save_grid = True
+ p.do_not_save_samples = True
+
+ state.job_count = len(images) * p.n_iter
+
+ for i, image in enumerate(images):
+ state.job = f"{i+1} out of {len(images)}"
+
+ if state.interrupted:
+ break
+
+ img = Image.open(image)
+ p.init_images = [img] * p.batch_size
+
+ proc = modules.scripts.scripts_img2img.run(p, *args)
+ if proc is None:
+ proc = process_images(p)
+
+ for n, processed_image in enumerate(proc.images):
+ filename = os.path.basename(image)
+
+ if n > 0:
+ left, right = os.path.splitext(filename)
+ filename = f"{left}-{n}{right}"
+
+ 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):
is_inpaint = mode == 1
- is_upscale = mode == 2
+ is_batch = mode == 2
if is_inpaint:
if mask_mode == 0:
@@ -23,8 +63,8 @@ def img2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: mask = ImageChops.lighter(alpha_mask, mask.convert('L')).convert('L')
image = image.convert('RGB')
else:
- image = init_img
- mask = init_mask
+ image = init_img_inpaint
+ mask = init_mask_inpaint
else:
image = init_img
mask = None
@@ -60,79 +100,19 @@ def img2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: resize_mode=resize_mode,
denoising_strength=denoising_strength,
inpaint_full_res=inpaint_full_res,
+ inpaint_full_res_padding=inpaint_full_res_padding,
inpainting_mask_invert=inpainting_mask_invert,
)
print(f"\nimg2img: {prompt}", file=shared.progress_print_out)
p.extra_generation_params["Mask blur"] = mask_blur
- if is_upscale:
- initial_info = None
-
- processing.fix_seed(p)
- seed = p.seed
-
- upscaler = shared.sd_upscalers[upscaler_index]
- img = upscaler.upscale(init_img, init_img.width * 2, init_img.height * 2)
-
- devices.torch_gc()
-
- grid = images.split_grid(img, tile_w=width, tile_h=height, overlap=upscale_overlap)
-
- batch_size = p.batch_size
- upscale_count = p.n_iter
- p.n_iter = 1
- p.do_not_save_grid = True
- p.do_not_save_samples = True
-
- work = []
-
- for y, h, row in grid.tiles:
- for tiledata in row:
- work.append(tiledata[2])
-
- batch_count = math.ceil(len(work) / batch_size)
- state.job_count = batch_count * upscale_count
-
- print(f"SD upscaling will process a total of {len(work)} images tiled as {len(grid.tiles[0][2])}x{len(grid.tiles)} per upscale in a total of {state.job_count} batches.")
-
- result_images = []
- for n in range(upscale_count):
- start_seed = seed + n
- p.seed = start_seed
-
- work_results = []
- for i in range(batch_count):
- p.batch_size = batch_size
- p.init_images = work[i*batch_size:(i+1)*batch_size]
-
- state.job = f"Batch {i + 1 + n * batch_count} out of {state.job_count}"
- processed = process_images(p)
-
- if initial_info is None:
- initial_info = processed.info
-
- p.seed = processed.seed + 1
- work_results += processed.images
-
- image_index = 0
- for y, h, row in grid.tiles:
- for tiledata in row:
- tiledata[2] = work_results[image_index] if image_index < len(work_results) else Image.new("RGB", (p.width, p.height))
- image_index += 1
-
- combined_image = images.combine_grid(grid)
- result_images.append(combined_image)
-
- if opts.samples_save:
- images.save_image(combined_image, p.outpath_samples, "", start_seed, prompt, opts.samples_format, info=initial_info, p=p)
-
- processed = Processed(p, result_images, seed, initial_info)
+ if is_batch:
+ process_batch(p, img2img_batch_input_dir, img2img_batch_output_dir, args)
+ processed = Processed(p, [], p.seed, "")
else:
-
processed = modules.scripts.scripts_img2img.run(p, *args)
-
if processed is None:
processed = process_images(p)
diff --git a/modules/processing.py b/modules/processing.py index e844b7e2..f44c3f26 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -491,7 +491,7 @@ 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, 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
@@ -505,6 +505,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): self.mask_blur = mask_blur
self.inpainting_fill = inpainting_fill
self.inpaint_full_res = inpaint_full_res
+ self.inpaint_full_res_padding = inpaint_full_res_padding
self.inpainting_mask_invert = inpainting_mask_invert
self.mask = None
self.nmask = None
@@ -527,7 +528,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): if self.inpaint_full_res:
self.mask_for_overlay = self.image_mask
mask = self.image_mask.convert('L')
- crop_region = masking.get_crop_region(np.array(mask), opts.upscale_at_full_resolution_padding)
+ crop_region = masking.get_crop_region(np.array(mask), self.inpaint_full_res_padding)
crop_region = masking.expand_crop_region(crop_region, self.width, self.height, mask.width, mask.height)
x1, y1, x2, y2 = crop_region
diff --git a/modules/scripts.py b/modules/scripts.py index 0e0b949b..9ab207dc 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -143,7 +143,6 @@ class ScriptRunner: return inputs
-
def run(self, p: StableDiffusionProcessing, *args):
script_index = args[0]
diff --git a/modules/shared.py b/modules/shared.py index 0a852838..841a9877 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -147,14 +147,13 @@ class Options: "save_txt": OptionInfo(False, "Create a text file next to every image with generation parameters."),
"ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers. 0 = no tiling.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}),
"ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for ESRGAN upscalers. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}),
- "realesrgan_enabled_models": OptionInfo(["Real-ESRGAN 4x plus", "Real-ESRGAN 4x plus anime 6B"],"Select which RealESRGAN models to show in the web UI. (Requires restart)", gr.CheckboxGroup, lambda: {"choices": realesrgan_models_names()}),
+ "realesrgan_enabled_models": OptionInfo(["Real-ESRGAN 4x plus", "Real-ESRGAN 4x plus anime 6B"], "Select which RealESRGAN models to show in the web UI. (Requires restart)", gr.CheckboxGroup, lambda: {"choices": realesrgan_models_names()}),
"SWIN_tile": OptionInfo(192, "Tile size for all SwinIR.", gr.Slider, {"minimum": 16, "maximum": 512, "step": 16}),
"SWIN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for SwinIR. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}),
"ldsr_steps": OptionInfo(100, "LDSR processing steps. Lower = faster", gr.Slider, {"minimum": 1, "maximum": 200, "step": 1}),
"ldsr_pre_down":OptionInfo(1, "LDSR Pre-process downssample scale. 1 = no down-sampling, 4 = 1/4 scale.", gr.Slider, {"minimum": 1, "maximum": 4, "step": 1}),
"ldsr_post_down":OptionInfo(1, "LDSR Post-process down-sample scale. 1 = no down-sampling, 4 = 1/4 scale.", gr.Slider, {"minimum": 1, "maximum": 4, "step": 1}),
"random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
- "upscale_at_full_resolution_padding": OptionInfo(16, "Inpainting at full resolution: padding, in pixels, for the masked region.", gr.Slider, {"minimum": 0, "maximum": 128, "step": 4}),
"upscaler_for_hires_fix": OptionInfo(None, "Upscaler for highres. fix", gr.Radio, lambda: {"choices": [x.name for x in sd_upscalers]}),
"show_progressbar": OptionInfo(True, "Show progressbar"),
"show_progress_every_n_steps": OptionInfo(0, "Show show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}),
diff --git a/modules/ui.py b/modules/ui.py index 572dcfb9..3c898bd2 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -527,36 +527,47 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo): progressbar = gr.HTML(elem_id="progressbar")
img2img_preview = gr.Image(elem_id='img2img_preview', visible=False)
setup_progressbar(progressbar, img2img_preview)
-
+
with gr.Row().style(equal_height=False):
with gr.Column(variant='panel'):
- with gr.Group():
- switch_mode = gr.Radio(label='Mode', elem_id="img2img_mode", choices=['Redraw whole image', 'Inpaint a part of image', 'SD upscale'], value='Redraw whole image', type="index", show_label=False)
- init_img = gr.Image(label="Image for img2img", source="upload", interactive=True, type="pil")
- init_img_with_mask = gr.Image(label="Image for inpainting with mask", elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", visible=False, image_mode="RGBA")
- init_mask = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False)
- init_img_with_mask_comment = gr.HTML(elem_id="mask_bug_info", value="<small>if the editor shows ERROR, switch to another tab and back, then to another img2img mode above and back</small>", visible=False)
- with gr.Row():
- resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", show_label=False, choices=["Just resize", "Crop and resize", "Resize and fill"], type="index", value="Just resize")
- mask_mode = gr.Radio(label="Mask mode", show_label=False, choices=["Draw mask", "Upload mask"], type="index", value="Draw mask")
+ with gr.Tabs(elem_id="mode_img2img") as tabs_img2img_mode:
+ with gr.TabItem('img2img'):
+ init_img = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil")
- steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20)
- sampler_index = gr.Radio(label='Sampling method', choices=[x.name for x in samplers_for_img2img], value=samplers_for_img2img[0].name, type="index")
- mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, visible=False)
- inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index", visible=False)
+ with gr.TabItem('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_comment = gr.HTML(elem_id="mask_bug_info", value="<small>if the editor shows ERROR, switch to another tab and back, then to \"Upload mask\" mode above and back</small>")
+
+ init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", visible=False)
+ init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False)
+
+ mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4)
+
+ with gr.Row():
+ mask_mode = gr.Radio(label="Mask mode", show_label=False, choices=["Draw mask", "Upload mask"], type="index", value="Draw mask")
+ inpainting_mask_invert = gr.Radio(label='Masking mode', show_label=False, choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index")
+
+ inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index")
+
+ 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)
+
+ with gr.TabItem('Batch img2img'):
+ gr.HTML("<p class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.</p>")
+ img2img_batch_input_dir = gr.Textbox(label="Input directory")
+ img2img_batch_output_dir = gr.Textbox(label="Output directory")
with gr.Row():
- inpaint_full_res = gr.Checkbox(label='Inpaint at full resolution', value=False, visible=False)
- inpainting_mask_invert = gr.Radio(label='Masking mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", visible=False)
+ resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", show_label=False, choices=["Just resize", "Crop and resize", "Resize and fill"], type="index", value="Just resize")
+
+ steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20)
+ 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.Row():
restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1)
tiling = gr.Checkbox(label='Tiling', value=False)
- sd_upscale_overlap = gr.Slider(minimum=0, maximum=256, step=16, label='Tile overlap', value=64, visible=False)
-
- with gr.Row():
- sd_upscale_upscaler_name = gr.Radio(label='Upscaler', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index", visible=False)
with gr.Row():
batch_count = gr.Slider(minimum=1, maximum=cmd_opts.max_batch_count, step=1, label='Batch count', value=1)
@@ -589,7 +600,6 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo): img2img_send_to_extras = gr.Button('Send to extras')
img2img_save_style = gr.Button('Save prompt as style')
-
with gr.Group():
html_info = gr.HTML()
generation_info = gr.Textbox(visible=False)
@@ -597,70 +607,36 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo): 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)
- def apply_mode(mode, uploadmask):
- is_classic = mode == 0
- is_inpaint = mode == 1
- is_upscale = mode == 2
-
- return {
- init_img: gr_show(not is_inpaint or (is_inpaint and uploadmask == 1)),
- init_img_with_mask: gr_show(is_inpaint and uploadmask == 0),
- init_img_with_mask_comment: gr_show(is_inpaint and uploadmask == 0),
- init_mask: gr_show(is_inpaint and uploadmask == 1),
- mask_mode: gr_show(is_inpaint),
- mask_blur: gr_show(is_inpaint),
- inpainting_fill: gr_show(is_inpaint),
- sd_upscale_upscaler_name: gr_show(is_upscale),
- sd_upscale_overlap: gr_show(is_upscale),
- inpaint_full_res: gr_show(is_inpaint),
- inpainting_mask_invert: gr_show(is_inpaint),
- img2img_interrogate: gr_show(not is_inpaint),
- }
-
- switch_mode.change(
- apply_mode,
- inputs=[switch_mode, mask_mode],
- outputs=[
- init_img,
- init_img_with_mask,
- init_img_with_mask_comment,
- init_mask,
- mask_mode,
- mask_blur,
- inpainting_fill,
- sd_upscale_upscaler_name,
- sd_upscale_overlap,
- inpaint_full_res,
- inpainting_mask_invert,
- img2img_interrogate,
- ]
- )
-
mask_mode.change(
- lambda mode: {
- init_img: gr_show(mode == 1),
+ lambda mode, img: {
+ #init_img_with_mask: gr.Image.update(visible=mode == 0, value=img["image"]),
init_img_with_mask: gr_show(mode == 0),
- init_mask: gr_show(mode == 1),
+ init_img_with_mask_comment: gr_show(mode == 0),
+ init_img_inpaint: gr_show(mode == 1),
+ init_mask_inpaint: gr_show(mode == 1),
},
- inputs=[mask_mode],
+ inputs=[mask_mode, init_img_with_mask],
outputs=[
- init_img,
init_img_with_mask,
- init_mask,
+ init_img_with_mask_comment,
+ init_img_inpaint,
+ init_mask_inpaint,
],
)
img2img_args = dict(
fn=img2img,
- _js="submit",
+ _js="submit_img2img",
inputs=[
+ dummy_component,
img2img_prompt,
img2img_negative_prompt,
img2img_prompt_style,
img2img_prompt_style2,
init_img,
init_img_with_mask,
- init_mask,
+ init_img_inpaint,
+ init_mask_inpaint,
mask_mode,
steps,
sampler_index,
@@ -668,7 +644,6 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo): inpainting_fill,
restore_faces,
tiling,
- switch_mode,
batch_count,
batch_size,
cfg_scale,
@@ -678,10 +653,11 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo): height,
width,
resize_mode,
- sd_upscale_upscaler_name,
- sd_upscale_overlap,
inpaint_full_res,
+ inpaint_full_res_padding,
inpainting_mask_invert,
+ img2img_batch_input_dir,
+ img2img_batch_output_dir,
] + custom_inputs,
outputs=[
img2img_gallery,
@@ -748,7 +724,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo): with gr.Blocks(analytics_enabled=False) as extras_interface:
with gr.Row().style(equal_height=False):
with gr.Column(variant='panel'):
- with gr.Tabs():
+ with gr.Tabs(elem_id="mode_extras"):
with gr.TabItem('Single Image'):
image = gr.Image(label="Source", source="upload", interactive=True, type="pil")
@@ -778,9 +754,11 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo): html_info_x = gr.HTML()
html_info = gr.HTML()
- extras_args = dict(
+ submit.click(
fn=run_extras,
+ _js="get_extras_tab_index",
inputs=[
+ dummy_component,
image,
image_batch,
gfpgan_visibility,
@@ -798,8 +776,6 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo): ]
)
- submit.click(**extras_args)
-
pnginfo_interface = gr.Interface(
wrap_gradio_call(run_pnginfo),
inputs=[
@@ -929,6 +905,12 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo): outputs=[init_img_with_mask],
)
+ tabs_img2img_mode.change(
+ fn=lambda x: x,
+ inputs=[init_img_with_mask],
+ outputs=[init_img_with_mask],
+ )
+
send_to_img2img.click(
fn=lambda x: image_from_url_text(x),
_js="extract_image_from_gallery_img2img",
diff --git a/scripts/batch.py b/scripts/batch.py deleted file mode 100644 index 1af4a7bc..00000000 --- a/scripts/batch.py +++ /dev/null @@ -1,59 +0,0 @@ -import math
-import os
-import sys
-import traceback
-
-import modules.scripts as scripts
-import gradio as gr
-
-from modules.processing import Processed, process_images
-from PIL import Image
-from modules.shared import opts, cmd_opts, state
-
-
-class Script(scripts.Script):
- def title(self):
- return "Batch processing"
-
- def show(self, is_img2img):
- return is_img2img
-
- def ui(self, is_img2img):
- input_dir = gr.Textbox(label="Input directory", lines=1)
- output_dir = gr.Textbox(label="Output directory", lines=1)
-
- return [input_dir, output_dir]
-
- def run(self, p, input_dir, output_dir):
- images = [file for file in [os.path.join(input_dir, x) for x in os.listdir(input_dir)] if os.path.isfile(file)]
-
- batch_count = math.ceil(len(images) / p.batch_size)
- print(f"Will process {len(images)} images in {batch_count} batches.")
-
- p.batch_count = 1
- p.do_not_save_grid = True
- p.do_not_save_samples = True
-
- state.job_count = batch_count
-
- for batch_no in range(batch_count):
- batch_images = []
- for path in images[batch_no*p.batch_size:(batch_no+1)*p.batch_size]:
- try:
- img = Image.open(path)
- batch_images.append((img, path))
- except:
- print(f"Error processing {path}:", file=sys.stderr)
- print(traceback.format_exc(), file=sys.stderr)
-
- if len(batch_images) == 0:
- continue
-
- state.job = f"{batch_no} out of {batch_count}: {batch_images[0][1]}"
- p.init_images = [x[0] for x in batch_images]
- proc = process_images(p)
- for image, (_, path) in zip(proc.images, batch_images):
- filename = os.path.basename(path)
- image.save(os.path.join(output_dir, filename))
-
- return Processed(p, [], p.seed, "")
diff --git a/scripts/sd_upscale.py b/scripts/sd_upscale.py new file mode 100644 index 00000000..b87a145b --- /dev/null +++ b/scripts/sd_upscale.py @@ -0,0 +1,93 @@ +import math
+
+import modules.scripts as scripts
+import gradio as gr
+from PIL import Image
+
+from modules import processing, shared, sd_samplers, images, devices
+from modules.processing import Processed
+from modules.shared import opts, cmd_opts, state
+
+
+class Script(scripts.Script):
+ def title(self):
+ return "SD upscale"
+
+ def show(self, is_img2img):
+ return is_img2img
+
+ def ui(self, is_img2img):
+ info = gr.HTML("<p style=\"margin-bottom:0.75em\">Will upscale the image to twice the dimensions; use width and height sliders to set tile size</p>")
+ overlap = gr.Slider(minimum=0, maximum=256, step=16, label='Tile overlap', value=64, visible=False)
+ upscaler_index = gr.Radio(label='Upscaler', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index", visible=False)
+
+ return [info, overlap, upscaler_index]
+
+ def run(self, p, _, overlap, upscaler_index):
+ processing.fix_seed(p)
+ upscaler = shared.sd_upscalers[upscaler_index]
+
+ p.extra_generation_params["SD upscale overlap"] = overlap
+ p.extra_generation_params["SD upscale upscaler"] = upscaler.name
+
+ initial_info = None
+ seed = p.seed
+
+ init_img = p.init_images[0]
+ img = upscaler.upscale(init_img, init_img.width * 2, init_img.height * 2)
+
+ devices.torch_gc()
+
+ grid = images.split_grid(img, tile_w=p.width, tile_h=p.height, overlap=overlap)
+
+ batch_size = p.batch_size
+ upscale_count = p.n_iter
+ p.n_iter = 1
+ p.do_not_save_grid = True
+ p.do_not_save_samples = True
+
+ work = []
+
+ for y, h, row in grid.tiles:
+ for tiledata in row:
+ work.append(tiledata[2])
+
+ batch_count = math.ceil(len(work) / batch_size)
+ state.job_count = batch_count * upscale_count
+
+ print(f"SD upscaling will process a total of {len(work)} images tiled as {len(grid.tiles[0][2])}x{len(grid.tiles)} per upscale in a total of {state.job_count} batches.")
+
+ result_images = []
+ for n in range(upscale_count):
+ start_seed = seed + n
+ p.seed = start_seed
+
+ work_results = []
+ for i in range(batch_count):
+ p.batch_size = batch_size
+ p.init_images = work[i*batch_size:(i+1)*batch_size]
+
+ state.job = f"Batch {i + 1 + n * batch_count} out of {state.job_count}"
+ processed = processing.process_images(p)
+
+ if initial_info is None:
+ initial_info = processed.info
+
+ p.seed = processed.seed + 1
+ work_results += processed.images
+
+ image_index = 0
+ for y, h, row in grid.tiles:
+ for tiledata in row:
+ tiledata[2] = work_results[image_index] if image_index < len(work_results) else Image.new("RGB", (p.width, p.height))
+ image_index += 1
+
+ combined_image = images.combine_grid(grid)
+ result_images.append(combined_image)
+
+ if opts.samples_save:
+ images.save_image(combined_image, p.outpath_samples, "", start_seed, p.prompt, opts.samples_format, info=initial_info, p=p)
+
+ processed = Processed(p, result_images, seed, initial_info)
+
+ return processed
@@ -97,6 +97,11 @@ background: transparent;
}
+.my-4{
+ margin-top: 0;
+ margin-bottom: 0;
+}
+
#toprow div{
border: none;
gap: 0;
@@ -198,7 +203,8 @@ input[type="range"]{ #mask_bug_info {
text-align: center;
display: block;
- margin-bottom: 0.5em;
+ margin-top: -0.75em;
+ margin-bottom: -0.75em;
}
#txt2img_negative_prompt, #img2img_negative_prompt{
|