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Code Issues Projects Releases Wiki Activity

Refactored the UI, added a web_playground.py to be run without any models.

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Alex Volkov 2022-08-28 16:40:48 -06:00 committed by hlky
parent 8d15f865e9
commit 64ca78ca76
6 changed files with 572 additions and 655 deletions
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0
frontend/__init__.py Normal file
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66
frontend/css_and_js.py Normal file
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def css(opt):
css_hide_progressbar = """
.wrap .m-12 svg { display:none!important; }
.wrap .m-12::before { content:"Loading..." }
.progress-bar { display:none!important; }
.meta-text { display:none!important; }
"""
styling = """
[data-testid="image"] {min-height: 512px !important}
* #body>.col:nth-child(2){width:250%;max-width:89vw}
#prompt_row input{
font-size:20px
}
#edit_mode_select{width:auto !important}
input[type=number]:disabled { -moz-appearance: textfield;+ }
#generate, #img2img_mask_btn,#img2img_edit_btn{
position: absolute;
right: 16px;
top: 14px;
}
@media (max-width: 420px){
#generate, #img2img_mask_btn,#img2img_edit_btn{
position: absolute;
right: 16px;
top: 5px;
}
}
"""
return styling if opt.no_progressbar_hiding else styling + css_hide_progressbar
# This is the code that finds which selected item the user has in the gallery
js_part_getindex_txt2img="""
const root = document.querySelector('gradio-app').shadowRoot;
const getIndex = function(){
const selected = root.querySelector('#txt2img_gallery_output .\\\\!ring-2');
return selected ? [...selected.parentNode.children].indexOf(selected) : 0;
};"""
js_part_getindex_img2img="""
const root = document.querySelector('gradio-app').shadowRoot;
const getIndex = function(){
const selected = root.querySelector('#img2img_gallery_output .\\\\!ring-2');
return selected ? [...selected.parentNode.children].indexOf(selected) : 0;
};"""
js_part_clear_img2img="""
root.querySelector('#img2img_editor .modify-upload button:last-child')?.click();
"""
js_return_selected_txt2img = "(x) => {" + js_part_getindex_txt2img + js_part_clear_img2img + """
return [x[getIndex()].replace('data:;','data:image/png;')];
}"""
js_return_selected_img2img = "(x) => {" + js_part_getindex_img2img + js_part_clear_img2img + """
return [x[getIndex()].replace('data:;','data:image/png;')];
}"""
js_part_copy_to_clipboard="""
const data = x[getIndex()];
const blob = await (await fetch(data.replace('data:;','data:image/png;'))).blob();
const item = new ClipboardItem({'image/png': blob});
navigator.clipboard.write([item]);
return x;
}"""
js_copy_selected_txt2img = "async (x) => {" + js_part_getindex_txt2img + js_part_copy_to_clipboard
js_copy_selected_img2img = "async (x) => {" + js_part_getindex_img2img + js_part_copy_to_clipboard

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frontend/frontend.py Normal file
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import gradio as gr
from frontend.css_and_js import *
from frontend.css_and_js import css
import frontend.ui_functions as uifn
def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x, txt2img_defaults={}, RealESRGAN=True, GFPGAN=True,
txt2img_toggles={}, txt2img_toggle_defaults='k_euler', show_embeddings=False, img2img_defaults={},
img2img_toggles={}, img2img_toggle_defaults={}, sample_img2img=None, img2img_mask_modes=None,
img2img_resize_modes=None, user_defaults={}, run_GFPGAN=lambda x: x, run_RealESRGAN=lambda x: x):
with gr.Blocks(css=css(opt), analytics_enabled=False, title="Stable Diffusion WebUI") as demo:
with gr.Tabs(elem_id='tabss') as tabs:
with gr.TabItem("Stable Diffusion Text-to-Image Unified", id='txt2img_tab'):
with gr.Row(elem_id="prompt_row"):
txt2img_prompt = gr.Textbox(label="Prompt",
elem_id='prompt_input',
placeholder="A corgi wearing a top hat as an oil painting.",
lines=1,
max_lines=1 if txt2img_defaults['submit_on_enter'] == 'Yes' else 25,
value=txt2img_defaults['prompt'],
show_label=False)
txt2img_btn = gr.Button("Generate", elem_id="generate", variant="primary")
with gr.Row(elem_id='body').style(equal_height=False):
with gr.Column():
txt2img_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height",
value=txt2img_defaults["height"])
txt2img_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width",
value=txt2img_defaults["width"])
txt2img_cfg = gr.Slider(minimum=1.0, maximum=30.0, step=0.5,
label='Classifier Free Guidance Scale (how strongly the image should follow the prompt)',
value=txt2img_defaults['cfg_scale'])
txt2img_seed = gr.Textbox(label="Seed (blank to randomize)", lines=1, max_lines=1,
value=txt2img_defaults["seed"])
txt2img_batch_count = gr.Slider(minimum=1, maximum=250, step=1,
label='Batch count (how many batches of images to generate)',
value=txt2img_defaults['n_iter'])
txt2img_batch_size = gr.Slider(minimum=1, maximum=8, step=1,
label='Batch size (how many images are in a batch; memory-hungry)',
value=txt2img_defaults['batch_size'])
with gr.Column():
output_txt2img_gallery = gr.Gallery(label="Images", elem_id="txt2img_gallery_output").style(grid=[4, 4])
with gr.Tabs():
with gr.TabItem("Generated image actions", id="text2img_actions_tab"):
gr.Markdown(
'Select an image from the gallery, then click one of the buttons below to perform an action.')
with gr.Row():
output_txt2img_copy_clipboard = gr.Button("Copy to clipboard").click(fn=None,
inputs=output_txt2img_gallery,
outputs=[],
_js=js_copy_selected_txt2img)
output_txt2img_copy_to_input_btn = gr.Button("Push to img2img")
if RealESRGAN is not None:
output_txt2img_to_upscale_esrgan = gr.Button("Upscale w/ ESRGAN")
with gr.TabItem("Output Info", id="text2img_output_info_tab"):
output_txt2img_params = gr.Textbox(label="Generation parameters", interactive=False)
with gr.Row():
output_txt2img_copy_params = gr.Button("Copy full parameters").click(
inputs=output_txt2img_params, outputs=[],
_js='(x) => navigator.clipboard.writeText(x)', fn=None, show_progress=False)
output_txt2img_seed = gr.Number(label='Seed', interactive=False, visible=False)
output_txt2img_copy_seed = gr.Button("Copy only seed").click(
inputs=output_txt2img_seed, outputs=[],
_js='(x) => navigator.clipboard.writeText(x)', fn=None, show_progress=False)
output_txt2img_stats = gr.HTML(label='Stats')
with gr.Column():
txt2img_steps = gr.Slider(minimum=1, maximum=250, step=1, label="Sampling Steps",
value=txt2img_defaults['ddim_steps'])
txt2img_sampling = gr.Dropdown(label='Sampling method (k_lms is default k-diffusion sampler)',
choices=["DDIM", "PLMS", 'k_dpm_2_a', 'k_dpm_2', 'k_euler_a',
'k_euler', 'k_heun', 'k_lms'],
value=txt2img_defaults['sampler_name'])
with gr.Tabs():
with gr.TabItem('Simple'):
txt2img_submit_on_enter = gr.Radio(['Yes', 'No'],
label="Submit on enter? (no means multiline)",
value=txt2img_defaults['submit_on_enter'],
interactive=True)
txt2img_submit_on_enter.change(
lambda x: gr.update(max_lines=1 if x == 'Single' else 25), txt2img_submit_on_enter,
txt2img_prompt)
with gr.TabItem('Advanced'):
txt2img_toggles = gr.CheckboxGroup(label='', choices=txt2img_toggles,
value=txt2img_toggle_defaults, type="index")
txt2img_realesrgan_model_name = gr.Dropdown(label='RealESRGAN model',
choices=['RealESRGAN_x4plus',
'RealESRGAN_x4plus_anime_6B'],
value='RealESRGAN_x4plus',
visible=RealESRGAN is not None) # TODO: Feels like I shouldnt slot it in here.
txt2img_ddim_eta = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label="DDIM ETA",
value=txt2img_defaults['ddim_eta'], visible=False)
txt2img_embeddings = gr.File(label="Embeddings file for textual inversion",
visible=show_embeddings)
txt2img_btn.click(
txt2img,
[txt2img_prompt, txt2img_steps, txt2img_sampling, txt2img_toggles, txt2img_realesrgan_model_name,
txt2img_ddim_eta, txt2img_batch_count, txt2img_batch_size, txt2img_cfg, txt2img_seed,
txt2img_height, txt2img_width, txt2img_embeddings],
[output_txt2img_gallery, output_txt2img_seed, output_txt2img_params, output_txt2img_stats]
)
txt2img_prompt.submit(
txt2img,
[txt2img_prompt, txt2img_steps, txt2img_sampling, txt2img_toggles, txt2img_realesrgan_model_name,
txt2img_ddim_eta, txt2img_batch_count, txt2img_batch_size, txt2img_cfg, txt2img_seed,
txt2img_height, txt2img_width, txt2img_embeddings],
[output_txt2img_gallery, output_txt2img_seed, output_txt2img_params, output_txt2img_stats]
)
with gr.TabItem("Stable Diffusion Image-to-Image Unified", id="img2img_tab"):
with gr.Row(elem_id="prompt_row"):
img2img_prompt = gr.Textbox(label="Prompt",
elem_id='img2img_prompt_input',
placeholder="A fantasy landscape, trending on artstation.",
lines=1,
max_lines=1 if txt2img_defaults['submit_on_enter'] == 'Yes' else 25,
value=img2img_defaults['prompt'],
show_label=False).style()
img2img_btn_mask = gr.Button("Generate", variant="primary", visible=False,
elem_id="img2img_mask_btn")
img2img_btn_editor = gr.Button("Generate", variant="primary", elem_id="img2img_edit_btn")
with gr.Row().style(equal_height=False):
with gr.Column():
gr.Markdown('#### Img2Img input')
img2img_image_editor = gr.Image(value=sample_img2img, source="upload", interactive=True,
type="pil", tool="select", elem_id="img2img_editor")
img2img_image_mask = gr.Image(value=sample_img2img, source="upload", interactive=True,
type="pil", tool="sketch", visible=False,
elem_id="img2img_mask")
with gr.Row():
img2img_image_editor_mode = gr.Radio(choices=["Mask", "Crop"], label="Image Editor Mode",
value="Crop", elem_id='edit_mode_select')
img2img_painterro_btn = gr.Button("Advanced Editor")
img2img_copy_from_painterro_btn = gr.Button(value="Get Image from Advanced Editor")
img2img_show_help_btn = gr.Button("Show Hints")
img2img_hide_help_btn = gr.Button("Hide Hints", visible=False)
img2img_help = gr.Markdown(visible=False, value="")
with gr.Column():
gr.Markdown('#### Img2Img Results')
output_img2img_gallery = gr.Gallery(label="Images", elem_id="img2img_gallery_output").style(grid=[4,4,4])
with gr.Tabs():
with gr.TabItem("Generated image actions", id="img2img_actions_tab"):
with gr.Group():
gr.Markdown("Select an image, then press one of the buttons below")
output_img2img_copy_to_clipboard_btn = gr.Button("Copy to clipboard")
output_img2img_copy_to_input_btn = gr.Button("Push to img2img input")
output_img2img_copy_to_mask_btn = gr.Button("Push to img2img input mask")
gr.Markdown("Warning: This will clear your current image and mask settings!")
with gr.TabItem("Output info", id="img2img_output_info_tab"):
output_img2img_params = gr.Textbox(label="Generation parameters")
with gr.Row():
output_img2img_copy_params = gr.Button("Copy full parameters").click(
inputs=output_img2img_params, outputs=[],
_js='(x) => navigator.clipboard.writeText(x)', fn=None, show_progress=False)
output_img2img_seed = gr.Number(label='Seed', interactive=False, visible=False)
output_img2img_copy_seed = gr.Button("Copy only seed").click(
inputs=output_img2img_seed, outputs=[],
_js='(x) => navigator.clipboard.writeText(x)', fn=None, show_progress=False)
output_img2img_stats = gr.HTML(label='Stats')
gr.Markdown('# img2img settings')
with gr.Row():
with gr.Column():
img2img_batch_size = gr.Slider(minimum=1, maximum=8, step=1,
label='Batch size (how many images are in a batch; memory-hungry)',
value=img2img_defaults['batch_size'])
img2img_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width",
value=img2img_defaults["width"])
img2img_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height",
value=img2img_defaults["height"])
img2img_seed = gr.Textbox(label="Seed (blank to randomize)", lines=1,
value=img2img_defaults["seed"])
img2img_steps = gr.Slider(minimum=1, maximum=250, step=1, label="Sampling Steps",
value=img2img_defaults['ddim_steps'])
img2img_batch_count = gr.Slider(minimum=1, maximum=250, step=1,
label='Batch count (how many batches of images to generate)',
value=img2img_defaults['n_iter'])
with gr.Column():
img2img_mask = gr.Radio(choices=["Keep masked area", "Regenerate only masked area"],
label="Mask Mode", type="index",
value=img2img_mask_modes[img2img_defaults['mask_mode']], visible=False)
img2img_mask_blur_strength = gr.Slider(minimum=1, maximum=10, step=1,
label="How much blurry should the mask be? (to avoid hard edges)",
value=3, visible=False)
img2img_sampling = gr.Dropdown(label='Sampling method (k_lms is default k-diffusion sampler)',
choices=["DDIM", 'k_dpm_2_a', 'k_dpm_2', 'k_euler_a', 'k_euler',
'k_heun', 'k_lms'],
value=img2img_defaults['sampler_name'])
img2img_toggles = gr.CheckboxGroup(label='', choices=img2img_toggles,
value=img2img_toggle_defaults, type="index")
img2img_realesrgan_model_name = gr.Dropdown(label='RealESRGAN model',
choices=['RealESRGAN_x4plus',
'RealESRGAN_x4plus_anime_6B'],
value='RealESRGAN_x4plus',
visible=RealESRGAN is not None) # TODO: Feels like I shouldnt slot it in here.
img2img_cfg = gr.Slider(minimum=1.0, maximum=30.0, step=0.5,
label='Classifier Free Guidance Scale (how strongly the image should follow the prompt)',
value=img2img_defaults['cfg_scale'])
img2img_denoising = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising Strength',
value=img2img_defaults['denoising_strength'])
img2img_resize = gr.Radio(label="Resize mode",
choices=["Just resize", "Crop and resize", "Resize and fill"],
type="index",
value=img2img_resize_modes[img2img_defaults['resize_mode']])
img2img_embeddings = gr.File(label="Embeddings file for textual inversion",
visible=show_embeddings)
img2img_image_editor_mode.change(
uifn.change_image_editor_mode,
[img2img_image_editor_mode, img2img_image_editor, img2img_resize, img2img_width, img2img_height],
[img2img_image_editor, img2img_image_mask, img2img_btn_editor, img2img_btn_mask,
img2img_painterro_btn, img2img_copy_from_painterro_btn, img2img_mask, img2img_mask_blur_strength]
)
img2img_image_editor.edit(
uifn.update_image_mask,
[img2img_image_editor, img2img_resize, img2img_width, img2img_height],
img2img_image_mask
)
img2img_show_help_btn.click(
uifn.show_help,
None,
[img2img_show_help_btn, img2img_hide_help_btn, img2img_help]
)
img2img_hide_help_btn.click(
uifn.hide_help,
None,
[img2img_show_help_btn, img2img_hide_help_btn, img2img_help]
)
output_txt2img_copy_to_input_btn.click(
uifn.copy_img_to_input,
[output_txt2img_gallery],
[img2img_image_editor, img2img_image_mask, tabs],
_js=js_return_selected_txt2img
)
output_img2img_copy_to_input_btn.click(
uifn.copy_img_to_edit,
[output_img2img_gallery],
[img2img_image_editor, tabs, img2img_image_editor_mode],
_js=js_return_selected_img2img
)
output_img2img_copy_to_mask_btn.click(
uifn.copy_img_to_mask,
[output_img2img_gallery],
[img2img_image_mask, tabs, img2img_image_editor_mode],
_js=js_return_selected_img2img
)
output_img2img_copy_to_clipboard_btn.click(fn=None, inputs=output_img2img_gallery, outputs=[],
_js=js_copy_selected_img2img)
img2img_btn_mask.click(
img2img,
[img2img_prompt, img2img_image_editor_mode, img2img_image_mask, img2img_mask,
img2img_mask_blur_strength, img2img_steps, img2img_sampling, img2img_toggles,
img2img_realesrgan_model_name, img2img_batch_count, img2img_batch_size, img2img_cfg,
img2img_denoising, img2img_seed, img2img_height, img2img_width, img2img_resize,
img2img_embeddings],
[output_img2img_gallery, output_img2img_seed, output_img2img_params, output_img2img_stats]
)
def img2img_submit_params():
return (img2img,
[img2img_prompt, img2img_image_editor_mode, img2img_image_editor, img2img_mask,
img2img_mask_blur_strength, img2img_steps, img2img_sampling, img2img_toggles,
img2img_realesrgan_model_name, img2img_batch_count, img2img_batch_size, img2img_cfg,
img2img_denoising, img2img_seed, img2img_height, img2img_width, img2img_resize,
img2img_embeddings],
[output_img2img_gallery, output_img2img_seed, output_img2img_params, output_img2img_stats])
img2img_btn_editor.click(*img2img_submit_params())
img2img_prompt.submit(*img2img_submit_params())
img2img_painterro_btn.click(None, [img2img_image_editor], None, _js="""(img) => {
try {
Painterro({
hiddenTools: ['arrow'],
saveHandler: function (image, done) {
localStorage.setItem('painterro-image', image.asDataURL());
done(true);
},
}).show(Array.isArray(img) ? img[0] : img);
} catch(e) {
const script = document.createElement('script');
script.src = 'https://unpkg.com/painterro@1.2.78/build/painterro.min.js';
document.head.appendChild(script);
const style = document.createElement('style');
style.appendChild(document.createTextNode('.ptro-holder-wrapper { z-index: 9999 !important; }'));
document.head.appendChild(style);
}
return [];
}""")
img2img_copy_from_painterro_btn.click(None, None, [img2img_image_editor, img2img_image_mask], _js="""() => {
const image = localStorage.getItem('painterro-image')
return [image, image];
}""")
if GFPGAN is not None:
gfpgan_defaults = {
'strength': 100,
}
if 'gfpgan' in user_defaults:
gfpgan_defaults.update(user_defaults['gfpgan'])
with gr.TabItem("GFPGAN", id='cfpgan_tab'):
gr.Markdown("Fix faces on images")
with gr.Row():
with gr.Column():
gfpgan_source = gr.Image(label="Source", source="upload", interactive=True, type="pil")
gfpgan_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Effect strength",
value=gfpgan_defaults['strength'])
gfpgan_btn = gr.Button("Generate", variant="primary")
with gr.Column():
gfpgan_output = gr.Image(label="Output")
gfpgan_btn.click(
run_GFPGAN,
[gfpgan_source, gfpgan_strength],
[gfpgan_output]
)
if RealESRGAN is not None:
with gr.TabItem("RealESRGAN", id='realesrgan_tab'):
gr.Markdown("Upscale images")
with gr.Row():
with gr.Column():
realesrgan_source = gr.Image(label="Source", source="upload", interactive=True, type="pil")
realesrgan_model_name = gr.Dropdown(label='RealESRGAN model', choices=['RealESRGAN_x4plus',
'RealESRGAN_x4plus_anime_6B'],
value='RealESRGAN_x4plus')
realesrgan_btn = gr.Button("Generate")
with gr.Column():
realesrgan_output = gr.Image(label="Output")
realesrgan_btn.click(
run_RealESRGAN,
[realesrgan_source, realesrgan_model_name],
[realesrgan_output]
)
output_txt2img_to_upscale_esrgan.click(
uifn.copy_img_to_upscale_esrgan,
output_txt2img_gallery,
[realesrgan_source, tabs],
_js=js_return_selected_txt2img)
gr.HTML("""
<div id="90" style="max-width: 100%; font-size: 14px; text-align: center;" class="output-markdown gr-prose border-solid border border-gray-200 rounded gr-panel">
<p>For help and advanced usage guides, visit the <a href="https://github.com/hlky/stable-diffusion-webui/wiki" target="_blank">Project Wiki</a></p>
<p>Stable Diffusion WebUI is an open-source project. You can find the latest stable builds on the <a href="https://github.com/hlky/stable-diffusion" target="_blank">main repository</a>.
If you would like to contribute to developement or test bleeding edge builds, you can visit the <a href="https://github.com/hlky/stable-diffusion-webui" target="_blank">developement repository</a>.</p>
</div>
""")
return demo

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import re
import gradio as gr
from PIL import Image, ImageFont, ImageDraw, ImageFilter, ImageOps
from io import BytesIO
import base64
import re
def change_image_editor_mode(choice, cropped_image, resize_mode, width, height):
if choice == "Mask":
return [gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), gr.update(visible=True)]
return [gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)]
def update_image_mask(cropped_image, resize_mode, width, height):
resized_cropped_image = resize_image(resize_mode, cropped_image, width, height) if cropped_image else None
return gr.update(value=resized_cropped_image)
def copy_img_to_input(img):
try:
image_data = re.sub('^data:image/.+;base64,', '', img)
processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
tab_update = gr.update(selected='img2img_tab')
img_update = gr.update(value=processed_image)
return processed_image, processed_image , tab_update
except IndexError:
return [None, None]
def copy_img_to_edit(img):
try:
image_data = re.sub('^data:image/.+;base64,', '', img)
processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
tab_update = gr.update(selected='img2img_tab')
img_update = gr.update(value=processed_image)
mode_update = gr.update(value='Crop')
return processed_image, tab_update, mode_update
except IndexError:
return [None, None]
def copy_img_to_mask(img):
try:
image_data = re.sub('^data:image/.+;base64,', '', img)
processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
tab_update = gr.update(selected='img2img_tab')
img_update = gr.update(value=processed_image)
mode_update = gr.update(value='Mask')
return processed_image, tab_update, mode_update
except IndexError:
return [None, None]
def copy_img_to_upscale_esrgan(img):
tabs_update = gr.update(selected='realesrgan_tab')
image_data = re.sub('^data:image/.+;base64,', '', img)
processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
return processed_image, tabs_update
help_text = """
## Mask/Crop
* The masking/cropping is very temperamental.
* It may take some time for the image to show when switching from Crop to Mask.
* If the image doesn't appear after switching to Mask, switch back to Crop and then back again to Mask
* If the mask appears distorted (the brush is weirdly shaped instead of round), switch back to Crop and then back again to Mask.
## Advanced Editor
* For now the button needs to be clicked twice the first time.
* Once you have edited your image, you _need_ to click the save button for the next step to work.
* Clear the image from the crop editor (click the x)
* Click "Get Image from Advanced Editor" to get the image you saved. If it doesn't work, try opening the editor and saving again.
If it keeps not working, try switching modes again, switch tabs, clear the image or reload.
"""
def show_help():
return [gr.update(visible=False), gr.update(visible=True), gr.update(value=help_text)]
def hide_help():
return [gr.update(visible=True), gr.update(visible=False), gr.update(value="")]
def resize_image(resize_mode, im, width, height):
LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS)
if resize_mode == 0:
res = im.resize((width, height), resample=LANCZOS)
elif resize_mode == 1:
ratio = width / height
src_ratio = im.width / im.height
src_w = width if ratio > src_ratio else im.width * height // im.height
src_h = height if ratio <= src_ratio else im.height * width // im.width
resized = im.resize((src_w, src_h), resample=LANCZOS)
res = Image.new("RGB", (width, height))
res.paste(resized, box=(width // 2 - src_w // 2, height // 2 - src_h // 2))
else:
ratio = width / height
src_ratio = im.width / im.height
src_w = width if ratio < src_ratio else im.width * height // im.height
src_h = height if ratio >= src_ratio else im.height * width // im.width
resized = im.resize((src_w, src_h), resample=LANCZOS)
res = Image.new("RGB", (width, height))
res.paste(resized, box=(width // 2 - src_w // 2, height // 2 - src_h // 2))
if ratio < src_ratio:
fill_height = height // 2 - src_h // 2
res.paste(resized.resize((width, fill_height), box=(0, 0, width, 0)), box=(0, 0))
res.paste(resized.resize((width, fill_height), box=(0, resized.height, width, resized.height)), box=(0, fill_height + src_h))
elif ratio > src_ratio:
fill_width = width // 2 - src_w // 2
res.paste(resized.resize((fill_width, height), box=(0, 0, 0, height)), box=(0, 0))
res.paste(resized.resize((fill_width, height), box=(resized.width, 0, resized.width, height)), box=(fill_width + src_w, 0))
return res

326
webui.py
View File

@ -1,5 +1,7 @@
import argparse, os, sys, glob, re
from frontend.frontend import draw_gradio_ui
parser = argparse.ArgumentParser()
parser.add_argument("--outdir", type=str, nargs="?", help="dir to write results to", default=None)
parser.add_argument("--outdir_txt2img", type=str, nargs="?", help="dir to write txt2img results to (overrides --outdir)", default=None)
@ -471,40 +473,6 @@ def draw_prompt_matrix(im, width, height, all_prompts):
return result
def resize_image(resize_mode, im, width, height):
if resize_mode == 0:
res = im.resize((width, height), resample=LANCZOS)
elif resize_mode == 1:
ratio = width / height
src_ratio = im.width / im.height
src_w = width if ratio > src_ratio else im.width * height // im.height
src_h = height if ratio <= src_ratio else im.height * width // im.width
resized = im.resize((src_w, src_h), resample=LANCZOS)
res = Image.new("RGB", (width, height))
res.paste(resized, box=(width // 2 - src_w // 2, height // 2 - src_h // 2))
else:
ratio = width / height
src_ratio = im.width / im.height
src_w = width if ratio < src_ratio else im.width * height // im.height
src_h = height if ratio >= src_ratio else im.height * width // im.width
resized = im.resize((src_w, src_h), resample=LANCZOS)
res = Image.new("RGB", (width, height))
res.paste(resized, box=(width // 2 - src_w // 2, height // 2 - src_h // 2))
if ratio < src_ratio:
fill_height = height // 2 - src_h // 2
res.paste(resized.resize((width, fill_height), box=(0, 0, width, 0)), box=(0, 0))
res.paste(resized.resize((width, fill_height), box=(0, resized.height, width, resized.height)), box=(0, fill_height + src_h))
elif ratio > src_ratio:
fill_width = width // 2 - src_w // 2
res.paste(resized.resize((fill_width, height), box=(0, 0, 0, height)), box=(0, 0))
res.paste(resized.resize((fill_width, height), box=(resized.width, 0, resized.width, height)), box=(fill_width + src_w, 0))
return res
def check_prompt_length(prompt, comments):
@ -1463,295 +1431,7 @@ def hide_help():
return [gr.update(visible=True), gr.update(visible=False), gr.update(value="")]
css_hide_progressbar = """
.wrap .m-12 svg { display:none!important; }
.wrap .m-12::before { content:"Loading..." }
.progress-bar { display:none!important; }
.meta-text { display:none!important; }
"""
styling = """
[data-testid="image"] {min-height: 512px !important}
* #body>.col:nth-child(2){width:250%;max-width:89vw}
#generate{width: 100%; }
#prompt_row input{
font-size:20px
}
input[type=number]:disabled { -moz-appearance: textfield;+ }
"""
css = styling if opt.no_progressbar_hiding else styling + css_hide_progressbar
# This is the code that finds which selected item the user has in the gallery
js_part_getindex_txt2img="""
const root = document.querySelector('gradio-app').shadowRoot;
const getIndex = function(){
const selected = root.querySelector('#txt2img_gallery_output .\\\\!ring-2');
return selected ? [...selected.parentNode.children].indexOf(selected) : 0;
};"""
js_part_getindex_img2img="""
const root = document.querySelector('gradio-app').shadowRoot;
const getIndex = function(){
const selected = root.querySelector('#img2img_gallery_output .\\\\!ring-2');
return selected ? [...selected.parentNode.children].indexOf(selected) : 0;
};"""
js_part_clear_img2img="""
root.querySelector('#img2img_editor .modify-upload button:last-child')?.click();
root.querySelector('#img2img_editor')?.parentNode.querySelector('input[type="radio"][value="Mask"]')?.click();
root.querySelector('#img2img_mask .modify-upload button:last-child')?.click();
"""
js_return_selected_txt2img = "(x) => {" + js_part_getindex_txt2img + js_part_clear_img2img + """
return [x[getIndex()].replace('data:;','data:image/png;')];
}"""
js_return_selected_img2img = "(x) => {" + js_part_getindex_img2img + js_part_clear_img2img + """
return [x[getIndex()].replace('data:;','data:image/png;')];
}"""
js_part_copy_to_clipboard="""
const data = x[getIndex()];
const blob = await (await fetch(data.replace('data:;','data:image/png;'))).blob();
const item = new ClipboardItem({'image/png': blob});
navigator.clipboard.write([item]);
return x;
}"""
js_copy_selected_txt2img = "async (x) => {" + js_part_getindex_txt2img + js_part_copy_to_clipboard
js_copy_selected_img2img = "async (x) => {" + js_part_getindex_img2img + js_part_copy_to_clipboard
with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion WebUI") as demo:
with gr.Tabs(elem_id='tabss') as tabs:
with gr.TabItem("Stable Diffusion Text-to-Image Unified", id='txt2img_tab'):
with gr.Row(elem_id="prompt_row"):
txt2img_prompt = gr.Textbox(label="Prompt",
elem_id='prompt_input',
placeholder="A corgi wearing a top hat as an oil painting.",
lines=1,
max_lines=1 if txt2img_defaults['submit_on_enter'] == 'Yes' else 25,
value=txt2img_defaults['prompt'],
show_label=False)
with gr.Row(elem_id='body').style(equal_height=False):
with gr.Column():
txt2img_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=txt2img_defaults["height"])
txt2img_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=txt2img_defaults["width"])
txt2img_cfg = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='Classifier Free Guidance Scale (how strongly the image should follow the prompt)', value=txt2img_defaults['cfg_scale'])
txt2img_seed = gr.Textbox(label="Seed (blank to randomize)", lines=1, max_lines=1, value=txt2img_defaults["seed"])
txt2img_batch_count = gr.Slider(minimum=1, maximum=250, step=1, label='Batch count (how many batches of images to generate)', value=txt2img_defaults['n_iter'])
txt2img_batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size (how many images are in a batch; memory-hungry)', value=txt2img_defaults['batch_size'])
with gr.Column():
output_txt2img_gallery = gr.Gallery(label="Images", elem_id="txt2img_gallery_output").style(grid=[4,4])
with gr.Tabs():
with gr.TabItem("Generated image actions", id="text2img_actions_tab"):
gr.Markdown('Select an image from the gallery, then click one of the buttons below to perform an action.')
with gr.Row():
output_txt2img_copy_clipboard = gr.Button("Copy to clipboard").click(fn=None, inputs=output_txt2img_gallery, outputs=[], _js=js_copy_selected_txt2img)
output_txt2img_copy_to_input_btn = gr.Button("Push to img2img")
if RealESRGAN is not None:
output_txt2img_to_upscale_esrgan = gr.Button("Upscale w/ ESRGAN")
with gr.TabItem("Output Info", id="text2img_output_info_tab"):
output_txt2img_params = gr.Textbox(label="Generation parameters", interactive=False)
with gr.Row():
output_txt2img_copy_params = gr.Button("Copy full parameters").click(inputs=output_txt2img_params, outputs=[], _js='(x) => navigator.clipboard.writeText(x)', fn=None, show_progress=False)
output_txt2img_seed = gr.Number(label='Seed', interactive=False, visible=False)
output_txt2img_copy_seed = gr.Button("Copy only seed").click(inputs=output_txt2img_seed, outputs=[], _js='(x) => navigator.clipboard.writeText(x)', fn=None, show_progress=False)
output_txt2img_stats = gr.HTML(label='Stats')
with gr.Column():
txt2img_btn = gr.Button("Generate", elem_id="generate", variant="primary")
txt2img_steps = gr.Slider(minimum=1, maximum=250, step=1, label="Sampling Steps", value=txt2img_defaults['ddim_steps'])
txt2img_sampling = gr.Dropdown(label='Sampling method (k_lms is default k-diffusion sampler)', choices=["DDIM", "PLMS", 'k_dpm_2_a', 'k_dpm_2', 'k_euler_a', 'k_euler', 'k_heun', 'k_lms'], value=txt2img_defaults['sampler_name'])
with gr.Tabs():
with gr.TabItem('Simple'):
txt2img_submit_on_enter = gr.Radio(['Yes', 'No'], label="Submit on enter? (no means multiline)", value=txt2img_defaults['submit_on_enter'], interactive=True)
txt2img_submit_on_enter.change(lambda x: gr.update(max_lines=1 if x == 'Single' else 25) , txt2img_submit_on_enter, txt2img_prompt)
with gr.TabItem('Advanced'):
txt2img_toggles = gr.CheckboxGroup(label='', choices=txt2img_toggles, value=txt2img_toggle_defaults, type="index")
txt2img_realesrgan_model_name = gr.Dropdown(label='RealESRGAN model', choices=['RealESRGAN_x4plus', 'RealESRGAN_x4plus_anime_6B'], value='RealESRGAN_x4plus', visible=RealESRGAN is not None) # TODO: Feels like I shouldnt slot it in here.
txt2img_ddim_eta = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label="DDIM ETA", value=txt2img_defaults['ddim_eta'], visible=False)
txt2img_embeddings = gr.File(label = "Embeddings file for textual inversion", visible=hasattr(model, "embedding_manager"))
txt2img_btn.click(
txt2img,
[txt2img_prompt, txt2img_steps, txt2img_sampling, txt2img_toggles, txt2img_realesrgan_model_name, txt2img_ddim_eta, txt2img_batch_count, txt2img_batch_size, txt2img_cfg, txt2img_seed, txt2img_height, txt2img_width, txt2img_embeddings],
[output_txt2img_gallery, output_txt2img_seed, output_txt2img_params, output_txt2img_stats]
)
txt2img_prompt.submit(
txt2img,
[txt2img_prompt, txt2img_steps, txt2img_sampling, txt2img_toggles, txt2img_realesrgan_model_name, txt2img_ddim_eta, txt2img_batch_count, txt2img_batch_size, txt2img_cfg, txt2img_seed, txt2img_height, txt2img_width, txt2img_embeddings],
[output_txt2img_gallery, output_txt2img_seed, output_txt2img_params, output_txt2img_stats]
)
with gr.TabItem("Stable Diffusion Image-to-Image Unified", id="img2img_tab"):
with gr.Row(elem_id="prompt_row"):
img2img_prompt = gr.Textbox(label="Prompt",
elem_id='img2img_prompt_input',
placeholder="A fantasy landscape, trending on artstation.",
lines=1,
max_lines=1 if txt2img_defaults['submit_on_enter'] == 'Yes' else 25,
value=img2img_defaults['prompt'],
show_label=False).style()
img2img_btn_mask = gr.Button("Generate",variant="primary", visible=False, elem_id="img2img_mask_btn")
img2img_btn_editor = gr.Button("Generate",variant="primary", elem_id="img2img_editot_btn")
with gr.Row().style(equal_height=False):
with gr.Column():
img2img_image_editor_mode = gr.Radio(choices=["Mask", "Crop"], label="Image Editor Mode", value="Crop")
img2img_show_help_btn = gr.Button("Show Hints")
img2img_hide_help_btn = gr.Button("Hide Hints", visible=False)
img2img_help = gr.Markdown(visible=False, value="")
with gr.Row():
img2img_painterro_btn = gr.Button("Advanced Editor")
img2img_copy_from_painterro_btn = gr.Button(value="Get Image from Advanced Editor")
img2img_image_editor = gr.Image(value=sample_img2img, source="upload", interactive=True, type="pil", tool="select", elem_id="img2img_editor")
img2img_image_mask = gr.Image(value=sample_img2img, source="upload", interactive=True, type="pil", tool="sketch", visible=False, elem_id="img2img_mask")
img2img_mask = gr.Radio(choices=["Keep masked area", "Regenerate only masked area"], label="Mask Mode", type="index", value=img2img_mask_modes[img2img_defaults['mask_mode']], visible=False)
img2img_mask_blur_strength = gr.Slider(minimum=1, maximum=10, step=1, label="How much blurry should the mask be? (to avoid hard edges)", value=3, visible=False)
img2img_steps = gr.Slider(minimum=1, maximum=250, step=1, label="Sampling Steps", value=img2img_defaults['ddim_steps'])
img2img_sampling = gr.Dropdown(label='Sampling method (k_lms is default k-diffusion sampler)', choices=["DDIM", 'k_dpm_2_a', 'k_dpm_2', 'k_euler_a', 'k_euler', 'k_heun', 'k_lms'], value=img2img_defaults['sampler_name'])
img2img_toggles = gr.CheckboxGroup(label='', choices=img2img_toggles, value=img2img_toggle_defaults, type="index")
img2img_realesrgan_model_name = gr.Dropdown(label='RealESRGAN model', choices=['RealESRGAN_x4plus', 'RealESRGAN_x4plus_anime_6B'], value='RealESRGAN_x4plus', visible=RealESRGAN is not None) # TODO: Feels like I shouldnt slot it in here.
img2img_batch_count = gr.Slider(minimum=1, maximum=250, step=1, label='Batch count (how many batches of images to generate)', value=img2img_defaults['n_iter'])
img2img_batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size (how many images are in a batch; memory-hungry)', value=img2img_defaults['batch_size'])
img2img_cfg = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='Classifier Free Guidance Scale (how strongly the image should follow the prompt)', value=img2img_defaults['cfg_scale'])
img2img_denoising = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising Strength', value=img2img_defaults['denoising_strength'])
img2img_seed = gr.Textbox(label="Seed (blank to randomize)", lines=1, value=img2img_defaults["seed"])
img2img_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=img2img_defaults["height"])
img2img_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=img2img_defaults["width"])
img2img_resize = gr.Radio(label="Resize mode", choices=["Just resize", "Crop and resize", "Resize and fill"], type="index", value=img2img_resize_modes[img2img_defaults['resize_mode']])
img2img_embeddings = gr.File(label = "Embeddings file for textual inversion", visible=hasattr(model, "embedding_manager"))
with gr.Column():
output_img2img_gallery = gr.Gallery(label="Images", elem_id="img2img_gallery_output")
with gr.Tabs():
with gr.TabItem("Generated image actions", id="img2img_actions_tab"):
gr.Markdown("Select an image, then press one of the buttons below")
output_img2img_copy_to_clipboard_btn = gr.Button("Copy to clipboard")
output_img2img_copy_to_input_btn = gr.Button("Push to img2img input")
gr.Markdown("Warning: This will clear your current image and mask settings!")
with gr.TabItem("Output info", id="img2img_output_info_tab"):
output_img2img_params = gr.Textbox(label="Generation parameters")
with gr.Row():
output_img2img_copy_params = gr.Button("Copy full parameters").click(inputs=output_img2img_params, outputs=[], _js='(x) => navigator.clipboard.writeText(x)', fn=None, show_progress=False)
output_img2img_seed = gr.Number(label='Seed', interactive=False, visible=False)
output_img2img_copy_seed = gr.Button("Copy only seed").click(inputs=output_img2img_seed, outputs=[], _js='(x) => navigator.clipboard.writeText(x)', fn=None, show_progress=False)
output_img2img_stats = gr.HTML(label='Stats')
img2img_image_editor_mode.change(
change_image_editor_mode,
[img2img_image_editor_mode, img2img_image_editor, img2img_resize, img2img_width, img2img_height],
[img2img_image_editor, img2img_image_mask, img2img_btn_editor, img2img_btn_mask, img2img_painterro_btn, img2img_copy_from_painterro_btn, img2img_mask, img2img_mask_blur_strength]
)
img2img_image_editor.edit(
update_image_mask,
[img2img_image_editor, img2img_resize, img2img_width, img2img_height],
img2img_image_mask
)
img2img_show_help_btn.click(
show_help,
None,
[img2img_show_help_btn, img2img_hide_help_btn, img2img_help]
)
img2img_hide_help_btn.click(
hide_help,
None,
[img2img_show_help_btn, img2img_hide_help_btn, img2img_help]
)
output_txt2img_copy_to_input_btn.click(
copy_img_to_input,
[output_txt2img_gallery],
[img2img_image_editor, img2img_image_mask, tabs],
_js=js_return_selected_txt2img
)
output_img2img_copy_to_input_btn.click(
copy_img_to_input,
[output_img2img_gallery],
[img2img_image_editor, img2img_image_mask, tabs],
_js=js_return_selected_img2img
)
output_img2img_copy_to_clipboard_btn.click(fn=None, inputs=output_img2img_gallery, outputs=[], _js=js_copy_selected_img2img)
img2img_btn_mask.click(
img2img,
[img2img_prompt, img2img_image_editor_mode, img2img_image_mask, img2img_mask, img2img_mask_blur_strength, img2img_steps, img2img_sampling, img2img_toggles, img2img_realesrgan_model_name, img2img_batch_count, img2img_batch_size, img2img_cfg, img2img_denoising, img2img_seed, img2img_height, img2img_width, img2img_resize, img2img_embeddings],
[output_img2img_gallery, output_img2img_seed, output_img2img_params, output_img2img_stats]
)
img2img_btn_editor.click(
img2img,
[img2img_prompt, img2img_image_editor_mode, img2img_image_editor, img2img_mask, img2img_mask_blur_strength, img2img_steps, img2img_sampling, img2img_toggles, img2img_realesrgan_model_name, img2img_batch_count, img2img_batch_size, img2img_cfg, img2img_denoising, img2img_seed, img2img_height, img2img_width, img2img_resize, img2img_embeddings],
[output_img2img_gallery, output_img2img_seed, output_img2img_params, output_img2img_stats]
)
img2img_painterro_btn.click(None, [img2img_image_editor], None, _js="""(img) => {
try {
Painterro({
hiddenTools: ['arrow'],
saveHandler: function (image, done) {
localStorage.setItem('painterro-image', image.asDataURL());
done(true);
},
}).show(Array.isArray(img) ? img[0] : img);
} catch(e) {
const script = document.createElement('script');
script.src = 'https://unpkg.com/painterro@1.2.78/build/painterro.min.js';
document.head.appendChild(script);
const style = document.createElement('style');
style.appendChild(document.createTextNode('.ptro-holder-wrapper { z-index: 9999 !important; }'));
document.head.appendChild(style);
}
return [];
}""")
img2img_copy_from_painterro_btn.click(None, None, [img2img_image_editor, img2img_image_mask], _js="""() => {
const image = localStorage.getItem('painterro-image')
return [image, image];
}""")
if GFPGAN is not None:
gfpgan_defaults = {
'strength': 100,
}
if 'gfpgan' in user_defaults:
gfpgan_defaults.update(user_defaults['gfpgan'])
with gr.TabItem("GFPGAN", id='cfpgan_tab'):
gr.Markdown("Fix faces on images")
with gr.Row():
with gr.Column():
gfpgan_source = gr.Image(label="Source", source="upload", interactive=True, type="pil")
gfpgan_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Effect strength", value=gfpgan_defaults['strength'])
gfpgan_btn = gr.Button("Generate", variant="primary")
with gr.Column():
gfpgan_output = gr.Image(label="Output")
gfpgan_btn.click(
run_GFPGAN,
[gfpgan_source, gfpgan_strength],
[gfpgan_output]
)
if RealESRGAN is not None:
with gr.TabItem("RealESRGAN", id='realesrgan_tab'):
gr.Markdown("Upscale images")
with gr.Row():
with gr.Column():
realesrgan_source = gr.Image(label="Source", source="upload", interactive=True, type="pil")
realesrgan_model_name = gr.Dropdown(label='RealESRGAN model', choices=['RealESRGAN_x4plus', 'RealESRGAN_x4plus_anime_6B'], value='RealESRGAN_x4plus')
realesrgan_btn = gr.Button("Generate")
with gr.Column():
realesrgan_output = gr.Image(label="Output")
realesrgan_btn.click(
run_RealESRGAN,
[realesrgan_source, realesrgan_model_name],
[realesrgan_output]
)
gr.HTML("""
<div id="90" style="max-width: 100%; font-size: 14px; text-align: center;" class="output-markdown gr-prose border-solid border border-gray-200 rounded gr-panel">
<p>For help and advanced usage guides, visit the <a href="https://github.com/hlky/stable-diffusion-webui/wiki" target="_blank">Project Wiki</a></p>
<p>Stable Diffusion WebUI is an open-source project. You can find the latest stable builds on the <a href="https://github.com/hlky/stable-diffusion" target="_blank">main repository</a>.
If you would like to contribute to developement or test bleeding edge builds, you can visit the <a href="https://github.com/hlky/stable-diffusion-webui" target="_blank">developement repository</a>.</p>
</div>
""")
demo = draw_gradio_ui(opt, txt2img_defaults=txt2img_defaults)
class ServerLauncher(threading.Thread):
def __init__(self, demo):

352
webui_playground.py
View File

@ -6,6 +6,8 @@ from io import BytesIO
import base64
import re
from frontend.frontend import draw_gradio_ui
"""
This file is here to play around with the interface without loading the whole model
@ -161,60 +163,6 @@ if 'img2img' in user_defaults:
img2img_toggle_defaults = [img2img_toggles[i] for i in img2img_defaults['toggles']]
img2img_image_mode = 'sketch'
def change_image_editor_mode(choice, cropped_image, resize_mode, width, height):
if choice == "Mask":
return [gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), gr.update(visible=True)]
return [gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)]
def update_image_mask(cropped_image, resize_mode, width, height):
resized_cropped_image = resize_image(resize_mode, cropped_image, width, height) if cropped_image else None
return gr.update(value=resized_cropped_image)
def copy_img_to_input(img):
try:
image_data = re.sub('^data:image/.+;base64,', '', img)
processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
tab_update = gr.update(selected='img2img_tab')
img_update = gr.update(value=processed_image)
return {img2img_image_mask: processed_image, img2img_image_editor: img_update, tabs: tab_update}
except IndexError:
return [None, None]
def copy_img_to_upscale_esrgan(img):
update = gr.update(selected='realesrgan_tab')
image_data = re.sub('^data:image/.+;base64,', '', img)
processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
return {realesrgan_source: processed_image, tabs: update}
def copy_img_to_upscale_gobig(img):
update = gr.update(selected='gobig_tab')
image_data = re.sub('^data:image/.+;base64,', '', img)
processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
return {realesrganGoBig_source: processed_image, tabs: update}
help_text = """
## Mask/Crop
* The masking/cropping is very temperamental.
* It may take some time for the image to show when switching from Crop to Mask.
* If the image doesn't appear after switching to Mask, switch back to Crop and then back again to Mask
* If the mask appears distorted (the brush is weirdly shaped instead of round), switch back to Crop and then back again to Mask.
## Advanced Editor
* For now the button needs to be clicked twice the first time.
* Once you have edited your image, you _need_ to click the save button for the next step to work.
* Clear the image from the crop editor (click the x)
* Click "Get Image from Advanced Editor" to get the image you saved. If it doesn't work, try opening the editor and saving again.
If it keeps not working, try switching modes again, switch tabs, clear the image or reload.
"""
def show_help():
return [gr.update(visible=False), gr.update(visible=True), gr.update(value=help_text)]
def hide_help():
return [gr.update(visible=True), gr.update(visible=False), gr.update(value="")]
css_hide_progressbar = """
.wrap .m-12 svg { display:none!important; }
@ -233,283 +181,25 @@ styling = """
input[type=number]:disabled { -moz-appearance: textfield;+ }
"""
css = styling if opt.no_progressbar_hiding else styling + css_hide_progressbar
# This is the code that finds which selected item the user has in the gallery
js_part="""let getIndex = function(){
let selected = document.querySelector('gradio-app').shadowRoot.querySelector('#gallery_output .\\\\!ring-2');
return selected ? [...selected.parentNode.children].indexOf(selected) : 0;
};"""
return_selected_img_js = "(x) => {" + js_part+ " document.querySelector('gradio-app').shadowRoot.querySelector('#img2img_editor .modify-upload button:last-child')?.click();return [x[getIndex()].replace('data:;','data:image/png;')]}"
copy_selected_img_js = "async (x) => {" + js_part+ """
let data = x[getIndex()];
const blob = await (await fetch(data.replace('data:;','data:image/png;'))).blob();
let item = new ClipboardItem({'image/png': blob})
navigator.clipboard.write([item]);
return x
}"""
with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion WebUI") as demo:
with gr.Tabs(elem_id='tabss') as tabs:
with gr.TabItem("Stable Diffusion Text-to-Image Unified", id='txt2img_tab'):
with gr.Row(elem_id="prompt_row"):
txt2img_prompt = gr.Textbox(label="Prompt",
elem_id='prompt_input',
placeholder="A corgi wearing a top hat as an oil painting.",
lines=1,
max_lines=1 if txt2img_defaults['submit_on_enter'] == 'Yes' else 25,
value=txt2img_defaults['prompt'],
show_label=False)
with gr.Row(elem_id='body').style(equal_height=False):
with gr.Column():
txt2img_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=txt2img_defaults["height"])
txt2img_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=txt2img_defaults["width"])
txt2img_cfg = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='Classifier Free Guidance Scale (how strongly the image should follow the prompt)', value=txt2img_defaults['cfg_scale'])
txt2img_seed = gr.Textbox(label="Seed (blank to randomize)", lines=1, max_lines=1, value=txt2img_defaults["seed"])
txt2img_batch_count = gr.Slider(minimum=1, maximum=250, step=1, label='Batch count (how many batches of images to generate)', value=txt2img_defaults['n_iter'])
txt2img_batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size (how many images are in a batch; memory-hungry)', value=txt2img_defaults['batch_size'])
with gr.Column():
with gr.Group():
output_txt2img_gallery = gr.Gallery(label="Images", elem_id="gallery_output").style(grid=[4,4])
gr.Markdown('Selected image actions:')
output_txt2img_copy_clipboard = gr.Button("Copy to clipboard").click(fn=None, inputs=output_txt2img_gallery, outputs=[], _js=copy_selected_img_js)
output_txt2img_copy_to_input_btn = gr.Button("Push to img2img")
if RealESRGAN is not None:
output_txt2img_to_upscale_esrgan = gr.Button("Upscale w/ ESRCan")
output_txt2img_to_upscale_gobig = gr.Button("Upscale w/ GoBig")
with gr.Row():
with gr.Group():
output_txt2img_seed = gr.Number(label='Seed', interactive=False)
output_txt2img_copy_seed = gr.Button("Copy").click(inputs=output_txt2img_seed, outputs=[], _js='(x) => navigator.clipboard.writeText(x)', fn=None, show_progress=False)
with gr.Group():
output_txt2img_select_image = gr.Number(label='Image # and click Copy to copy to img2img', value=1, precision=None)
with gr.Group():
output_txt2img_params = gr.Textbox(label="Copy-paste generation parameters", interactive=False)
output_txt2img_copy_params = gr.Button("Copy").click(inputs=output_txt2img_params, outputs=[], _js='(x) => navigator.clipboard.writeText(x)', fn=None, show_progress=False)
output_txt2img_stats = gr.HTML(label='Stats')
with gr.Column():
txt2img_btn = gr.Button("Generate", elem_id="generate", variant="primary")
txt2img_steps = gr.Slider(minimum=1, maximum=250, step=1, label="Sampling Steps", value=txt2img_defaults['ddim_steps'])
txt2img_sampling = gr.Dropdown(label='Sampling method (k_lms is default k-diffusion sampler)', choices=["DDIM", "PLMS", 'k_dpm_2_a', 'k_dpm_2', 'k_euler_a', 'k_euler', 'k_heun', 'k_lms'], value=txt2img_defaults['sampler_name'])
with gr.Tabs():
with gr.TabItem('Simple'):
txt2img_submit_on_enter = gr.Radio(['Yes', 'No'], label="Submit on enter? (no means multiline)", value=txt2img_defaults['submit_on_enter'], interactive=True)
txt2img_submit_on_enter.change(lambda x: gr.update(max_lines=1 if x == 'Single' else 25) , txt2img_submit_on_enter, txt2img_prompt)
with gr.TabItem('Advanced'):
txt2img_toggles = gr.CheckboxGroup(label='', choices=txt2img_toggles, value=txt2img_toggle_defaults, type="index")
txt2img_realesrgan_model_name = gr.Dropdown(label='RealESRGAN model', choices=['RealESRGAN_x4plus', 'RealESRGAN_x4plus_anime_6B'], value='RealESRGAN_x4plus', visible=RealESRGAN is not None) # TODO: Feels like I shouldnt slot it in here.
txt2img_ddim_eta = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label="DDIM ETA", value=txt2img_defaults['ddim_eta'], visible=False)
txt2img_embeddings = gr.File(label = "Embeddings file for textual inversion", visible=hasattr(model, "embedding_manager"))
txt2img_btn.click(
txt2img,
[txt2img_prompt, txt2img_steps, txt2img_sampling, txt2img_toggles, txt2img_realesrgan_model_name, txt2img_ddim_eta, txt2img_batch_count, txt2img_batch_size, txt2img_cfg, txt2img_seed, txt2img_height, txt2img_width, txt2img_embeddings],
[output_txt2img_gallery, output_txt2img_seed, output_txt2img_params, output_txt2img_stats]
)
txt2img_prompt.submit(
txt2img,
[txt2img_prompt, txt2img_steps, txt2img_sampling, txt2img_toggles, txt2img_realesrgan_model_name, txt2img_ddim_eta, txt2img_batch_count, txt2img_batch_size, txt2img_cfg, txt2img_seed, txt2img_height, txt2img_width, txt2img_embeddings],
[output_txt2img_gallery, output_txt2img_seed, output_txt2img_params, output_txt2img_stats]
demo = draw_gradio_ui(opt,
user_defaults=user_defaults,
txt2img=txt2img,
img2img=img2img,
txt2img_defaults=txt2img_defaults,
txt2img_toggles=txt2img_toggles,
txt2img_toggle_defaults=txt2img_toggle_defaults,
show_embeddings=hasattr(model, "embedding_manager"),
img2img_defaults=img2img_defaults,
img2img_toggles=img2img_toggles,
img2img_toggle_defaults=img2img_toggle_defaults,
img2img_mask_modes=img2img_mask_modes,
img2img_resize_modes=img2img_resize_modes,
sample_img2img=sample_img2img,
RealESRGAN=RealESRGAN,
GFPGAN=GFPGAN,
run_GFPGAN=run_GFPGAN,
run_RealESRGAN=run_RealESRGAN
)
with gr.TabItem("Stable Diffusion Image-to-Image Unified", id="img2img_tab"):
with gr.Row(elem_id="prompt_row"):
img2img_prompt = gr.Textbox(label="Prompt",
elem_id='img2img_prompt_input',
placeholder="A fantasy landscape, trending on artstation.",
lines=1,
max_lines=1 if txt2img_defaults['submit_on_enter'] == 'Yes' else 25,
value=img2img_defaults['prompt'],
show_label=False).style()
img2img_btn_mask = gr.Button("Generate",variant="primary", visible=False, elem_id="img2img_mask_btn")
img2img_btn_editor = gr.Button("Generate",variant="primary", elem_id="img2img_editot_btn")
with gr.Row().style(equal_height=False):
with gr.Column():
img2img_image_editor_mode = gr.Radio(choices=["Mask", "Crop"], label="Image Editor Mode", value="Crop")
img2img_show_help_btn = gr.Button("Show Hints")
img2img_hide_help_btn = gr.Button("Hide Hints", visible=False)
img2img_help = gr.Markdown(visible=False, value="")
with gr.Row():
img2img_painterro_btn = gr.Button("Advanced Editor")
img2img_copy_from_painterro_btn = gr.Button(value="Get Image from Advanced Editor")
img2img_image_editor = gr.Image(value=sample_img2img, source="upload", interactive=True, type="pil", tool="select", elem_id="img2img_editor")
img2img_image_mask = gr.Image(value=sample_img2img, source="upload", interactive=True, type="pil", tool="sketch", visible=False, elem_id="img2img_mask")
img2img_mask = gr.Radio(choices=["Keep masked area", "Regenerate only masked area"], label="Mask Mode", type="index", value=img2img_mask_modes[img2img_defaults['mask_mode']], visible=False)
img2img_mask_blur_strength = gr.Slider(minimum=1, maximum=10, step=1, label="How much blurry should the mask be? (to avoid hard edges)", value=3, visible=False)
img2img_steps = gr.Slider(minimum=1, maximum=250, step=1, label="Sampling Steps", value=img2img_defaults['ddim_steps'])
img2img_sampling = gr.Dropdown(label='Sampling method (k_lms is default k-diffusion sampler)', choices=["DDIM", 'k_dpm_2_a', 'k_dpm_2', 'k_euler_a', 'k_euler', 'k_heun', 'k_lms'], value=img2img_defaults['sampler_name'])
img2img_toggles = gr.CheckboxGroup(label='', choices=img2img_toggles, value=img2img_toggle_defaults, type="index")
img2img_realesrgan_model_name = gr.Dropdown(label='RealESRGAN model', choices=['RealESRGAN_x4plus', 'RealESRGAN_x4plus_anime_6B'], value='RealESRGAN_x4plus', visible=RealESRGAN is not None) # TODO: Feels like I shouldnt slot it in here.
img2img_batch_count = gr.Slider(minimum=1, maximum=250, step=1, label='Batch count (how many batches of images to generate)', value=img2img_defaults['n_iter'])
img2img_batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size (how many images are in a batch; memory-hungry)', value=img2img_defaults['batch_size'])
img2img_cfg = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='Classifier Free Guidance Scale (how strongly the image should follow the prompt)', value=img2img_defaults['cfg_scale'])
img2img_denoising = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising Strength', value=img2img_defaults['denoising_strength'])
img2img_seed = gr.Textbox(label="Seed (blank to randomize)", lines=1, value=img2img_defaults["seed"])
img2img_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=img2img_defaults["height"])
img2img_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=img2img_defaults["width"])
img2img_resize = gr.Radio(label="Resize mode", choices=["Just resize", "Crop and resize", "Resize and fill"], type="index", value=img2img_resize_modes[img2img_defaults['resize_mode']])
img2img_embeddings = gr.File(label = "Embeddings file for textual inversion", visible=hasattr(model, "embedding_manager"))
with gr.Column():
with gr.Group():
output_img2img_gallery = gr.Gallery(label="Generated Images", elem_id="gallery_output").style(grid=[4,4])
output_img2img_copy_to_input_btn = gr.Button("⬅️ Copy selected image to input")
if RealESRGAN is not None:
output_txt2img_copy_to_gobig_input_btn = gr.Button("Upscale w/ goBig input")
gr.Markdown("Clear the input image before copying your output to your input. It may take some time to load the image.")
output_img2img_seed = gr.Number(label='Seed')
output_img2img_params = gr.Textbox(label="Copy-paste generation parameters")
output_img2img_stats = gr.HTML(label='Stats')
img2img_image_editor_mode.change(
change_image_editor_mode,
[img2img_image_editor_mode, img2img_image_editor, img2img_resize, img2img_width, img2img_height],
[img2img_image_editor, img2img_image_mask, img2img_btn_editor, img2img_btn_mask, img2img_painterro_btn, img2img_copy_from_painterro_btn, img2img_mask, img2img_mask_blur_strength]
)
img2img_image_editor.edit(
update_image_mask,
[img2img_image_editor, img2img_resize, img2img_width, img2img_height],
img2img_image_mask
)
img2img_show_help_btn.click(
show_help,
None,
[img2img_show_help_btn, img2img_hide_help_btn, img2img_help]
)
img2img_hide_help_btn.click(
hide_help,
None,
[img2img_show_help_btn, img2img_hide_help_btn, img2img_help]
)
output_img2img_copy_to_input_btn.click(
copy_img_to_input,
[output_img2img_gallery],
[img2img_image_editor, img2img_image_mask, tabs],
_js=return_selected_img_js
)
output_txt2img_copy_to_input_btn.click(
copy_img_to_input,
[output_txt2img_gallery],
[img2img_image_editor, img2img_image_mask, tabs],
_js=return_selected_img_js
)
img2img_btn_mask.click(
img2img,
[img2img_prompt, img2img_image_editor_mode, img2img_image_mask, img2img_mask, img2img_mask_blur_strength, img2img_steps, img2img_sampling, img2img_toggles, img2img_realesrgan_model_name, img2img_batch_count, img2img_batch_size, img2img_cfg, img2img_denoising, img2img_seed, img2img_height, img2img_width, img2img_resize, img2img_embeddings],
[output_img2img_gallery, output_img2img_seed, output_img2img_params, output_img2img_stats]
)
img2img_btn_editor.click(
img2img,
[img2img_prompt, img2img_image_editor_mode, img2img_image_editor, img2img_mask, img2img_mask_blur_strength, img2img_steps, img2img_sampling, img2img_toggles, img2img_realesrgan_model_name, img2img_batch_count, img2img_batch_size, img2img_cfg, img2img_denoising, img2img_seed, img2img_height, img2img_width, img2img_resize, img2img_embeddings],
[output_img2img_gallery, output_img2img_seed, output_img2img_params, output_img2img_stats]
)
img2img_painterro_btn.click(None, [img2img_image_editor], None, _js="""(img) => {
try {
Painterro({
hiddenTools: ['arrow'],
saveHandler: function (image, done) {
localStorage.setItem('painterro-image', image.asDataURL());
done(true);
},
}).show(Array.isArray(img) ? img[0] : img);
} catch(e) {
const script = document.createElement('script');
script.src = 'https://unpkg.com/painterro@1.2.78/build/painterro.min.js';
document.head.appendChild(script);
const style = document.createElement('style');
style.appendChild(document.createTextNode('.ptro-holder-wrapper { z-index: 9999 !important; }'));
document.head.appendChild(style);
}
return [];
}""")
img2img_copy_from_painterro_btn.click(None, None, [img2img_image_editor, img2img_image_mask], _js="""() => {
const image = localStorage.getItem('painterro-image')
return [image, image];
}""")
if GFPGAN is not None:
gfpgan_defaults = {
'strength': 100,
}
if 'gfpgan' in user_defaults:
gfpgan_defaults.update(user_defaults['gfpgan'])
with gr.TabItem("GFPGAN", id='cfpgan_tab'):
gr.Markdown("Fix faces on images")
with gr.Row():
with gr.Column():
gfpgan_source = gr.Image(label="Source", source="upload", interactive=True, type="pil")
gfpgan_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Effect strength", value=gfpgan_defaults['strength'])
gfpgan_btn = gr.Button("Generate", variant="primary")
with gr.Column():
gfpgan_output = gr.Image(label="Output")
gfpgan_btn.click(
run_GFPGAN,
[gfpgan_source, gfpgan_strength],
[gfpgan_output]
)
if RealESRGAN is not None:
with gr.TabItem("RealESRGAN", id='realesrgan_tab'):
gr.Markdown("Upscale images")
with gr.Row():
with gr.Column():
realesrgan_source = gr.Image(label="Source", source="upload", interactive=True, type="pil")
realesrgan_model_name = gr.Dropdown(label='RealESRGAN model', choices=['RealESRGAN_x4plus', 'RealESRGAN_x4plus_anime_6B'], value='RealESRGAN_x4plus')
realesrgan_btn = gr.Button("Generate")
with gr.Column():
realesrgan_output = gr.Image(label="Output")
realesrgan_btn.click(
run_RealESRGAN,
[realesrgan_source, realesrgan_model_name],
[realesrgan_output]
)
output_txt2img_to_upscale_esrgan.click(
copy_img_to_upscale_esrgan,
output_txt2img_gallery,
[realesrgan_source, tabs],
_js=return_selected_img_js)
with gr.TabItem("goBIG", id='gobig_tab'):
gr.Markdown("Upscale and detail images")
with gr.Row():
with gr.Column():
realesrganGoBig_source = gr.Image(source="upload", interactive=True, type="pil", tool="select")
realesrganGoBig_model_name = gr.Dropdown(label='RealESRGAN model', choices=['RealESRGAN_x4plus', 'RealESRGAN_x4plus_anime_6B'], value='RealESRGAN_x4plus')
realesrganGoBig_btn = gr.Button("Generate")
with gr.Column():
realesrganGoBig_output = gr.Image(label="Output")
realesrganGoBig_btn.click(
run_goBIG,
[realesrganGoBig_source, realesrganGoBig_model_name],
[realesrganGoBig_output]
)
output_txt2img_to_upscale_gobig.click(
copy_img_to_upscale_gobig,
output_txt2img_gallery,
[realesrganGoBig_source, tabs],
_js=return_selected_img_js)
output_txt2img_copy_to_gobig_input_btn.click(
copy_img_to_upscale_gobig,
output_txt2img_gallery,
[realesrganGoBig_source, tabs],
_js=return_selected_img_js
)
demo.queue()
# demo.queue()
demo.launch(share=False, debug=True)