mirror of
https://github.com/sd-webui/stable-diffusion-webui.git
synced 2024-12-14 14:52:31 +03:00
bdac53c5a1
* decouple python from js
* bring the painterro btn back
* refactor painterro code
replicate 7ddbd6533a as close as possible
* improve reliability
* fix big brain import
Co-authored-by: hlky <106811348+hlky@users.noreply.github.com>
354 lines
25 KiB
Python
354 lines
25 KiB
Python
import gradio as gr
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from frontend.css_and_js import *
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from frontend.css_and_js import css
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import frontend.ui_functions as uifn
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def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x, txt2img_defaults={}, RealESRGAN=True, GFPGAN=True,
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txt2img_toggles={}, txt2img_toggle_defaults='k_euler', show_embeddings=False, img2img_defaults={},
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img2img_toggles={}, img2img_toggle_defaults={}, sample_img2img=None, img2img_mask_modes=None,
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img2img_resize_modes=None, user_defaults={}, run_GFPGAN=lambda x: x, run_RealESRGAN=lambda x: x):
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with gr.Blocks(css=css(opt), analytics_enabled=False, title="Stable Diffusion WebUI") as demo:
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with gr.Tabs(elem_id='tabss') as tabs:
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with gr.TabItem("Stable Diffusion Text-to-Image Unified", id='txt2img_tab'):
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with gr.Row(elem_id="prompt_row"):
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txt2img_prompt = gr.Textbox(label="Prompt",
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elem_id='prompt_input',
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placeholder="A corgi wearing a top hat as an oil painting.",
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lines=1,
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max_lines=1 if txt2img_defaults['submit_on_enter'] == 'Yes' else 25,
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value=txt2img_defaults['prompt'],
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show_label=False)
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txt2img_btn = gr.Button("Generate", elem_id="generate", variant="primary")
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with gr.Row(elem_id='body').style(equal_height=False):
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with gr.Column():
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txt2img_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height",
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value=txt2img_defaults["height"])
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txt2img_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width",
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value=txt2img_defaults["width"])
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txt2img_cfg = gr.Slider(minimum=1.0, maximum=30.0, step=0.5,
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label='Classifier Free Guidance Scale (how strongly the image should follow the prompt)',
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value=txt2img_defaults['cfg_scale'])
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txt2img_seed = gr.Textbox(label="Seed (blank to randomize)", lines=1, max_lines=1,
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value=txt2img_defaults["seed"])
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txt2img_batch_count = gr.Slider(minimum=1, maximum=250, step=1,
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label='Batch count (how many batches of images to generate)',
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value=txt2img_defaults['n_iter'])
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txt2img_batch_size = gr.Slider(minimum=1, maximum=8, step=1,
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label='Batch size (how many images are in a batch; memory-hungry)',
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value=txt2img_defaults['batch_size'])
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with gr.Column():
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output_txt2img_gallery = gr.Gallery(label="Images", elem_id="txt2img_gallery_output").style(grid=[4, 4])
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with gr.Tabs():
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with gr.TabItem("Generated image actions", id="text2img_actions_tab"):
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gr.Markdown(
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'Select an image from the gallery, then click one of the buttons below to perform an action.')
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with gr.Row():
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output_txt2img_copy_clipboard = gr.Button("Copy to clipboard").click(fn=None,
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inputs=output_txt2img_gallery,
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outputs=[],
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_js=js_copy_to_clipboard('txt2img_gallery_output'))
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output_txt2img_copy_to_input_btn = gr.Button("Push to img2img")
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if RealESRGAN is not None:
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output_txt2img_to_upscale_esrgan = gr.Button("Upscale w/ ESRGAN")
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with gr.TabItem("Output Info", id="text2img_output_info_tab"):
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output_txt2img_params = gr.Textbox(label="Generation parameters", interactive=False)
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with gr.Row():
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output_txt2img_copy_params = gr.Button("Copy full parameters").click(
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inputs=output_txt2img_params, outputs=[],
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_js='(x) => navigator.clipboard.writeText(x)', fn=None, show_progress=False)
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output_txt2img_seed = gr.Number(label='Seed', interactive=False, visible=False)
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output_txt2img_copy_seed = gr.Button("Copy only seed").click(
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inputs=output_txt2img_seed, outputs=[],
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_js='(x) => navigator.clipboard.writeText(x)', fn=None, show_progress=False)
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output_txt2img_stats = gr.HTML(label='Stats')
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with gr.Column():
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txt2img_steps = gr.Slider(minimum=1, maximum=250, step=1, label="Sampling Steps",
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value=txt2img_defaults['ddim_steps'])
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txt2img_sampling = gr.Dropdown(label='Sampling method (k_lms is default k-diffusion sampler)',
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choices=["DDIM", "PLMS", 'k_dpm_2_a', 'k_dpm_2', 'k_euler_a',
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'k_euler', 'k_heun', 'k_lms'],
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value=txt2img_defaults['sampler_name'])
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with gr.Tabs():
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with gr.TabItem('Simple'):
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txt2img_submit_on_enter = gr.Radio(['Yes', 'No'],
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label="Submit on enter? (no means multiline)",
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value=txt2img_defaults['submit_on_enter'],
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interactive=True)
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txt2img_submit_on_enter.change(
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lambda x: gr.update(max_lines=1 if x == 'Yes' else 25), txt2img_submit_on_enter,
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txt2img_prompt)
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with gr.TabItem('Advanced'):
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txt2img_toggles = gr.CheckboxGroup(label='', choices=txt2img_toggles,
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value=txt2img_toggle_defaults, type="index")
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txt2img_realesrgan_model_name = gr.Dropdown(label='RealESRGAN model',
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choices=['RealESRGAN_x4plus',
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'RealESRGAN_x4plus_anime_6B'],
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value='RealESRGAN_x4plus',
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visible=RealESRGAN is not None) # TODO: Feels like I shouldnt slot it in here.
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txt2img_ddim_eta = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label="DDIM ETA",
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value=txt2img_defaults['ddim_eta'], visible=False)
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txt2img_variant_amount = gr.Slider(minimum=0.0, maximum=1.0, label='Variation Amount',
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value=txt2img_defaults['variant_amount'])
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txt2img_variant_seed = gr.Textbox(label="Variant Seed (blank to randomize)", lines=1,
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max_lines=1, value=txt2img_defaults["variant_seed"])
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txt2img_embeddings = gr.File(label="Embeddings file for textual inversion",
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visible=show_embeddings)
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txt2img_btn.click(
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txt2img,
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[txt2img_prompt, txt2img_steps, txt2img_sampling, txt2img_toggles, txt2img_realesrgan_model_name,
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txt2img_ddim_eta, txt2img_batch_count, txt2img_batch_size, txt2img_cfg, txt2img_seed,
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txt2img_height, txt2img_width, txt2img_embeddings, txt2img_variant_amount, txt2img_variant_seed],
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[output_txt2img_gallery, output_txt2img_seed, output_txt2img_params, output_txt2img_stats]
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)
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txt2img_prompt.submit(
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txt2img,
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[txt2img_prompt, txt2img_steps, txt2img_sampling, txt2img_toggles, txt2img_realesrgan_model_name,
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txt2img_ddim_eta, txt2img_batch_count, txt2img_batch_size, txt2img_cfg, txt2img_seed,
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txt2img_height, txt2img_width, txt2img_embeddings, txt2img_variant_amount, txt2img_variant_seed],
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[output_txt2img_gallery, output_txt2img_seed, output_txt2img_params, output_txt2img_stats]
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)
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with gr.TabItem("Stable Diffusion Image-to-Image Unified", id="img2img_tab"):
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with gr.Row(elem_id="prompt_row"):
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img2img_prompt = gr.Textbox(label="Prompt",
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elem_id='img2img_prompt_input',
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placeholder="A fantasy landscape, trending on artstation.",
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lines=1,
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max_lines=1 if txt2img_defaults['submit_on_enter'] == 'Yes' else 25,
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value=img2img_defaults['prompt'],
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show_label=False).style()
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img2img_btn_mask = gr.Button("Generate", variant="primary", visible=False,
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elem_id="img2img_mask_btn")
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img2img_btn_editor = gr.Button("Generate", variant="primary", elem_id="img2img_edit_btn")
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with gr.Row().style(equal_height=False):
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with gr.Column():
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gr.Markdown('#### Img2Img input')
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img2img_image_editor = gr.Image(value=sample_img2img, source="upload", interactive=True,
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type="pil", tool="select", elem_id="img2img_editor",
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image_mode="RGBA")
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img2img_image_mask = gr.Image(value=sample_img2img, source="upload", interactive=True,
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type="pil", tool="sketch", visible=False,
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elem_id="img2img_mask")
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with gr.Row():
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img2img_image_editor_mode = gr.Radio(choices=["Mask", "Crop", "Uncrop"], label="Image Editor Mode",
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value="Crop", elem_id='edit_mode_select')
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img2img_painterro_btn = gr.Button("Advanced Editor")
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img2img_show_help_btn = gr.Button("Show Hints")
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img2img_hide_help_btn = gr.Button("Hide Hints", visible=False)
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img2img_help = gr.Markdown(visible=False, value="")
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with gr.Column():
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gr.Markdown('#### Img2Img Results')
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output_img2img_gallery = gr.Gallery(label="Images", elem_id="img2img_gallery_output").style(grid=[4,4,4])
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with gr.Tabs():
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with gr.TabItem("Generated image actions", id="img2img_actions_tab"):
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with gr.Group():
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gr.Markdown("Select an image, then press one of the buttons below")
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output_img2img_copy_to_clipboard_btn = gr.Button("Copy to clipboard")
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output_img2img_copy_to_input_btn = gr.Button("Push to img2img input")
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output_img2img_copy_to_mask_btn = gr.Button("Push to img2img input mask")
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gr.Markdown("Warning: This will clear your current image and mask settings!")
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with gr.TabItem("Output info", id="img2img_output_info_tab"):
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output_img2img_params = gr.Textbox(label="Generation parameters")
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with gr.Row():
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output_img2img_copy_params = gr.Button("Copy full parameters").click(
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inputs=output_img2img_params, outputs=[],
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_js='(x) => navigator.clipboard.writeText(x)', fn=None, show_progress=False)
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output_img2img_seed = gr.Number(label='Seed', interactive=False, visible=False)
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output_img2img_copy_seed = gr.Button("Copy only seed").click(
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inputs=output_img2img_seed, outputs=[],
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_js='(x) => navigator.clipboard.writeText(x)', fn=None, show_progress=False)
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output_img2img_stats = gr.HTML(label='Stats')
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gr.Markdown('# img2img settings')
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with gr.Row():
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with gr.Column():
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img2img_batch_size = gr.Slider(minimum=1, maximum=8, step=1,
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label='Batch size (how many images are in a batch; memory-hungry)',
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value=img2img_defaults['batch_size'])
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img2img_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width",
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value=img2img_defaults["width"])
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img2img_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height",
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value=img2img_defaults["height"])
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img2img_seed = gr.Textbox(label="Seed (blank to randomize)", lines=1,
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value=img2img_defaults["seed"])
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img2img_steps = gr.Slider(minimum=1, maximum=250, step=1, label="Sampling Steps",
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value=img2img_defaults['ddim_steps'])
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img2img_batch_count = gr.Slider(minimum=1, maximum=250, step=1,
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label='Batch count (how many batches of images to generate)',
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value=img2img_defaults['n_iter'])
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with gr.Column():
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img2img_mask = gr.Radio(choices=["Keep masked area", "Regenerate only masked area"],
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label="Mask Mode", type="index",
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value=img2img_mask_modes[img2img_defaults['mask_mode']], visible=False)
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img2img_mask_blur_strength = gr.Slider(minimum=1, maximum=10, step=1,
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label="How much blurry should the mask be? (to avoid hard edges)",
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value=3, visible=False)
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img2img_sampling = gr.Dropdown(label='Sampling method (k_lms is default k-diffusion sampler)',
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choices=["DDIM", 'k_dpm_2_a', 'k_dpm_2', 'k_euler_a', 'k_euler',
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'k_heun', 'k_lms'],
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value=img2img_defaults['sampler_name'])
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img2img_toggles = gr.CheckboxGroup(label='', choices=img2img_toggles,
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value=img2img_toggle_defaults, type="index")
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img2img_realesrgan_model_name = gr.Dropdown(label='RealESRGAN model',
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choices=['RealESRGAN_x4plus',
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'RealESRGAN_x4plus_anime_6B'],
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value='RealESRGAN_x4plus',
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visible=RealESRGAN is not None) # TODO: Feels like I shouldnt slot it in here.
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img2img_cfg = gr.Slider(minimum=1.0, maximum=30.0, step=0.5,
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label='Classifier Free Guidance Scale (how strongly the image should follow the prompt)',
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value=img2img_defaults['cfg_scale'])
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img2img_denoising = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising Strength',
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value=img2img_defaults['denoising_strength'])
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img2img_resize = gr.Radio(label="Resize mode",
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choices=["Just resize", "Crop and resize", "Resize and fill"],
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type="index",
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value=img2img_resize_modes[img2img_defaults['resize_mode']])
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img2img_embeddings = gr.File(label="Embeddings file for textual inversion",
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visible=show_embeddings)
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img2img_image_editor_mode.change(
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uifn.change_image_editor_mode,
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[img2img_image_editor_mode, img2img_image_editor, img2img_resize, img2img_width, img2img_height],
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[img2img_image_editor, img2img_image_mask, img2img_btn_editor, img2img_btn_mask,
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img2img_painterro_btn, img2img_mask, img2img_mask_blur_strength]
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)
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img2img_image_editor.edit(
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uifn.update_image_mask,
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[img2img_image_editor, img2img_resize, img2img_width, img2img_height],
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img2img_image_mask
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)
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img2img_show_help_btn.click(
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uifn.show_help,
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None,
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[img2img_show_help_btn, img2img_hide_help_btn, img2img_help]
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)
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img2img_hide_help_btn.click(
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uifn.hide_help,
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None,
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[img2img_show_help_btn, img2img_hide_help_btn, img2img_help]
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)
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output_txt2img_copy_to_input_btn.click(
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uifn.copy_img_to_input,
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[output_txt2img_gallery],
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[img2img_image_editor, img2img_image_mask, tabs],
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_js=js_move_image('txt2img_gallery_output', 'img2img_editor')
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)
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output_img2img_copy_to_input_btn.click(
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uifn.copy_img_to_edit,
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[output_img2img_gallery],
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[img2img_image_editor, tabs, img2img_image_editor_mode],
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_js=js_move_image('img2img_gallery_output', 'img2img_editor')
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)
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output_img2img_copy_to_mask_btn.click(
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uifn.copy_img_to_mask,
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[output_img2img_gallery],
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[img2img_image_mask, tabs, img2img_image_editor_mode],
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_js=js_move_image('img2img_gallery_output', 'img2img_editor')
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)
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output_img2img_copy_to_clipboard_btn.click(fn=None, inputs=output_img2img_gallery, outputs=[],
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_js=js_copy_to_clipboard('img2img_gallery_output'))
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img2img_btn_mask.click(
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img2img,
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[img2img_prompt, img2img_image_editor_mode, img2img_image_mask, img2img_mask,
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img2img_mask_blur_strength, img2img_steps, img2img_sampling, img2img_toggles,
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img2img_realesrgan_model_name, img2img_batch_count, img2img_batch_size, img2img_cfg,
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img2img_denoising, img2img_seed, img2img_height, img2img_width, img2img_resize,
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img2img_embeddings],
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[output_img2img_gallery, output_img2img_seed, output_img2img_params, output_img2img_stats]
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)
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def img2img_submit_params():
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return (img2img,
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[img2img_prompt, img2img_image_editor_mode, img2img_image_editor, img2img_mask,
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img2img_mask_blur_strength, img2img_steps, img2img_sampling, img2img_toggles,
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img2img_realesrgan_model_name, img2img_batch_count, img2img_batch_size, img2img_cfg,
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img2img_denoising, img2img_seed, img2img_height, img2img_width, img2img_resize,
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img2img_embeddings],
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[output_img2img_gallery, output_img2img_seed, output_img2img_params, output_img2img_stats])
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img2img_btn_editor.click(*img2img_submit_params())
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img2img_prompt.submit(*img2img_submit_params())
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img2img_painterro_btn.click(None, [img2img_image_editor], [img2img_image_editor, img2img_image_mask], _js=js_painterro_launch('img2img_editor'))
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if GFPGAN is not None:
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gfpgan_defaults = {
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'strength': 100,
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}
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if 'gfpgan' in user_defaults:
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gfpgan_defaults.update(user_defaults['gfpgan'])
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with gr.TabItem("GFPGAN", id='cfpgan_tab'):
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gr.Markdown("Fix faces on images")
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with gr.Row():
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with gr.Column():
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gfpgan_source = gr.Image(label="Source", source="upload", interactive=True, type="pil")
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gfpgan_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Effect strength",
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value=gfpgan_defaults['strength'])
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gfpgan_btn = gr.Button("Generate", variant="primary")
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with gr.Column():
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gfpgan_output = gr.Image(label="Output")
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gfpgan_btn.click(
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run_GFPGAN,
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[gfpgan_source, gfpgan_strength],
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[gfpgan_output]
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)
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if RealESRGAN is not None:
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with gr.TabItem("RealESRGAN", id='realesrgan_tab'):
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gr.Markdown("Upscale images")
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with gr.Row():
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with gr.Column():
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realesrgan_source = gr.Image(label="Source", source="upload", interactive=True, type="pil")
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realesrgan_model_name = gr.Dropdown(label='RealESRGAN model', choices=['RealESRGAN_x4plus',
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'RealESRGAN_x4plus_anime_6B'],
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value='RealESRGAN_x4plus')
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realesrgan_btn = gr.Button("Generate")
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with gr.Column():
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realesrgan_output = gr.Image(label="Output")
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realesrgan_btn.click(
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run_RealESRGAN,
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[realesrgan_source, realesrgan_model_name],
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[realesrgan_output]
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)
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output_txt2img_to_upscale_esrgan.click(
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uifn.copy_img_to_upscale_esrgan,
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output_txt2img_gallery,
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[realesrgan_source, tabs],
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_js=js_move_image('txt2img_gallery_output', 'img2img_editor'))
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gr.HTML("""
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<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">
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<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>
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<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>.
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If you would like to contribute to development or test bleeding edge builds, you can visit the <a href="https://github.com/hlky/stable-diffusion-webui" target="_blank">developement repository</a>.</p>
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</div>
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""")
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# Hack: Detect the load event on the frontend
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# Won't be needed in the next version of gradio
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# See the relevant PR: https://github.com/gradio-app/gradio/pull/2108
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load_detector = gr.Number(value=0, label="Load Detector", visible=False)
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load_detector.change(None, None, None, _js=js(opt))
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demo.load(lambda x: 42, inputs=load_detector, outputs=load_detector)
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return demo
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