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("""

For help and advanced usage guides, visit the Project Wiki

Stable Diffusion WebUI is an open-source project. You can find the latest stable builds on the main repository. If you would like to contribute to developement or test bleeding edge builds, you can visit the developement repository.

""") return demo