mirror of
https://github.com/sd-webui/stable-diffusion-webui.git
synced 2024-12-14 14:52:31 +03:00
Working on reslying the UI
Signed-off-by: Alex Volkov <alex.volkov@fundbox.com>
This commit is contained in:
Alex Volkov
hlky
parent
55487bc60c
commit
43889682c6
102
webui.py
102
webui.py
@ -1246,6 +1246,7 @@ txt2img_defaults = {
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'height': 512,
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'width': 512,
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'fp': None,
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'submit_on_enter': 'Yes'
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}
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if 'txt2img' in user_defaults:
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@ -1322,7 +1323,8 @@ def copy_img_to_input(selected=1, imgs = []):
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idx = int(0 if selected - 1 < 0 else selected - 1)
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image_data = re.sub('^data:image/.+;base64,', '', imgs[idx])
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processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
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return [processed_image, processed_image]
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update = gr.update(selected='Stable Diffusion Image-to-Image Unified')
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return [processed_image, processed_image, update]
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except IndexError:
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return [None, None]
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@ -1348,45 +1350,90 @@ def show_help():
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def hide_help():
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return [gr.update(visible=True), gr.update(visible=False), gr.update(value="")]
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with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion WebUI") as demo:
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with gr.Tabs():
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styling = """
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[data-testid="image"] {min-height: 512px !important};
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*{
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border: 1px solid red
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}
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* #body>.col:nth-child(2){width:250%;max-width:89vw}
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#generate{width: 100%; }
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#prompt_row input{
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font-size:20px
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}
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"""
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with gr.Blocks(css=styling, 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"):
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with gr.Row().style(equal_height=False):
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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).style()
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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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gr.Markdown("Generate images from text with Stable Diffusion")
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txt2img_prompt = gr.Textbox(label="Prompt", placeholder="A corgi wearing a top hat as an oil painting.", lines=1, value=txt2img_defaults['prompt'])
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txt2img_steps = gr.Slider(minimum=1, maximum=250, step=1, label="Sampling Steps", value=txt2img_defaults['ddim_steps'])
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txt2img_sampling = gr.Radio(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'])
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txt2img_toggles = gr.CheckboxGroup(label='', choices=txt2img_toggles, value=txt2img_toggle_defaults, type="index")
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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.
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txt2img_ddim_eta = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label="DDIM ETA", value=txt2img_defaults['ddim_eta'], visible=False)
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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'])
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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'])
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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'])
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txt2img_seed = gr.Textbox(label="Seed (blank to randomize)", lines=1, value=txt2img_defaults["seed"])
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txt2img_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=txt2img_defaults["height"])
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txt2img_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=txt2img_defaults["width"])
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txt2img_embeddings = gr.File(label = "Embeddings file for textual inversion", visible=hasattr(model, "embedding_manager"))
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txt2img_btn = gr.Button("Generate")
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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'])
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txt2img_seed = gr.Textbox(label="Seed (blank to randomize)", lines=1, value=txt2img_defaults["seed"])
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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'])
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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'])
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with gr.Column():
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output_txt2img_gallery = gr.Gallery(label="Images")
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output_txt2img_select_image = gr.Number(label='Select image number from results for copying', value=1, precision=None)
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output_txt2img_copy_to_input_btn = gr.Button("Copy selected image to img2img input")
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output_txt2img_seed = gr.Number(label='Seed')
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output_txt2img_params = gr.Textbox(label="Copy-paste generation parameters")
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output_txt2img_gallery = gr.Gallery(label="Images", elem_id="gallery_output").style(grid=[4,4])
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with gr.Row():
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with gr.Group():
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output_txt2img_seed = gr.Number(label='Seed', interactive=False)
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output_txt2img_copy_seed = gr.Button("Copy", full_width=True).click(inputs=output_txt2img_seed, outputs=[], _js='(x) => navigator.clipboard.writeText(x)', fn=None, show_progress=False)
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with gr.Group():
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output_txt2img_select_image = gr.Number(label='Image # and click Copy to copy to img2img', value=1, precision=None)
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output_txt2img_copy_to_input_btn = gr.Button("Push to img2img", full_width=True)
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with gr.Group():
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output_txt2img_params = gr.Textbox(label="Copy-paste generation parameters", interactive=False)
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output_txt2img_copy_params = gr.Button("Copy", full_width=True).click(inputs=output_txt2img_params, outputs=[], _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_btn = gr.Button("Generate", full_width=True, elem_id="generate", variant="primary")
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txt2img_steps = gr.Slider(minimum=1, maximum=250, step=1, label="Sampling Steps", value=txt2img_defaults['ddim_steps'])
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txt2img_sampling = gr.Radio(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'])
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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'], label="Submit on enter? (no means multiline)", value=txt2img_defaults['submit_on_enter'], interactive=True)
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txt2img_submit_on_enter.change(lambda x: gr.update(max_lines=1 if x == 'Single' else 25) , txt2img_submit_on_enter, txt2img_prompt)
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with gr.TabItem('Advanced'):
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txt2img_toggles = gr.CheckboxGroup(label='', choices=txt2img_toggles, value=txt2img_toggle_defaults, type="index")
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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.
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txt2img_ddim_eta = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label="DDIM ETA", value=txt2img_defaults['ddim_eta'], visible=False)
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txt2img_embeddings = gr.File(label = "Embeddings file for textual inversion", visible=hasattr(model, "embedding_manager"))
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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, txt2img_ddim_eta, txt2img_batch_count, txt2img_batch_size, txt2img_cfg, txt2img_seed, txt2img_height, txt2img_width, txt2img_embeddings],
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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, txt2img_ddim_eta, txt2img_batch_count, txt2img_batch_size, txt2img_cfg, txt2img_seed, txt2img_height, txt2img_width, txt2img_embeddings],
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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"):
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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 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=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, elem_id="img2img_mask_btn").style(full_width=True)
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img2img_btn_editor = gr.Button("Generate",variant="primary", elem_id="img2img_editot_btn").style(full_width=True)
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with gr.Row().style(equal_height=False):
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with gr.Column():
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gr.Markdown("Generate images from images with Stable Diffusion")
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img2img_prompt = gr.Textbox(label="Prompt", placeholder="A fantasy landscape, trending on artstation.", lines=1, value=img2img_defaults['prompt'])
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img2img_image_editor_mode = gr.Radio(choices=["Mask", "Crop"], label="Image Editor Mode", value="Crop")
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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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@ -1411,8 +1458,7 @@ with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion WebUI")
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img2img_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=img2img_defaults["width"])
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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']])
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img2img_embeddings = gr.File(label = "Embeddings file for textual inversion", visible=hasattr(model, "embedding_manager"))
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img2img_btn_mask = gr.Button("Generate", visible=False).style(full_width=True)
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img2img_btn_editor = gr.Button("Generate").style(full_width=True)
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with gr.Column():
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output_img2img_gallery = gr.Gallery(label="Images")
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output_img2img_select_image = gr.Number(label='Select image number from results for copying', value=1, precision=None)
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@ -1455,7 +1501,7 @@ with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion WebUI")
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output_txt2img_copy_to_input_btn.click(
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copy_img_to_input,
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[output_txt2img_select_image, output_txt2img_gallery],
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[img2img_image_editor, img2img_image_mask]
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[img2img_image_editor, img2img_image_mask, tabs]
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)
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img2img_btn_mask.click(
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@ -1509,7 +1555,7 @@ with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion WebUI")
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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", value=gfpgan_defaults['strength'])
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gfpgan_btn = gr.Button("Generate")
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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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409
webui_playground.py
Normal file
409
webui_playground.py
Normal file
@ -0,0 +1,409 @@
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import gradio as gr
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import time
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import os
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"""
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This file is here to play around with the interface without loading the whole model
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TBD - extract all the UI into this file and import from the main webui.
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"""
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GFPGAN = True
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RealESRGAN = True
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def txt2img(*args, **kwargs):
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time.sleep(.5)
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return "yay"
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def img2img(*args, **kwargs):
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time.sleep(.2)
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return "yay"
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def run_GFPGAN(*args, **kwargs):
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time.sleep(.1)
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return "yo"
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def run_RealESRGAN(*args, **kwargs):
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time.sleep(.2)
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return "yo"
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class model():
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def __init__():
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pass
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css_hide_progressbar = """
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.wrap .m-12 svg { display:none!important; }
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.wrap .m-12::before { content:"Loading..." }
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.progress-bar { display:none!important; }
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.meta-text { display:none!important; }
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"""
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css = css_hide_progressbar
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css = css + """
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[data-testid="image"] {min-height: 512px !important};
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#main_body {display:none !important};
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#main_body>.col:nth-child(2){width:200%;}
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"""
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user_defaults = {}
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# make sure these indicies line up at the top of txt2img()
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txt2img_toggles = [
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'Create prompt matrix (separate multiple prompts using |, and get all combinations of them)',
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'Normalize Prompt Weights (ensure sum of weights add up to 1.0)',
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'Save individual images',
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'Save grid',
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'Sort samples by prompt',
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'Write sample info files',
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'jpg samples',
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]
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if GFPGAN is not None:
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txt2img_toggles.append('Fix faces using GFPGAN')
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if RealESRGAN is not None:
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txt2img_toggles.append('Upscale images using RealESRGAN')
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txt2img_defaults = {
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'prompt': '',
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'ddim_steps': 50,
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'toggles': [1, 2, 3],
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'sampler_name': 'k_lms',
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'ddim_eta': 0.0,
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'n_iter': 1,
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'batch_size': 1,
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'cfg_scale': 7.5,
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'seed': '',
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'height': 512,
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'width': 512,
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'fp': None,
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'submit_on_enter': 'Yes'
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}
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if 'txt2img' in user_defaults:
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txt2img_defaults.update(user_defaults['txt2img'])
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txt2img_toggle_defaults = [txt2img_toggles[i] for i in txt2img_defaults['toggles']]
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sample_img2img = "assets/stable-samples/img2img/sketch-mountains-input.jpg"
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sample_img2img = sample_img2img if os.path.exists(sample_img2img) else None
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# make sure these indicies line up at the top of img2img()
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img2img_toggles = [
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'Create prompt matrix (separate multiple prompts using |, and get all combinations of them)',
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'Normalize Prompt Weights (ensure sum of weights add up to 1.0)',
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'Loopback (use images from previous batch when creating next batch)',
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'Random loopback seed',
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'Save individual images',
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'Save grid',
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'Sort samples by prompt',
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'Write sample info files',
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'jpg samples',
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]
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if GFPGAN is not None:
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img2img_toggles.append('Fix faces using GFPGAN')
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if RealESRGAN is not None:
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img2img_toggles.append('Upscale images using RealESRGAN')
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img2img_mask_modes = [
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"Keep masked area",
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"Regenerate only masked area",
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]
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img2img_resize_modes = [
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"Just resize",
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"Crop and resize",
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"Resize and fill",
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]
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img2img_defaults = {
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'prompt': '',
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'ddim_steps': 50,
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'toggles': [1, 4, 5],
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'sampler_name': 'k_lms',
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'ddim_eta': 0.0,
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'n_iter': 1,
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'batch_size': 1,
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'cfg_scale': 5.0,
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'denoising_strength': 0.75,
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'mask_mode': 0,
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'resize_mode': 0,
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'seed': '',
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'height': 512,
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'width': 512,
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'fp': None,
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}
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if 'img2img' in user_defaults:
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img2img_defaults.update(user_defaults['img2img'])
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img2img_toggle_defaults = [img2img_toggles[i] for i in img2img_defaults['toggles']]
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img2img_image_mode = 'sketch'
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def change_image_editor_mode(choice, cropped_image, resize_mode, width, height):
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if choice == "Mask":
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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)]
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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)]
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def update_image_mask(cropped_image, resize_mode, width, height):
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resized_cropped_image = resize_image(resize_mode, cropped_image, width, height) if cropped_image else None
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return gr.update(value=resized_cropped_image)
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def copy_img_to_input(selected=1, imgs = []):
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try:
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idx = int(0 if selected - 1 < 0 else selected - 1)
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image_data = re.sub('^data:image/.+;base64,', '', imgs[idx])
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processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
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update = gr.update(selected='Stable Diffusion Image-to-Image Unified')
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return [processed_image, processed_image, update]
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except IndexError:
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return [None, None]
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help_text = """
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## Mask/Crop
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* The masking/cropping is very temperamental.
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* It may take some time for the image to show when switching from Crop to Mask.
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* If the image doesn't appear after switching to Mask, switch back to Crop and then back again to Mask
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* If the mask appears distorted (the brush is weirdly shaped instead of round), switch back to Crop and then back again to Mask.
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## Advanced Editor
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* For now the button needs to be clicked twice the first time.
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* Once you have edited your image, you _need_ to click the save button for the next step to work.
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* 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 run():
|
||||
print
|
||||
|
||||
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="")]
|
||||
|
||||
styling = """
|
||||
[data-testid="image"] {min-height: 512px !important};
|
||||
*{
|
||||
border: 1px solid red
|
||||
}
|
||||
* #body>.col:nth-child(2){width:250%;max-width:89vw}
|
||||
#generate{width: 100%; }
|
||||
#prompt_row input{
|
||||
font-size:20px
|
||||
}
|
||||
|
||||
"""
|
||||
with gr.Blocks(css=styling, 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"):
|
||||
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).style()
|
||||
|
||||
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, 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="gallery_output").style(grid=[4,4])
|
||||
with gr.Row():
|
||||
with gr.Group():
|
||||
output_txt2img_seed = gr.Number(label='Seed', interactive=False)
|
||||
output_txt2img_copy_seed = gr.Button("Copy", full_width=True).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)
|
||||
output_txt2img_copy_to_input_btn = gr.Button("Push to img2img", full_width=True)
|
||||
with gr.Group():
|
||||
output_txt2img_params = gr.Textbox(label="Copy-paste generation parameters", interactive=False)
|
||||
output_txt2img_copy_params = gr.Button("Copy", full_width=True).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", full_width=True, 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.Radio(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"):
|
||||
with gr.Row(elem_id="prompt_row"):
|
||||
img2img_prompt = gr.Textbox(label="Prompt",
|
||||
elem_id='img2img_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=img2img_defaults['prompt'],
|
||||
show_label=False).style()
|
||||
img2img_btn_mask = gr.Button("Generate",variant="primary", visible=False, elem_id="img2img_mask_btn").style(full_width=True)
|
||||
img2img_btn_editor = gr.Button("Generate",variant="primary", elem_id="img2img_editot_btn").style(full_width=True)
|
||||
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")
|
||||
img2img_image_mask = gr.Image(value=sample_img2img, source="upload", interactive=True, type="pil", tool="sketch", visible=False)
|
||||
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.Radio(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")
|
||||
output_img2img_select_image = gr.Number(label='Select image number from results for copying', value=1, precision=None)
|
||||
gr.Markdown("Clear the input image before copying your output to your input. It may take some time to load the image.")
|
||||
output_img2img_copy_to_input_btn = gr.Button("Copy selected image to input")
|
||||
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_select_image, output_img2img_gallery],
|
||||
[img2img_image_editor, img2img_image_mask]
|
||||
)
|
||||
|
||||
output_txt2img_copy_to_input_btn.click(
|
||||
copy_img_to_input,
|
||||
[output_txt2img_select_image, output_txt2img_gallery],
|
||||
[img2img_image_editor, img2img_image_mask, tabs]
|
||||
)
|
||||
|
||||
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"):
|
||||
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"):
|
||||
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]
|
||||
)
|
||||
|
||||
demo.queue()
|
||||
demo.launch(share=False, debug=True, encrypt=False)
|
||||
Loading…
Reference in New Issue
Block a user