d3113f5c3f
* feat: use consistent file name in gradio returns and uses filepaths instead of numpy image by saving to temp dir uses double the temp dir file storage on disk as it saves to temp dir and gradio temp dir when displaying the image, but reuses logged output image * feat: delete temp images after yielding to gradio * feat: use args temp path if given * chore: code cleanup, remove redundant if statement
653 lines
42 KiB
Python
653 lines
42 KiB
Python
import gradio as gr
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import random
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import os
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import json
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import time
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import shared
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import modules.config
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import fooocus_version
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import modules.html
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import modules.async_worker as worker
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import modules.constants as constants
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import modules.flags as flags
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import modules.gradio_hijack as grh
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import modules.style_sorter as style_sorter
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import modules.meta_parser
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import args_manager
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import copy
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from modules.sdxl_styles import legal_style_names
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from modules.private_logger import get_current_html_path
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from modules.ui_gradio_extensions import reload_javascript
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from modules.auth import auth_enabled, check_auth
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def get_task(*args):
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args = list(args)
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args.pop(0)
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return worker.AsyncTask(args=args)
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def generate_clicked(task):
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import ldm_patched.modules.model_management as model_management
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with model_management.interrupt_processing_mutex:
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model_management.interrupt_processing = False
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# outputs=[progress_html, progress_window, progress_gallery, gallery]
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execution_start_time = time.perf_counter()
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finished = False
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yield gr.update(visible=True, value=modules.html.make_progress_html(1, 'Waiting for task to start ...')), \
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gr.update(visible=True, value=None), \
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gr.update(visible=False, value=None), \
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gr.update(visible=False)
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worker.async_tasks.append(task)
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while not finished:
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time.sleep(0.01)
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if len(task.yields) > 0:
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flag, product = task.yields.pop(0)
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if flag == 'preview':
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# help bad internet connection by skipping duplicated preview
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if len(task.yields) > 0: # if we have the next item
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if task.yields[0][0] == 'preview': # if the next item is also a preview
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# print('Skipped one preview for better internet connection.')
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continue
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percentage, title, image = product
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yield gr.update(visible=True, value=modules.html.make_progress_html(percentage, title)), \
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gr.update(visible=True, value=image) if image is not None else gr.update(), \
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gr.update(), \
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gr.update(visible=False)
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if flag == 'results':
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yield gr.update(visible=True), \
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gr.update(visible=True), \
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gr.update(visible=True, value=product), \
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gr.update(visible=False)
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if flag == 'finish':
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yield gr.update(visible=False), \
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gr.update(visible=False), \
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gr.update(visible=False), \
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gr.update(visible=True, value=product)
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finished = True
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# delete Fooocus temp images, only keep gradio temp images
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if args_manager.args.disable_image_log:
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for filepath in product:
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os.remove(filepath)
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execution_time = time.perf_counter() - execution_start_time
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print(f'Total time: {execution_time:.2f} seconds')
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return
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reload_javascript()
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title = f'Fooocus {fooocus_version.version}'
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if isinstance(args_manager.args.preset, str):
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title += ' ' + args_manager.args.preset
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shared.gradio_root = gr.Blocks(
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title=title,
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css=modules.html.css).queue()
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with shared.gradio_root:
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currentTask = gr.State(worker.AsyncTask(args=[]))
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with gr.Row():
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with gr.Column(scale=2):
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with gr.Row():
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progress_window = grh.Image(label='Preview', show_label=True, visible=False, height=768,
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elem_classes=['main_view'])
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progress_gallery = gr.Gallery(label='Finished Images', show_label=True, object_fit='contain',
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height=768, visible=False, elem_classes=['main_view', 'image_gallery'])
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progress_html = gr.HTML(value=modules.html.make_progress_html(32, 'Progress 32%'), visible=False,
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elem_id='progress-bar', elem_classes='progress-bar')
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gallery = gr.Gallery(label='Gallery', show_label=False, object_fit='contain', visible=True, height=768,
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elem_classes=['resizable_area', 'main_view', 'final_gallery', 'image_gallery'],
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elem_id='final_gallery')
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with gr.Row(elem_classes='type_row'):
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with gr.Column(scale=17):
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prompt = gr.Textbox(show_label=False, placeholder="Type prompt here or paste parameters.", elem_id='positive_prompt',
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container=False, autofocus=True, elem_classes='type_row', lines=1024)
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default_prompt = modules.config.default_prompt
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if isinstance(default_prompt, str) and default_prompt != '':
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shared.gradio_root.load(lambda: default_prompt, outputs=prompt)
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with gr.Column(scale=3, min_width=0):
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generate_button = gr.Button(label="Generate", value="Generate", elem_classes='type_row', elem_id='generate_button', visible=True)
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load_parameter_button = gr.Button(label="Load Parameters", value="Load Parameters", elem_classes='type_row', elem_id='load_parameter_button', visible=False)
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skip_button = gr.Button(label="Skip", value="Skip", elem_classes='type_row_half', visible=False)
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stop_button = gr.Button(label="Stop", value="Stop", elem_classes='type_row_half', elem_id='stop_button', visible=False)
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def stop_clicked(currentTask):
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import ldm_patched.modules.model_management as model_management
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currentTask.last_stop = 'stop'
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if (currentTask.processing):
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model_management.interrupt_current_processing()
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return currentTask
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def skip_clicked(currentTask):
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import ldm_patched.modules.model_management as model_management
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currentTask.last_stop = 'skip'
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if (currentTask.processing):
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model_management.interrupt_current_processing()
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return currentTask
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stop_button.click(stop_clicked, inputs=currentTask, outputs=currentTask, queue=False, show_progress=False, _js='cancelGenerateForever')
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skip_button.click(skip_clicked, inputs=currentTask, outputs=currentTask, queue=False, show_progress=False)
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with gr.Row(elem_classes='advanced_check_row'):
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input_image_checkbox = gr.Checkbox(label='Input Image', value=False, container=False, elem_classes='min_check')
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advanced_checkbox = gr.Checkbox(label='Advanced', value=modules.config.default_advanced_checkbox, container=False, elem_classes='min_check')
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with gr.Row(visible=False) as image_input_panel:
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with gr.Tabs():
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with gr.TabItem(label='Upscale or Variation') as uov_tab:
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with gr.Row():
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with gr.Column():
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uov_input_image = grh.Image(label='Drag above image to here', source='upload', type='numpy')
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with gr.Column():
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uov_method = gr.Radio(label='Upscale or Variation:', choices=flags.uov_list, value=flags.disabled)
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gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/390" target="_blank">\U0001F4D4 Document</a>')
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with gr.TabItem(label='Image Prompt') as ip_tab:
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with gr.Row():
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ip_images = []
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ip_types = []
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ip_stops = []
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ip_weights = []
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ip_ctrls = []
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ip_ad_cols = []
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for _ in range(4):
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with gr.Column():
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ip_image = grh.Image(label='Image', source='upload', type='numpy', show_label=False, height=300)
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ip_images.append(ip_image)
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ip_ctrls.append(ip_image)
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with gr.Column(visible=False) as ad_col:
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with gr.Row():
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default_end, default_weight = flags.default_parameters[flags.default_ip]
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ip_stop = gr.Slider(label='Stop At', minimum=0.0, maximum=1.0, step=0.001, value=default_end)
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ip_stops.append(ip_stop)
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ip_ctrls.append(ip_stop)
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ip_weight = gr.Slider(label='Weight', minimum=0.0, maximum=2.0, step=0.001, value=default_weight)
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ip_weights.append(ip_weight)
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ip_ctrls.append(ip_weight)
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ip_type = gr.Radio(label='Type', choices=flags.ip_list, value=flags.default_ip, container=False)
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ip_types.append(ip_type)
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ip_ctrls.append(ip_type)
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ip_type.change(lambda x: flags.default_parameters[x], inputs=[ip_type], outputs=[ip_stop, ip_weight], queue=False, show_progress=False)
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ip_ad_cols.append(ad_col)
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ip_advanced = gr.Checkbox(label='Advanced', value=False, container=False)
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gr.HTML('* \"Image Prompt\" is powered by Fooocus Image Mixture Engine (v1.0.1). <a href="https://github.com/lllyasviel/Fooocus/discussions/557" target="_blank">\U0001F4D4 Document</a>')
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def ip_advance_checked(x):
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return [gr.update(visible=x)] * len(ip_ad_cols) + \
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[flags.default_ip] * len(ip_types) + \
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[flags.default_parameters[flags.default_ip][0]] * len(ip_stops) + \
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[flags.default_parameters[flags.default_ip][1]] * len(ip_weights)
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ip_advanced.change(ip_advance_checked, inputs=ip_advanced,
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outputs=ip_ad_cols + ip_types + ip_stops + ip_weights,
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queue=False, show_progress=False)
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with gr.TabItem(label='Inpaint or Outpaint') as inpaint_tab:
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with gr.Row():
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inpaint_input_image = grh.Image(label='Drag inpaint or outpaint image to here', source='upload', type='numpy', tool='sketch', height=500, brush_color="#FFFFFF", elem_id='inpaint_canvas')
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inpaint_mask_image = grh.Image(label='Mask Upload', source='upload', type='numpy', height=500, visible=False)
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with gr.Row():
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inpaint_additional_prompt = gr.Textbox(placeholder="Describe what you want to inpaint.", elem_id='inpaint_additional_prompt', label='Inpaint Additional Prompt', visible=False)
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outpaint_selections = gr.CheckboxGroup(choices=['Left', 'Right', 'Top', 'Bottom'], value=[], label='Outpaint Direction')
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inpaint_mode = gr.Dropdown(choices=modules.flags.inpaint_options, value=modules.flags.inpaint_option_default, label='Method')
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example_inpaint_prompts = gr.Dataset(samples=modules.config.example_inpaint_prompts, label='Additional Prompt Quick List', components=[inpaint_additional_prompt], visible=False)
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gr.HTML('* Powered by Fooocus Inpaint Engine <a href="https://github.com/lllyasviel/Fooocus/discussions/414" target="_blank">\U0001F4D4 Document</a>')
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example_inpaint_prompts.click(lambda x: x[0], inputs=example_inpaint_prompts, outputs=inpaint_additional_prompt, show_progress=False, queue=False)
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with gr.TabItem(label='Describe') as desc_tab:
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with gr.Row():
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with gr.Column():
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desc_input_image = grh.Image(label='Drag any image to here', source='upload', type='numpy')
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with gr.Column():
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desc_method = gr.Radio(
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label='Content Type',
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choices=[flags.desc_type_photo, flags.desc_type_anime],
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value=flags.desc_type_photo)
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desc_btn = gr.Button(value='Describe this Image into Prompt')
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gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/1363" target="_blank">\U0001F4D4 Document</a>')
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switch_js = "(x) => {if(x){viewer_to_bottom(100);viewer_to_bottom(500);}else{viewer_to_top();} return x;}"
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down_js = "() => {viewer_to_bottom();}"
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input_image_checkbox.change(lambda x: gr.update(visible=x), inputs=input_image_checkbox,
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outputs=image_input_panel, queue=False, show_progress=False, _js=switch_js)
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ip_advanced.change(lambda: None, queue=False, show_progress=False, _js=down_js)
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current_tab = gr.Textbox(value='uov', visible=False)
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uov_tab.select(lambda: 'uov', outputs=current_tab, queue=False, _js=down_js, show_progress=False)
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inpaint_tab.select(lambda: 'inpaint', outputs=current_tab, queue=False, _js=down_js, show_progress=False)
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ip_tab.select(lambda: 'ip', outputs=current_tab, queue=False, _js=down_js, show_progress=False)
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desc_tab.select(lambda: 'desc', outputs=current_tab, queue=False, _js=down_js, show_progress=False)
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with gr.Column(scale=1, visible=modules.config.default_advanced_checkbox) as advanced_column:
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with gr.Tab(label='Setting'):
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performance_selection = gr.Radio(label='Performance',
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choices=modules.flags.performance_selections,
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value=modules.config.default_performance)
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aspect_ratios_selection = gr.Radio(label='Aspect Ratios', choices=modules.config.available_aspect_ratios,
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value=modules.config.default_aspect_ratio, info='width × height',
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elem_classes='aspect_ratios')
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image_number = gr.Slider(label='Image Number', minimum=1, maximum=modules.config.default_max_image_number, step=1, value=modules.config.default_image_number)
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negative_prompt = gr.Textbox(label='Negative Prompt', show_label=True, placeholder="Type prompt here.",
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info='Describing what you do not want to see.', lines=2,
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elem_id='negative_prompt',
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value=modules.config.default_prompt_negative)
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seed_random = gr.Checkbox(label='Random', value=True)
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image_seed = gr.Textbox(label='Seed', value=0, max_lines=1, visible=False) # workaround for https://github.com/gradio-app/gradio/issues/5354
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def random_checked(r):
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return gr.update(visible=not r)
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def refresh_seed(r, seed_string):
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if r:
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return random.randint(constants.MIN_SEED, constants.MAX_SEED)
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else:
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try:
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seed_value = int(seed_string)
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if constants.MIN_SEED <= seed_value <= constants.MAX_SEED:
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return seed_value
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except ValueError:
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pass
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return random.randint(constants.MIN_SEED, constants.MAX_SEED)
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seed_random.change(random_checked, inputs=[seed_random], outputs=[image_seed],
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queue=False, show_progress=False)
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def update_history_link():
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if args_manager.args.disable_image_log:
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return gr.update(value='')
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return gr.update(value=f'<a href="file={get_current_html_path()}" target="_blank">\U0001F4DA History Log</a>')
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history_link = gr.HTML()
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shared.gradio_root.load(update_history_link, outputs=history_link, queue=False, show_progress=False)
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with gr.Tab(label='Style'):
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style_sorter.try_load_sorted_styles(
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style_names=legal_style_names,
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default_selected=modules.config.default_styles)
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style_search_bar = gr.Textbox(show_label=False, container=False,
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placeholder="\U0001F50E Type here to search styles ...",
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value="",
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label='Search Styles')
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style_selections = gr.CheckboxGroup(show_label=False, container=False,
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choices=copy.deepcopy(style_sorter.all_styles),
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value=copy.deepcopy(modules.config.default_styles),
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label='Selected Styles',
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elem_classes=['style_selections'])
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gradio_receiver_style_selections = gr.Textbox(elem_id='gradio_receiver_style_selections', visible=False)
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shared.gradio_root.load(lambda: gr.update(choices=copy.deepcopy(style_sorter.all_styles)),
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outputs=style_selections)
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style_search_bar.change(style_sorter.search_styles,
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inputs=[style_selections, style_search_bar],
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outputs=style_selections,
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queue=False,
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show_progress=False).then(
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lambda: None, _js='()=>{refresh_style_localization();}')
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gradio_receiver_style_selections.input(style_sorter.sort_styles,
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inputs=style_selections,
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outputs=style_selections,
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queue=False,
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show_progress=False).then(
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lambda: None, _js='()=>{refresh_style_localization();}')
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with gr.Tab(label='Model'):
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with gr.Group():
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with gr.Row():
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base_model = gr.Dropdown(label='Base Model (SDXL only)', choices=modules.config.model_filenames, value=modules.config.default_base_model_name, show_label=True)
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refiner_model = gr.Dropdown(label='Refiner (SDXL or SD 1.5)', choices=['None'] + modules.config.model_filenames, value=modules.config.default_refiner_model_name, show_label=True)
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refiner_switch = gr.Slider(label='Refiner Switch At', minimum=0.1, maximum=1.0, step=0.0001,
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info='Use 0.4 for SD1.5 realistic models; '
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'or 0.667 for SD1.5 anime models; '
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'or 0.8 for XL-refiners; '
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'or any value for switching two SDXL models.',
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value=modules.config.default_refiner_switch,
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visible=modules.config.default_refiner_model_name != 'None')
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refiner_model.change(lambda x: gr.update(visible=x != 'None'),
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inputs=refiner_model, outputs=refiner_switch, show_progress=False, queue=False)
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with gr.Group():
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lora_ctrls = []
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for i, (n, v) in enumerate(modules.config.default_loras):
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with gr.Row():
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lora_enabled = gr.Checkbox(label='Enable', value=True,
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elem_classes=['lora_enable', 'min_check'])
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lora_model = gr.Dropdown(label=f'LoRA {i + 1}',
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choices=['None'] + modules.config.lora_filenames, value=n,
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elem_classes='lora_model')
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lora_weight = gr.Slider(label='Weight', minimum=modules.config.default_loras_min_weight,
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maximum=modules.config.default_loras_max_weight, step=0.01, value=v,
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elem_classes='lora_weight')
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lora_ctrls += [lora_enabled, lora_model, lora_weight]
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with gr.Row():
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model_refresh = gr.Button(label='Refresh', value='\U0001f504 Refresh All Files', variant='secondary', elem_classes='refresh_button')
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with gr.Tab(label='Advanced'):
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guidance_scale = gr.Slider(label='Guidance Scale', minimum=1.0, maximum=30.0, step=0.01,
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value=modules.config.default_cfg_scale,
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info='Higher value means style is cleaner, vivider, and more artistic.')
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sharpness = gr.Slider(label='Image Sharpness', minimum=0.0, maximum=30.0, step=0.001,
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value=modules.config.default_sample_sharpness,
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info='Higher value means image and texture are sharper.')
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gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/117" target="_blank">\U0001F4D4 Document</a>')
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dev_mode = gr.Checkbox(label='Developer Debug Mode', value=False, container=False)
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with gr.Column(visible=False) as dev_tools:
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with gr.Tab(label='Debug Tools'):
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adm_scaler_positive = gr.Slider(label='Positive ADM Guidance Scaler', minimum=0.1, maximum=3.0,
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step=0.001, value=1.5, info='The scaler multiplied to positive ADM (use 1.0 to disable). ')
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adm_scaler_negative = gr.Slider(label='Negative ADM Guidance Scaler', minimum=0.1, maximum=3.0,
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step=0.001, value=0.8, info='The scaler multiplied to negative ADM (use 1.0 to disable). ')
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adm_scaler_end = gr.Slider(label='ADM Guidance End At Step', minimum=0.0, maximum=1.0,
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step=0.001, value=0.3,
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info='When to end the guidance from positive/negative ADM. ')
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refiner_swap_method = gr.Dropdown(label='Refiner swap method', value='joint',
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choices=['joint', 'separate', 'vae'])
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adaptive_cfg = gr.Slider(label='CFG Mimicking from TSNR', minimum=1.0, maximum=30.0, step=0.01,
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value=modules.config.default_cfg_tsnr,
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info='Enabling Fooocus\'s implementation of CFG mimicking for TSNR '
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'(effective when real CFG > mimicked CFG).')
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sampler_name = gr.Dropdown(label='Sampler', choices=flags.sampler_list,
|
||
value=modules.config.default_sampler)
|
||
scheduler_name = gr.Dropdown(label='Scheduler', choices=flags.scheduler_list,
|
||
value=modules.config.default_scheduler)
|
||
|
||
generate_image_grid = gr.Checkbox(label='Generate Image Grid for Each Batch',
|
||
info='(Experimental) This may cause performance problems on some computers and certain internet conditions.',
|
||
value=False)
|
||
|
||
overwrite_step = gr.Slider(label='Forced Overwrite of Sampling Step',
|
||
minimum=-1, maximum=200, step=1,
|
||
value=modules.config.default_overwrite_step,
|
||
info='Set as -1 to disable. For developer debugging.')
|
||
overwrite_switch = gr.Slider(label='Forced Overwrite of Refiner Switch Step',
|
||
minimum=-1, maximum=200, step=1,
|
||
value=modules.config.default_overwrite_switch,
|
||
info='Set as -1 to disable. For developer debugging.')
|
||
overwrite_width = gr.Slider(label='Forced Overwrite of Generating Width',
|
||
minimum=-1, maximum=2048, step=1, value=-1,
|
||
info='Set as -1 to disable. For developer debugging. '
|
||
'Results will be worse for non-standard numbers that SDXL is not trained on.')
|
||
overwrite_height = gr.Slider(label='Forced Overwrite of Generating Height',
|
||
minimum=-1, maximum=2048, step=1, value=-1,
|
||
info='Set as -1 to disable. For developer debugging. '
|
||
'Results will be worse for non-standard numbers that SDXL is not trained on.')
|
||
overwrite_vary_strength = gr.Slider(label='Forced Overwrite of Denoising Strength of "Vary"',
|
||
minimum=-1, maximum=1.0, step=0.001, value=-1,
|
||
info='Set as negative number to disable. For developer debugging.')
|
||
overwrite_upscale_strength = gr.Slider(label='Forced Overwrite of Denoising Strength of "Upscale"',
|
||
minimum=-1, maximum=1.0, step=0.001, value=-1,
|
||
info='Set as negative number to disable. For developer debugging.')
|
||
disable_preview = gr.Checkbox(label='Disable Preview', value=False,
|
||
info='Disable preview during generation.')
|
||
disable_intermediate_results = gr.Checkbox(label='Disable Intermediate Results',
|
||
value=modules.config.default_performance == 'Extreme Speed',
|
||
interactive=modules.config.default_performance != 'Extreme Speed',
|
||
info='Disable intermediate results during generation, only show final gallery.')
|
||
disable_seed_increment = gr.Checkbox(label='Disable seed increment',
|
||
info='Disable automatic seed increment when image number is > 1.',
|
||
value=False)
|
||
|
||
with gr.Tab(label='Control'):
|
||
debugging_cn_preprocessor = gr.Checkbox(label='Debug Preprocessors', value=False,
|
||
info='See the results from preprocessors.')
|
||
skipping_cn_preprocessor = gr.Checkbox(label='Skip Preprocessors', value=False,
|
||
info='Do not preprocess images. (Inputs are already canny/depth/cropped-face/etc.)')
|
||
|
||
mixing_image_prompt_and_vary_upscale = gr.Checkbox(label='Mixing Image Prompt and Vary/Upscale',
|
||
value=False)
|
||
mixing_image_prompt_and_inpaint = gr.Checkbox(label='Mixing Image Prompt and Inpaint',
|
||
value=False)
|
||
|
||
controlnet_softness = gr.Slider(label='Softness of ControlNet', minimum=0.0, maximum=1.0,
|
||
step=0.001, value=0.25,
|
||
info='Similar to the Control Mode in A1111 (use 0.0 to disable). ')
|
||
|
||
with gr.Tab(label='Canny'):
|
||
canny_low_threshold = gr.Slider(label='Canny Low Threshold', minimum=1, maximum=255,
|
||
step=1, value=64)
|
||
canny_high_threshold = gr.Slider(label='Canny High Threshold', minimum=1, maximum=255,
|
||
step=1, value=128)
|
||
|
||
with gr.Tab(label='Inpaint'):
|
||
debugging_inpaint_preprocessor = gr.Checkbox(label='Debug Inpaint Preprocessing', value=False)
|
||
inpaint_disable_initial_latent = gr.Checkbox(label='Disable initial latent in inpaint', value=False)
|
||
inpaint_engine = gr.Dropdown(label='Inpaint Engine',
|
||
value=modules.config.default_inpaint_engine_version,
|
||
choices=flags.inpaint_engine_versions,
|
||
info='Version of Fooocus inpaint model')
|
||
inpaint_strength = gr.Slider(label='Inpaint Denoising Strength',
|
||
minimum=0.0, maximum=1.0, step=0.001, value=1.0,
|
||
info='Same as the denoising strength in A1111 inpaint. '
|
||
'Only used in inpaint, not used in outpaint. '
|
||
'(Outpaint always use 1.0)')
|
||
inpaint_respective_field = gr.Slider(label='Inpaint Respective Field',
|
||
minimum=0.0, maximum=1.0, step=0.001, value=0.618,
|
||
info='The area to inpaint. '
|
||
'Value 0 is same as "Only Masked" in A1111. '
|
||
'Value 1 is same as "Whole Image" in A1111. '
|
||
'Only used in inpaint, not used in outpaint. '
|
||
'(Outpaint always use 1.0)')
|
||
inpaint_erode_or_dilate = gr.Slider(label='Mask Erode or Dilate',
|
||
minimum=-64, maximum=64, step=1, value=0,
|
||
info='Positive value will make white area in the mask larger, '
|
||
'negative value will make white area smaller.'
|
||
'(default is 0, always process before any mask invert)')
|
||
inpaint_mask_upload_checkbox = gr.Checkbox(label='Enable Mask Upload', value=False)
|
||
invert_mask_checkbox = gr.Checkbox(label='Invert Mask', value=False)
|
||
|
||
inpaint_ctrls = [debugging_inpaint_preprocessor, inpaint_disable_initial_latent, inpaint_engine,
|
||
inpaint_strength, inpaint_respective_field,
|
||
inpaint_mask_upload_checkbox, invert_mask_checkbox, inpaint_erode_or_dilate]
|
||
|
||
inpaint_mask_upload_checkbox.change(lambda x: gr.update(visible=x),
|
||
inputs=inpaint_mask_upload_checkbox,
|
||
outputs=inpaint_mask_image, queue=False, show_progress=False)
|
||
|
||
with gr.Tab(label='FreeU'):
|
||
freeu_enabled = gr.Checkbox(label='Enabled', value=False)
|
||
freeu_b1 = gr.Slider(label='B1', minimum=0, maximum=2, step=0.01, value=1.01)
|
||
freeu_b2 = gr.Slider(label='B2', minimum=0, maximum=2, step=0.01, value=1.02)
|
||
freeu_s1 = gr.Slider(label='S1', minimum=0, maximum=4, step=0.01, value=0.99)
|
||
freeu_s2 = gr.Slider(label='S2', minimum=0, maximum=4, step=0.01, value=0.95)
|
||
freeu_ctrls = [freeu_enabled, freeu_b1, freeu_b2, freeu_s1, freeu_s2]
|
||
|
||
def dev_mode_checked(r):
|
||
return gr.update(visible=r)
|
||
|
||
|
||
dev_mode.change(dev_mode_checked, inputs=[dev_mode], outputs=[dev_tools],
|
||
queue=False, show_progress=False)
|
||
|
||
def model_refresh_clicked():
|
||
modules.config.update_all_model_names()
|
||
results = [gr.update(choices=modules.config.model_filenames)]
|
||
results += [gr.update(choices=['None'] + modules.config.model_filenames)]
|
||
for i in range(modules.config.default_max_lora_number):
|
||
results += [gr.update(interactive=True), gr.update(choices=['None'] + modules.config.lora_filenames), gr.update()]
|
||
return results
|
||
|
||
model_refresh.click(model_refresh_clicked, [], [base_model, refiner_model] + lora_ctrls,
|
||
queue=False, show_progress=False)
|
||
|
||
performance_selection.change(lambda x: [gr.update(interactive=x != 'Extreme Speed')] * 11 +
|
||
[gr.update(visible=x != 'Extreme Speed')] * 1 +
|
||
[gr.update(interactive=x != 'Extreme Speed', value=x == 'Extreme Speed', )] * 1,
|
||
inputs=performance_selection,
|
||
outputs=[
|
||
guidance_scale, sharpness, adm_scaler_end, adm_scaler_positive,
|
||
adm_scaler_negative, refiner_switch, refiner_model, sampler_name,
|
||
scheduler_name, adaptive_cfg, refiner_swap_method, negative_prompt, disable_intermediate_results
|
||
], queue=False, show_progress=False)
|
||
|
||
advanced_checkbox.change(lambda x: gr.update(visible=x), advanced_checkbox, advanced_column,
|
||
queue=False, show_progress=False) \
|
||
.then(fn=lambda: None, _js='refresh_grid_delayed', queue=False, show_progress=False)
|
||
|
||
def inpaint_mode_change(mode):
|
||
assert mode in modules.flags.inpaint_options
|
||
|
||
# inpaint_additional_prompt, outpaint_selections, example_inpaint_prompts,
|
||
# inpaint_disable_initial_latent, inpaint_engine,
|
||
# inpaint_strength, inpaint_respective_field
|
||
|
||
if mode == modules.flags.inpaint_option_detail:
|
||
return [
|
||
gr.update(visible=True), gr.update(visible=False, value=[]),
|
||
gr.Dataset.update(visible=True, samples=modules.config.example_inpaint_prompts),
|
||
False, 'None', 0.5, 0.0
|
||
]
|
||
|
||
if mode == modules.flags.inpaint_option_modify:
|
||
return [
|
||
gr.update(visible=True), gr.update(visible=False, value=[]),
|
||
gr.Dataset.update(visible=False, samples=modules.config.example_inpaint_prompts),
|
||
True, modules.config.default_inpaint_engine_version, 1.0, 0.0
|
||
]
|
||
|
||
return [
|
||
gr.update(visible=False, value=''), gr.update(visible=True),
|
||
gr.Dataset.update(visible=False, samples=modules.config.example_inpaint_prompts),
|
||
False, modules.config.default_inpaint_engine_version, 1.0, 0.618
|
||
]
|
||
|
||
inpaint_mode.input(inpaint_mode_change, inputs=inpaint_mode, outputs=[
|
||
inpaint_additional_prompt, outpaint_selections, example_inpaint_prompts,
|
||
inpaint_disable_initial_latent, inpaint_engine,
|
||
inpaint_strength, inpaint_respective_field
|
||
], show_progress=False, queue=False)
|
||
|
||
ctrls = [currentTask, generate_image_grid]
|
||
ctrls += [
|
||
prompt, negative_prompt, style_selections,
|
||
performance_selection, aspect_ratios_selection, image_number, image_seed, sharpness, guidance_scale
|
||
]
|
||
|
||
ctrls += [base_model, refiner_model, refiner_switch] + lora_ctrls
|
||
ctrls += [input_image_checkbox, current_tab]
|
||
ctrls += [uov_method, uov_input_image]
|
||
ctrls += [outpaint_selections, inpaint_input_image, inpaint_additional_prompt, inpaint_mask_image]
|
||
ctrls += [disable_preview, disable_intermediate_results, disable_seed_increment]
|
||
ctrls += [adm_scaler_positive, adm_scaler_negative, adm_scaler_end, adaptive_cfg]
|
||
ctrls += [sampler_name, scheduler_name]
|
||
ctrls += [overwrite_step, overwrite_switch, overwrite_width, overwrite_height, overwrite_vary_strength]
|
||
ctrls += [overwrite_upscale_strength, mixing_image_prompt_and_vary_upscale, mixing_image_prompt_and_inpaint]
|
||
ctrls += [debugging_cn_preprocessor, skipping_cn_preprocessor, canny_low_threshold, canny_high_threshold]
|
||
ctrls += [refiner_swap_method, controlnet_softness]
|
||
ctrls += freeu_ctrls
|
||
ctrls += inpaint_ctrls
|
||
ctrls += ip_ctrls
|
||
|
||
state_is_generating = gr.State(False)
|
||
|
||
def parse_meta(raw_prompt_txt, is_generating):
|
||
loaded_json = None
|
||
try:
|
||
if '{' in raw_prompt_txt:
|
||
if '}' in raw_prompt_txt:
|
||
if ':' in raw_prompt_txt:
|
||
loaded_json = json.loads(raw_prompt_txt)
|
||
assert isinstance(loaded_json, dict)
|
||
except:
|
||
loaded_json = None
|
||
|
||
if loaded_json is None:
|
||
if is_generating:
|
||
return gr.update(), gr.update(), gr.update()
|
||
else:
|
||
return gr.update(), gr.update(visible=True), gr.update(visible=False)
|
||
|
||
return json.dumps(loaded_json), gr.update(visible=False), gr.update(visible=True)
|
||
|
||
prompt.input(parse_meta, inputs=[prompt, state_is_generating], outputs=[prompt, generate_button, load_parameter_button], queue=False, show_progress=False)
|
||
|
||
load_parameter_button.click(modules.meta_parser.load_parameter_button_click, inputs=[prompt, state_is_generating], outputs=[
|
||
advanced_checkbox,
|
||
image_number,
|
||
prompt,
|
||
negative_prompt,
|
||
style_selections,
|
||
performance_selection,
|
||
aspect_ratios_selection,
|
||
overwrite_width,
|
||
overwrite_height,
|
||
sharpness,
|
||
guidance_scale,
|
||
adm_scaler_positive,
|
||
adm_scaler_negative,
|
||
adm_scaler_end,
|
||
base_model,
|
||
refiner_model,
|
||
refiner_switch,
|
||
sampler_name,
|
||
scheduler_name,
|
||
seed_random,
|
||
image_seed,
|
||
generate_button,
|
||
load_parameter_button
|
||
] + lora_ctrls, queue=False, show_progress=False)
|
||
|
||
generate_button.click(lambda: (gr.update(visible=True, interactive=True), gr.update(visible=True, interactive=True), gr.update(visible=False, interactive=False), [], True),
|
||
outputs=[stop_button, skip_button, generate_button, gallery, state_is_generating]) \
|
||
.then(fn=refresh_seed, inputs=[seed_random, image_seed], outputs=image_seed) \
|
||
.then(fn=get_task, inputs=ctrls, outputs=currentTask) \
|
||
.then(fn=generate_clicked, inputs=currentTask, outputs=[progress_html, progress_window, progress_gallery, gallery]) \
|
||
.then(lambda: (gr.update(visible=True, interactive=True), gr.update(visible=False, interactive=False), gr.update(visible=False, interactive=False), False),
|
||
outputs=[generate_button, stop_button, skip_button, state_is_generating]) \
|
||
.then(fn=update_history_link, outputs=history_link) \
|
||
.then(fn=lambda: None, _js='playNotification').then(fn=lambda: None, _js='refresh_grid_delayed')
|
||
|
||
for notification_file in ['notification.ogg', 'notification.mp3']:
|
||
if os.path.exists(notification_file):
|
||
gr.Audio(interactive=False, value=notification_file, elem_id='audio_notification', visible=False)
|
||
break
|
||
|
||
def trigger_describe(mode, img):
|
||
if mode == flags.desc_type_photo:
|
||
from extras.interrogate import default_interrogator as default_interrogator_photo
|
||
return default_interrogator_photo(img), ["Fooocus V2", "Fooocus Enhance", "Fooocus Sharp"]
|
||
if mode == flags.desc_type_anime:
|
||
from extras.wd14tagger import default_interrogator as default_interrogator_anime
|
||
return default_interrogator_anime(img), ["Fooocus V2", "Fooocus Masterpiece"]
|
||
return mode, ["Fooocus V2"]
|
||
|
||
desc_btn.click(trigger_describe, inputs=[desc_method, desc_input_image],
|
||
outputs=[prompt, style_selections], show_progress=True, queue=True)
|
||
|
||
|
||
def dump_default_english_config():
|
||
from modules.localization import dump_english_config
|
||
dump_english_config(grh.all_components)
|
||
|
||
|
||
# dump_default_english_config()
|
||
|
||
shared.gradio_root.launch(
|
||
inbrowser=args_manager.args.in_browser,
|
||
server_name=args_manager.args.listen,
|
||
server_port=args_manager.args.port,
|
||
share=args_manager.args.share,
|
||
auth=check_auth if (args_manager.args.share or args_manager.args.listen) and auth_enabled else None,
|
||
allowed_paths=[modules.config.path_outputs],
|
||
blocked_paths=[constants.AUTH_FILENAME]
|
||
)
|