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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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import launch |
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from extras.inpaint_mask import SAMOptions |
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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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from modules.util import is_json |
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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: worker.AsyncTask): |
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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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if len(task.args) == 0: |
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return |
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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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if len(task.yields) > 0: |
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if task.yields[0][0] == 'preview': |
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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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if not args_manager.args.disable_enhance_output_sorting: |
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product = sort_enhance_images(product, task) |
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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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if args_manager.args.disable_image_log: |
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for filepath in product: |
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if isinstance(filepath, str) and os.path.exists(filepath): |
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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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def sort_enhance_images(images, task): |
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if not task.should_enhance or len(images) <= task.images_to_enhance_count: |
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return images |
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sorted_images = [] |
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walk_index = task.images_to_enhance_count |
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for index, enhanced_img in enumerate(images[:task.images_to_enhance_count]): |
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sorted_images.append(enhanced_img) |
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if index not in task.enhance_stats: |
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continue |
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target_index = walk_index + task.enhance_stats[index] |
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if walk_index < len(images) and target_index <= len(images): |
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sorted_images += images[walk_index:target_index] |
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walk_index += task.enhance_stats[index] |
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return sorted_images |
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def inpaint_mode_change(mode, inpaint_engine_version): |
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assert mode in modules.flags.inpaint_options |
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if mode == modules.flags.inpaint_option_detail: |
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return [ |
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gr.update(visible=True), gr.update(visible=False, value=[]), |
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gr.Dataset.update(visible=True, samples=modules.config.example_inpaint_prompts), |
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False, 'None', 0.5, 0.0 |
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] |
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if inpaint_engine_version == 'empty': |
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inpaint_engine_version = modules.config.default_inpaint_engine_version |
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if mode == modules.flags.inpaint_option_modify: |
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return [ |
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gr.update(visible=True), gr.update(visible=False, value=[]), |
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gr.Dataset.update(visible=False, samples=modules.config.example_inpaint_prompts), |
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True, inpaint_engine_version, 1.0, 0.0 |
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] |
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return [ |
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gr.update(visible=False, value=''), gr.update(visible=True), |
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gr.Dataset.update(visible=False, samples=modules.config.example_inpaint_prompts), |
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False, inpaint_engine_version, 1.0, 0.618 |
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] |
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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(title=title).queue() |
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with shared.gradio_root: |
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currentTask = gr.State(worker.AsyncTask(args=[])) |
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inpaint_engine_state = gr.State('empty') |
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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(): |
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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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autofocus=True, lines=3) |
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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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reset_button = gr.Button(label="Reconnect", value="Reconnect", elem_classes='type_row', elem_id='reset_button', visible=False) |
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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', elem_id='skip_button', 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=modules.config.default_image_prompt_checkbox, container=False, elem_classes='min_check') |
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enhance_checkbox = gr.Checkbox(label='Enhance', value=modules.config.default_enhance_checkbox, 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=modules.config.default_image_prompt_checkbox) as image_input_panel: |
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with gr.Tabs(selected=modules.config.default_selected_image_input_tab_id): |
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with gr.Tab(label='Upscale or Variation', id='uov_tab') 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='Image', source='upload', type='numpy', show_label=False) |
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with gr.Column(): |
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uov_method = gr.Radio(label='Upscale or Variation:', choices=flags.uov_list, value=modules.config.default_uov_method) |
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gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/390" target="_blank">\U0001F4D4 Documentation</a>') |
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with gr.Tab(label='Image Prompt', id='ip_tab') 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 image_count in range(modules.config.default_controlnet_image_count): |
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image_count += 1 |
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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, value=modules.config.default_ip_images[image_count]) |
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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=modules.config.default_image_prompt_advanced_checkbox) as ad_col: |
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with gr.Row(): |
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ip_stop = gr.Slider(label='Stop At', minimum=0.0, maximum=1.0, step=0.001, value=modules.config.default_ip_stop_ats[image_count]) |
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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=modules.config.default_ip_weights[image_count]) |
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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=modules.config.default_ip_types[image_count], 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=modules.config.default_image_prompt_advanced_checkbox, 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 Documentation</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.Tab(label='Inpaint or Outpaint', id='inpaint_tab') as inpaint_tab: |
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with gr.Row(): |
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with gr.Column(): |
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inpaint_input_image = grh.Image(label='Image', source='upload', type='numpy', tool='sketch', height=500, brush_color="#FFFFFF", elem_id='inpaint_canvas', show_label=False) |
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inpaint_advanced_masking_checkbox = gr.Checkbox(label='Enable Advanced Masking Features', value=modules.config.default_inpaint_advanced_masking_checkbox) |
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inpaint_mode = gr.Dropdown(choices=modules.flags.inpaint_options, value=modules.config.default_inpaint_method, label='Method') |
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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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example_inpaint_prompts = gr.Dataset(samples=modules.config.example_inpaint_prompts, |
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label='Additional Prompt Quick List', |
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components=[inpaint_additional_prompt], |
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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 Documentation</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.Column(visible=modules.config.default_inpaint_advanced_masking_checkbox) as inpaint_mask_generation_col: |
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inpaint_mask_image = grh.Image(label='Mask Upload', source='upload', type='numpy', tool='sketch', height=500, brush_color="#FFFFFF", mask_opacity=1, elem_id='inpaint_mask_canvas') |
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invert_mask_checkbox = gr.Checkbox(label='Invert Mask When Generating', value=modules.config.default_invert_mask_checkbox) |
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inpaint_mask_model = gr.Dropdown(label='Mask generation model', |
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choices=flags.inpaint_mask_models, |
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value=modules.config.default_inpaint_mask_model) |
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inpaint_mask_cloth_category = gr.Dropdown(label='Cloth category', |
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choices=flags.inpaint_mask_cloth_category, |
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value=modules.config.default_inpaint_mask_cloth_category, |
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visible=False) |
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inpaint_mask_dino_prompt_text = gr.Textbox(label='Detection prompt', value='', visible=False, info='Use singular whenever possible', placeholder='Describe what you want to detect.') |
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example_inpaint_mask_dino_prompt_text = gr.Dataset( |
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samples=modules.config.example_enhance_detection_prompts, |
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label='Detection Prompt Quick List', |
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components=[inpaint_mask_dino_prompt_text], |
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visible=modules.config.default_inpaint_mask_model == 'sam') |
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example_inpaint_mask_dino_prompt_text.click(lambda x: x[0], |
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inputs=example_inpaint_mask_dino_prompt_text, |
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outputs=inpaint_mask_dino_prompt_text, |
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show_progress=False, queue=False) |
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with gr.Accordion("Advanced options", visible=False, open=False) as inpaint_mask_advanced_options: |
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inpaint_mask_sam_model = gr.Dropdown(label='SAM model', choices=flags.inpaint_mask_sam_model, value=modules.config.default_inpaint_mask_sam_model) |
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inpaint_mask_box_threshold = gr.Slider(label="Box Threshold", minimum=0.0, maximum=1.0, value=0.3, step=0.05) |
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inpaint_mask_text_threshold = gr.Slider(label="Text Threshold", minimum=0.0, maximum=1.0, value=0.25, step=0.05) |
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inpaint_mask_sam_max_detections = gr.Slider(label="Maximum number of detections", info="Set to 0 to detect all", minimum=0, maximum=10, value=modules.config.default_sam_max_detections, step=1, interactive=True) |
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generate_mask_button = gr.Button(value='Generate mask from image') |
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def generate_mask(image, mask_model, cloth_category, dino_prompt_text, sam_model, box_threshold, text_threshold, sam_max_detections, dino_erode_or_dilate, dino_debug): |
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from extras.inpaint_mask import generate_mask_from_image |
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extras = {} |
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sam_options = None |
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if mask_model == 'u2net_cloth_seg': |
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extras['cloth_category'] = cloth_category |
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elif mask_model == 'sam': |
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sam_options = SAMOptions( |
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dino_prompt=dino_prompt_text, |
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dino_box_threshold=box_threshold, |
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dino_text_threshold=text_threshold, |
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dino_erode_or_dilate=dino_erode_or_dilate, |
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dino_debug=dino_debug, |
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max_detections=sam_max_detections, |
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model_type=sam_model |
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) |
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mask, _, _, _ = generate_mask_from_image(image, mask_model, extras, sam_options) |
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return mask |
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inpaint_mask_model.change(lambda x: [gr.update(visible=x == 'u2net_cloth_seg')] + |
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[gr.update(visible=x == 'sam')] * 2 + |
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[gr.Dataset.update(visible=x == 'sam', |
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samples=modules.config.example_enhance_detection_prompts)], |
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inputs=inpaint_mask_model, |
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outputs=[inpaint_mask_cloth_category, |
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inpaint_mask_dino_prompt_text, |
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inpaint_mask_advanced_options, |
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example_inpaint_mask_dino_prompt_text], |
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queue=False, show_progress=False) |
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with gr.Tab(label='Describe', id='describe_tab') as describe_tab: |
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with gr.Row(): |
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with gr.Column(): |
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describe_input_image = grh.Image(label='Image', source='upload', type='numpy', show_label=False) |
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with gr.Column(): |
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describe_methods = gr.CheckboxGroup( |
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label='Content Type', |
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choices=flags.describe_types, |
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value=modules.config.default_describe_content_type) |
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describe_apply_styles = gr.Checkbox(label='Apply Styles', value=modules.config.default_describe_apply_prompts_checkbox) |
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describe_btn = gr.Button(value='Describe this Image into Prompt') |
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describe_image_size = gr.Textbox(label='Image Size and Recommended Size', elem_id='describe_image_size', visible=False) |
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gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/1363" target="_blank">\U0001F4D4 Documentation</a>') |
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def trigger_show_image_properties(image): |
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value = modules.util.get_image_size_info(image, modules.flags.sdxl_aspect_ratios) |
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return gr.update(value=value, visible=True) |
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describe_input_image.upload(trigger_show_image_properties, inputs=describe_input_image, |
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outputs=describe_image_size, show_progress=False, queue=False) |
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with gr.Tab(label='Enhance', id='enhance_tab') as enhance_tab: |
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with gr.Row(): |
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with gr.Column(): |
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enhance_input_image = grh.Image(label='Use with Enhance, skips image generation', source='upload', type='numpy') |
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gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/3281" target="_blank">\U0001F4D4 Documentation</a>') |
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with gr.Tab(label='Metadata', id='metadata_tab') as metadata_tab: |
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with gr.Column(): |
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metadata_input_image = grh.Image(label='For images created by Fooocus', source='upload', type='pil') |
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metadata_json = gr.JSON(label='Metadata') |
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metadata_import_button = gr.Button(value='Apply Metadata') |
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|
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def trigger_metadata_preview(file): |
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parameters, metadata_scheme = modules.meta_parser.read_info_from_image(file) |
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results = {} |
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if parameters is not None: |
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results['parameters'] = parameters |
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|
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if isinstance(metadata_scheme, flags.MetadataScheme): |
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results['metadata_scheme'] = metadata_scheme.value |
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return results |
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metadata_input_image.upload(trigger_metadata_preview, inputs=metadata_input_image, |
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outputs=metadata_json, queue=False, show_progress=True) |
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|
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with gr.Row(visible=modules.config.default_enhance_checkbox) as enhance_input_panel: |
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with gr.Tabs(): |
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with gr.Tab(label='Upscale or Variation'): |
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with gr.Row(): |
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with gr.Column(): |
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enhance_uov_method = gr.Radio(label='Upscale or Variation:', choices=flags.uov_list, |
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value=modules.config.default_enhance_uov_method) |
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enhance_uov_processing_order = gr.Radio(label='Order of Processing', |
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info='Use before to enhance small details and after to enhance large areas.', |
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choices=flags.enhancement_uov_processing_order, |
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value=modules.config.default_enhance_uov_processing_order) |
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enhance_uov_prompt_type = gr.Radio(label='Prompt', |
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info='Choose which prompt to use for Upscale or Variation.', |
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choices=flags.enhancement_uov_prompt_types, |
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value=modules.config.default_enhance_uov_prompt_type, |
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visible=modules.config.default_enhance_uov_processing_order == flags.enhancement_uov_after) |
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|
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enhance_uov_processing_order.change(lambda x: gr.update(visible=x == flags.enhancement_uov_after), |
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inputs=enhance_uov_processing_order, |
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outputs=enhance_uov_prompt_type, |
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queue=False, show_progress=False) |
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gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/3281" target="_blank">\U0001F4D4 Documentation</a>') |
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enhance_ctrls = [] |
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enhance_inpaint_mode_ctrls = [] |
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enhance_inpaint_engine_ctrls = [] |
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enhance_inpaint_update_ctrls = [] |
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for index in range(modules.config.default_enhance_tabs): |
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with gr.Tab(label=f'#{index + 1}') as enhance_tab_item: |
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enhance_enabled = gr.Checkbox(label='Enable', value=False, elem_classes='min_check', |
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container=False) |
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|
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enhance_mask_dino_prompt_text = gr.Textbox(label='Detection prompt', |
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info='Use singular whenever possible', |
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placeholder='Describe what you want to detect.', |
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interactive=True, |
|
visible=modules.config.default_enhance_inpaint_mask_model == 'sam') |
|
example_enhance_mask_dino_prompt_text = gr.Dataset( |
|
samples=modules.config.example_enhance_detection_prompts, |
|
label='Detection Prompt Quick List', |
|
components=[enhance_mask_dino_prompt_text], |
|
visible=modules.config.default_enhance_inpaint_mask_model == 'sam') |
|
example_enhance_mask_dino_prompt_text.click(lambda x: x[0], |
|
inputs=example_enhance_mask_dino_prompt_text, |
|
outputs=enhance_mask_dino_prompt_text, |
|
show_progress=False, queue=False) |
|
|
|
enhance_prompt = gr.Textbox(label="Enhancement positive prompt", |
|
placeholder="Uses original prompt instead if empty.", |
|
elem_id='enhance_prompt') |
|
enhance_negative_prompt = gr.Textbox(label="Enhancement negative prompt", |
|
placeholder="Uses original negative prompt instead if empty.", |
|
elem_id='enhance_negative_prompt') |
|
|
|
with gr.Accordion("Detection", open=False): |
|
enhance_mask_model = gr.Dropdown(label='Mask generation model', |
|
choices=flags.inpaint_mask_models, |
|
value=modules.config.default_enhance_inpaint_mask_model) |
|
enhance_mask_cloth_category = gr.Dropdown(label='Cloth category', |
|
choices=flags.inpaint_mask_cloth_category, |
|
value=modules.config.default_inpaint_mask_cloth_category, |
|
visible=modules.config.default_enhance_inpaint_mask_model == 'u2net_cloth_seg', |
|
interactive=True) |
|
|
|
with gr.Accordion("SAM Options", |
|
visible=modules.config.default_enhance_inpaint_mask_model == 'sam', |
|
open=False) as sam_options: |
|
enhance_mask_sam_model = gr.Dropdown(label='SAM model', |
|
choices=flags.inpaint_mask_sam_model, |
|
value=modules.config.default_inpaint_mask_sam_model, |
|
interactive=True) |
|
enhance_mask_box_threshold = gr.Slider(label="Box Threshold", minimum=0.0, |
|
maximum=1.0, value=0.3, step=0.05, |
|
interactive=True) |
|
enhance_mask_text_threshold = gr.Slider(label="Text Threshold", minimum=0.0, |
|
maximum=1.0, value=0.25, step=0.05, |
|
interactive=True) |
|
enhance_mask_sam_max_detections = gr.Slider(label="Maximum number of detections", |
|
info="Set to 0 to detect all", |
|
minimum=0, maximum=10, |
|
value=modules.config.default_sam_max_detections, |
|
step=1, interactive=True) |
|
|
|
with gr.Accordion("Inpaint", visible=True, open=False): |
|
enhance_inpaint_mode = gr.Dropdown(choices=modules.flags.inpaint_options, |
|
value=modules.config.default_inpaint_method, |
|
label='Method', interactive=True) |
|
enhance_inpaint_disable_initial_latent = gr.Checkbox( |
|
label='Disable initial latent in inpaint', value=False) |
|
enhance_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. If set, use performance Quality or Speed (no performance LoRAs) for best results.') |
|
enhance_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)') |
|
enhance_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)') |
|
enhance_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 processed before any mask invert)') |
|
enhance_mask_invert = gr.Checkbox(label='Invert Mask', value=False) |
|
|
|
gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/3281" target="_blank">\U0001F4D4 Documentation</a>') |
|
|
|
enhance_ctrls += [ |
|
enhance_enabled, |
|
enhance_mask_dino_prompt_text, |
|
enhance_prompt, |
|
enhance_negative_prompt, |
|
enhance_mask_model, |
|
enhance_mask_cloth_category, |
|
enhance_mask_sam_model, |
|
enhance_mask_text_threshold, |
|
enhance_mask_box_threshold, |
|
enhance_mask_sam_max_detections, |
|
enhance_inpaint_disable_initial_latent, |
|
enhance_inpaint_engine, |
|
enhance_inpaint_strength, |
|
enhance_inpaint_respective_field, |
|
enhance_inpaint_erode_or_dilate, |
|
enhance_mask_invert |
|
] |
|
|
|
enhance_inpaint_mode_ctrls += [enhance_inpaint_mode] |
|
enhance_inpaint_engine_ctrls += [enhance_inpaint_engine] |
|
|
|
enhance_inpaint_update_ctrls += [[ |
|
enhance_inpaint_mode, enhance_inpaint_disable_initial_latent, enhance_inpaint_engine, |
|
enhance_inpaint_strength, enhance_inpaint_respective_field |
|
]] |
|
|
|
enhance_inpaint_mode.change(inpaint_mode_change, inputs=[enhance_inpaint_mode, inpaint_engine_state], outputs=[ |
|
inpaint_additional_prompt, outpaint_selections, example_inpaint_prompts, |
|
enhance_inpaint_disable_initial_latent, enhance_inpaint_engine, |
|
enhance_inpaint_strength, enhance_inpaint_respective_field |
|
], show_progress=False, queue=False) |
|
|
|
enhance_mask_model.change( |
|
lambda x: [gr.update(visible=x == 'u2net_cloth_seg')] + |
|
[gr.update(visible=x == 'sam')] * 2 + |
|
[gr.Dataset.update(visible=x == 'sam', |
|
samples=modules.config.example_enhance_detection_prompts)], |
|
inputs=enhance_mask_model, |
|
outputs=[enhance_mask_cloth_category, enhance_mask_dino_prompt_text, sam_options, |
|
example_enhance_mask_dino_prompt_text], |
|
queue=False, show_progress=False) |
|
|
|
switch_js = "(x) => {if(x){viewer_to_bottom(100);viewer_to_bottom(500);}else{viewer_to_top();} return x;}" |
|
down_js = "() => {viewer_to_bottom();}" |
|
|
|
input_image_checkbox.change(lambda x: gr.update(visible=x), inputs=input_image_checkbox, |
|
outputs=image_input_panel, queue=False, show_progress=False, _js=switch_js) |
|
ip_advanced.change(lambda: None, queue=False, show_progress=False, _js=down_js) |
|
|
|
current_tab = gr.Textbox(value='uov', visible=False) |
|
uov_tab.select(lambda: 'uov', outputs=current_tab, queue=False, _js=down_js, show_progress=False) |
|
inpaint_tab.select(lambda: 'inpaint', outputs=current_tab, queue=False, _js=down_js, show_progress=False) |
|
ip_tab.select(lambda: 'ip', outputs=current_tab, queue=False, _js=down_js, show_progress=False) |
|
describe_tab.select(lambda: 'desc', outputs=current_tab, queue=False, _js=down_js, show_progress=False) |
|
enhance_tab.select(lambda: 'enhance', outputs=current_tab, queue=False, _js=down_js, show_progress=False) |
|
metadata_tab.select(lambda: 'metadata', outputs=current_tab, queue=False, _js=down_js, show_progress=False) |
|
enhance_checkbox.change(lambda x: gr.update(visible=x), inputs=enhance_checkbox, |
|
outputs=enhance_input_panel, queue=False, show_progress=False, _js=switch_js) |
|
|
|
with gr.Column(scale=1, visible=modules.config.default_advanced_checkbox) as advanced_column: |
|
with gr.Tab(label='Settings'): |
|
if not args_manager.args.disable_preset_selection: |
|
preset_selection = gr.Dropdown(label='Preset', |
|
choices=modules.config.available_presets, |
|
value=args_manager.args.preset if args_manager.args.preset else "initial", |
|
interactive=True) |
|
|
|
performance_selection = gr.Radio(label='Performance', |
|
choices=flags.Performance.values(), |
|
value=modules.config.default_performance, |
|
elem_classes=['performance_selection']) |
|
|
|
with gr.Accordion(label='Aspect Ratios', open=False, elem_id='aspect_ratios_accordion') as aspect_ratios_accordion: |
|
aspect_ratios_selection = gr.Radio(label='Aspect Ratios', show_label=False, |
|
choices=modules.config.available_aspect_ratios_labels, |
|
value=modules.config.default_aspect_ratio, |
|
info='width × height', |
|
elem_classes='aspect_ratios') |
|
|
|
aspect_ratios_selection.change(lambda x: None, inputs=aspect_ratios_selection, queue=False, show_progress=False, _js='(x)=>{refresh_aspect_ratios_label(x);}') |
|
shared.gradio_root.load(lambda x: None, inputs=aspect_ratios_selection, queue=False, show_progress=False, _js='(x)=>{refresh_aspect_ratios_label(x);}') |
|
|
|
image_number = gr.Slider(label='Image Number', minimum=1, maximum=modules.config.default_max_image_number, step=1, value=modules.config.default_image_number) |
|
|
|
output_format = gr.Radio(label='Output Format', |
|
choices=flags.OutputFormat.list(), |
|
value=modules.config.default_output_format) |
|
|
|
negative_prompt = gr.Textbox(label='Negative Prompt', show_label=True, placeholder="Type prompt here.", |
|
info='Describing what you do not want to see.', lines=2, |
|
elem_id='negative_prompt', |
|
value=modules.config.default_prompt_negative) |
|
seed_random = gr.Checkbox(label='Random', value=True) |
|
image_seed = gr.Textbox(label='Seed', value=0, max_lines=1, visible=False) |
|
|
|
def random_checked(r): |
|
return gr.update(visible=not r) |
|
|
|
def refresh_seed(r, seed_string): |
|
if r: |
|
return random.randint(constants.MIN_SEED, constants.MAX_SEED) |
|
else: |
|
try: |
|
seed_value = int(seed_string) |
|
if constants.MIN_SEED <= seed_value <= constants.MAX_SEED: |
|
return seed_value |
|
except ValueError: |
|
pass |
|
return random.randint(constants.MIN_SEED, constants.MAX_SEED) |
|
|
|
seed_random.change(random_checked, inputs=[seed_random], outputs=[image_seed], |
|
queue=False, show_progress=False) |
|
|
|
def update_history_link(): |
|
if args_manager.args.disable_image_log: |
|
return gr.update(value='') |
|
|
|
return gr.update(value=f'<a href="file={get_current_html_path(output_format)}" target="_blank">\U0001F4DA History Log</a>') |
|
|
|
history_link = gr.HTML() |
|
shared.gradio_root.load(update_history_link, outputs=history_link, queue=False, show_progress=False) |
|
|
|
with gr.Tab(label='Styles', elem_classes=['style_selections_tab']): |
|
style_sorter.try_load_sorted_styles( |
|
style_names=legal_style_names, |
|
default_selected=modules.config.default_styles) |
|
|
|
style_search_bar = gr.Textbox(show_label=False, container=False, |
|
placeholder="\U0001F50E Type here to search styles ...", |
|
value="", |
|
label='Search Styles') |
|
style_selections = gr.CheckboxGroup(show_label=False, container=False, |
|
choices=copy.deepcopy(style_sorter.all_styles), |
|
value=copy.deepcopy(modules.config.default_styles), |
|
label='Selected Styles', |
|
elem_classes=['style_selections']) |
|
gradio_receiver_style_selections = gr.Textbox(elem_id='gradio_receiver_style_selections', visible=False) |
|
|
|
shared.gradio_root.load(lambda: gr.update(choices=copy.deepcopy(style_sorter.all_styles)), |
|
outputs=style_selections) |
|
|
|
style_search_bar.change(style_sorter.search_styles, |
|
inputs=[style_selections, style_search_bar], |
|
outputs=style_selections, |
|
queue=False, |
|
show_progress=False).then( |
|
lambda: None, _js='()=>{refresh_style_localization();}') |
|
|
|
gradio_receiver_style_selections.input(style_sorter.sort_styles, |
|
inputs=style_selections, |
|
outputs=style_selections, |
|
queue=False, |
|
show_progress=False).then( |
|
lambda: None, _js='()=>{refresh_style_localization();}') |
|
|
|
with gr.Tab(label='Models'): |
|
with gr.Group(): |
|
with gr.Row(): |
|
base_model = gr.Dropdown(label='Base Model (SDXL only)', choices=modules.config.model_filenames, value=modules.config.default_base_model_name, show_label=True) |
|
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) |
|
|
|
refiner_switch = gr.Slider(label='Refiner Switch At', minimum=0.1, maximum=1.0, step=0.0001, |
|
info='Use 0.4 for SD1.5 realistic models; ' |
|
'or 0.667 for SD1.5 anime models; ' |
|
'or 0.8 for XL-refiners; ' |
|
'or any value for switching two SDXL models.', |
|
value=modules.config.default_refiner_switch, |
|
visible=modules.config.default_refiner_model_name != 'None') |
|
|
|
refiner_model.change(lambda x: gr.update(visible=x != 'None'), |
|
inputs=refiner_model, outputs=refiner_switch, show_progress=False, queue=False) |
|
|
|
with gr.Group(): |
|
lora_ctrls = [] |
|
|
|
for i, (enabled, filename, weight) in enumerate(modules.config.default_loras): |
|
with gr.Row(): |
|
lora_enabled = gr.Checkbox(label='Enable', value=enabled, |
|
elem_classes=['lora_enable', 'min_check'], scale=1) |
|
lora_model = gr.Dropdown(label=f'LoRA {i + 1}', |
|
choices=['None'] + modules.config.lora_filenames, value=filename, |
|
elem_classes='lora_model', scale=5) |
|
lora_weight = gr.Slider(label='Weight', minimum=modules.config.default_loras_min_weight, |
|
maximum=modules.config.default_loras_max_weight, step=0.01, value=weight, |
|
elem_classes='lora_weight', scale=5) |
|
lora_ctrls += [lora_enabled, lora_model, lora_weight] |
|
|
|
with gr.Row(): |
|
refresh_files = gr.Button(label='Refresh', value='\U0001f504 Refresh All Files', variant='secondary', elem_classes='refresh_button') |
|
with gr.Tab(label='Advanced'): |
|
guidance_scale = gr.Slider(label='Guidance Scale', minimum=1.0, maximum=30.0, step=0.01, |
|
value=modules.config.default_cfg_scale, |
|
info='Higher value means style is cleaner, vivider, and more artistic.') |
|
sharpness = gr.Slider(label='Image Sharpness', minimum=0.0, maximum=30.0, step=0.001, |
|
value=modules.config.default_sample_sharpness, |
|
info='Higher value means image and texture are sharper.') |
|
gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/117" target="_blank">\U0001F4D4 Documentation</a>') |
|
dev_mode = gr.Checkbox(label='Developer Debug Mode', value=modules.config.default_developer_debug_mode_checkbox, container=False) |
|
|
|
with gr.Column(visible=modules.config.default_developer_debug_mode_checkbox) as dev_tools: |
|
with gr.Tab(label='Debug Tools'): |
|
adm_scaler_positive = gr.Slider(label='Positive ADM Guidance Scaler', minimum=0.1, maximum=3.0, |
|
step=0.001, value=1.5, info='The scaler multiplied to positive ADM (use 1.0 to disable). ') |
|
adm_scaler_negative = gr.Slider(label='Negative ADM Guidance Scaler', minimum=0.1, maximum=3.0, |
|
step=0.001, value=0.8, info='The scaler multiplied to negative ADM (use 1.0 to disable). ') |
|
adm_scaler_end = gr.Slider(label='ADM Guidance End At Step', minimum=0.0, maximum=1.0, |
|
step=0.001, value=0.3, |
|
info='When to end the guidance from positive/negative ADM. ') |
|
|
|
refiner_swap_method = gr.Dropdown(label='Refiner swap method', value=flags.refiner_swap_method, |
|
choices=['joint', 'separate', 'vae']) |
|
|
|
adaptive_cfg = gr.Slider(label='CFG Mimicking from TSNR', minimum=1.0, maximum=30.0, step=0.01, |
|
value=modules.config.default_cfg_tsnr, |
|
info='Enabling Fooocus\'s implementation of CFG mimicking for TSNR ' |
|
'(effective when real CFG > mimicked CFG).') |
|
clip_skip = gr.Slider(label='CLIP Skip', minimum=1, maximum=flags.clip_skip_max, step=1, |
|
value=modules.config.default_clip_skip, |
|
info='Bypass CLIP layers to avoid overfitting (use 1 to not skip any layers, 2 is recommended).') |
|
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) |
|
vae_name = gr.Dropdown(label='VAE', choices=[modules.flags.default_vae] + modules.config.vae_filenames, |
|
value=modules.config.default_vae, show_label=True) |
|
|
|
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=modules.config.default_overwrite_upscale, |
|
info='Set as negative number to disable. For developer debugging.') |
|
|
|
disable_preview = gr.Checkbox(label='Disable Preview', value=modules.config.default_black_out_nsfw, |
|
interactive=not modules.config.default_black_out_nsfw, |
|
info='Disable preview during generation.') |
|
disable_intermediate_results = gr.Checkbox(label='Disable Intermediate Results', |
|
value=flags.Performance.has_restricted_features(modules.config.default_performance), |
|
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) |
|
read_wildcards_in_order = gr.Checkbox(label="Read wildcards in order", value=False) |
|
|
|
black_out_nsfw = gr.Checkbox(label='Black Out NSFW', value=modules.config.default_black_out_nsfw, |
|
interactive=not modules.config.default_black_out_nsfw, |
|
info='Use black image if NSFW is detected.') |
|
|
|
black_out_nsfw.change(lambda x: gr.update(value=x, interactive=not x), |
|
inputs=black_out_nsfw, outputs=disable_preview, queue=False, |
|
show_progress=False) |
|
|
|
if not args_manager.args.disable_image_log: |
|
save_final_enhanced_image_only = gr.Checkbox(label='Save only final enhanced image', |
|
value=modules.config.default_save_only_final_enhanced_image) |
|
|
|
if not args_manager.args.disable_metadata: |
|
save_metadata_to_images = gr.Checkbox(label='Save Metadata to Images', value=modules.config.default_save_metadata_to_images, |
|
info='Adds parameters to generated images allowing manual regeneration.') |
|
metadata_scheme = gr.Radio(label='Metadata Scheme', choices=flags.metadata_scheme, value=modules.config.default_metadata_scheme, |
|
info='Image Prompt parameters are not included. Use png and a1111 for compatibility with Civitai.', |
|
visible=modules.config.default_save_metadata_to_images) |
|
|
|
save_metadata_to_images.change(lambda x: gr.update(visible=x), inputs=[save_metadata_to_images], outputs=[metadata_scheme], |
|
queue=False, show_progress=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) |
|
debugging_enhance_masks_checkbox = gr.Checkbox(label='Debug Enhance Masks', value=False, |
|
info='Show enhance masks in preview and final results') |
|
debugging_dino = gr.Checkbox(label='Debug GroundingDINO', value=False, |
|
info='Use GroundingDINO boxes instead of more detailed SAM masks') |
|
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. If set, use performance Quality or Speed (no performance LoRAs) for best results.') |
|
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 processed before any mask invert)') |
|
dino_erode_or_dilate = gr.Slider(label='GroundingDINO Box 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, processed before SAM)') |
|
|
|
inpaint_mask_color = gr.ColorPicker(label='Inpaint brush color', value='#FFFFFF', elem_id='inpaint_brush_color') |
|
|
|
inpaint_ctrls = [debugging_inpaint_preprocessor, inpaint_disable_initial_latent, inpaint_engine, |
|
inpaint_strength, inpaint_respective_field, |
|
inpaint_advanced_masking_checkbox, invert_mask_checkbox, inpaint_erode_or_dilate] |
|
|
|
inpaint_advanced_masking_checkbox.change(lambda x: [gr.update(visible=x)] * 2, |
|
inputs=inpaint_advanced_masking_checkbox, |
|
outputs=[inpaint_mask_image, inpaint_mask_generation_col], |
|
queue=False, show_progress=False) |
|
|
|
inpaint_mask_color.change(lambda x: gr.update(brush_color=x), inputs=inpaint_mask_color, |
|
outputs=inpaint_input_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 refresh_files_clicked(): |
|
modules.config.update_files() |
|
results = [gr.update(choices=modules.config.model_filenames)] |
|
results += [gr.update(choices=['None'] + modules.config.model_filenames)] |
|
results += [gr.update(choices=[flags.default_vae] + modules.config.vae_filenames)] |
|
if not args_manager.args.disable_preset_selection: |
|
results += [gr.update(choices=modules.config.available_presets)] |
|
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 |
|
|
|
refresh_files_output = [base_model, refiner_model, vae_name] |
|
if not args_manager.args.disable_preset_selection: |
|
refresh_files_output += [preset_selection] |
|
refresh_files.click(refresh_files_clicked, [], refresh_files_output + lora_ctrls, |
|
queue=False, show_progress=False) |
|
|
|
state_is_generating = gr.State(False) |
|
|
|
load_data_outputs = [advanced_checkbox, image_number, prompt, negative_prompt, style_selections, |
|
performance_selection, overwrite_step, overwrite_switch, aspect_ratios_selection, |
|
overwrite_width, overwrite_height, guidance_scale, sharpness, adm_scaler_positive, |
|
adm_scaler_negative, adm_scaler_end, refiner_swap_method, adaptive_cfg, clip_skip, |
|
base_model, refiner_model, refiner_switch, sampler_name, scheduler_name, vae_name, |
|
seed_random, image_seed, inpaint_engine, inpaint_engine_state, |
|
inpaint_mode] + enhance_inpaint_mode_ctrls + [generate_button, |
|
load_parameter_button] + freeu_ctrls + lora_ctrls |
|
|
|
if not args_manager.args.disable_preset_selection: |
|
def preset_selection_change(preset, is_generating, inpaint_mode): |
|
preset_content = modules.config.try_get_preset_content(preset) if preset != 'initial' else {} |
|
preset_prepared = modules.meta_parser.parse_meta_from_preset(preset_content) |
|
|
|
default_model = preset_prepared.get('base_model') |
|
previous_default_models = preset_prepared.get('previous_default_models', []) |
|
checkpoint_downloads = preset_prepared.get('checkpoint_downloads', {}) |
|
embeddings_downloads = preset_prepared.get('embeddings_downloads', {}) |
|
lora_downloads = preset_prepared.get('lora_downloads', {}) |
|
vae_downloads = preset_prepared.get('vae_downloads', {}) |
|
|
|
preset_prepared['base_model'], preset_prepared['checkpoint_downloads'] = launch.download_models( |
|
default_model, previous_default_models, checkpoint_downloads, embeddings_downloads, lora_downloads, |
|
vae_downloads) |
|
|
|
if 'prompt' in preset_prepared and preset_prepared.get('prompt') == '': |
|
del preset_prepared['prompt'] |
|
|
|
return modules.meta_parser.load_parameter_button_click(json.dumps(preset_prepared), is_generating, inpaint_mode) |
|
|
|
|
|
def inpaint_engine_state_change(inpaint_engine_version, *args): |
|
if inpaint_engine_version == 'empty': |
|
inpaint_engine_version = modules.config.default_inpaint_engine_version |
|
|
|
result = [] |
|
for inpaint_mode in args: |
|
if inpaint_mode != modules.flags.inpaint_option_detail: |
|
result.append(gr.update(value=inpaint_engine_version)) |
|
else: |
|
result.append(gr.update()) |
|
|
|
return result |
|
|
|
preset_selection.change(preset_selection_change, inputs=[preset_selection, state_is_generating, inpaint_mode], outputs=load_data_outputs, queue=False, show_progress=True) \ |
|
.then(fn=style_sorter.sort_styles, inputs=style_selections, outputs=style_selections, queue=False, show_progress=False) \ |
|
.then(lambda: None, _js='()=>{refresh_style_localization();}') \ |
|
.then(inpaint_engine_state_change, inputs=[inpaint_engine_state] + enhance_inpaint_mode_ctrls, outputs=enhance_inpaint_engine_ctrls, queue=False, show_progress=False) |
|
|
|
performance_selection.change(lambda x: [gr.update(interactive=not flags.Performance.has_restricted_features(x))] * 11 + |
|
[gr.update(visible=not flags.Performance.has_restricted_features(x))] * 1 + |
|
[gr.update(value=flags.Performance.has_restricted_features(x))] * 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) |
|
|
|
output_format.input(lambda x: gr.update(output_format=x), inputs=output_format) |
|
|
|
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) |
|
|
|
inpaint_mode.change(inpaint_mode_change, inputs=[inpaint_mode, inpaint_engine_state], 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) |
|
|
|
|
|
default_inpaint_ctrls = [inpaint_mode, inpaint_disable_initial_latent, inpaint_engine, inpaint_strength, inpaint_respective_field] |
|
for mode, disable_initial_latent, engine, strength, respective_field in [default_inpaint_ctrls] + enhance_inpaint_update_ctrls: |
|
shared.gradio_root.load(inpaint_mode_change, inputs=[mode, inpaint_engine_state], outputs=[ |
|
inpaint_additional_prompt, outpaint_selections, example_inpaint_prompts, disable_initial_latent, |
|
engine, strength, respective_field |
|
], show_progress=False, queue=False) |
|
|
|
generate_mask_button.click(fn=generate_mask, |
|
inputs=[inpaint_input_image, inpaint_mask_model, inpaint_mask_cloth_category, |
|
inpaint_mask_dino_prompt_text, inpaint_mask_sam_model, |
|
inpaint_mask_box_threshold, inpaint_mask_text_threshold, |
|
inpaint_mask_sam_max_detections, dino_erode_or_dilate, debugging_dino], |
|
outputs=inpaint_mask_image, show_progress=True, queue=True) |
|
|
|
ctrls = [currentTask, generate_image_grid] |
|
ctrls += [ |
|
prompt, negative_prompt, style_selections, |
|
performance_selection, aspect_ratios_selection, image_number, output_format, image_seed, |
|
read_wildcards_in_order, 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, black_out_nsfw] |
|
ctrls += [adm_scaler_positive, adm_scaler_negative, adm_scaler_end, adaptive_cfg, clip_skip] |
|
ctrls += [sampler_name, scheduler_name, vae_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 |
|
|
|
if not args_manager.args.disable_image_log: |
|
ctrls += [save_final_enhanced_image_only] |
|
|
|
if not args_manager.args.disable_metadata: |
|
ctrls += [save_metadata_to_images, metadata_scheme] |
|
|
|
ctrls += ip_ctrls |
|
ctrls += [debugging_dino, dino_erode_or_dilate, debugging_enhance_masks_checkbox, |
|
enhance_input_image, enhance_checkbox, enhance_uov_method, enhance_uov_processing_order, |
|
enhance_uov_prompt_type] |
|
ctrls += enhance_ctrls |
|
|
|
def parse_meta(raw_prompt_txt, is_generating): |
|
loaded_json = None |
|
if is_json(raw_prompt_txt): |
|
loaded_json = json.loads(raw_prompt_txt) |
|
|
|
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, inpaint_mode], outputs=load_data_outputs, queue=False, show_progress=False) |
|
|
|
def trigger_metadata_import(file, state_is_generating): |
|
parameters, metadata_scheme = modules.meta_parser.read_info_from_image(file) |
|
if parameters is None: |
|
print('Could not find metadata in the image!') |
|
parsed_parameters = {} |
|
else: |
|
metadata_parser = modules.meta_parser.get_metadata_parser(metadata_scheme) |
|
parsed_parameters = metadata_parser.to_json(parameters) |
|
|
|
return modules.meta_parser.load_parameter_button_click(parsed_parameters, state_is_generating, inpaint_mode) |
|
|
|
metadata_import_button.click(trigger_metadata_import, inputs=[metadata_input_image, state_is_generating], outputs=load_data_outputs, queue=False, show_progress=True) \ |
|
.then(style_sorter.sort_styles, inputs=style_selections, outputs=style_selections, 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') |
|
|
|
reset_button.click(lambda: [worker.AsyncTask(args=[]), False, gr.update(visible=True, interactive=True)] + |
|
[gr.update(visible=False)] * 6 + |
|
[gr.update(visible=True, value=[])], |
|
outputs=[currentTask, state_is_generating, generate_button, |
|
reset_button, stop_button, skip_button, |
|
progress_html, progress_window, progress_gallery, gallery], |
|
queue=False) |
|
|
|
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(modes, img, apply_styles): |
|
describe_prompts = [] |
|
styles = set() |
|
|
|
if flags.describe_type_photo in modes: |
|
from extras.interrogate import default_interrogator as default_interrogator_photo |
|
describe_prompts.append(default_interrogator_photo(img)) |
|
styles.update(["Fooocus V2", "Fooocus Enhance", "Fooocus Sharp"]) |
|
|
|
if flags.describe_type_anime in modes: |
|
from extras.wd14tagger import default_interrogator as default_interrogator_anime |
|
describe_prompts.append(default_interrogator_anime(img)) |
|
styles.update(["Fooocus V2", "Fooocus Masterpiece"]) |
|
|
|
if len(styles) == 0 or not apply_styles: |
|
styles = gr.update() |
|
else: |
|
styles = list(styles) |
|
|
|
if len(describe_prompts) == 0: |
|
describe_prompt = gr.update() |
|
else: |
|
describe_prompt = ', '.join(describe_prompts) |
|
|
|
return describe_prompt, styles |
|
|
|
describe_btn.click(trigger_describe, inputs=[describe_methods, describe_input_image, describe_apply_styles], |
|
outputs=[prompt, style_selections], show_progress=True, queue=True) \ |
|
.then(fn=style_sorter.sort_styles, inputs=style_selections, outputs=style_selections, queue=False, show_progress=False) \ |
|
.then(lambda: None, _js='()=>{refresh_style_localization();}') |
|
|
|
if args_manager.args.enable_auto_describe_image: |
|
def trigger_auto_describe(mode, img, prompt, apply_styles): |
|
|
|
if prompt == '': |
|
return trigger_describe(mode, img, apply_styles) |
|
return gr.update(), gr.update() |
|
|
|
uov_input_image.upload(trigger_auto_describe, inputs=[describe_methods, uov_input_image, prompt, describe_apply_styles], |
|
outputs=[prompt, style_selections], show_progress=True, queue=True) \ |
|
.then(fn=style_sorter.sort_styles, inputs=style_selections, outputs=style_selections, queue=False, show_progress=False) \ |
|
.then(lambda: None, _js='()=>{refresh_style_localization();}') |
|
|
|
enhance_input_image.upload(lambda: gr.update(value=True), outputs=enhance_checkbox, queue=False, show_progress=False) \ |
|
.then(trigger_auto_describe, inputs=[describe_methods, enhance_input_image, prompt, describe_apply_styles], |
|
outputs=[prompt, style_selections], show_progress=True, queue=True) \ |
|
.then(fn=style_sorter.sort_styles, inputs=style_selections, outputs=style_selections, queue=False, show_progress=False) \ |
|
.then(lambda: None, _js='()=>{refresh_style_localization();}') |
|
|
|
def dump_default_english_config(): |
|
from modules.localization import dump_english_config |
|
dump_english_config(grh.all_components) |
|
|
|
|
|
|
|
|
|
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] |
|
) |
|
|
