| | import gradio as gr |
| | import random |
| | import os |
| | import json |
| | import time |
| | import shared |
| | import modules.config |
| | import fooocus_version |
| | import modules.html |
| | import modules.async_worker as worker |
| | import modules.constants as constants |
| | import modules.flags as flags |
| | import modules.gradio_hijack as grh |
| | import modules.style_sorter as style_sorter |
| | import modules.meta_parser |
| | import args_manager |
| | import copy |
| | import launch |
| | from extras.inpaint_mask import SAMOptions |
| |
|
| | from modules.sdxl_styles import legal_style_names |
| | from modules.private_logger import get_current_html_path |
| | from modules.ui_gradio_extensions import reload_javascript |
| | from modules.auth import auth_enabled, check_auth |
| | from modules.util import is_json |
| |
|
| | def get_task(*args): |
| | args = list(args) |
| | args.pop(0) |
| |
|
| | return worker.AsyncTask(args=args) |
| |
|
| | def generate_clicked(task: worker.AsyncTask): |
| | import ldm_patched.modules.model_management as model_management |
| |
|
| | with model_management.interrupt_processing_mutex: |
| | model_management.interrupt_processing = False |
| | |
| |
|
| | if len(task.args) == 0: |
| | return |
| |
|
| | execution_start_time = time.perf_counter() |
| | finished = False |
| |
|
| | yield gr.update(visible=True, value=modules.html.make_progress_html(1, 'Waiting for task to start ...')), \ |
| | gr.update(visible=True, value=None), \ |
| | gr.update(visible=False, value=None), \ |
| | gr.update(visible=False) |
| |
|
| | worker.async_tasks.append(task) |
| |
|
| | while not finished: |
| | time.sleep(0.01) |
| | if len(task.yields) > 0: |
| | flag, product = task.yields.pop(0) |
| | if flag == 'preview': |
| |
|
| | |
| | if len(task.yields) > 0: |
| | if task.yields[0][0] == 'preview': |
| | |
| | continue |
| |
|
| | percentage, title, image = product |
| | yield gr.update(visible=True, value=modules.html.make_progress_html(percentage, title)), \ |
| | gr.update(visible=True, value=image) if image is not None else gr.update(), \ |
| | gr.update(), \ |
| | gr.update(visible=False) |
| | if flag == 'results': |
| | yield gr.update(visible=True), \ |
| | gr.update(visible=True), \ |
| | gr.update(visible=True, value=product), \ |
| | gr.update(visible=False) |
| | if flag == 'finish': |
| | if not args_manager.args.disable_enhance_output_sorting: |
| | product = sort_enhance_images(product, task) |
| |
|
| | yield gr.update(visible=False), \ |
| | gr.update(visible=False), \ |
| | gr.update(visible=False), \ |
| | gr.update(visible=True, value=product) |
| | finished = True |
| |
|
| | |
| | if args_manager.args.disable_image_log: |
| | for filepath in product: |
| | if isinstance(filepath, str) and os.path.exists(filepath): |
| | os.remove(filepath) |
| |
|
| | execution_time = time.perf_counter() - execution_start_time |
| | print(f'Total time: {execution_time:.2f} seconds') |
| | return |
| |
|
| |
|
| | def sort_enhance_images(images, task): |
| | if not task.should_enhance or len(images) <= task.images_to_enhance_count: |
| | return images |
| |
|
| | sorted_images = [] |
| | walk_index = task.images_to_enhance_count |
| |
|
| | for index, enhanced_img in enumerate(images[:task.images_to_enhance_count]): |
| | sorted_images.append(enhanced_img) |
| | if index not in task.enhance_stats: |
| | continue |
| | target_index = walk_index + task.enhance_stats[index] |
| | if walk_index < len(images) and target_index <= len(images): |
| | sorted_images += images[walk_index:target_index] |
| | walk_index += task.enhance_stats[index] |
| |
|
| | return sorted_images |
| |
|
| |
|
| | def inpaint_mode_change(mode, inpaint_engine_version): |
| | assert mode in modules.flags.inpaint_options |
| |
|
| | |
| | |
| | |
| |
|
| | 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 inpaint_engine_version == 'empty': |
| | inpaint_engine_version = modules.config.default_inpaint_engine_version |
| |
|
| | 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, 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, inpaint_engine_version, 1.0, 0.618 |
| | ] |
| |
|
| |
|
| | reload_javascript() |
| |
|
| | title = f'Fooocus {fooocus_version.version}' |
| |
|
| | if isinstance(args_manager.args.preset, str): |
| | title += ' ' + args_manager.args.preset |
| |
|
| | shared.gradio_root = gr.Blocks(title=title).queue() |
| |
|
| | with shared.gradio_root: |
| | currentTask = gr.State(worker.AsyncTask(args=[])) |
| | inpaint_engine_state = gr.State('empty') |
| | with gr.Row(): |
| | with gr.Column(scale=2): |
| | with gr.Row(): |
| | progress_window = grh.Image(label='Preview', show_label=True, visible=False, height=768, |
| | elem_classes=['main_view']) |
| | progress_gallery = gr.Gallery(label='Finished Images', show_label=True, object_fit='contain', |
| | height=768, visible=False, elem_classes=['main_view', 'image_gallery']) |
| | progress_html = gr.HTML(value=modules.html.make_progress_html(32, 'Progress 32%'), visible=False, |
| | elem_id='progress-bar', elem_classes='progress-bar') |
| | gallery = gr.Gallery(label='Gallery', show_label=False, object_fit='contain', visible=True, height=768, |
| | elem_classes=['resizable_area', 'main_view', 'final_gallery', 'image_gallery'], |
| | elem_id='final_gallery') |
| | with gr.Row(): |
| | with gr.Column(scale=17): |
| | prompt = gr.Textbox(show_label=False, placeholder="Type prompt here or paste parameters.", elem_id='positive_prompt', |
| | autofocus=True, lines=3) |
| |
|
| | default_prompt = modules.config.default_prompt |
| | if isinstance(default_prompt, str) and default_prompt != '': |
| | shared.gradio_root.load(lambda: default_prompt, outputs=prompt) |
| |
|
| | with gr.Column(scale=3, min_width=0): |
| | generate_button = gr.Button(label="Generate", value="Generate", elem_classes='type_row', elem_id='generate_button', visible=True) |
| | reset_button = gr.Button(label="Reconnect", value="Reconnect", elem_classes='type_row', elem_id='reset_button', visible=False) |
| | load_parameter_button = gr.Button(label="Load Parameters", value="Load Parameters", elem_classes='type_row', elem_id='load_parameter_button', visible=False) |
| | skip_button = gr.Button(label="Skip", value="Skip", elem_classes='type_row_half', elem_id='skip_button', visible=False) |
| | stop_button = gr.Button(label="Stop", value="Stop", elem_classes='type_row_half', elem_id='stop_button', visible=False) |
| |
|
| | def stop_clicked(currentTask): |
| | import ldm_patched.modules.model_management as model_management |
| | currentTask.last_stop = 'stop' |
| | if (currentTask.processing): |
| | model_management.interrupt_current_processing() |
| | return currentTask |
| |
|
| | def skip_clicked(currentTask): |
| | import ldm_patched.modules.model_management as model_management |
| | currentTask.last_stop = 'skip' |
| | if (currentTask.processing): |
| | model_management.interrupt_current_processing() |
| | return currentTask |
| |
|
| | stop_button.click(stop_clicked, inputs=currentTask, outputs=currentTask, queue=False, show_progress=False, _js='cancelGenerateForever') |
| | skip_button.click(skip_clicked, inputs=currentTask, outputs=currentTask, queue=False, show_progress=False) |
| | with gr.Row(elem_classes='advanced_check_row'): |
| | input_image_checkbox = gr.Checkbox(label='Input Image', value=modules.config.default_image_prompt_checkbox, container=False, elem_classes='min_check') |
| | enhance_checkbox = gr.Checkbox(label='Enhance', value=modules.config.default_enhance_checkbox, container=False, elem_classes='min_check') |
| | advanced_checkbox = gr.Checkbox(label='Advanced', value=modules.config.default_advanced_checkbox, container=False, elem_classes='min_check') |
| | with gr.Row(visible=modules.config.default_image_prompt_checkbox) as image_input_panel: |
| | with gr.Tabs(selected=modules.config.default_selected_image_input_tab_id): |
| | with gr.Tab(label='Upscale or Variation', id='uov_tab') as uov_tab: |
| | with gr.Row(): |
| | with gr.Column(): |
| | uov_input_image = grh.Image(label='Image', source='upload', type='numpy', show_label=False) |
| | with gr.Column(): |
| | uov_method = gr.Radio(label='Upscale or Variation:', choices=flags.uov_list, value=modules.config.default_uov_method) |
| | gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/390" target="_blank">\U0001F4D4 Documentation</a>') |
| | with gr.Tab(label='Image Prompt', id='ip_tab') as ip_tab: |
| | with gr.Row(): |
| | ip_images = [] |
| | ip_types = [] |
| | ip_stops = [] |
| | ip_weights = [] |
| | ip_ctrls = [] |
| | ip_ad_cols = [] |
| | for image_count in range(modules.config.default_controlnet_image_count): |
| | image_count += 1 |
| | with gr.Column(): |
| | ip_image = grh.Image(label='Image', source='upload', type='numpy', show_label=False, height=300, value=modules.config.default_ip_images[image_count]) |
| | ip_images.append(ip_image) |
| | ip_ctrls.append(ip_image) |
| | with gr.Column(visible=modules.config.default_image_prompt_advanced_checkbox) as ad_col: |
| | with gr.Row(): |
| | 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]) |
| | ip_stops.append(ip_stop) |
| | ip_ctrls.append(ip_stop) |
| |
|
| | ip_weight = gr.Slider(label='Weight', minimum=0.0, maximum=2.0, step=0.001, value=modules.config.default_ip_weights[image_count]) |
| | ip_weights.append(ip_weight) |
| | ip_ctrls.append(ip_weight) |
| |
|
| | ip_type = gr.Radio(label='Type', choices=flags.ip_list, value=modules.config.default_ip_types[image_count], container=False) |
| | ip_types.append(ip_type) |
| | ip_ctrls.append(ip_type) |
| |
|
| | ip_type.change(lambda x: flags.default_parameters[x], inputs=[ip_type], outputs=[ip_stop, ip_weight], queue=False, show_progress=False) |
| | ip_ad_cols.append(ad_col) |
| | ip_advanced = gr.Checkbox(label='Advanced', value=modules.config.default_image_prompt_advanced_checkbox, container=False) |
| | 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>') |
| |
|
| | def ip_advance_checked(x): |
| | return [gr.update(visible=x)] * len(ip_ad_cols) + \ |
| | [flags.default_ip] * len(ip_types) + \ |
| | [flags.default_parameters[flags.default_ip][0]] * len(ip_stops) + \ |
| | [flags.default_parameters[flags.default_ip][1]] * len(ip_weights) |
| |
|
| | ip_advanced.change(ip_advance_checked, inputs=ip_advanced, |
| | outputs=ip_ad_cols + ip_types + ip_stops + ip_weights, |
| | queue=False, show_progress=False) |
| |
|
| | with gr.Tab(label='Inpaint or Outpaint', id='inpaint_tab') as inpaint_tab: |
| | with gr.Row(): |
| | with gr.Column(): |
| | 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) |
| | inpaint_advanced_masking_checkbox = gr.Checkbox(label='Enable Advanced Masking Features', value=modules.config.default_inpaint_advanced_masking_checkbox) |
| | inpaint_mode = gr.Dropdown(choices=modules.flags.inpaint_options, value=modules.config.default_inpaint_method, label='Method') |
| | inpaint_additional_prompt = gr.Textbox(placeholder="Describe what you want to inpaint.", elem_id='inpaint_additional_prompt', label='Inpaint Additional Prompt', visible=False) |
| | outpaint_selections = gr.CheckboxGroup(choices=['Left', 'Right', 'Top', 'Bottom'], value=[], label='Outpaint Direction') |
| | example_inpaint_prompts = gr.Dataset(samples=modules.config.example_inpaint_prompts, |
| | label='Additional Prompt Quick List', |
| | components=[inpaint_additional_prompt], |
| | visible=False) |
| | gr.HTML('* Powered by Fooocus Inpaint Engine <a href="https://github.com/lllyasviel/Fooocus/discussions/414" target="_blank">\U0001F4D4 Documentation</a>') |
| | example_inpaint_prompts.click(lambda x: x[0], inputs=example_inpaint_prompts, outputs=inpaint_additional_prompt, show_progress=False, queue=False) |
| |
|
| | with gr.Column(visible=modules.config.default_inpaint_advanced_masking_checkbox) as inpaint_mask_generation_col: |
| | 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') |
| | invert_mask_checkbox = gr.Checkbox(label='Invert Mask When Generating', value=modules.config.default_invert_mask_checkbox) |
| | inpaint_mask_model = gr.Dropdown(label='Mask generation model', |
| | choices=flags.inpaint_mask_models, |
| | value=modules.config.default_inpaint_mask_model) |
| | inpaint_mask_cloth_category = gr.Dropdown(label='Cloth category', |
| | choices=flags.inpaint_mask_cloth_category, |
| | value=modules.config.default_inpaint_mask_cloth_category, |
| | visible=False) |
| | 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.') |
| | example_inpaint_mask_dino_prompt_text = gr.Dataset( |
| | samples=modules.config.example_enhance_detection_prompts, |
| | label='Detection Prompt Quick List', |
| | components=[inpaint_mask_dino_prompt_text], |
| | visible=modules.config.default_inpaint_mask_model == 'sam') |
| | example_inpaint_mask_dino_prompt_text.click(lambda x: x[0], |
| | inputs=example_inpaint_mask_dino_prompt_text, |
| | outputs=inpaint_mask_dino_prompt_text, |
| | show_progress=False, queue=False) |
| |
|
| | with gr.Accordion("Advanced options", visible=False, open=False) as inpaint_mask_advanced_options: |
| | inpaint_mask_sam_model = gr.Dropdown(label='SAM model', choices=flags.inpaint_mask_sam_model, value=modules.config.default_inpaint_mask_sam_model) |
| | inpaint_mask_box_threshold = gr.Slider(label="Box Threshold", minimum=0.0, maximum=1.0, value=0.3, step=0.05) |
| | inpaint_mask_text_threshold = gr.Slider(label="Text Threshold", minimum=0.0, maximum=1.0, value=0.25, step=0.05) |
| | 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) |
| | generate_mask_button = gr.Button(value='Generate mask from image') |
| |
|
| | 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): |
| | from extras.inpaint_mask import generate_mask_from_image |
| |
|
| | extras = {} |
| | sam_options = None |
| | if mask_model == 'u2net_cloth_seg': |
| | extras['cloth_category'] = cloth_category |
| | elif mask_model == 'sam': |
| | sam_options = SAMOptions( |
| | dino_prompt=dino_prompt_text, |
| | dino_box_threshold=box_threshold, |
| | dino_text_threshold=text_threshold, |
| | dino_erode_or_dilate=dino_erode_or_dilate, |
| | dino_debug=dino_debug, |
| | max_detections=sam_max_detections, |
| | model_type=sam_model |
| | ) |
| |
|
| | mask, _, _, _ = generate_mask_from_image(image, mask_model, extras, sam_options) |
| |
|
| | return mask |
| |
|
| |
|
| | inpaint_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=inpaint_mask_model, |
| | outputs=[inpaint_mask_cloth_category, |
| | inpaint_mask_dino_prompt_text, |
| | inpaint_mask_advanced_options, |
| | example_inpaint_mask_dino_prompt_text], |
| | queue=False, show_progress=False) |
| |
|
| | with gr.Tab(label='Describe', id='describe_tab') as describe_tab: |
| | with gr.Row(): |
| | with gr.Column(): |
| | describe_input_image = grh.Image(label='Image', source='upload', type='numpy', show_label=False) |
| | with gr.Column(): |
| | describe_methods = gr.CheckboxGroup( |
| | label='Content Type', |
| | choices=flags.describe_types, |
| | value=modules.config.default_describe_content_type) |
| | describe_apply_styles = gr.Checkbox(label='Apply Styles', value=modules.config.default_describe_apply_prompts_checkbox) |
| | describe_btn = gr.Button(value='Describe this Image into Prompt') |
| | describe_image_size = gr.Textbox(label='Image Size and Recommended Size', elem_id='describe_image_size', visible=False) |
| | gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/1363" target="_blank">\U0001F4D4 Documentation</a>') |
| |
|
| | def trigger_show_image_properties(image): |
| | value = modules.util.get_image_size_info(image, modules.flags.sdxl_aspect_ratios) |
| | return gr.update(value=value, visible=True) |
| |
|
| | describe_input_image.upload(trigger_show_image_properties, inputs=describe_input_image, |
| | outputs=describe_image_size, show_progress=False, queue=False) |
| |
|
| | with gr.Tab(label='Enhance', id='enhance_tab') as enhance_tab: |
| | with gr.Row(): |
| | with gr.Column(): |
| | enhance_input_image = grh.Image(label='Use with Enhance, skips image generation', source='upload', type='numpy') |
| | gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/3281" target="_blank">\U0001F4D4 Documentation</a>') |
| |
|
| | with gr.Tab(label='Metadata', id='metadata_tab') as metadata_tab: |
| | with gr.Column(): |
| | metadata_input_image = grh.Image(label='For images created by Fooocus', source='upload', type='pil') |
| | metadata_json = gr.JSON(label='Metadata') |
| | metadata_import_button = gr.Button(value='Apply Metadata') |
| |
|
| | def trigger_metadata_preview(file): |
| | parameters, metadata_scheme = modules.meta_parser.read_info_from_image(file) |
| |
|
| | results = {} |
| | if parameters is not None: |
| | results['parameters'] = parameters |
| |
|
| | if isinstance(metadata_scheme, flags.MetadataScheme): |
| | results['metadata_scheme'] = metadata_scheme.value |
| |
|
| | return results |
| |
|
| | metadata_input_image.upload(trigger_metadata_preview, inputs=metadata_input_image, |
| | outputs=metadata_json, queue=False, show_progress=True) |
| |
|
| | with gr.Row(visible=modules.config.default_enhance_checkbox) as enhance_input_panel: |
| | with gr.Tabs(): |
| | with gr.Tab(label='Upscale or Variation'): |
| | with gr.Row(): |
| | with gr.Column(): |
| | enhance_uov_method = gr.Radio(label='Upscale or Variation:', choices=flags.uov_list, |
| | value=modules.config.default_enhance_uov_method) |
| | enhance_uov_processing_order = gr.Radio(label='Order of Processing', |
| | info='Use before to enhance small details and after to enhance large areas.', |
| | choices=flags.enhancement_uov_processing_order, |
| | value=modules.config.default_enhance_uov_processing_order) |
| | enhance_uov_prompt_type = gr.Radio(label='Prompt', |
| | info='Choose which prompt to use for Upscale or Variation.', |
| | choices=flags.enhancement_uov_prompt_types, |
| | value=modules.config.default_enhance_uov_prompt_type, |
| | visible=modules.config.default_enhance_uov_processing_order == flags.enhancement_uov_after) |
| |
|
| | enhance_uov_processing_order.change(lambda x: gr.update(visible=x == flags.enhancement_uov_after), |
| | inputs=enhance_uov_processing_order, |
| | outputs=enhance_uov_prompt_type, |
| | queue=False, show_progress=False) |
| | gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/3281" target="_blank">\U0001F4D4 Documentation</a>') |
| | enhance_ctrls = [] |
| | enhance_inpaint_mode_ctrls = [] |
| | enhance_inpaint_engine_ctrls = [] |
| | enhance_inpaint_update_ctrls = [] |
| | for index in range(modules.config.default_enhance_tabs): |
| | with gr.Tab(label=f'#{index + 1}') as enhance_tab_item: |
| | enhance_enabled = gr.Checkbox(label='Enable', value=False, elem_classes='min_check', |
| | container=False) |
| |
|
| | enhance_mask_dino_prompt_text = gr.Textbox(label='Detection prompt', |
| | info='Use singular whenever possible', |
| | placeholder='Describe what you want to detect.', |
| | 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] |
| | ) |
| |
|
