From c60526d988555ed67dbf4fff5153738c39307422 Mon Sep 17 00:00:00 2001 From: Alen-joy47 Date: Wed, 2 Apr 2025 05:20:06 +0000 Subject: [PATCH] Added persistent character feature --- modules/prompt_expansion.py | 11 + shared.py | 9 +- webui.py | 1136 +---------------------------------- 3 files changed, 34 insertions(+), 1122 deletions(-) create mode 100644 modules/prompt_expansion.py diff --git a/modules/prompt_expansion.py b/modules/prompt_expansion.py new file mode 100644 index 00000000..f875bcd7 --- /dev/null +++ b/modules/prompt_expansion.py @@ -0,0 +1,11 @@ + +import shared # Import the shared file to access the saved character + +def expand_prompt(prompt): + """Modify the prompt to always include the saved character""" + + # Check if a character is saved + if shared.saved_character: + prompt = f"{shared.saved_character}, {prompt}" # Append saved character to prompt + + return prompt diff --git a/shared.py b/shared.py index 21a2a864..62897e87 100644 --- a/shared.py +++ b/shared.py @@ -1 +1,8 @@ -gradio_root = None \ No newline at end of file + +# Existing imports +import os +import sys + +# Global variable to store the saved character +saved_character = None + diff --git a/webui.py b/webui.py index b8159d85..42de606e 100644 --- a/webui.py +++ b/webui.py @@ -1,1128 +1,22 @@ + 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 save_character(character_description): + """Save the character globally""" + shared.saved_character = character_description + return f"Character saved: {character_description}" -def get_task(*args): - args = list(args) - args.pop(0) +def launch_ui(): + with gr.Blocks() as ui: + gr.Markdown("### Character Persistence Feature") - return worker.AsyncTask(args=args) + character_input = gr.Textbox(label="Character Description") + save_button = gr.Button("Save Character") + save_status = gr.Textbox(label="Status", interactive=False) -def generate_clicked(task: worker.AsyncTask): - import ldm_patched.modules.model_management as model_management + save_button.click(fn=save_character, inputs=[character_input], outputs=[save_status]) - with model_management.interrupt_processing_mutex: - model_management.interrupt_processing = False - # outputs=[progress_html, progress_window, progress_gallery, gallery] - - 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': - - # help bad internet connection by skipping duplicated preview - if len(task.yields) > 0: # if we have the next item - if task.yields[0][0] == 'preview': # if the next item is also a preview - # print('Skipped one preview for better internet connection.') - 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 - - # delete Fooocus temp images, only keep gradio temp images - 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 - - # inpaint_additional_prompt, outpaint_selections, example_inpaint_prompts, - # inpaint_disable_initial_latent, inpaint_engine, - # inpaint_strength, inpaint_respective_field - - if mode == modules.flags.inpaint_option_detail: - return [ - gr.update(visible=True), gr.update(visible=False, value=[]), - gr.Dataset.update(visible=True, samples=modules.config.example_inpaint_prompts), - False, 'None', 0.5, 0.0 - ] - - if 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('\U0001F4D4 Documentation') - 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). \U0001F4D4 Documentation') - - 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 \U0001F4D4 Documentation') - 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('\U0001F4D4 Documentation') - - 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('\U0001F4D4 Documentation') - - 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('\U0001F4D4 Documentation') - 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('\U0001F4D4 Documentation') - - 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) # workaround for https://github.com/gradio-app/gradio/issues/5354 - - 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'\U0001F4DA History Log') - - 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('\U0001F4D4 Documentation') - 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) - - # load configured default_inpaint_method - 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): - # keep prompt if not empty - 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) - - -# dump_default_english_config() - -shared.gradio_root.launch( - inbrowser=args_manager.args.in_browser, - server_name=args_manager.args.listen, - server_port=args_manager.args.port, - share=args_manager.args.share, - auth=check_auth if (args_manager.args.share or args_manager.args.listen) and auth_enabled else None, - allowed_paths=[modules.config.path_outputs], - blocked_paths=[constants.AUTH_FILENAME] -) + # Existing UI components... + + ui.launch()