| 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 | |
| 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): | |
| # import ldm_patched.modules.model_management as model_management | |
| # with model_management.interrupt_processing_mutex: | |
| # model_management.interrupt_processing = False | |
| # # outputs=[progress_html, progress_window, progress_gallery, gallery] | |
| # 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': | |
| # 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 | |
| reload_javascript() | |
| title = 'AI Describe Image' | |
| if isinstance(args_manager.args.preset, str): | |
| title += ' ' + args_manager.args.preset | |
| shared.gradio_root = gr.Blocks( | |
| title=title, | |
| css=modules.html.css).queue() | |
| with shared.gradio_root: | |
| # currentTask = gr.State(worker.AsyncTask(args=[])) | |
| 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(visible=True) as image_input_panel: | |
| with gr.Tabs(): | |
| # with gr.TabItem(label='Upscale or Variation') as uov_tab: | |
| # with gr.Row(): | |
| # with gr.Column(): | |
| # uov_input_image = grh.Image(label='Drag above image to here', source='upload', type='numpy') | |
| # with gr.Column(): | |
| # uov_method = gr.Radio(label='Upscale or Variation:', choices=flags.uov_list, value=flags.disabled) | |
| # gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/390" target="_blank">\U0001F4D4 Document</a>') | |
| # with gr.TabItem(label='Image Prompt') as ip_tab: | |
| # with gr.Row(): | |
| # ip_images = [] | |
| # ip_types = [] | |
| # ip_stops = [] | |
| # ip_weights = [] | |
| # ip_ctrls = [] | |
| # ip_ad_cols = [] | |
| # for _ in range(flags.controlnet_image_count): | |
| # with gr.Column(): | |
| # ip_image = grh.Image(label='Image', source='upload', type='numpy', show_label=False, height=300) | |
| # ip_images.append(ip_image) | |
| # ip_ctrls.append(ip_image) | |
| # with gr.Column(visible=False) as ad_col: | |
| # with gr.Row(): | |
| # default_end, default_weight = flags.default_parameters[flags.default_ip] | |
| # ip_stop = gr.Slider(label='Stop At', minimum=0.0, maximum=1.0, step=0.001, value=default_end) | |
| # 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=default_weight) | |
| # ip_weights.append(ip_weight) | |
| # ip_ctrls.append(ip_weight) | |
| # ip_type = gr.Radio(label='Type', choices=flags.ip_list, value=flags.default_ip, 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=False, 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 Document</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.TabItem(label='Inpaint or Outpaint') as inpaint_tab: | |
| # with gr.Row(): | |
| # inpaint_input_image = grh.Image(label='Drag inpaint or outpaint image to here', source='upload', type='numpy', tool='sketch', height=500, brush_color="#FFFFFF", elem_id='inpaint_canvas') | |
| # inpaint_mask_image = grh.Image(label='Mask Upload', source='upload', type='numpy', height=500, visible=False) | |
| # with gr.Row(): | |
| # 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') | |
| # inpaint_mode = gr.Dropdown(choices=modules.flags.inpaint_options, value=modules.flags.inpaint_option_default, label='Method') | |
| # 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 Document</a>') | |
| # example_inpaint_prompts.click(lambda x: x[0], inputs=example_inpaint_prompts, outputs=inpaint_additional_prompt, show_progress=False, queue=False) | |
| with gr.TabItem(label='Describe') as desc_tab: | |
| with gr.Row(): | |
| with gr.Column(): | |
| desc_input_image = grh.Image(label='Drag any image to here', source='upload', type='numpy') | |
| with gr.Column(): | |
| # with gr.Row(elem_classes='type_row'): | |
| with gr.Row(): | |
| prompt = gr.Textbox(label="Output", show_label=True, elem_id='positive_prompt', container=True, autofocus=True, show_copy_button=True, interactive=True) | |
| 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) | |
| # 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', 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=False, 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(): | |
| desc_method = gr.Radio( | |
| label='Content Type', | |
| choices=[flags.desc_type_photo, flags.desc_type_anime], | |
| value=flags.desc_type_photo) | |
| desc_btn = gr.Button(value='Describe this Image into Prompt') | |
| # gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/1363" target="_blank">\U0001F4D4 Document</a>') | |
| # with gr.TabItem(label='Metadata') as load_tab: | |
| # with gr.Column(): | |
| # metadata_input_image = grh.Image(label='Drag any image generated by Fooocus here', source='upload', type='filepath') | |
| # metadata_json = gr.JSON(label='Metadata') | |
| # metadata_import_button = gr.Button(value='Apply Metadata') | |
| # def trigger_metadata_preview(filepath): | |
| # parameters, metadata_scheme = modules.meta_parser.read_info_from_image(filepath) | |
| # 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) | |
| 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='desc', 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) | |
| # desc_tab.select(lambda: 'desc', outputs=current_tab, queue=False, _js=down_js, show_progress=False) | |
| # with gr.Column(scale=1, visible=modules.config.default_advanced_checkbox) as advanced_column: | |
| # with gr.Tab(label='Setting'): | |
| # performance_selection = gr.Radio(label='Performance', | |
| # choices=modules.flags.performance_selections, | |
| # value=modules.config.default_performance) | |
| # aspect_ratios_selection = gr.Radio(label='Aspect Ratios', choices=modules.config.available_aspect_ratios, | |
| # value=modules.config.default_aspect_ratio, info='width × height', | |
| # elem_classes='aspect_ratios') | |
| # 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=modules.flags.output_formats, | |
| # 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'<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='Style'): | |
| # 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='Model'): | |
| # 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, (n, v) in enumerate(modules.config.default_loras): | |
| # with gr.Row(): | |
| # lora_enabled = gr.Checkbox(label='Enable', value=True, | |
| # elem_classes=['lora_enable', 'min_check'], scale=1) | |
| # lora_model = gr.Dropdown(label=f'LoRA {i + 1}', | |
| # choices=['None'] + modules.config.lora_filenames, value=n, | |
| # 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=v, | |
| # elem_classes='lora_weight', scale=5) | |
| # lora_ctrls += [lora_enabled, lora_model, lora_weight] | |
| # with gr.Row(): | |
| # model_refresh = 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 Document</a>') | |
| # dev_mode = gr.Checkbox(label='Developer Debug Mode', value=False, container=False) | |
| # with gr.Column(visible=False) 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).') | |
| # sampler_name = gr.Dropdown(label='Sampler', choices=flags.sampler_list, | |
| # value=modules.config.default_sampler) | |
| # scheduler_name = gr.Dropdown(label='Scheduler', choices=flags.scheduler_list, | |
| # value=modules.config.default_scheduler) | |
| # generate_image_grid = gr.Checkbox(label='Generate Image Grid for Each Batch', | |
| # info='(Experimental) This may cause performance problems on some computers and certain internet conditions.', | |
| # value=False) | |
| # overwrite_step = gr.Slider(label='Forced Overwrite of Sampling Step', | |
| # minimum=-1, maximum=200, step=1, | |
| # value=modules.config.default_overwrite_step, | |
| # info='Set as -1 to disable. For developer debugging.') | |
| # overwrite_switch = gr.Slider(label='Forced Overwrite of Refiner Switch Step', | |
| # minimum=-1, maximum=200, step=1, | |
| # value=modules.config.default_overwrite_switch, | |
| # info='Set as -1 to disable. For developer debugging.') | |
| # overwrite_width = gr.Slider(label='Forced Overwrite of Generating Width', | |
| # minimum=-1, maximum=2048, step=1, value=-1, | |
| # info='Set as -1 to disable. For developer debugging. ' | |
| # 'Results will be worse for non-standard numbers that SDXL is not trained on.') | |
| # overwrite_height = gr.Slider(label='Forced Overwrite of Generating Height', | |
| # minimum=-1, maximum=2048, step=1, value=-1, | |
| # info='Set as -1 to disable. For developer debugging. ' | |
| # 'Results will be worse for non-standard numbers that SDXL is not trained on.') | |
| # overwrite_vary_strength = gr.Slider(label='Forced Overwrite of Denoising Strength of "Vary"', | |
| # minimum=-1, maximum=1.0, step=0.001, value=-1, | |
| # info='Set as negative number to disable. For developer debugging.') | |
| # overwrite_upscale_strength = gr.Slider(label='Forced Overwrite of Denoising Strength of "Upscale"', | |
| # minimum=-1, maximum=1.0, step=0.001, value=-1, | |
| # info='Set as negative number to disable. For developer debugging.') | |
| # disable_preview = gr.Checkbox(label='Disable Preview', value=False, | |
| # info='Disable preview during generation.') | |
| # disable_intermediate_results = gr.Checkbox(label='Disable Intermediate Results', | |
| # value=modules.config.default_performance == 'Extreme Speed', | |
| # interactive=modules.config.default_performance != 'Extreme Speed', | |
| # info='Disable intermediate results during generation, only show final gallery.') | |
| # disable_seed_increment = gr.Checkbox(label='Disable seed increment', | |
| # info='Disable automatic seed increment when image number is > 1.', | |
| # value=False) | |
| # # 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) | |
| # # inpaint_disable_initial_latent = gr.Checkbox(label='Disable initial latent in inpaint', value=False) | |
| # # inpaint_engine = gr.Dropdown(label='Inpaint Engine', | |
| # # value=modules.config.default_inpaint_engine_version, | |
| # # choices=flags.inpaint_engine_versions, | |
| # # info='Version of Fooocus inpaint model') | |
| # # inpaint_strength = gr.Slider(label='Inpaint Denoising Strength', | |
| # # minimum=0.0, maximum=1.0, step=0.001, value=1.0, | |
| # # info='Same as the denoising strength in A1111 inpaint. ' | |
| # # 'Only used in inpaint, not used in outpaint. ' | |
| # # '(Outpaint always use 1.0)') | |
| # # inpaint_respective_field = gr.Slider(label='Inpaint Respective Field', | |
| # # minimum=0.0, maximum=1.0, step=0.001, value=0.618, | |
| # # info='The area to inpaint. ' | |
| # # 'Value 0 is same as "Only Masked" in A1111. ' | |
| # # 'Value 1 is same as "Whole Image" in A1111. ' | |
| # # 'Only used in inpaint, not used in outpaint. ' | |
| # # '(Outpaint always use 1.0)') | |
| # # inpaint_erode_or_dilate = gr.Slider(label='Mask Erode or Dilate', | |
| # # minimum=-64, maximum=64, step=1, value=0, | |
| # # info='Positive value will make white area in the mask larger, ' | |
| # # 'negative value will make white area smaller.' | |
| # # '(default is 0, always process before any mask invert)') | |
| # # inpaint_mask_upload_checkbox = gr.Checkbox(label='Enable Mask Upload', value=False) | |
| # # invert_mask_checkbox = gr.Checkbox(label='Invert Mask', value=False) | |
| # # inpaint_ctrls = [debugging_inpaint_preprocessor, inpaint_disable_initial_latent, inpaint_engine, | |
| # # inpaint_strength, inpaint_respective_field, | |
| # # inpaint_mask_upload_checkbox, invert_mask_checkbox, inpaint_erode_or_dilate] | |
| # # inpaint_mask_upload_checkbox.change(lambda x: gr.update(visible=x), | |
| # # inputs=inpaint_mask_upload_checkbox, | |
| # # outputs=inpaint_mask_image, queue=False, show_progress=False) | |
| # with gr.Tab(label='FreeU'): | |
| # freeu_enabled = gr.Checkbox(label='Enabled', value=False) | |
| # freeu_b1 = gr.Slider(label='B1', minimum=0, maximum=2, step=0.01, value=1.01) | |
| # freeu_b2 = gr.Slider(label='B2', minimum=0, maximum=2, step=0.01, value=1.02) | |
| # freeu_s1 = gr.Slider(label='S1', minimum=0, maximum=4, step=0.01, value=0.99) | |
| # freeu_s2 = gr.Slider(label='S2', minimum=0, maximum=4, step=0.01, value=0.95) | |
| # freeu_ctrls = [freeu_enabled, freeu_b1, freeu_b2, freeu_s1, freeu_s2] | |
| # def dev_mode_checked(r): | |
| # return gr.update(visible=r) | |
| # dev_mode.change(dev_mode_checked, inputs=[dev_mode], outputs=[dev_tools], | |
| # queue=False, show_progress=False) | |
| # def model_refresh_clicked(): | |
| # modules.config.update_all_model_names() | |
| # results = [gr.update(choices=modules.config.model_filenames)] | |
| # results += [gr.update(choices=['None'] + modules.config.model_filenames)] | |
| # for i in range(modules.config.default_max_lora_number): | |
| # results += [gr.update(interactive=True), gr.update(choices=['None'] + modules.config.lora_filenames), gr.update()] | |
| # return results | |
| # model_refresh.click(model_refresh_clicked, [], [base_model, refiner_model] + lora_ctrls, | |
| # queue=False, show_progress=False) | |
| # performance_selection.change(lambda x: [gr.update(interactive=x != 'Extreme Speed')] * 11 + | |
| # [gr.update(visible=x != 'Extreme Speed')] * 1 + | |
| # [gr.update(interactive=x != 'Extreme Speed', value=x == 'Extreme Speed', )] * 1, | |
| # inputs=performance_selection, | |
| # outputs=[ | |
| # guidance_scale, sharpness, adm_scaler_end, adm_scaler_positive, | |
| # adm_scaler_negative, refiner_switch, refiner_model, sampler_name, | |
| # scheduler_name, adaptive_cfg, refiner_swap_method, negative_prompt, disable_intermediate_results | |
| # ], queue=False, show_progress=False) | |
| # 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) | |
| # def inpaint_mode_change(mode): | |
| # assert mode in modules.flags.inpaint_options | |
| # # inpaint_additional_prompt, outpaint_selections, example_inpaint_prompts, | |
| # # inpaint_disable_initial_latent, inpaint_engine, | |
| # # inpaint_strength, inpaint_respective_field | |
| # if mode == modules.flags.inpaint_option_detail: | |
| # return [ | |
| # gr.update(visible=True), gr.update(visible=False, value=[]), | |
| # gr.Dataset.update(visible=True, samples=modules.config.example_inpaint_prompts), | |
| # False, 'None', 0.5, 0.0 | |
| # ] | |
| # if mode == modules.flags.inpaint_option_modify: | |
| # return [ | |
| # gr.update(visible=True), gr.update(visible=False, value=[]), | |
| # gr.Dataset.update(visible=False, samples=modules.config.example_inpaint_prompts), | |
| # True, modules.config.default_inpaint_engine_version, 1.0, 0.0 | |
| # ] | |
| # return [ | |
| # gr.update(visible=False, value=''), gr.update(visible=True), | |
| # gr.Dataset.update(visible=False, samples=modules.config.example_inpaint_prompts), | |
| # False, modules.config.default_inpaint_engine_version, 1.0, 0.618 | |
| # ] | |
| # inpaint_mode.input(inpaint_mode_change, inputs=inpaint_mode, outputs=[ | |
| # inpaint_additional_prompt, outpaint_selections, example_inpaint_prompts, | |
| # inpaint_disable_initial_latent, inpaint_engine, | |
| # inpaint_strength, inpaint_respective_field | |
| # ], show_progress=False, queue=False) | |
| # ctrls = [currentTask, generate_image_grid] | |
| # ctrls += [ | |
| # prompt, negative_prompt, style_selections, | |
| # performance_selection, aspect_ratios_selection, image_number, output_format, image_seed, sharpness, guidance_scale | |
| # ] | |
| # ctrls += [base_model, refiner_model, refiner_switch] + lora_ctrls | |
| # # ctrls += [input_image_checkbox, current_tab] | |
| # # ctrls += [uov_method, uov_input_image] | |
| # # ctrls += [outpaint_selections, inpaint_input_image, inpaint_additional_prompt, inpaint_mask_image] | |
| # ctrls += [disable_preview, disable_intermediate_results, disable_seed_increment] | |
| # ctrls += [adm_scaler_positive, adm_scaler_negative, adm_scaler_end, adaptive_cfg] | |
| # ctrls += [sampler_name, scheduler_name] | |
| # ctrls += [overwrite_step, overwrite_switch, overwrite_width, overwrite_height, overwrite_vary_strength] | |
| # ctrls += [overwrite_upscale_strength, mixing_image_prompt_and_vary_upscale, mixing_image_prompt_and_inpaint] | |
| # ctrls += [debugging_cn_preprocessor, skipping_cn_preprocessor, canny_low_threshold, canny_high_threshold] | |
| # ctrls += [refiner_swap_method, controlnet_softness] | |
| # ctrls += freeu_ctrls | |
| # ctrls += inpaint_ctrls | |
| # if not args_manager.args.disable_metadata: | |
| # ctrls += [save_metadata_to_images, metadata_scheme] | |
| # ctrls += ip_ctrls | |
| # state_is_generating = gr.State(False) | |
| # 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_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, base_model, | |
| # refiner_model, refiner_switch, sampler_name, scheduler_name, seed_random, image_seed, | |
| # generate_button, load_parameter_button] + freeu_ctrls + lora_ctrls | |
| # load_parameter_button.click(modules.meta_parser.load_parameter_button_click, inputs=[prompt, state_is_generating], outputs=load_data_outputs, queue=False, show_progress=False) | |
| # # def trigger_metadata_import(filepath, state_is_generating): | |
| # # parameters, metadata_scheme = modules.meta_parser.read_info_from_image(filepath) | |
| # # 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.parse_json(parameters) | |
| # # return modules.meta_parser.load_parameter_button_click(parsed_parameters, state_is_generating) | |
| # # 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') | |
| for notification_file in ['notification.ogg', 'notification.mp3']: | |
| if os.path.exists(notification_file): | |
| gr.Audio(interactive=False, value=notification_file, elem_id='audio_notification', visible=False) | |
| break | |
| def trigger_describe(mode, img): | |
| if mode == flags.desc_type_photo: | |
| from extras.interrogate import default_interrogator as default_interrogator_photo | |
| return default_interrogator_photo(img), ["Fooocus V2", "Fooocus Enhance", "Fooocus Sharp"] | |
| if mode == flags.desc_type_anime: | |
| from extras.wd14tagger import default_interrogator as default_interrogator_anime | |
| return default_interrogator_anime(img), ["Fooocus V2", "Fooocus Masterpiece"] | |
| return mode, ["Fooocus V2"] | |
| desc_btn.click(trigger_describe, inputs=[desc_method, desc_input_image], | |
| outputs=prompt, show_progress=True, queue=True) | |
| def dump_default_english_config(): | |
| from modules.localization import dump_english_config | |
| dump_english_config(grh.all_components) | |
| # dump_default_english_config() | |
| shared.gradio_root.launch( | |
| inbrowser=args_manager.args.in_browser, | |
| server_name=args_manager.args.listen, | |
| server_port=args_manager.args.port, | |
| share=args_manager.args.share, | |
| auth=check_auth if (args_manager.args.share or args_manager.args.listen) and auth_enabled else None, | |
| allowed_paths=[modules.config.path_outputs], | |
| blocked_paths=[constants.AUTH_FILENAME] | |
| ) | |