diff --git a/webui.py b/webui.py
index 97f102c048..fb865c08a8 100644
--- a/webui.py
+++ b/webui.py
@@ -4,839 +4,112 @@
 import json
 import time
 import shared
-import modules.config
+import modules.config as config
 import fooocus_version
-import modules.html
+import modules.html as 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 modules.meta_parser as meta_parser
 from modules.rembg import rembg_run
 import args_manager
 import copy
 import launch
-
-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
-
-PHOTOPEA_MAIN_URL = "https://www.photopea.com/"
-PHOTOPEA_IFRAME_ID = "webui-photopea-iframe"
-PHOTOPEA_IFRAME_HEIGHT = 684
-PHOTOPEA_IFRAME_WIDTH = "100%"
-PHOTOPEA_IFRAME_LOADED_EVENT = "onPhotopeaLoaded"
-
-
-def get_photopea_url_params():
-    return "#%7B%22resources%22:%5B%22data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIAAQMAAADOtka5AAAAAXNSR0IB2cksfwAAAAlwSFlzAAALEwAACxMBAJqcGAAAAANQTFRF////p8QbyAAAADZJREFUeJztwQEBAAAAgiD/r25IQAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAfBuCAAAB0niJ8AAAAABJRU5ErkJggg==%22%5D%7D"
-
+from SegBody import segment_body
 
 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:
-                        os.remove(filepath)
-
-    execution_time = time.perf_counter() - execution_start_time
-    global time_taken 
-    time_taken = f"Total time: {execution_time:.2f} seconds"
-    print(time_taken)
-    return
-
-
-reload_javascript()
-
-title = f'DeFooocus {fooocus_version.version}'
-
-if isinstance(args_manager.args.preset, str):
-    title += ' ' + args_manager.args.preset
-
-shared.gradio_root = gr.Blocks(
-    title=title,
-    css=modules.html.css,
-    theme="ehristoforu/Indigo_Theme").queue()
-
-with shared.gradio_root:
-    currentTask = gr.State(worker.AsyncTask(args=[]))
-    with gr.Row():
-        with gr.Column(scale=2):
-            with gr.Tab("Generation"):
-                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.Tab("Photopea"):
-                with gr.Row():
-                    photopea = gr.HTML(
-                        f"""<iframe id="{PHOTOPEA_IFRAME_ID}" 
-                        src = "{PHOTOPEA_MAIN_URL}{get_photopea_url_params()}" 
-                        width = "{PHOTOPEA_IFRAME_WIDTH}" 
-                        height = "{PHOTOPEA_IFRAME_HEIGHT}"
-                        onload = "{PHOTOPEA_IFRAME_LOADED_EVENT}(this)">"""
-                    )
-                gr.Markdown("Powered by [🦜 Photopea API](https://www.photopea.com/api)")
-            with gr.Tab("rembg"):
-                with gr.Column(scale=1):
-                    rembg_input = grh.Image(label='Drag above image to here', source='upload', type='filepath', scale=20)
-                    rembg_button = gr.Button(value="Remove Background", interactive=True, scale=1)
-                with gr.Column(scale=3):
-                    rembg_output = grh.Image(label='rembg Output', interactive=False, height=380)
-                gr.Markdown("Powered by [🪄 rembg 2.0.53](https://github.com/danielgatis/rembg/releases/tag/v2.0.53)")
-            rembg_button.click(rembg_run, inputs=rembg_input, outputs=rembg_output, show_progress="full")  
-            with gr.Row(elem_classes='type_row'):
-                with gr.Column(scale=17):
-                    prompt = gr.Textbox(show_label=False, placeholder="Type prompt here or paste parameters.", elem_id='positive_prompt',
-                                        container=False, autofocus=True, elem_classes='type_row', lines=1024)
-
-                    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(visible=False) 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():
-                            with gr.Column():
-                                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_mode = gr.Dropdown(choices=modules.flags.inpaint_options, value=modules.flags.inpaint_option_default, label='Method')
-                                inpaint_additional_prompt = gr.Textbox(placeholder="Describe what you want to inpaint.", elem_id='inpaint_additional_prompt', label='Inpaint Additional Prompt', visible=False)
-                                outpaint_selections = gr.CheckboxGroup(choices=['Left', 'Right', 'Top', 'Bottom'], value=[], label='Outpaint Direction')
-                                example_inpaint_prompts = gr.Dataset(samples=modules.config.example_inpaint_prompts,
-                                                                     label='Additional Prompt Quick List',
-                                                                     components=[inpaint_additional_prompt],
-                                                                     visible=False)
-                                gr.HTML('* Powered by Fooocus Inpaint Engine <a href="https://github.com/lllyasviel/Fooocus/discussions/414" target="_blank">\U0001F4D4 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.Column(visible=False) as inpaint_mask_generation_col:
-                                inpaint_mask_image = grh.Image(label='Mask Upload', source='upload', type='numpy',
-                                                               height=500)
-                                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_sam_prompt_text = gr.Textbox(label='Segmentation prompt', value='', visible=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_sam_quant = gr.Checkbox(label='Quantization', value=False)
-                                    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)
-                                generate_mask_button = gr.Button(value='Generate mask from image')
-
-                                def generate_mask(image, mask_model, cloth_category, sam_prompt_text, sam_model, sam_quant, box_threshold, text_threshold):
-                                    from extras.inpaint_mask import generate_mask_from_image
-
-                                    extras = {}
-                                    if mask_model == 'u2net_cloth_seg':
-                                        extras['cloth_category'] = cloth_category
-                                    elif mask_model == 'sam':
-                                        extras['sam_prompt_text'] = sam_prompt_text
-                                        extras['sam_model'] = sam_model
-                                        extras['sam_quant'] = sam_quant
-                                        extras['box_threshold'] = box_threshold
-                                        extras['text_threshold'] = text_threshold
-
-                                    return generate_mask_from_image(image, mask_model, extras)
-
-                                generate_mask_button.click(fn=generate_mask,
-                                                           inputs=[
-                                                               inpaint_input_image, inpaint_mask_model,
-                                                               inpaint_mask_cloth_category,
-                                                               inpaint_mask_sam_prompt_text,
-                                                               inpaint_mask_sam_model,
-                                                               inpaint_mask_sam_quant,
-                                                               inpaint_mask_box_threshold,
-                                                               inpaint_mask_text_threshold
-                                                           ],
-                                                           outputs=inpaint_mask_image, show_progress=True, queue=True)
-
-                                inpaint_mask_model.change(lambda x: [gr.update(visible=x == 'u2net_cloth_seg'), gr.update(visible=x == 'sam'), gr.update(visible=x == 'sam')],
-                                                          inputs=inpaint_mask_model,
-                                                          outputs=[inpaint_mask_cloth_category, inpaint_mask_sam_prompt_text, inpaint_mask_advanced_options],
-                                                          queue=False, show_progress=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():
-                                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='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)
-            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='Settings'):
-                performance_selection = gr.Radio(label='Performance',
-                                                 choices=modules.flags.performance_selections,
-                                                 value=modules.config.default_performance,
-                                                 elem_classes='performance_selections')
-                if not args_manager.args.disable_preset_selection:
-                    preset_selection = gr.Radio(label='Preset',
-                                                choices=modules.config.available_presets,
-                                                value=args_manager.args.preset if args_manager.args.preset else "initial",
-                                                interactive=True)
-                
-                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)
-
-                
-                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)
-                translate_prompts = gr.Checkbox(label='Translate Prompts',
-                                                          info='Uses the internet to translate prompts to English.',
-                                                          value=False)
-                seed_random = gr.Checkbox(label='Randomize seed', 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()}" target="_blank">\U0001F4DA History Log</a>')
-
-                history_link = gr.HTML()
-                shared.gradio_root.load(update_history_link, outputs=history_link, queue=False, show_progress=False)
-
-            with gr.Tab(label='Styles'):
-                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, (n, v) in enumerate(modules.config.default_loras):
-                        with gr.Row():
-                            lora_model = gr.Dropdown(label=f'LoRA {i + 1}',
-                                                     choices=['None'] + modules.config.lora_filenames, value=n)
-                            lora_weight = gr.Slider(label='Weight', minimum=-2, maximum=2, step=0.01, value=v,
-                                                    elem_classes='lora_weight')
-                            lora_ctrls += [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>')
-                output_format = gr.Radio(label='Output Format',
-                                            choices=modules.flags.output_formats,
-                                            value=modules.config.default_output_format)
-
-                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=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=modules.config.default_performance == 'Extreme Speed',
-                                                      interactive=modules.config.default_performance != 'Extreme Speed',
-                                                      info='Disable intermediate results during generation, only show final gallery.')
-
-                        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_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 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)] * 2,
-                                                            inputs=inpaint_mask_upload_checkbox,
-                                                            outputs=[inpaint_mask_image, inpaint_mask_generation_col],
-                                                            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()
-                    modules.config.update_presets()
-                    results = []
-                    results += [gr.update(choices=modules.config.model_filenames),
-                                gr.update(choices=['None'] + modules.config.model_filenames)]
-                    if not args_manager.args.disable_preset_selection:
-                        results += [gr.update(choices=modules.config.available_presets)]
-                    for i in range(flags.lora_count):
-                        results += [gr.update(choices=['None'] + modules.config.lora_filenames), gr.update()]
-                    return results
-
-                model_refresh_output = [base_model, refiner_model]
-                if not args_manager.args.disable_preset_selection:
-                    model_refresh_output += [preset_selection]
-                model_refresh.click(model_refresh_clicked, [],  model_refresh_output + lora_ctrls,
-                                    queue=False, show_progress=False)
-
-            with gr.Tab(label='Audio'):
-                play_notification = gr.Checkbox(label='Play notification after rendering', value=False)
-                notification_file = 'notification.mp3'
-                if os.path.exists(notification_file):
-                    notification = gr.State(value=notification_file)
-                    notification_input = gr.Audio(label='Notification', interactive=True, elem_id='audio_notification', visible=False, show_edit_button=False)
-
-                    def play_notification_checked(r, notification):
-                        return gr.update(visible=r, value=notification if r else None)
-
-                    def notification_input_changed(notification_input, notification):
-                        if notification_input:
-                            notification = notification_input
-                        return notification
-
-                    play_notification.change(fn=play_notification_checked, inputs=[play_notification, notification], outputs=[notification_input], queue=False)
-                    notification_input.change(fn=notification_input_changed, inputs=[notification_input, notification], outputs=[notification], queue=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, base_model,
-                             refiner_model, refiner_switch, sampler_name, scheduler_name, seed_random, image_seed,
-                             generate_button, load_parameter_button] + freeu_ctrls + lora_ctrls
-
-        if not args_manager.args.disable_preset_selection:
-            def preset_selection_change(preset, is_generating):
-                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', {})
-
-                preset_prepared['base_model'], preset_prepared['lora_downloads'] = launch.download_models(
-                    default_model, previous_default_models, checkpoint_downloads, embeddings_downloads, lora_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)
-
-            preset_selection.change(preset_selection_change, inputs=[preset_selection, state_is_generating], 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();}')
-
-
-        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)
+def generate_clicked(clothing_image, person_image, performance_selection, preset_selection, style_selections, segmentation_mask):
+    pass
+
+def generate_segmentation_mask(image):
+    seg_image, mask_image = segment_body(image, face=False)
+    mask_image = mask_image.resize((512, 512))
+    return mask_image
+
+title = "FashionCore"
+description = "Try on different clothes and accessories on your images."
+
+with gr.Blocks(title=title, css=config.css) as demo:
+    gr.Markdown(description)
+    
+    with gr.Tab("Free Version"):
+        with gr.Row():
+            with gr.Column():
+                clothing_image = gr.Image(label="Clothing Image", source="upload", type="numpy")
+                person_image = gr.Image(label="Person Image", source="upload", type="numpy", tool="sketch", elem_id="person_image")
+                segmentation_mask = gr.Image(label="Segmentation Mask", visible=False)
+                with gr.Accordion("Settings", open=False):
+                    performance_selection = gr.Radio(label="Performance", choices=flags.performance_selections, value="Quality")
+                    preset_selection = gr.Radio(label="Preset", choices=["Realistic"], value="Realistic")
+                    style_selections = gr.CheckboxGroup(label="Styles", choices=[
+                        "Fooocus V2",
+                        "Fooocus Photograph",
+                        "Fooocus Negative",
+                        "Fooocus Masterpiece",
+                        "Fooocus Enhance",
+                        "Fooocus Sharp",
+                        "Fooocus Cinematic",
+                        "SAI Analog Film"
+                    ], value=[
+                        "Fooocus V2",
+                        "Fooocus Photograph",
+                        "Fooocus Negative",
+                        "Fooocus Masterpiece", 
+                        "Fooocus Enhance",
+                        "Fooocus Sharp",
+                        "Fooocus Cinematic",
+                        "SAI Analog Film"
+                    ])
+                with gr.Accordion("Advanced Settings", open=False):
+                    auto_mask_checkbox = gr.Checkbox(label="Use Auto Mask", value=True)
+                    debug_mode_checkbox = gr.Checkbox(label="Debug Mode", value=False)
+            
+            with gr.Column():
+                generated_image = gr.Image(label="Generated Image", visible=False)
+                generate_button = gr.Button("Generate")
         
-        output_format.input(lambda x: gr.update(output_format=x), inputs=output_format)
+        def generate_mask_clicked(person_image):
+            if auto_mask_checkbox.value and debug_mode_checkbox.value:
+                return generate_segmentation_mask(person_image)
+            return None
         
-        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, translate_prompts, 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, black_out_nsfw]
-        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]
+        person_image.change(fn=generate_mask_clicked, inputs=person_image, outputs=segmentation_mask)
+        generate_button.click(fn=generate_clicked, inputs=[clothing_image, person_image, performance_selection, preset_selection, style_selections, segmentation_mask], outputs=generated_image)
+    
+    with gr.Tab("Paid Version"):
+        gr.Markdown("Upgrade to the paid version to access advanced features and models.")
         
-        ctrls += ip_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], 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')
-
-        def trigger_describe(mode, img):
-            if mode == flags.desc_type_photo:
-                from extras.interrogate import default_interrogator as default_interrogator_photo
-                return default_interrogator_photo(img), ["Fooocus V2", "Fooocus Enhance", "Fooocus Sharp"]
-            if mode == flags.desc_type_anime:
-                from extras.wd14tagger import default_interrogator as default_interrogator_anime
-                return default_interrogator_anime(img), ["Fooocus V2", "Fooocus Masterpiece"]
-            return mode, ["Fooocus V2"]
-
-        desc_btn.click(trigger_describe, inputs=[desc_method, desc_input_image],
-                       outputs=[prompt, style_selections], show_progress=True, queue=True)
-
-        def trigger_uov_describe(mode, img, prompt):
-            # keep prompt if not empty
-            if prompt == '':
-                return trigger_describe(mode, img)
-            return gr.update(), gr.update()
-
-        uov_input_image.upload(trigger_uov_describe, inputs=[desc_method, uov_input_image, prompt],
-                       outputs=[prompt, style_selections], show_progress=True, queue=True)
-
-def dump_default_english_config():
-    from modules.localization import dump_english_config
-    dump_english_config(grh.all_components)
-
-
-# dump_default_english_config()
-
-shared.gradio_root.launch(
-    inbrowser=args_manager.args.in_browser,
-    server_name=args_manager.args.listen,
-    server_port=args_manager.args.port,
-    share=args_manager.args.share,
-    favicon_path="assets/favicon.png",
-    auth=check_auth if (args_manager.args.share or args_manager.args.listen) and auth_enabled else None,
-    blocked_paths=[constants.AUTH_FILENAME]
-)
+        with gr.Accordion("Advanced Features", open=False):
+            gr.Markdown("- Photopea integration for advanced editing")
+            gr.Markdown("- Additional advanced models and presets")
+            gr.Markdown("- Enhanced user interface and experience")
+    
+    with gr.Tab("Remove Background"):
+        with gr.Row():
+            rembg_input = grh.Image(label="Input Image", source="upload", type="filepath")
+            rembg_button = gr.Button("Remove Background")
+        with gr.Row():
+            rembg_output = grh.Image(label="Output Image")
+        rembg_button.click(rembg_run, inputs=rembg_input, outputs=rembg_output)
+    
+    with gr.Tab("Segmentation Mask"):
+        with gr.Row():
+            segmentation_input = gr.Image(label="Input Image", source="upload", type="pil")
+            segmentation_button = gr.Button("Generate Mask")
+        with gr.Row():
+            segmentation_output = gr.Image(label="Segmentation Mask")
+        segmentation_button.click(generate_segmentation_mask, inputs=segmentation_input, outputs=segmentation_output)
+
+demo.launch(inbrowser=args_manager.args.in_browser,
+            server_name=args_manager.args.listen,
+            server_port=args_manager.args.port,
+            share=args_manager.args.share,
+            favicon_path="assets/favicon.png",
+            auth=None,
+            blocked_paths=[constants.AUTH_FILENAME])
\ No newline at end of file