import random import gradio as gr from config import Config from .events import * def image_tab(): with gr.Row(): with gr.Column(): with gr.Group(): model = gr.Dropdown(label='Model', choices=[model['repo_id'] for model in Config.IMAGES_MODELS], value=Config.IMAGES_MODELS[0]['repo_id'], interactive=True) prompt = gr.Textbox(lines=5, label='Prompt', placeholder='Enter your prompt here...', value='A beautiful sunset over the mountains.') negative_prompt = gr.Textbox(lines=2, label='Negative Prompt', placeholder='Enter your negative prompt here...', visible=False) fast_generation = gr.Checkbox(label='Fast Generation (Hyper-SD 🧪)', value=False) with gr.Accordion('Loras', open=True): for m in Config.IMAGES_MODELS: if m['repo_id'] == model.value: lora_gallery_values = [] if m['loader'] == 'flux': lora_gallery_values = [(lora['image'], lora['title']) for lora in Config.IMAGES_LORAS_FLUX] elif m['loader'] == 'sdxl': lora_gallery_values = [(lora['image'], lora['title']) for lora in Config.IMAGES_LORAS_SDXL] lora_gallery = gr.Gallery( label='Loras', value=lora_gallery_values, allow_preview=False, interactive=True, rows=2, columns=3, ) with gr.Group(): with gr.Column(): with gr.Row(): custom_lora = gr.Textbox(label='Custom Lora', info='Enter a Huggingface repo path') selected_lora = gr.Textbox(label="Selected Lora", info="Choose from the gallery or enter a custom LoRA") custom_lora_info = gr.HTML(visible=False) add_lora = gr.Button(value="Add LoRA") enabled_loras = gr.State(value=[]) with gr.Group(): with gr.Row(): for i in range(6): # only support max 6 loras due to inference time with gr.Column(): with gr.Column(scale=2): globals()[f"lora_slider_{i}"] = gr.Slider(label=f"LoRA {i+1}", minimum=0, maximum=1, step=0.01, value=0.8, visible=False, interactive=True) with gr.Column(): globals()[f"lora_remove_{i}"] = gr.Button(value="Remove LoRA", visible=False) with gr.Accordion("Embeddings", open=False, visible=False) as embeddings_accordion: with gr.Group(): with gr.Row(): with gr.Group(): custom_embedding = gr.Textbox(label="Custom Embedding", info="Enter a Huggingface repo path") add_embedding = gr.Button(value="Add Embedding") custom_embedding_info = gr.HTML(visible=False) with gr.Row(): enabled_embeddings = gr.State(value=[]) enabled_embeddings_list = gr.Checkboxgroup(label="Enabled Embeddings", choices=[], visible=False) with gr.Accordion('Image Options', open=False): with gr.Tabs(): image_options = [ ('img2img', 'Image to Image', 'image', True), ('inpaint', 'Inpainting', 'imageeditor', True), ('canny', 'Edge Detection', 'image', True), ('pose', 'Pose Detection', 'image', True), ('depth', 'Depth Estimation', 'image', True), ('scribble', 'Scribble', 'imageeditor', False), ] for image_option, label, type, visible in image_options: with gr.Tab(label=image_option) as globals()[f"{image_option}_tab"]: if type == 'image': globals()[f"{image_option}_image"] = gr.Image(label=label, visible=visible, interactive=True, type='pil') elif type == 'imageeditor': globals()[f"{image_option}_image"] = gr.ImageEditor(label=label, visible=visible, interactive=True, brush=gr.Brush(colors=["#FFFFFF"], color_mode="fixed") if image_option == 'inpaint' else gr.Brush(), type='pil', image_mode='RGB', layers=False) globals()[f"{image_option}_strength"] = gr.Slider(label="Strength", minimum=0, maximum=1, step=0.01, value=1.0, interactive=True) resize_mode = gr.Radio( label="Resize Mode", choices=["crop and resize", "resize only", "resize and fill"], value="resize and fill", interactive=True ) with gr.Column(): with gr.Group(): output_images = gr.Gallery(label='Output Image', type='pil', interactive=False, value=[], allow_preview=True) generate = gr.Button(value="Generate", variant="primary") with gr.Accordion('Advance Settings', open=True): scheduler = gr.Dropdown( label='Scheduler', choices = [ "dpmpp_2m", "dpmpp_2m_k", "dpmpp_2m_sde", "dpmpp_2m_sde_k", "dpmpp_sde", "dpmpp_sde_k", "dpm2", "dpm2_k", "dpm2_a", "dpm2_a_k", "euler", "euler_a", "heun", "lms", "lms_k", "deis", "unipc", "fm_euler" ], value="fm_euler", interactive=True ) with gr.Row(): for column in range(2): with gr.Column(): options = [ ("Height", "image_height", 64, 2048, 64, 1024, True), ("Width", "image_width", 64, 2048, 64, 1024, True), ("Num Images Per Prompt", "image_num_images_per_prompt", 1, 4, 1, 1, True), ("Num Inference Steps", "image_num_inference_steps", 1, 100, 1, 20, True), ("Clip Skip", "image_clip_skip", 0, 2, 1, 2, False), ("Guidance Scale", "image_guidance_scale", 0, 20, 0.5, 3.5, True), ("Seed", "image_seed", 0, 100000, 1, random.randint(0, 100000), True), ] for label, var_name, min_val, max_val, step, value, visible in options[column::2]: globals()[var_name] = gr.Slider(label=label, minimum=min_val, maximum=max_val, step=step, value=value, visible=visible, interactive=True) with gr.Row(): refiner = gr.Checkbox(label="Refiner", value=False) vae = gr.Checkbox(label="VAE", value=True) # Events # Base Options model.change(update_model_options, [model], [negative_prompt, lora_gallery, embeddings_accordion, scribble_tab, scheduler, image_clip_skip, image_guidance_scale]) # type: ignore fast_generation.change(update_fast_generation, [model, fast_generation], [image_num_inference_steps, image_guidance_scale]) # type: ignore # Loras lora_gallery.select(selected_lora_from_gallery, None, selected_lora) custom_lora.change(update_selected_lora, custom_lora, [selected_lora, custom_lora_info]) add_lora.click(add_to_enabled_loras, [model, selected_lora, enabled_loras], [selected_lora, custom_lora_info, enabled_loras]) enabled_loras.change(update_lora_sliders, enabled_loras, [lora_slider_0, lora_slider_1, lora_slider_2, lora_slider_3, lora_slider_4, lora_slider_5, lora_remove_0, lora_remove_1, lora_remove_2, lora_remove_3, lora_remove_4, lora_remove_5]) # type: ignore for i in range(6): globals()[f"lora_remove_{i}"].click( lambda enabled_loras, index=i: remove_from_enabled_loras(enabled_loras, index), [enabled_loras], [enabled_loras] ) # Embeddings custom_embedding.change(update_custom_embedding, custom_embedding, [custom_embedding_info]) add_embedding.click(add_to_embeddings, [custom_embedding, enabled_embeddings], [custom_embedding, custom_embedding_info, enabled_embeddings]) enabled_embeddings.change(update_enabled_embeddings_list, enabled_embeddings, [enabled_embeddings_list]) # type: ignore enabled_embeddings_list.change(update_enabled_embeddings, enabled_embeddings_list, [enabled_embeddings]) # type: ignore # Generate Image generate.click( generate_image, # type: ignore [ model, prompt, negative_prompt, fast_generation, enabled_loras, enabled_embeddings, lora_slider_0, lora_slider_1, lora_slider_2, lora_slider_3, lora_slider_4, lora_slider_5, # type: ignore img2img_image, inpaint_image, canny_image, pose_image, depth_image, scribble_image, # type: ignore img2img_strength, inpaint_strength, canny_strength, pose_strength, depth_strength, scribble_strength, # type: ignore resize_mode, scheduler, image_height, image_width, image_num_images_per_prompt, # type: ignore image_num_inference_steps, image_clip_skip, image_guidance_scale, image_seed, # type: ignore refiner, vae ], [output_images] )