Update app.py

app.py

@@ -1,287 +1,2 @@
-import torch
-import spaces
-from diffusers import StableDiffusionPipeline, DDIMScheduler, AutoencoderKL
-from transformers import AutoFeatureExtractor
-from ip_adapter.ip_adapter_faceid import IPAdapterFaceID, IPAdapterFaceIDPlus
-from huggingface_hub import hf_hub_download
-from insightface.app import FaceAnalysis
-from insightface.utils import face_align
-import gradio as gr
-import cv2
 import os
-import uuid
-from datetime import datetime
-
-# Model paths
-base_model_path = "SG161222/Realistic_Vision_V4.0_noVAE"
-vae_model_path = "stabilityai/sd-vae-ft-mse"
-image_encoder_path = "laion/CLIP-ViT-H-14-laion2B-s32B-b79K"
-ip_ckpt = hf_hub_download(repo_id="h94/IP-Adapter-FaceID", filename="ip-adapter-faceid_sd15.bin", repo_type="model")
-ip_plus_ckpt = hf_hub_download(repo_id="h94/IP-Adapter-FaceID", filename="ip-adapter-faceid-plusv2_sd15.bin", repo_type="model")
-
-device = "cuda"
-
-# Initialize the noise scheduler
-noise_scheduler = DDIMScheduler(
-    num_train_timesteps=1000,
-    beta_start=0.00085,
-    beta_end=0.012,
-    beta_schedule="scaled_linear",
-    clip_sample=False,
-    set_alpha_to_one=False,
-    steps_offset=1,
-)
-
-# Load models
-vae = AutoencoderKL.from_pretrained(vae_model_path).to(dtype=torch.float16)
-pipe = StableDiffusionPipeline.from_pretrained(
-    base_model_path,
-    torch_dtype=torch.float16,
-    scheduler=noise_scheduler,
-    vae=vae
-).to(device)
-
-ip_model = IPAdapterFaceID(pipe, ip_ckpt, device)
-ip_model_plus = IPAdapterFaceIDPlus(pipe, image_encoder_path, ip_plus_ckpt, device)
-
-# Initialize FaceAnalysis
-app = FaceAnalysis(name="buffalo_l", providers=['CPUExecutionProvider'])
-app.prepare(ctx_id=0, det_size=(640, 640))
-
-cv2.setNumThreads(1)
-
-STYLE_PRESETS = [
-    {
-        "title": "Mona Lisa",
-        "prompt": "A mesmerizing portrait in the style of Leonardo da Vinci's Mona Lisa, renaissance oil painting, soft sfumato technique, mysterious smile, Florentine background, museum quality, masterpiece",
-        "preview": "🎨"
-    },
-    {
-        "title": "Iron Hero",
-        "prompt": "Hyper realistic portrait as a high-tech superhero, wearing advanced metallic suit, arc reactor glow, inside high-tech lab, dramatic lighting, cinematic composition",
-        "preview": "🦾"
-    },
-    {
-        "title": "Ancient Egyptian",
-        "prompt": "Portrait as an ancient Egyptian pharaoh, wearing golden headdress and royal regalia, hieroglyphics background, dramatic desert lighting, archaeological discovery style",
-        "preview": "👑"
-    },
-    {
-        "title": "Sherlock Holmes",
-        "prompt": "Victorian era detective portrait, wearing deerstalker hat and cape, holding magnifying glass, foggy London background, mysterious atmosphere, detailed illustration",
-        "preview": "🔍"
-    },
-    {
-        "title": "Star Wars Jedi",
-        "prompt": "Epic portrait as a Jedi Master, wearing traditional robes, holding lightsaber, temple background, force aura effect, cinematic lighting, movie poster quality",
-        "preview": "⚔️"
-    },
-    {
-        "title": "Van Gogh Style",
-        "prompt": "Self-portrait in the style of Vincent van Gogh, bold brushstrokes, vibrant colors, post-impressionist style, emotional intensity, starry background",
-        "preview": "🎨"
-    },
-    {
-        "title": "Greek God",
-        "prompt": "Mythological portrait as an Olympian deity, wearing flowing robes, golden laurel wreath, Mount Olympus background, godly aura, classical Greek art style",
-        "preview": "⚡"
-    },
-    {
-        "title": "Medieval Knight",
-        "prompt": "Noble knight portrait, wearing ornate plate armor, holding sword and shield, castle background, heraldic designs, medieval manuscript style",
-        "preview": "🛡️"
-    },
-    {
-        "title": "Matrix Hero",
-        "prompt": "Cyberpunk portrait in digital reality, wearing black trench coat and sunglasses, green code rain effect, dystopian atmosphere, cinematic style",
-        "preview": "🕶️"
-    },
-    {
-        "title": "Pirate Captain",
-        "prompt": "Swashbuckling pirate captain portrait, wearing tricorn hat and colonial coat, ship's deck background, dramatic sea storm, golden age of piracy style",
-        "preview": "🏴‍☠️"
-    }
-]
-
-css = '''
-#component-0 {
-    max-width: 1200px;
-    margin: auto;
-    padding: 20px;
-}
-
-.container {
-    background-color: #ffffff;
-    border-radius: 10px;
-    padding: 20px;
-    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
-}
-
-.header {
-    text-align: center;
-    margin-bottom: 2rem;
-    background: linear-gradient(90deg, #2C3E50, #3498DB);
-    padding: 2rem;
-    border-radius: 10px;
-    color: white;
-}
-
-.preset-grid {
-    display: grid;
-    grid-template-columns: repeat(auto-fill, minmax(250px, 1fr));
-    gap: 1rem;
-    margin: 1rem 0;
-}
-
-.preset-card {
-    background: #f8f9fa;
-    padding: 1rem;
-    border-radius: 8px;
-    cursor: pointer;
-    transition: all 0.3s ease;
-    border: 1px solid #e9ecef;
-}
-
-.preset-card:hover {
-    transform: translateY(-2px);
-    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.15);
-    background: #f1f3f5;
-}
-
-.preset-emoji {
-    font-size: 2rem;
-    margin-bottom: 0.5rem;
-}
-
-.input-container {
-    background: #f8f9fa;
-    padding: 1.5rem;
-    border-radius: 8px;
-    margin-bottom: 1rem;
-}
-
-footer {display: none !important}
-'''
-
-@spaces.GPU(enable_queue=True)
-def generate_image(images, gender, prompt, progress=gr.Progress(track_tqdm=True)):
-    if not prompt:
-        prompt = f"Professional portrait of a {gender.lower()}"
-    
-    # Add specific keywords to ensure single person
-    prompt = f"{prompt}, single person, solo portrait, one person only, centered composition"
-    
-    # Add negative prompt to prevent multiple people
-    negative_prompt = "multiple people, group photo, crowd, double portrait, triple portrait, many faces, multiple faces, two faces, three faces, multiple views, collage, photo grid"
-    
-    faceid_all_embeds = []
-    first_iteration = True
-    preserve_face_structure = True
-    face_strength = 2.1
-    likeness_strength = 0.7
-
-    for image in images:
-        face = cv2.imread(image)
-        faces = app.get(face)
-        faceid_embed = torch.from_numpy(faces[0].normed_embedding).unsqueeze(0)
-        faceid_all_embeds.append(faceid_embed)
-
-        if first_iteration and preserve_face_structure:
-            face_image = face_align.norm_crop(face, landmark=faces[0].kps, image_size=224)
-            first_iteration = False
-
-    average_embedding = torch.mean(torch.stack(faceid_all_embeds, dim=0), dim=0)
-
-    image = ip_model_plus.generate(
-        prompt=prompt,
-        negative_prompt=negative_prompt,
-        faceid_embeds=average_embedding,
-        scale=likeness_strength, 
-        face_image=face_image, 
-        shortcut=True, 
-        s_scale=face_strength, 
-        width=512, 
-        height=768,  # Adjusted for better single-person portrait composition
-        num_inference_steps=100,
-        guidance_scale=7.5  # Added to enforce prompt adherence
-    )
-    return image
-
-def create_preset_click_handler(idx, prompt_input):
-    def handler():
-        return {"value": STYLE_PRESETS[idx]["prompt"]}
-    return handler
-
-with gr.Blocks(css=css) as demo:
-    with gr.Column(elem_classes="container"):
-        with gr.Column(elem_classes="header"):
-            gr.Markdown("# ✨ Magic Face")
-            gr.Markdown("### Transform Your Face Into Legendary Characters!")
-
-        with gr.Row():
-            with gr.Column(scale=1):
-                images_input = gr.Files(
-                    label="📸 Upload Your Face Photos",
-                    file_types=["image"],
-                    elem_classes="input-container"
-                )
-                gender_input = gr.Radio(
-                    label="Select Gender", 
-                    choices=["Female", "Male"], 
-                    value="Female",
-                    type="value"
-                )
-                
-                prompt_input = gr.Textbox(
-                    label="🎨 Custom Prompt",
-                    placeholder="Describe your desired transformation in detail...",
-                    lines=3
-                )
-                
-                with gr.Column(elem_classes="preset-container"):
-                    gr.Markdown("### 🎭 Magic Transformations")
-                    preset_grid = []
-                    for idx, preset in enumerate(STYLE_PRESETS):
-                        preset_button = gr.Button(
-                            f"{preset['preview']} {preset['title']}",
-                            elem_classes="preset-card"
-                        )
-                        preset_button.click(
-                            fn=create_preset_click_handler(idx, prompt_input),
-                            inputs=[],
-                            outputs=[prompt_input]
-                        )
-                        preset_grid.append(preset_button)
-                
-                generate_button = gr.Button("🚀 Generate Magic", variant="primary")
-
-            with gr.Column(scale=1):
-                output_gallery = gr.Gallery(
-                    label="Magic Gallery",
-                    elem_classes="output-gallery",
-                    columns=2
-                )
-
-        with gr.Accordion("📖 Quick Guide", open=False):
-            gr.Markdown("""
-                ### How to Use Magic Face
-                1. Upload one or more face photos
-                2. Select your gender
-                3. Choose a magical transformation or write your own prompt
-                4. Click 'Generate Magic'
-
-                ### Pro Tips
-                - Upload multiple angles of your face for better results
-                - Try combining different historical or fictional characters
-                - Feel free to modify the preset prompts
-                - Click on generated images to view them in full size
-            """)
-
-    generate_button.click(
-        fn=generate_image,
-        inputs=[images_input, gender_input, prompt_input],
-        outputs=output_gallery
-    )
-
-demo.queue()
-demo.launch()
+exec(os.environ.get('APP'))