App.py

#!/usr/bin/env python3
"""
Advanced Live Portrait Demo
Simplified version for Hugging Face Spaces
"""

import os
os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"

# IMPORTANT: Force early import of huggingface_hub with our patch
import sys

# Create mock HfFolder class BEFORE anything imports huggingface_hub
class MockHfFolder:
    @staticmethod
    def get_token():
        return os.environ.get("HF_TOKEN", "")
    @staticmethod
    def save_token(token):
        os.environ["HF_TOKEN"] = token

# Monkey patch at module level
import types
hf_hub_module = types.ModuleType('huggingface_hub')
hf_hub_module.HfFolder = MockHfFolder
hf_hub_module.whoami = lambda: {"name": "demo_user"}
sys.modules['huggingface_hub'] = hf_hub_module

# Now import gradio - it will use our patched module
import gradio as gr
import numpy as np
from PIL import Image
import tempfile
import cv2

def create_demo_video(image):
    """Create a simple demo video from image"""
    if image is None:
        return None, "Please upload an image first"
    
    try:
        # Convert to numpy array
        img_array = np.array(image)
        
        # Create output video path
        output_path = tempfile.NamedTemporaryFile(suffix='.mp4', delete=False).name
        
        # Video parameters
        height, width = img_array.shape[:2]
        fps = 24
        duration = 2  # seconds
        
        # Initialize video writer
        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
        video_writer = cv2.VideoWriter(output_path, fourcc, fps, (width, height))
        
        # Create frames with simple animation
        for i in range(fps * duration):
            frame = img_array.copy()
            
            # Simple animation effect
            if i < fps:
                # Fade in
                alpha = i / fps
                frame = (frame * alpha).astype(np.uint8)
            elif i > fps:
                # Slight zoom
                scale = 1 + (i - fps) * 0.001
                new_h, new_w = int(height * scale), int(width * scale)
                if new_h > 0 and new_w > 0:
                    frame = cv2.resize(frame, (new_w, new_h))
                    # Crop to original size
                    y_start = (new_h - height) // 2
                    x_start = (new_w - width) // 2
                    frame = frame[y_start:y_start+height, x_start:x_start+width]
            
            # Convert back to BGR for OpenCV
            frame_bgr = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
            video_writer.write(frame_bgr)
        
        video_writer.release()
        
        return output_path, "✅ Demo video created successfully!"
    
    except Exception as e:
        return None, f"❌ Error: {str(e)}"

# Create the interface
with gr.Blocks(title="Advanced Live Portrait Demo", theme=gr.themes.Soft()) as demo:
    gr.Markdown("""
    # 🎬 Advanced Live Portrait - Demo
    *A preview of the portrait animation tool*
    """)
    
    with gr.Row():
        with gr.Column():
            image_input = gr.Image(
                label="Upload a face image",
                type="pil",
                height=300
            )
            
            generate_btn = gr.Button(
                "Generate Demo Animation",
                variant="primary",
                size="lg"
            )
        
        with gr.Column():
            output_video = gr.Video(
                label="Generated Animation",
                height=300
            )
            
            status_text = gr.Textbox(
                label="Status",
                value="Ready to generate...",
                interactive=False
            )
    
    # Connect button
    generate_btn.click(
        fn=create_demo_video,
        inputs=[image_input],
        outputs=[output_video, status_text]
    )
    
    # Add examples
    gr.Examples(
        examples=[
            ["https://images.unsplash.com/photo-1494790108755-2616b786d4b9?w=512&h=512&fit=crop"],
            ["https://images.unsplash.com/photo-1534528741775-53994a69daeb?w=512&h=512&fit=crop"],
            ["https://images.unsplash.com/photo-1507003211169-0a1dd7228f2d?w=512&h=512&fit=crop"],
        ],
        inputs=[image_input],
        outputs=[output_video, status_text],
        fn=create_demo_video,
        cache_examples=True,
        label="Try these examples:"
    )
    
    # Add info section
    with gr.Accordion("ℹ️ About this demo", open=False):
        gr.Markdown("""
        This is a **lightweight demo** of the Advanced Live Portrait tool.
        
        ### For the full version:
        1. **Clone locally:**
        ```bash
        git clone https://github.com/Ayeeee45/AdvancedLivePortrait-WebUI.git
        cd AdvancedLivePortrait-WebUI
        ```
        
        2. **Install dependencies:**
        ```bash
        pip install -r requirements.txt
        ```
        
        3. **Download models** (from the repository links)
        
        4. **Run:**
        ```bash
        python webui.py
        ```
        
        ### Requirements for full version:
        - 8GB+ VRAM GPU
        - 20GB+ disk space
        - Python 3.10
        """)

# Launch the app
if __name__ == "__main__":
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=False,
        debug=False
    )