Create App.py

App.py

@@ -0,0 +1,180 @@
+#!/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
+    )