Create App.py

App.py

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+import os
+import sys
+import subprocess
+import importlib
+import warnings
+from pathlib import Path
+
+# Suppress warnings
+warnings.filterwarnings("ignore")
+
+# Set environment variables
+os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
+os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
+os.environ["PYTHONWARNINGS"] = "ignore"
+
+# Monkey patch HfFolder before any imports
+class MockHfFolder:
+    @staticmethod
+    def get_token():
+        return os.environ.get("HF_TOKEN", "")
+    @staticmethod
+    def save_token(token):
+        os.environ["HF_TOKEN"] = token
+
+# Patch it into sys.modules BEFORE importing anything
+sys.modules['huggingface_hub'] = type(sys)('huggingface_hub')
+sys.modules['huggingface_hub'].HfFolder = MockHfFolder
+
+print("Starting Advanced Live Portrait setup...")
+
+# Change to /tmp for workspace
+workspace = Path("/tmp/AdvancedLivePortrait")
+workspace.mkdir(exist_ok=True)
+os.chdir(workspace)
+
+# Clone repository if not exists
+if not (workspace / ".git").exists():
+    print("Cloning repository...")
+    subprocess.run(["git", "clone", "https://github.com/Ayeeee45/AdvancedLivePortrait-WebUI.git", "."], 
+                   check=True, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+else:
+    print("Repository already exists, pulling updates...")
+    subprocess.run(["git", "pull"], check=True, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+
+print("Installing dependencies...")
+
+# Install base dependencies first
+base_packages = [
+    "gradio==3.41.1",
+    "huggingface-hub==0.19.4",
+    "numpy==1.24.4",
+    "pillow==10.1.0",
+    "opencv-python-headless==4.8.1.78",
+    "ffmpeg-python==0.2.0",
+    "moviepy==1.0.3",
+    "tqdm==4.66.1",
+]
+
+for package in base_packages:
+    subprocess.run([sys.executable, "-m", "pip", "install", "-q", package], 
+                   check=False)
+
+# Check for CUDA and install appropriate torch
+try:
+    import torch
+    print(f"Torch already installed: {torch.__version__}")
+    if torch.cuda.is_available():
+        print(f"CUDA available: {torch.version.cuda}")
+except:
+    print("Installing PyTorch...")
+    subprocess.run([sys.executable, "-m", "pip", "install", "-q",
+                   "torch==2.1.0", "torchvision==0.16.0", "torchaudio==2.1.0",
+                   "--index-url", "https://download.pytorch.org/whl/cu118"], 
+                   check=False)
+
+# Install from requirements.txt if exists
+if os.path.exists("requirements.txt"):
+    print("Installing from requirements.txt...")
+    subprocess.run([sys.executable, "-m", "pip", "install", "-q", "-r", "requirements.txt"], 
+                   check=False)
+
+# Install additional commonly needed packages
+additional_packages = [
+    "scipy==1.11.4",
+    "scikit-image==0.22.0",
+    "pyyaml==6.0.1",
+    "insightface==0.7.3",
+    "gfpgan==1.3.8",
+    "realesrgan==0.3.0",
+    "basicsr==1.4.2",
+    "facexlib==0.3.0",
+    "einops==0.7.0",
+]
+
+for package in additional_packages:
+    subprocess.run([sys.executable, "-m", "pip", "install", "-q", package], 
+                   check=False)
+
+print("Setup complete!")
+
+# Now create the interface
+import gradio as gr
+import cv2
+import numpy as np
+from PIL import Image
+import tempfile
+import time
+
+def create_demo_interface():
+    """Create a demo interface for the Space"""
+    
+    def process_demo(image, audio=None):
+        """Demo processing function"""
+        if image is None:
+            return None, "Please upload an image"
+        
+        # Convert to numpy
+        img_array = np.array(image)
+        
+        # Create a simple "processing" effect (just flip image for demo)
+        processed = cv2.flip(img_array, 1)
+        
+        # Save as video placeholder
+        height, width = processed.shape[:2]
+        fps = 30
+        seconds = 3
+        
+        # Create temp video file
+        temp_video = tempfile.NamedTemporaryFile(suffix='.mp4', delete=False).name
+        
+        # Create video writer
+        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+        out = cv2.VideoWriter(temp_video, fourcc, fps, (width, height))
+        
+        # Write frames
+        for i in range(fps * seconds):
+            # Create slight variation for each frame
+            frame = processed.copy()
+            if i % 10 == 0:
+                frame = cv2.flip(frame, 0)
+            out.write(cv2.cvtColor(frame, cv2.COLOR_RGB2BGR))
+        
+        out.release()
+        
+        return temp_video, "Demo complete! For full functionality, run locally."
+    
+    # Create interface
+    with gr.Blocks(title="Advanced Live Portrait", theme=gr.themes.Soft()) as demo:
+        gr.Markdown("""
+        # 🎬 Advanced Live Portrait WebUI
+        
+        **Create animated portraits from images and audio**
+        
+        *Note: This is a demo version. Full functionality requires local installation due to model size constraints.*
+        """)
+        
+        with gr.Row():
+            with gr.Column(scale=1):
+                gr.Markdown("### 📤 Input")
+                image_input = gr.Image(
+                    label="Source Face Image",
+                    type="pil",
+                    height=300
+                )
+                audio_input = gr.Audio(
+                    label="Driving Audio (Optional)",
+                    type="filepath",
+                    visible=False  # Hide for demo
+                )
+                
+                with gr.Row():
+                    generate_btn = gr.Button("🚀 Generate Demo", variant="primary")
+                    clear_btn = gr.Button("🗑️ Clear")
+                
+                gr.Markdown("""
+                ### 💡 Tips for Best Results:
+                - Use clear frontal face photos
+                - Good lighting works best
+                - Neutral expression recommended
+                """)
+            
+            with gr.Column(scale=2):
+                gr.Markdown("### 📤 Output")
+                output_video = gr.Video(
+                    label="Animated Result",
+                    height=400
+                )
+                status = gr.Textbox(
+                    label="Status",
+                    value="Ready to generate demo...",
+                    interactive=False
+                )
+                
+                gr.Markdown("""
+                ### 📚 Full Installation Instructions:
+                ```bash
+                # 1. Clone repository
+                git clone https://github.com/Ayeeee45/AdvancedLivePortrait-WebUI.git
+                cd AdvancedLivePortrait-WebUI
+                
+                # 2. Install dependencies
+                pip install -r requirements.txt
+                
+                # 3. Download models (see GitHub for links)
+                # 4. Run the application
+                python webui.py
+                ```
+                """)
+        
+        # Button actions
+        generate_btn.click(
+            fn=process_demo,
+            inputs=[image_input],
+            outputs=[output_video, status]
+        )
+        
+        clear_btn.click(
+            fn=lambda: [None, None, "Cleared"],
+            outputs=[image_input, output_video, status]
+        )
+        
+        # Example images
+        gr.Markdown("### 📸 Example Images")
+        gr.Examples(
+            examples=[
+                ["https://images.unsplash.com/photo-1494790108755-2616b786d4b9?w=300&h=300&fit=crop"],
+                ["https://images.unsplash.com/photo-1534528741775-53994a69daeb?w=300&h=300&fit=crop"],
+                ["https://images.unsplash.com/photo-1507003211169-0a1dd7228f2d?w=300&h=300&fit=crop"],
+            ],
+            inputs=[image_input],
+            outputs=[output_video, status],
+            fn=process_demo,
+            cache_examples=True
+        )
+    
+    return demo
+
+# Launch the interface
+if __name__ == "__main__":
+    print("Launching Gradio interface...")
+    demo = create_demo_interface()
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False,
+        debug=False
+    )