Face-to-3D: AI-Powered Face Generation & 3D Modeling

This application transforms 2D face images into realistic 3D face models using advanced AI techniques. It provides a user-friendly web interface for creating, viewing, and downloading 3D face models.

Features

• Generate realistic face images using AI
• High-resolution image upscaling
• Automatic 3D face model generation
• Interactive 3D model viewer in browser
• Download 3D models in OBJ format with textures
• Global access option via ngrok

System Requirements

• Python 3.8 or higher
• Node.js 14+ and npm
• Windows OS (tested on Windows 10/11)
• CUDA-capable GPU recommended (but CPU mode is supported)
• At least 8GB RAM
• 2GB free disk space

Project Setup

1. Clone and Setup Environment

# Clone the repository
git clone <repository-url>
cd <repository-name>

# Create and activate a virtual environment (recommended)
python -m venv venv
.\venv\Scripts\activate

# Install Python dependencies
pip install -r requirements.txt

# Install frontend dependencies
cd frontend
npm install
cd ..

2. Environment Configuration

Create a .env file in the root directory with the following variables:

FLASK_ENV=development
FLASK_APP=app.py
PORT=5000

Running the Application

Development Mode

1. Start the Backend Server:

# From the root directory
python app.py

2. Start the Frontend Development Server:

# In a new terminal
cd frontend
npm run dev

3. Access the Application:

• Backend API: http://localhost:5000
• Frontend development server: http://localhost:5173

Production Mode

For a production deployment with backend and frontend served together:

# From the root directory
powershell -File deploy.ps1

The application will be available at http://localhost:5000

Global Access with ngrok (Optional)

To make your local application accessible globally:

1. Install and Configure ngrok:

   • Sign up at ngrok.com
   • Get your authtoken
   • Configure ngrok:

     ./frontend/ngrok.exe config add-authtoken YOUR_AUTHTOKEN

2. Deploy Globally:

   # Option 1: Deploy everything at once
   powershell -File deploy-global.ps1
   
   # Option 2: If server is already running
   powershell -File start-ngrok.ps1

Project Structure

├── app.py              # Main Flask application
├── api.py             # API endpoints
├── frontend/          # React frontend application
├── requirements.txt   # Python dependencies
├── .env              # Environment variables
└── deploy scripts    # Various deployment scripts

Troubleshooting

Common Issues and Solutions

1. Port Already in Use

   # Check what's using port 5000
   netstat -ano | findstr :5000
   # Kill the process if needed (replace PID with actual process ID)
   taskkill /PID <PID> /F

2. CUDA/GPU Issues

   • Ensure you have compatible NVIDIA drivers installed
   • The application will fallback to CPU mode if CUDA is unavailable

3. Memory Issues

   • Close other memory-intensive applications
   • Ensure you have at least 8GB of RAM available

4. Permission Issues

   • Run as administrator using run_as_admin.bat
   • Check file permissions in the project directory

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Built with Flask and React
• Uses advanced AI techniques for face generation and 3D modeling
• Powered by PyTorch for deep learning operations