A native macOS application for real-time face swapping using deep learning technology.

• macOS 10.15 (Catalina) or later
• Python 3.10
• Apple Silicon (M1/M2) or Intel processor
• Minimum 8GB RAM
• 2GB free disk space
• Webcam access

1. Download the latest .dmg file from the Releases page
2. Open the .dmg file
3. Drag the Face Swap app to your Applications folder
4. Right-click the app and select "Open" for first launch (required for Gatekeeper)

# Create virtual environment
python -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

Required packages (see requirements.txt for specific versions):

• opencv-python
• numpy
• torch
• torchvision
• PyQt6
• dlib
• mediapipe

1. Install development dependencies:

pip install pyinstaller create-dmg

2. Build the .app bundle:

pyinstaller --windowed --name "Face Swap" --icon assets/icon.icns main.py

3. Create the .dmg installer:

create-dmg \
  --volname "Face Swap" \
  --window-pos 200 120 \
  --window-size 800 400 \
  --icon-size 100 \
  --icon "Face Swap.app" 200 190 \
  --hide-extension "Face Swap.app" \
  --app-drop-link 600 185 \
  "Face Swap.dmg" \
  "dist/Face Swap.app"

mac-face-swap/
├── src/
│   ├── main.py           # Application entry point
│   ├── face_swap/        # Core face swapping logic
│   ├── gui/             # PyQt6 GUI components
│   └── utils/           # Helper functions
├── assets/              # Icons and resources
├── tests/              # Unit and integration tests
└── scripts/            # Build and packaging scripts

pytest tests/

1. App won't open: Ensure you right-click and select "Open" for first launch
2. Camera access denied: Grant camera permissions in System Preferences > Security & Privacy
3. Performance issues: Check minimum system requirements and close resource-intensive applications

Please report issues on the GitHub Issues page with:

• macOS version
• Hardware specifications
• Steps to reproduce
• Error messages or screenshots

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

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

• MediaPipe for face detection
• PyTorch for deep learning framework
• OpenCV for image processing

• App is signed and notarized with Apple Developer certificate
• No data collection or network access required
• All processing done locally on device