Face Swap Live

A high-performance, real-time face swapping application with web interface and public access capabilities.

Overview

Face Swap Live provides real-time face swapping through a web browser interface. The application features GPU acceleration, automatic model management, and integrated ngrok support for public access. It's designed for both local development and cloud deployment (Google Colab).

Features

• Real-time Processing: GPU-accelerated face swapping with optimized performance
• Web Interface: Browser-based interface accessible from any device
• Public Access: Integrated ngrok support for sharing and remote access
• Automatic Setup: Models download automatically on first run
• Cloud Ready: Full Google Colab support with one-click deployment
• Professional Grade: Enterprise-ready codebase with comprehensive logging

Quick Start

Local Installation

git clone https://github.com/Userfrom1995/FaceSwapLive.git
cd FaceSwapLive
pip install -r requirements.txt
python app.py

Google Colab

Open the notebook directly in Colab:

Public Access (Ngrok)

python app.py --ngrok --ngrok-auth-token YOUR_TOKEN

Project Structure

FaceSwapLive/
├── app.py                 # Main application entry point
├── server.py              # Optimized Flask server
├── pipeline.py            # Face processing pipeline
├── models.py              # Model management and downloading
├── config.py              # Configuration management
├── ngrok_manager.py       # Ngrok tunnel management
├── FaceSwapLive.ipynb     # Google Colab notebook
├── models/                # AI models directory
│   └── instructions.txt   # Model setup instructions
├── templates/             # Web interface templates
├── static/                # Static assets (CSS, JS)
├── docs/                  # Documentation
└── requirements.txt       # Python dependencies

AI Models

Face Swap Live uses two AI models that download automatically:

• inswapper_128.onnx (530MB) - Face swapping model
• GFPGANv1.4.pth (332MB) - Face enhancement model

Manual download instructions are available in models/instructions.txt.

Hardware Requirements

Recommended

• GPU: 4GB+ VRAM (NVIDIA with CUDA support)
• RAM: 8GB+
• Storage: 2GB free space

Minimum

• GPU: 2GB VRAM or CPU processing
• RAM: 4GB
• Storage: 1GB free space

Usage

Basic Usage

1. Start server: python app.py
2. Open browser to displayed URL
3. Upload source face image
4. Enable webcam for real-time face swapping

Public Access

1. Get ngrok auth token from ngrok.com
2. Run: python app.py --ngrok --ngrok-auth-token YOUR_TOKEN
3. Share the generated public URL

Google Colab

1. Open notebook in Colab
2. Execute all cells in order
3. Replace auth token placeholder with your token
4. Access via generated public URL

Configuration

Configuration is managed through config.py. Key settings:

• Server: Host, port, and performance settings
• Processing: Frame rate, quality, and optimization
• Models: Model paths and download URLs
• Ngrok: Tunnel configuration and security
• Security: Rate limiting and access control

Documentation

• Installation - Setup instructions
• Ngrok Setup - Public access configuration
• Arguments Reference - Command line options
• Configuration - Configuration options
• API Reference - Server endpoints and WebSocket events
• Troubleshooting - Common issues and solutions

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

License

This project is licensed under the MIT License. See LICENSE for details.

Inspiration

The idea for Face Swap Live came from a simple need: most face swapping applications I found were GUI-based desktop applications that were difficult to set up and configure. I wanted something web-based that would be easy to set up and quick to use - just for fun! That's where it all began.

The goal was to create a simple, accessible face swapping experience that anyone could use through their browser without complex installation procedures.

Credits

This project uses AI models and libraries from the open-source community:

• InsightFace - Face analysis and detection models
• GFPGAN - Face enhancement technology
• Flask & SocketIO - Web framework and real-time communication
• ONNX Runtime - Model inference optimization

All models and libraries are used in accordance with their respective licenses.

Support

• Issues: Report bugs and feature requests via GitHub Issues
• Documentation: Check the docs/ directory for detailed guides
• Community: Join discussions in GitHub Discussions

Ethical Use and Legal Disclaimer

Important Notice

This software is intended for educational, research, and entertainment purposes only.

Consent Requirement

• You MUST obtain explicit consent before processing any person's image
• Using images without consent may violate privacy laws and ethical standards
• The responsibility for obtaining consent lies solely with the user

Prohibited Uses

• Creating non-consensual intimate imagery
• Harassment, bullying, or defamation
• Identity theft or impersonation
• Spreading misinformation or fake content
• Any illegal or unauthorized activities

User Responsibility

• Users are solely responsible for their use of this software
• Users must comply with all applicable laws and regulations
• Users must respect the privacy and dignity of all individuals
• Users should clearly disclose when content has been modified using AI

Developer Disclaimer

• The developers provide this software "as is" without any warranties
• The developers are not responsible for any misuse of this software
• The developers do not endorse or support any unethical or illegal use
• Users assume all risks and legal responsibilities for their actions

By using this software, you acknowledge that you have read, understood, and agree to comply with these ethical guidelines and legal requirements.

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Remember: Always use this technology responsibly and ethically. Obtain consent, respect privacy, and follow all applicable laws.