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---
title: FacePoke
emoji: 💬
colorFrom: yellow
colorTo: red
sdk: docker
pinned: true
license: mit
header: mini
app_file: app.py
app_port: 8080
---
# FacePoke
## Table of Contents
- [Introduction](#introduction)
- [Acknowledgements](#acknowledgements)
- [Installation](#installation)
- [Local Setup](#local-setup)
- [Docker Deployment](#docker-deployment)
- [Development](#development)
- [Contributing](#contributing)
- [License](#license)
## Introduction
A real-time head transformation app.
For best performance please run the app from your own machine (local or in the cloud).
**Repository**: [GitHub - jbilcke-hf/FacePoke](https://github.com/jbilcke-hf/FacePoke)
You can try the demo but it is a shared space, latency may be high if there are multiple users or if you live far from the datacenter hosting the Hugging Face Space.
**Live Demo**: [FacePoke on Hugging Face Spaces](https://huggingface.co/spaces/jbilcke-hf/FacePoke)
## Acknowledgements
This project is based on LivePortrait: https://arxiv.org/abs/2407.03168
It uses the face transformation routines from https://github.com/PowerHouseMan/ComfyUI-AdvancedLivePortrait
## Installation
### Before you install
FacePoke has only been tested in a Linux environment, using `Python 3.10` and `CUDA 12.4` (so a NVIDIA GPU).
Contributions are welcome to help supporting other platforms!
### Local Setup
1. Clone the repository:
```bash
git clone https://github.com/jbilcke-hf/FacePoke.git
cd FacePoke
```
2. Install Python dependencies:
Using a virtual environment (Python venv) is strongly recommended.
FacePoke has been tested with `Python 3.10`.
```bash
pip3 install --upgrade -r requirements.txt
```
3. Install frontend dependencies:
```bash
cd client
bun install
```
4. Build the frontend:
```bash
bun build ./src/index.tsx --outdir ../public/
```
5. Start the backend server:
```bash
python app.py
```
6. Open `http://localhost:8080` in your web browser.
### Docker Deployment
1. Build the Docker image:
```bash
docker build -t facepoke .
```
2. Run the container:
```bash
docker run -p 8080:8080 facepoke
```
3. To deploy to Hugging Face Spaces:
- Fork the repository on GitHub.
- Create a new Space on Hugging Face.
- Connect your GitHub repository to the Space.
- Configure the Space to use the Docker runtime.
## Development
The project structure is organized as follows:
- `app.py`: Main backend server handling WebSocket connections.
- `engine.py`: Core logic.
- `loader.py`: Initializes and loads AI models.
- `client/`: Frontend React application.
- `src/`: TypeScript source files.
- `public/`: Static assets and built files.
## Contributing
Contributions to FacePoke are welcome! Please read our [Contributing Guidelines](CONTRIBUTING.md) for details on how to submit pull requests, report issues, or request features.
## License
FacePoke is released under the MIT License. See the [LICENSE](LICENSE) file for details.
Please note that while the code of LivePortrait and Insightface are open-source with "no limitation for both academic and commercial usage", the model weights trained from Insightface data are available for [non-commercial research purposes only](https://github.com/deepinsight/insightface?tab=readme-ov-file#license).
---
Developed with ❤️ by Julian Bilcke at Hugging Face
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