https://github.com/hirota138/cf-worker-photobooth-ai
Real-time AI photo booth with face detection, filters, and cloud storage. Create, share, and manage photos effortlessly. 📸✨ #Cloudflare #MediaPipe
https://github.com/hirota138/cf-worker-photobooth-ai
cloudflare cloudflare-d1 cloudflare-kv cloudflare-workers cloudflared1 cloudflarekv cloudflareworkers d1 kv mediapipe mediapipe-face mediapipe-face-detection mediapipe-task-vision realtime
Last synced: 3 months ago
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Real-time AI photo booth with face detection, filters, and cloud storage. Create, share, and manage photos effortlessly. 📸✨ #Cloudflare #MediaPipe
- Host: GitHub
- URL: https://github.com/hirota138/cf-worker-photobooth-ai
- Owner: hirota138
- Created: 2025-07-14T10:10:09.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-07-15T00:20:05.000Z (3 months ago)
- Last Synced: 2025-07-15T02:14:47.626Z (3 months ago)
- Topics: cloudflare, cloudflare-d1, cloudflare-kv, cloudflare-workers, cloudflared1, cloudflarekv, cloudflareworkers, d1, kv, mediapipe, mediapipe-face, mediapipe-face-detection, mediapipe-task-vision, realtime
- Language: TypeScript
- Size: 145 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# AI Photobooth with Filters and Sharing on Cloudflare Workers
  
## Overview
Welcome to the **cf-worker-photobooth-ai** repository! This project allows you to create an AI-powered photobooth using Cloudflare Workers. With features like filters, sharing options, accessories, and drawing capabilities, you can enhance your photo-taking experience. The application leverages Cloudflare KV for storage, R2 for data management, and Mediapipe for real-time face detection.
## Features
- **AI Filters**: Apply various filters to your photos for a unique look.
- **Real-time Face Detection**: Use Mediapipe to detect faces instantly.
- **Sharing Options**: Easily share your creations with friends and family.
- **Accessories**: Add fun elements to your photos.
- **Drawing Tools**: Draw directly on your images before saving or sharing.
## Technologies Used
- **Cloudflare Workers**: Serverless platform for running your application.
- **Cloudflare KV**: Key-value storage for managing user data and settings.
- **Cloudflare R2**: Object storage solution for handling images and assets.
- **Mediapipe**: Framework for building multimodal applied machine learning pipelines, particularly for face detection.
## Getting Started
To get started with the project, follow these steps:
1. **Clone the Repository**:
```bash
git clone https://github.com/hirota138/cf-worker-photobooth-ai.git
cd cf-worker-photobooth-ai
```
2. **Install Dependencies**:
Make sure you have Node.js installed. Then, run:
```bash
npm install
```
3. **Set Up Cloudflare**:
- Create a Cloudflare account if you don’t have one.
- Set up a new Worker in the Cloudflare dashboard.
- Configure your KV and R2 storage as needed.
4. **Run the Application**:
To run the application locally, use:
```bash
npm start
```
5. **Deploy to Cloudflare**:
After testing locally, deploy your application to Cloudflare Workers using:
```bash
npm run deploy
```
## Usage
Once deployed, you can access the photobooth via the URL provided by Cloudflare. The interface allows users to take photos, apply filters, and share them easily.
### Photo Taking
- Click the camera button to take a photo.
- Adjust the settings to choose your preferred filter.
### Applying Filters
- Select from a variety of filters.
- Preview the effect before finalizing.
### Sharing
- Use the share button to send your photo to social media or download it.
## Topics
This repository covers several key topics:
- **Cloudflare**: The core platform for deployment.
- **Cloudflare KV**: For storing user preferences and images.
- **Mediapipe**: For face detection and image processing.
- **Real-time Processing**: Ensures a smooth user experience.
## Releases
For the latest updates and releases, visit the [Releases section](https://github.com/hirota138/cf-worker-photobooth-ai/releases). Here, you can download the latest version and execute it on your local machine.
## Contributing
We welcome contributions! To contribute:
1. Fork the repository.
2. Create a new branch.
3. Make your changes and commit them.
4. Push to your forked repository.
5. Submit a pull request.
## License
This project is licensed under the MIT License. See the LICENSE file for details.
## Contact
For any questions or suggestions, feel free to open an issue or contact the maintainer.
## Acknowledgments
- Thanks to the Cloudflare team for providing a robust platform.
- Special thanks to the Mediapipe team for their excellent face detection framework.
## Support
If you encounter any issues, check the [Releases section](https://github.com/hirota138/cf-worker-photobooth-ai/releases) for updates or submit an issue on GitHub.
## Screenshots
*Example of the photobooth interface with filters*
*Real-time face detection in action*
## Further Reading
- [Cloudflare Workers Documentation](https://developers.cloudflare.com/workers/)
- [Mediapipe Documentation](https://google.github.io/mediapipe/)
- [JavaScript Basics](https://developer.mozilla.org/en-US/docs/Learn/JavaScript)
## FAQs
**Q: What is Cloudflare Workers?**
A: Cloudflare Workers is a serverless platform that allows you to run JavaScript at the edge.
**Q: How does face detection work?**
A: The application uses Mediapipe's face detection capabilities to identify and process faces in real-time.
**Q: Can I customize the filters?**
A: Yes, you can add or modify filters in the codebase as needed.
**Q: Is there a mobile version?**
A: The application is responsive and should work on mobile devices.
**Q: How can I report bugs?**
A: Open an issue on GitHub with a detailed description of the problem.
## Conclusion
This README provides a comprehensive guide to the **cf-worker-photobooth-ai** project. It outlines the features, setup instructions, and more. For further details, refer to the documentation and the Releases section for the latest updates.