https://github.com/edwinhere/imageboard
Peer-to-Peer Imageboard
https://github.com/edwinhere/imageboard
Last synced: 10 months ago
JSON representation
Peer-to-Peer Imageboard
- Host: GitHub
- URL: https://github.com/edwinhere/imageboard
- Owner: edwinhere
- License: mit
- Created: 2025-04-22T16:13:51.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-22T16:38:28.000Z (about 1 year ago)
- Last Synced: 2025-04-22T17:51:34.939Z (about 1 year ago)
- Language: JavaScript
- Homepage: https://314chan.neocities.org/
- Size: 14.6 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Peer-to-Peer Imageboard
A decentralized imageboard platform that allows users to share and discuss images in a peer-to-peer network. This project combines modern web technologies with peer-to-peer networking to create a censorship-resistant image sharing platform.
## Features
- Decentralized peer-to-peer architecture
- Image sharing and discussion
- Real-time updates
- No central server required
- Built with modern web technologies
- Automated SFW (Safe For Work) content detection using [NSFWJS](https://github.com/infinitered/nsfwjs)
- Runs entirely client-side for privacy
## Prerequisites
- Modern web browser with WebRTC support
- A web server to host the static files
## Hosting Instructions
The application consists of static files that can be hosted on any web server.
## Contributing
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add some amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Support
For support, please open an issue in the GitHub repository or contact the maintainers.
## Acknowledgments
- Thanks to all contributors who have helped with this project
- Special thanks to the open-source community for the tools and libraries that made this possible
- SFW content detection powered by [NSFWJS](https://github.com/infinitered/nsfwjs)
## Setup
1. Clone this repository:
```bash
git clone https://github.com/yourusername/imageboard.git
cd imageboard
```
2. Setup ML models (using Makefile):
```bash
# Setup models
make setup-models
# To clean up models (optional)
make clean-models
```
3. Install dependencies and start the application:
```bash
# Add your installation and startup commands here
```