This web application utilizes Machine Learning (ML) to recognize and reconstruct a chessboard from a given image or upload. Users can interact with the reconstructed chessboard, making moves and exploring chess strategies.
- Chessboard Detection: Uses ML algorithms to identify the chessboard within an image.
- Chessboard Reconstruction: Converts the detected chessboard into a digital representation.
- Interactive Chessboard: Allows users to make moves and interact with the chessboard.
- Chess Logic Integration: Utilizes existing chess libraries for game mechanics and move validation.
- Frontend: HTML, CSS, JavaScript (with TensorFlow.js and OpenCV.js)
- Backend: Node.js (with Express.js)
- Machine Learning: TensorFlow.js and OpenCV.js
- Chess Libraries: Python-Chess or Chess.js
- Clone the repository:
git clone <link unavailable> - Install dependencies:
npm install - Start the application:
npm start - Access the web app at:
http://localhost:3000
Contributions are welcome! Please feel free to submit pull requests or open issues for new features, bug fixes, or improvements.
This project is licensed under the MIT License.
- Inspired by various chess recognition projects and tutorials.
- Special thanks to the TensorFlow.js and OpenCV.js communities for their support and resources.
Anhad Lamba