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https://github.com/tbtiberiu/chess-snapshot-api
API for detecting chess positions from images and analyzing them with the Stockfish engine.
https://github.com/tbtiberiu/chess-snapshot-api
chessboard-detection flask stockfish-engine
Last synced: 4 days ago
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API for detecting chess positions from images and analyzing them with the Stockfish engine.
- Host: GitHub
- URL: https://github.com/tbtiberiu/chess-snapshot-api
- Owner: tbtiberiu
- Created: 2024-02-17T13:20:34.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-08-27T08:10:44.000Z (3 months ago)
- Last Synced: 2024-08-27T10:38:46.894Z (3 months ago)
- Topics: chessboard-detection, flask, stockfish-engine
- Language: Python
- Homepage: https://online.fliphtml5.com/qtzgs/qunc/
- Size: 87.3 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Chess Snapshot API
The Chess Snapshot API provides an easy-to-use RESTful interface for detecting and analyzing chess positions from images. It utilizes the [Chess Position Detector](https://github.com/tbtiberiu/chess-position-detector.git) to convert a chessboard image into a FEN string and integrates the powerful Stockfish chess engine to determine the best move from any given position.
This API is intended for integration with a Flutter application, offering seamless support for the [Chess Snapshot App](https://github.com/tbtiberiu/chess_snapshot_app.git).
## Installation
### Prerequisites
- Python 3 ([Python 3.10](https://www.python.org/downloads/release/python-31014/) is recommended)
- [Ngrok](https://ngrok.com/download)
### Requirements
Ensure that Python is installed on your machine. You can install the necessary dependencies using `pip` and the `requirements.txt` file.
```bash
pip install -r requirements.txt
```
### Dependencies
- OpenCV
- Numpy
- Flask
- Stockfish
- ...
These dependencies are necessary for image processing, detection algorithms, and chess analysis.
## Usage
To use the `Chess Snapshot API`, follow these steps:
1. **Start the Flask Server**:
```bash
python app.py
```
2. **Expose the Server with Ngrok**:
```bash
ngrok http --domain=knowing-fit-poodle.ngrok-free.app 8080
```
### Endpoints
1. **Get Chess Position (FEN String)**
- **URL**: `/api/get_chess_position`
- **Method**: `POST`
- **Description**: This endpoint accepts an image file of a chessboard and returns the FEN string representing the position on the board.
- **Response Example**:
```json
{
"fen": "rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR"
}
```
2. **Get Best Move**
- **URL**: `/api/get_best_move`
- **Method**: `POST`
- **Description**: This endpoint accepts a FEN string and returns the best move as calculated by Stockfish.
- **Response Example**:
```json
{
"best_move": "e2e4"
}
```
## Acknowledgments
This project is based on advanced computer vision techniques and was supervised by Lect. Dr. Ioana Cristina Plajer.
**Read More:** [Chess Snapshot Full Documentation in Romanian (PDF)](ChessSnapshot.pdf)
## Additional Resources
- [Chess Position Detector GitHub Repository](https://github.com/tbtiberiu/chess-position-detector.git)
- [Chess Snapshot App GitHub Repository](https://github.com/tbtiberiu/chess_snapshot_app.git)