README.md

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 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.

Installation

Prerequisites

• Python 3 (Python 3.10 is recommended)
• Ngrok

Requirements

Ensure that Python is installed on your machine. You can install the necessary dependencies using pip and the requirements.txt file.

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:

   python app.py

2. Expose the Server with Ngrok:

   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:

     {
       "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:

     {
       "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)

Additional Resources

• Chess Position Detector GitHub Repository
• Chess Snapshot App GitHub Repository