LiveChess2FEN

LiveChess2FEN is a fully functional framework that automatically digitizes the configuration of a chessboard. It is optimized for execution on a Nvidia Jetson Nano.

This repository contains the code used in our paper. If you find this useful, please consider citing us.

Benchmarks

The following times are measured on the Nvidia Jetson Nano. Each time value is given per chessboard.

Piece classification times

Full digitization times

Static digitization times

See lc2fen/detectboard/laps.py -> check_board_position()

Setup

1. Install Python 3.5 or later and the following dependencies:

   • NumPy
   • OpenCV4
   • Matplotlib
   • scikit-learn
   • pillow
   • pyclipper
   • tqdm

2. Depending on the inference engine install the following dependencies:

   • Keras with tensorflow backend. Slower than ONNX.
   • ONNX Runtime.
   • (Optional) TensorRT. Fastest available, although more tricky to set up.

3. Create a selected_models and a predictions folder in the project root.

4. Download the prediction models from the releases and save them to the selected_models folder.

5. Download the contents of TestImages.zip->FullDetection from the releases into the predictions folder. You should have 5 test images and a boards.fen file.

6. Edit test_lc2fen.py and set the ACTIVATE_*, MODEL_PATH_*, IMG_SIZE_* and PRE_INPUT_* constants.

7. Run the test_lc2fen.py script.

Contributing

Contributions are very welcome! Please check the CONTRIBUTING file for more information on how to contribute to LiveChess2FEN.

License

You can find a non-legal quick summary here: tldrlegal AGPL

Copyright (c) 2020 David Mallasén Quintana

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see http://www.gnu.org/licenses/.