board_to_fen

Python package that converts digital chessboard image into Forsyth-Edwards notation (FEN) notation

board_to_fen is available on PyPI:

$ pip3 install board_to_fen

from board_to_fen.predict import get_fen_from_image

print(get_fen_from_image(PATH_TO_CHESSBOARD_IMAGE))

Note: The package uses tensorflow+keras and python-opencv API. They are pretty heavy.

get_fen_from_image takes has 3 arguments:

image_path [required]
end_of_row '/' by default
black_view False by default -> set True if chessboard is provided from black player perspective

For training You would probably want to download the source code by cloning the repository:

$ git clone https://github.com/mcdominik/board_to_fen.git

Download training data from:
I will supply url for data in the future

In the main repository dir, run

$ python3 ./board_to_fen/train_model.py

Warnings

Image has to be provided in neutral angle (white or black player's perspective).
Image has to be square (~3% tolerance depending on image resolution).
Image can't contain paddings, board borders etc. other than 64 squares (with pieces) itself.

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution for board-to-fen 0.1.1
File	Size	Uploaded
board_to_fen-0.1.1.tar.gz	22.9 MB	Feb 10, 2023	Details

Download URL	board_to_fen-0.1.1.tar.gz
Size	22.9 MB
Tags	Source
SHA-256 checksum How to use checksums	`87f27f72ced2fafa54c29f7a91851cacc4d9a9a68567016e1f8fd9a0bf3100db`
BLAKE2b-256 checksum How to use checksums	`3fa8d9e685d6d8046475c520cf7d0cb975564a236119897d12bd199ae2b81d80`
Upload date	Feb 10, 2023
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.1 CPython/3.11.2`