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chessvision ♟️

CI codecov Hugging Face python

uv ruff ty pytest

A fast, lightweight chess board and piece recognition toolkit.

chessvision demo


Install

# With uv (recommended)
uv tool install chessvision

# With pipx
pipx install chessvision
# As a library
uv add chessvision

# or
pip install chessvision

Usage

CLI

# Predict chess positions from a board, screenshot, or book page
chessvision board chessboard.png

# Predict chess positions from a PDF document
chessvision pdf document.pdf

# Predict a single square image
chessvision square square.png

Python API

from chessvision import (
    BoardDetector,
    BoardPredictor,
    Orientation,
    PieceClassifier,
    Turn,
)

# 1. Full Board Recognition
predictor = BoardPredictor()
prediction = predictor.predict(
    "chessboard.png", orientation=Orientation.AUTO, turn=Turn.AUTO, castling="auto"
)

print(prediction.render_board)
print(f"FEN: {prediction.fen}")
print(f"Confidence: {prediction.confidence:.2%}")
print(f"Valid: {prediction.is_valid}")
if not prediction.is_valid:
    print(f"Errors: {prediction.validation_errors}")
print(f"URL: {prediction.url}")

# Access the chess.Board object directly
board = prediction.board

# 2. Multi-Board Detection
detector = BoardDetector()
boards = detector.detect("page.png")  # Returns list of cropped PIL Images

for board in boards:
    prediction = predictor.predict(board)
    print(prediction.fen)

# 3. Single Square Classification
classifier = PieceClassifier()
square_prediction = classifier.predict_square("square.png")
print(f"{square_prediction.name} [{square_prediction.confidence:.2%}]")

# 4. Batch Squares Classification
batch_predictions = classifier.predict_squares(["e4.png", "e5.png"])
for prediction in batch_predictions:
    print(f"{prediction.name} [{prediction.confidence:.2%}]")

CLI Subcommands

chessvision board

Flag Short Default Description
--orientation -o auto Board perspective (auto, white, or black).
--turn -t auto Side to move (auto, white or black).
--castling -c auto Castling availability (see castling options).
--open False Open position directly in Lichess editor.

Castling Options

Value Description
auto Automatically infer castling (default)
- No castling for both sides
[KQkq] Specific castling rights (e.g. KQkq, KQ, Qk)
# Specify board perspective explicitly
chessvision board chessboard.png --orientation black
chessvision board chessboard.png -o white

# Specify castling availability explicitly
chessvision board chessboard.png --castling KQkq
chessvision board chessboard.png -c KQ

# Specify side to move explicitly
chessvision board chessboard.png --turn black
chessvision board chessboard.png -t white

# Open position directly in Lichess editor
chessvision board chessboard.png --open

chessvision pdf

# Predict chess positions from a PDF document
chessvision pdf document.pdf

chessvision square

# Predict piece on a square image
chessvision square square.png

square prediction demo


Model & Cache Management

chessvision automatically downloads the pre-trained ONNX piece classifier (chess_piece_classifier.onnx) from Hugging Face on its first run and caches it locally:

Default File Paths

OS Cache Path
Linux ~/.cache/chessvision/chess_piece_classifier.onnx
macOS ~/Library/Caches/chessvision/chess_piece_classifier.onnx
Windows %LOCALAPPDATA%\chessvision\Cache\chess_piece_classifier.onnx

Attributions

Training assets were extracted, and preprocessed from Lichess open-source piece sets and board themes (see their COPYING.md for individual asset licenses).


License

This project is licensed under the MIT License.

Metadata

Release files for chessvision 0.8.0

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