calib-targets 0.5.3

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calib-targets Python bindings

These bindings expose a native-feeling Python API backed by Rust (PyO3 + maturin).

Build & develop

pip install maturin
maturin develop
python -c "import calib_targets as ct; print(ct.detect_chessboard)"

Public API

Top-level detectors return typed dataclasses:

• detect_chessboard(image, *, chess_cfg=None, params=None) -> ChessboardDetectionResult | None
• detect_charuco(image, *, chess_cfg=None, params) -> CharucoDetectionResult
• detect_marker_board(image, *, chess_cfg=None, params=None) -> MarkerBoardDetectionResult | None
• render_target_bundle(document) -> GeneratedTargetBundle
• write_target_bundle(document, output_stem) -> WrittenTargetBundle

Configuration is typed-only (dataclasses):

• ChessConfig, ChessCornerParams, CoarseToFineParams, PyramidParams
• ChessboardParams, OrientationClusteringParams, GridGraphParams
• CharucoBoardSpec, CharucoDetectorParams, ScanDecodeConfig
• MarkerCircleSpec, MarkerBoardLayout, CircleScoreParams, CircleMatchParams, MarkerBoardParams
• PageSize, PageSpec, RenderOptions, ChessboardTargetSpec, CharucoTargetSpec, MarkerBoardTargetSpec, PrintableTargetDocument

Enums and literals:

• TargetKind, CirclePolarity, MarkerLayout
• DictionaryName (Literal) and DICTIONARY_NAMES

Inputs

• image must be a 2D numpy.ndarray with dtype=uint8.
• chess_cfg must be ChessConfig | None.
• params must be typed params dataclasses (or None where allowed).
• Dict/mapping inputs are intentionally rejected in the new API.

Results and compatibility

Result models are dataclasses with attribute access and editor navigation. Every config/result model provides:

• to_dict()
• from_dict(...)

This is the compatibility path for JSON pipelines and legacy dict-based code.

Migration guide

Old usage	New usage
detect_chessboard(img, params={"min_corners": 16})	detect_chessboard(img, params=ChessboardParams(min_corners=16))
detect_charuco(..., params={"board": {...}})	detect_charuco(..., params=CharucoDetectorParams(board=CharucoBoardSpec(...)))
result["detection"]["corners"]	result.detection.corners
N/A	result.to_dict() / ResultType.from_dict(...)

Examples

pip install pillow
python examples/detect_chessboard.py path/to/image.png
python examples/detect_charuco.py path/to/image.png
python examples/detect_marker_board.py path/to/image.png
python examples/generate_printable.py tmpdata/printable/charuco_a4

For the canonical printable-target JSON model, the repo-local CLI flow, and print-at-100%-scale guidance, see the workspace printable-target guide: https://vitalyvorobyev.github.io/calib-targets-rs/printable.html

Implementation note

The compiled module is internal (calib_targets._core). Public API stability is guaranteed only for top-level calib_targets exports.