| __all__: list[str] = [] | |
| import cv2 | |
| import cv2.typing | |
| import typing as _typing | |
| # Classes | |
| class BarcodeDetector(cv2.GraphicalCodeDetector): | |
| # Functions | |
| @_typing.overload | |
| def __init__(self) -> None: ... | |
| @_typing.overload | |
| def __init__(self, prototxt_path: str, model_path: str) -> None: ... | |
| @_typing.overload | |
| def decodeWithType(self, img: cv2.typing.MatLike, points: cv2.typing.MatLike) -> tuple[bool, _typing.Sequence[str], _typing.Sequence[str]]: ... | |
| @_typing.overload | |
| def decodeWithType(self, img: cv2.UMat, points: cv2.UMat) -> tuple[bool, _typing.Sequence[str], _typing.Sequence[str]]: ... | |
| @_typing.overload | |
| def detectAndDecodeWithType(self, img: cv2.typing.MatLike, points: cv2.typing.MatLike | None = ...) -> tuple[bool, _typing.Sequence[str], _typing.Sequence[str], cv2.typing.MatLike]: ... | |
| @_typing.overload | |
| def detectAndDecodeWithType(self, img: cv2.UMat, points: cv2.UMat | None = ...) -> tuple[bool, _typing.Sequence[str], _typing.Sequence[str], cv2.UMat]: ... | |
| def getDownsamplingThreshold(self) -> float: ... | |
| def setDownsamplingThreshold(self, thresh: float) -> BarcodeDetector: ... | |
| def getDetectorScales(self) -> _typing.Sequence[float]: ... | |
| def setDetectorScales(self, sizes: _typing.Sequence[float]) -> BarcodeDetector: ... | |
| def getGradientThreshold(self) -> float: ... | |
| def setGradientThreshold(self, thresh: float) -> BarcodeDetector: ... | |