| __all__: list[str] = [] |
|
|
| import cv2 |
| import cv2.typing |
| import os |
| import typing as _typing |
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|
| # Classes |
| class BarcodeDetector(cv2.GraphicalCodeDetector): |
| # Functions |
| @_typing.overload |
| def __init__(self) -> None: ... |
| @_typing.overload |
| def __init__(self, super_resolution_model_path: str | os.PathLike[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: ... |
|
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| def setDownsamplingThreshold(self, thresh: float) -> BarcodeDetector: ... |
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| def getDetectorScales(self) -> _typing.Sequence[float]: ... |
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| def setDetectorScales(self, sizes: _typing.Sequence[float]) -> BarcodeDetector: ... |
|
|
| def getGradientThreshold(self) -> float: ... |
|
|
| def setGradientThreshold(self, thresh: float) -> BarcodeDetector: ... |
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