initial

venv/lib/python3.12/site-packages/cv2/line_descriptor/__init__.pyi

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+__all__: list[str] = []
+
+import cv2
+import cv2.typing
+import typing as _typing
+
+
+# Classes
+class KeyLine:
+    angle: float
+    class_id: int
+    octave: int
+    pt: cv2.typing.Point2f
+    response: float
+    size: float
+    startPointX: float
+    startPointY: float
+    endPointX: float
+    endPointY: float
+    sPointInOctaveX: float
+    sPointInOctaveY: float
+    ePointInOctaveX: float
+    ePointInOctaveY: float
+    lineLength: float
+    numOfPixels: int
+
+    # Functions
+    def __init__(self) -> None: ...
+
+    def getStartPoint(self) -> cv2.typing.Point2f: ...
+
+    def getEndPoint(self) -> cv2.typing.Point2f: ...
+
+    def getStartPointInOctave(self) -> cv2.typing.Point2f: ...
+
+    def getEndPointInOctave(self) -> cv2.typing.Point2f: ...
+
+
+class BinaryDescriptor(cv2.Algorithm):
+    # Functions
+    @classmethod
+    def createBinaryDescriptor(cls) -> BinaryDescriptor: ...
+
+    def getNumOfOctaves(self) -> int: ...
+
+    def setNumOfOctaves(self, octaves: int) -> None: ...
+
+    def getWidthOfBand(self) -> int: ...
+
+    def setWidthOfBand(self, width: int) -> None: ...
+
+    def getReductionRatio(self) -> int: ...
+
+    def setReductionRatio(self, rRatio: int) -> None: ...
+
+    def detect(self, image: cv2.typing.MatLike, mask: cv2.typing.MatLike | None = ...) -> _typing.Sequence[KeyLine]: ...
+
+    def compute(self, image: cv2.typing.MatLike, keylines: _typing.Sequence[KeyLine], descriptors: cv2.typing.MatLike | None = ..., returnFloatDescr: bool = ...) -> tuple[_typing.Sequence[KeyLine], cv2.typing.MatLike]: ...
+
+
+class LSDParam:
+    scale: float
+    sigma_scale: float
+    quant: float
+    ang_th: float
+    log_eps: float
+    density_th: float
+    n_bins: int
+
+    # Functions
+    def __init__(self) -> None: ...
+
+
+class LSDDetector(cv2.Algorithm):
+    # Functions
+    def __init__(self, _params: LSDParam) -> None: ...
+
+    @classmethod
+    def createLSDDetector(cls) -> LSDDetector: ...
+
+    @classmethod
+    def createLSDDetectorWithParams(cls, params: LSDParam) -> LSDDetector: ...
+
+    @_typing.overload
+    def detect(self, image: cv2.typing.MatLike, scale: int, numOctaves: int, mask: cv2.typing.MatLike | None = ...) -> _typing.Sequence[KeyLine]: ...
+    @_typing.overload
+    def detect(self, images: _typing.Sequence[cv2.typing.MatLike], keylines: _typing.Sequence[_typing.Sequence[KeyLine]], scale: int, numOctaves: int, masks: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> None: ...
+
+
+class BinaryDescriptorMatcher(cv2.Algorithm):
+    # Functions
+    def __init__(self) -> None: ...
+
+    def match(self, queryDescriptors: cv2.typing.MatLike, trainDescriptors: cv2.typing.MatLike, mask: cv2.typing.MatLike | None = ...) -> _typing.Sequence[cv2.DMatch]: ...
+
+    def matchQuery(self, queryDescriptors: cv2.typing.MatLike, masks: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.DMatch]: ...
+
+    def knnMatch(self, queryDescriptors: cv2.typing.MatLike, trainDescriptors: cv2.typing.MatLike, k: int, mask: cv2.typing.MatLike | None = ..., compactResult: bool = ...) -> _typing.Sequence[_typing.Sequence[cv2.DMatch]]: ...
+
+    def knnMatchQuery(self, queryDescriptors: cv2.typing.MatLike, matches: _typing.Sequence[_typing.Sequence[cv2.DMatch]], k: int, masks: _typing.Sequence[cv2.typing.MatLike] | None = ..., compactResult: bool = ...) -> None: ...
+
+
+class DrawLinesMatchesFlags:
+    ...
+
+
+# Functions
+def drawKeylines(image: cv2.typing.MatLike, keylines: _typing.Sequence[KeyLine], outImage: cv2.typing.MatLike | None = ..., color: cv2.typing.Scalar = ..., flags: int = ...) -> cv2.typing.MatLike: ...
+
+def drawLineMatches(img1: cv2.typing.MatLike, keylines1: _typing.Sequence[KeyLine], img2: cv2.typing.MatLike, keylines2: _typing.Sequence[KeyLine], matches1to2: _typing.Sequence[cv2.DMatch], outImg: cv2.typing.MatLike | None = ..., matchColor: cv2.typing.Scalar = ..., singleLineColor: cv2.typing.Scalar = ..., matchesMask: _typing.Sequence[str] = ..., flags: int = ...) -> cv2.typing.MatLike: ...
+
+