initial

venv/lib/python3.12/site-packages/cv2/ppf_match_3d/__init__.pyi

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+__all__: list[str] = []
+
+import cv2.typing
+import typing as _typing
+
+
+# Classes
+class ICP:
+    # Functions
+    @_typing.overload
+    def __init__(self) -> None: ...
+    @_typing.overload
+    def __init__(self, iterations: int, tolerence: float = ..., rejectionScale: float = ..., numLevels: int = ..., sampleType: int = ..., numMaxCorr: int = ...) -> None: ...
+
+    @_typing.overload
+    def registerModelToScene(self, srcPC: cv2.typing.MatLike, dstPC: cv2.typing.MatLike) -> tuple[int, float, cv2.typing.Matx44d]: ...
+    @_typing.overload
+    def registerModelToScene(self, srcPC: cv2.typing.MatLike, dstPC: cv2.typing.MatLike, poses: _typing.Sequence[Pose3D]) -> tuple[int, _typing.Sequence[Pose3D]]: ...
+
+
+class Pose3D:
+    @property
+    def alpha(self) -> float: ...
+    @property
+    def residual(self) -> float: ...
+    @property
+    def modelIndex(self) -> int: ...
+    @property
+    def numVotes(self) -> int: ...
+    @property
+    def pose(self) -> cv2.typing.Matx44d: ...
+    @property
+    def angle(self) -> float: ...
+    @property
+    def t(self) -> cv2.typing.Vec3d: ...
+    @property
+    def q(self) -> cv2.typing.Vec4d: ...
+
+    # Functions
+    @_typing.overload
+    def __init__(self) -> None: ...
+    @_typing.overload
+    def __init__(self, Alpha: float, ModelIndex: int = ..., NumVotes: int = ...) -> None: ...
+
+    @_typing.overload
+    def updatePose(self, NewPose: cv2.typing.Matx44d) -> None: ...
+    @_typing.overload
+    def updatePose(self, NewR: cv2.typing.Matx33d, NewT: cv2.typing.Vec3d) -> None: ...
+
+    def updatePoseQuat(self, Q: cv2.typing.Vec4d, NewT: cv2.typing.Vec3d) -> None: ...
+
+    def appendPose(self, IncrementalPose: cv2.typing.Matx44d) -> None: ...
+
+    def printPose(self) -> None: ...
+
+
+class PoseCluster3D:
+    ...
+
+class PPF3DDetector:
+    # Functions
+    @_typing.overload
+    def __init__(self) -> None: ...
+    @_typing.overload
+    def __init__(self, relativeSamplingStep: float, relativeDistanceStep: float = ..., numAngles: float = ...) -> None: ...
+
+    def trainModel(self, Model: cv2.typing.MatLike) -> None: ...
+
+    def match(self, scene: cv2.typing.MatLike, relativeSceneSampleStep: float = ..., relativeSceneDistance: float = ...) -> _typing.Sequence[Pose3D]: ...
+
+
+
+# Functions
+def addNoisePC(pc: cv2.typing.MatLike, scale: float) -> cv2.typing.MatLike: ...
+
+def computeNormalsPC3d(PC: cv2.typing.MatLike, NumNeighbors: int, FlipViewpoint: bool, viewpoint: cv2.typing.Vec3f, PCNormals: cv2.typing.MatLike | None = ...) -> tuple[int, cv2.typing.MatLike]: ...
+
+def getRandomPose(Pose: cv2.typing.Matx44d) -> None: ...
+
+def loadPLYSimple(fileName: str, withNormals: int = ...) -> cv2.typing.MatLike: ...
+
+def samplePCByQuantization(pc: cv2.typing.MatLike, xrange: cv2.typing.Vec2f, yrange: cv2.typing.Vec2f, zrange: cv2.typing.Vec2f, sample_step_relative: float, weightByCenter: int = ...) -> cv2.typing.MatLike: ...
+
+def transformPCPose(pc: cv2.typing.MatLike, Pose: cv2.typing.Matx44d) -> cv2.typing.MatLike: ...
+
+def writePLY(PC: cv2.typing.MatLike, fileName: str) -> None: ...
+
+def writePLYVisibleNormals(PC: cv2.typing.MatLike, fileName: str) -> None: ...
+
+