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

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+__all__: list[str] = []
+
+import cv2
+import cv2.typing
+import typing as _typing
+
+
+# Classes
+class Params:
+    frameSize: cv2.typing.Size
+    intr: cv2.typing.Matx33f
+    rgb_intr: cv2.typing.Matx33f
+    depthFactor: float
+    bilateral_sigma_depth: float
+    bilateral_sigma_spatial: float
+    bilateral_kernel_size: int
+    pyramidLevels: int
+    tsdf_min_camera_movement: float
+    lightPose: cv2.typing.Vec3f
+    icpDistThresh: float
+    icpAngleThresh: float
+    icpIterations: _typing.Sequence[int]
+    truncateThreshold: float
+
+    # Functions
+    @classmethod
+    def defaultParams(cls) -> Params: ...
+
+    @classmethod
+    def coarseParams(cls) -> Params: ...
+
+    @classmethod
+    def hashTSDFParams(cls, isCoarse: bool) -> Params: ...
+
+
+class LargeKinfu:
+    # Functions
+    @classmethod
+    def create(cls, _params: Params) -> LargeKinfu: ...
+
+    @_typing.overload
+    def render(self, image: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
+    @_typing.overload
+    def render(self, image: cv2.UMat | None = ...) -> cv2.UMat: ...
+    @_typing.overload
+    def render(self, cameraPose: cv2.typing.Matx44f, image: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
+    @_typing.overload
+    def render(self, cameraPose: cv2.typing.Matx44f, image: cv2.UMat | None = ...) -> cv2.UMat: ...
+
+    @_typing.overload
+    def getCloud(self, points: cv2.typing.MatLike | None = ..., normals: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
+    @_typing.overload
+    def getCloud(self, points: cv2.UMat | None = ..., normals: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat]: ...
+
+    @_typing.overload
+    def getPoints(self, points: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
+    @_typing.overload
+    def getPoints(self, points: cv2.UMat | None = ...) -> cv2.UMat: ...
+
+    @_typing.overload
+    def getNormals(self, points: cv2.typing.MatLike, normals: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
+    @_typing.overload
+    def getNormals(self, points: cv2.UMat, normals: cv2.UMat | None = ...) -> cv2.UMat: ...
+
+    def reset(self) -> None: ...
+
+    @_typing.overload
+    def update(self, depth: cv2.typing.MatLike) -> bool: ...
+    @_typing.overload
+    def update(self, depth: cv2.UMat) -> bool: ...
+
+
+