__all__: list[str] = [] import cv2 import cv2.typing import typing as _typing # Enumerations SFM_IO_BUNDLER: int SFM_IO_VISUALSFM: int SFM_IO_OPENSFM: int SFM_IO_OPENMVG: int SFM_IO_THEIASFM: int SFM_DISTORTION_MODEL_POLYNOMIAL: int SFM_DISTORTION_MODEL_DIVISION: int SFM_REFINE_FOCAL_LENGTH: int SFM_REFINE_PRINCIPAL_POINT: int SFM_REFINE_RADIAL_DISTORTION_K1: int SFM_REFINE_RADIAL_DISTORTION_K2: int # Classes class libmv_CameraIntrinsicsOptions: distortion_model: int image_width: int image_height: int focal_length_x: float focal_length_y: float principal_point_x: float principal_point_y: float polynomial_k1: float polynomial_k2: float polynomial_k3: float polynomial_p1: float polynomial_p2: float division_k1: float division_k2: float # Functions def __init__(self, _distortion_model: int = ..., _focal_length_x: float = ..., _focal_length_y: float = ..., _principal_point_x: float = ..., _principal_point_y: float = ..., _polynomial_k1: float = ..., _polynomial_k2: float = ..., _polynomial_k3: float = ..., _polynomial_p1: float = ..., _polynomial_p2: float = ...) -> None: ... class libmv_ReconstructionOptions: keyframe1: int keyframe2: int refine_intrinsics: int select_keyframes: int verbosity_level: int # Functions def __init__(self, _keyframe1: int = ..., _keyframe2: int = ..., _refine_intrinsics: int = ..., _select_keyframes: int = ..., _verbosity_level: int = ...) -> None: ... class BaseSFM: # Functions @_typing.overload def run(self, points2d: _typing.Sequence[cv2.typing.MatLike]) -> None: ... @_typing.overload def run(self, points2d: _typing.Sequence[cv2.UMat]) -> None: ... @_typing.overload def run(self, points2d: _typing.Sequence[cv2.typing.MatLike], K: cv2.typing.MatLike, Rs: cv2.typing.MatLike | None = ..., Ts: cv2.typing.MatLike | None = ..., points3d: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def run(self, points2d: _typing.Sequence[cv2.UMat], K: cv2.UMat, Rs: cv2.UMat | None = ..., Ts: cv2.UMat | None = ..., points3d: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat]: ... def getError(self) -> float: ... @_typing.overload def getPoints(self, points3d: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def getPoints(self, points3d: cv2.UMat | None = ...) -> cv2.UMat: ... def getIntrinsics(self) -> cv2.typing.MatLike: ... @_typing.overload def getCameras(self, Rs: cv2.typing.MatLike | None = ..., Ts: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def getCameras(self, Rs: cv2.UMat | None = ..., Ts: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat]: ... def setReconstructionOptions(self, libmv_reconstruction_options: libmv_ReconstructionOptions) -> None: ... def setCameraIntrinsicOptions(self, libmv_camera_intrinsics_options: libmv_CameraIntrinsicsOptions) -> None: ... class SFMLibmvEuclideanReconstruction(BaseSFM): # Functions @_typing.overload def run(self, points2d: _typing.Sequence[cv2.typing.MatLike]) -> None: ... @_typing.overload def run(self, points2d: _typing.Sequence[cv2.UMat]) -> None: ... @_typing.overload def run(self, points2d: _typing.Sequence[cv2.typing.MatLike], K: cv2.typing.MatLike, Rs: cv2.typing.MatLike | None = ..., Ts: cv2.typing.MatLike | None = ..., points3d: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def run(self, points2d: _typing.Sequence[cv2.UMat], K: cv2.UMat, Rs: cv2.UMat | None = ..., Ts: cv2.UMat | None = ..., points3d: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat]: ... def getError(self) -> float: ... @_typing.overload def getPoints(self, points3d: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def getPoints(self, points3d: cv2.UMat | None = ...) -> cv2.UMat: ... def getIntrinsics(self) -> cv2.typing.MatLike: ... @_typing.overload def getCameras(self, Rs: cv2.typing.MatLike | None = ..., Ts: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def getCameras(self, Rs: cv2.UMat | None = ..., Ts: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat]: ... def setReconstructionOptions(self, libmv_reconstruction_options: libmv_ReconstructionOptions) -> None: ... def setCameraIntrinsicOptions(self, libmv_camera_intrinsics_options: libmv_CameraIntrinsicsOptions) -> None: ... # Functions @_typing.overload def KRtFromProjection(P: cv2.typing.MatLike, K: cv2.typing.MatLike | None = ..., R: cv2.typing.MatLike | None = ..., t: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def KRtFromProjection(P: cv2.UMat, K: cv2.UMat | None = ..., R: cv2.UMat | None = ..., t: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat, cv2.UMat]: ... @_typing.overload def applyTransformationToPoints(points: cv2.typing.MatLike, T: cv2.typing.MatLike, transformed_points: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def applyTransformationToPoints(points: cv2.UMat, T: cv2.UMat, transformed_points: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def computeOrientation(x1: _typing.Sequence[cv2.typing.MatLike], x2: _typing.Sequence[cv2.typing.MatLike], s: float, R: cv2.typing.MatLike | None = ..., t: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def computeOrientation(x1: _typing.Sequence[cv2.UMat], x2: _typing.Sequence[cv2.UMat], s: float, R: cv2.UMat | None = ..., t: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat]: ... @_typing.overload def depth(R: cv2.typing.MatLike, t: cv2.typing.MatLike, X: cv2.typing.MatLike) -> float: ... @_typing.overload def depth(R: cv2.UMat, t: cv2.UMat, X: cv2.UMat) -> float: ... @_typing.overload def essentialFromFundamental(F: cv2.typing.MatLike, K1: cv2.typing.MatLike, K2: cv2.typing.MatLike, E: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def essentialFromFundamental(F: cv2.UMat, K1: cv2.UMat, K2: cv2.UMat, E: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def essentialFromRt(R1: cv2.typing.MatLike, t1: cv2.typing.MatLike, R2: cv2.typing.MatLike, t2: cv2.typing.MatLike, E: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def essentialFromRt(R1: cv2.UMat, t1: cv2.UMat, R2: cv2.UMat, t2: cv2.UMat, E: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def euclideanToHomogeneous(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def euclideanToHomogeneous(src: cv2.UMat, dst: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def fundamentalFromCorrespondences7PointRobust(x1: cv2.typing.MatLike, x2: cv2.typing.MatLike, max_error: float, F: cv2.typing.MatLike | None = ..., inliers: cv2.typing.MatLike | None = ..., outliers_probability: float = ...) -> tuple[float, cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def fundamentalFromCorrespondences7PointRobust(x1: cv2.UMat, x2: cv2.UMat, max_error: float, F: cv2.UMat | None = ..., inliers: cv2.UMat | None = ..., outliers_probability: float = ...) -> tuple[float, cv2.UMat, cv2.UMat]: ... @_typing.overload def fundamentalFromCorrespondences8PointRobust(x1: cv2.typing.MatLike, x2: cv2.typing.MatLike, max_error: float, F: cv2.typing.MatLike | None = ..., inliers: cv2.typing.MatLike | None = ..., outliers_probability: float = ...) -> tuple[float, cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def fundamentalFromCorrespondences8PointRobust(x1: cv2.UMat, x2: cv2.UMat, max_error: float, F: cv2.UMat | None = ..., inliers: cv2.UMat | None = ..., outliers_probability: float = ...) -> tuple[float, cv2.UMat, cv2.UMat]: ... @_typing.overload def fundamentalFromEssential(E: cv2.typing.MatLike, K1: cv2.typing.MatLike, K2: cv2.typing.MatLike, F: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def fundamentalFromEssential(E: cv2.UMat, K1: cv2.UMat, K2: cv2.UMat, F: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def fundamentalFromProjections(P1: cv2.typing.MatLike, P2: cv2.typing.MatLike, F: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def fundamentalFromProjections(P1: cv2.UMat, P2: cv2.UMat, F: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def homogeneousToEuclidean(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def homogeneousToEuclidean(src: cv2.UMat, dst: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def importReconstruction(file: str, Rs: _typing.Sequence[cv2.typing.MatLike] | None = ..., Ts: _typing.Sequence[cv2.typing.MatLike] | None = ..., Ks: _typing.Sequence[cv2.typing.MatLike] | None = ..., points3d: _typing.Sequence[cv2.typing.MatLike] | None = ..., file_format: int = ...) -> tuple[_typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike]]: ... @_typing.overload def importReconstruction(file: str, Rs: _typing.Sequence[cv2.UMat] | None = ..., Ts: _typing.Sequence[cv2.UMat] | None = ..., Ks: _typing.Sequence[cv2.UMat] | None = ..., points3d: _typing.Sequence[cv2.UMat] | None = ..., file_format: int = ...) -> tuple[_typing.Sequence[cv2.UMat], _typing.Sequence[cv2.UMat], _typing.Sequence[cv2.UMat], _typing.Sequence[cv2.UMat]]: ... @_typing.overload def isotropicPreconditionerFromPoints(points: cv2.typing.MatLike, T: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def isotropicPreconditionerFromPoints(points: cv2.UMat, T: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def meanAndVarianceAlongRows(A: cv2.typing.MatLike, mean: cv2.typing.MatLike | None = ..., variance: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def meanAndVarianceAlongRows(A: cv2.UMat, mean: cv2.UMat | None = ..., variance: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat]: ... @_typing.overload def motionFromEssential(E: cv2.typing.MatLike, Rs: _typing.Sequence[cv2.typing.MatLike] | None = ..., ts: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> tuple[_typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike]]: ... @_typing.overload def motionFromEssential(E: cv2.UMat, Rs: _typing.Sequence[cv2.UMat] | None = ..., ts: _typing.Sequence[cv2.UMat] | None = ...) -> tuple[_typing.Sequence[cv2.UMat], _typing.Sequence[cv2.UMat]]: ... @_typing.overload def motionFromEssentialChooseSolution(Rs: _typing.Sequence[cv2.typing.MatLike], ts: _typing.Sequence[cv2.typing.MatLike], K1: cv2.typing.MatLike, x1: cv2.typing.MatLike, K2: cv2.typing.MatLike, x2: cv2.typing.MatLike) -> int: ... @_typing.overload def motionFromEssentialChooseSolution(Rs: _typing.Sequence[cv2.UMat], ts: _typing.Sequence[cv2.UMat], K1: cv2.UMat, x1: cv2.UMat, K2: cv2.UMat, x2: cv2.UMat) -> int: ... @_typing.overload def normalizeFundamental(F: cv2.typing.MatLike, F_normalized: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def normalizeFundamental(F: cv2.UMat, F_normalized: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def normalizeIsotropicPoints(points: cv2.typing.MatLike, normalized_points: cv2.typing.MatLike | None = ..., T: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def normalizeIsotropicPoints(points: cv2.UMat, normalized_points: cv2.UMat | None = ..., T: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat]: ... @_typing.overload def normalizePoints(points: cv2.typing.MatLike, normalized_points: cv2.typing.MatLike | None = ..., T: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def normalizePoints(points: cv2.UMat, normalized_points: cv2.UMat | None = ..., T: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat]: ... @_typing.overload def normalizedEightPointSolver(x1: cv2.typing.MatLike, x2: cv2.typing.MatLike, F: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def normalizedEightPointSolver(x1: cv2.UMat, x2: cv2.UMat, F: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def preconditionerFromPoints(points: cv2.typing.MatLike, T: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def preconditionerFromPoints(points: cv2.UMat, T: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def projectionFromKRt(K: cv2.typing.MatLike, R: cv2.typing.MatLike, t: cv2.typing.MatLike, P: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def projectionFromKRt(K: cv2.UMat, R: cv2.UMat, t: cv2.UMat, P: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def projectionsFromFundamental(F: cv2.typing.MatLike, P1: cv2.typing.MatLike | None = ..., P2: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def projectionsFromFundamental(F: cv2.UMat, P1: cv2.UMat | None = ..., P2: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat]: ... @_typing.overload def relativeCameraMotion(R1: cv2.typing.MatLike, t1: cv2.typing.MatLike, R2: cv2.typing.MatLike, t2: cv2.typing.MatLike, R: cv2.typing.MatLike | None = ..., t: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def relativeCameraMotion(R1: cv2.UMat, t1: cv2.UMat, R2: cv2.UMat, t2: cv2.UMat, R: cv2.UMat | None = ..., t: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat]: ... @_typing.overload def skew(x: cv2.typing.MatLike) -> cv2.typing.MatLike: ... @_typing.overload def skew(x: cv2.UMat) -> cv2.typing.MatLike: ... @_typing.overload def triangulatePoints(points2d: _typing.Sequence[cv2.typing.MatLike], projection_matrices: _typing.Sequence[cv2.typing.MatLike], points3d: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def triangulatePoints(points2d: _typing.Sequence[cv2.UMat], projection_matrices: _typing.Sequence[cv2.UMat], points3d: cv2.UMat | None = ...) -> cv2.UMat: ...