__all__: list[str] = [] import cv2 import cv2.typing import typing as _typing # Enumerations SR_FIXED: int SR_CROSS: int SupportRegionType = int """One of [SR_FIXED, SR_CROSS]""" ST_STANDART: int ST_BILINEAR: int SolverType = int """One of [ST_STANDART, ST_BILINEAR]""" INTERP_GEO: int INTERP_EPIC: int INTERP_RIC: int InterpolationType = int """One of [INTERP_GEO, INTERP_EPIC, INTERP_RIC]""" GPC_DESCRIPTOR_DCT: int GPC_DESCRIPTOR_WHT: int GPCDescType = int """One of [GPC_DESCRIPTOR_DCT, GPC_DESCRIPTOR_WHT]""" # Classes class DualTVL1OpticalFlow(cv2.DenseOpticalFlow): # Functions def getTau(self) -> float: ... def setTau(self, val: float) -> None: ... def getLambda(self) -> float: ... def setLambda(self, val: float) -> None: ... def getTheta(self) -> float: ... def setTheta(self, val: float) -> None: ... def getGamma(self) -> float: ... def setGamma(self, val: float) -> None: ... def getScalesNumber(self) -> int: ... def setScalesNumber(self, val: int) -> None: ... def getWarpingsNumber(self) -> int: ... def setWarpingsNumber(self, val: int) -> None: ... def getEpsilon(self) -> float: ... def setEpsilon(self, val: float) -> None: ... def getInnerIterations(self) -> int: ... def setInnerIterations(self, val: int) -> None: ... def getOuterIterations(self) -> int: ... def setOuterIterations(self, val: int) -> None: ... def getUseInitialFlow(self) -> bool: ... def setUseInitialFlow(self, val: bool) -> None: ... def getScaleStep(self) -> float: ... def setScaleStep(self, val: float) -> None: ... def getMedianFiltering(self) -> int: ... def setMedianFiltering(self, val: int) -> None: ... @classmethod def create(cls, tau: float = ..., lambda_: float = ..., theta: float = ..., nscales: int = ..., warps: int = ..., epsilon: float = ..., innnerIterations: int = ..., outerIterations: int = ..., scaleStep: float = ..., gamma: float = ..., medianFiltering: int = ..., useInitialFlow: bool = ...) -> DualTVL1OpticalFlow: ... class PCAPrior: ... class OpticalFlowPCAFlow(cv2.DenseOpticalFlow): ... class RLOFOpticalFlowParameter: # Functions def setUseMEstimator(self, val: bool) -> None: ... def setSolverType(self, val: SolverType) -> None: ... def getSolverType(self) -> SolverType: ... def setSupportRegionType(self, val: SupportRegionType) -> None: ... def getSupportRegionType(self) -> SupportRegionType: ... def setNormSigma0(self, val: float) -> None: ... def getNormSigma0(self) -> float: ... def setNormSigma1(self, val: float) -> None: ... def getNormSigma1(self) -> float: ... def setSmallWinSize(self, val: int) -> None: ... def getSmallWinSize(self) -> int: ... def setLargeWinSize(self, val: int) -> None: ... def getLargeWinSize(self) -> int: ... def setCrossSegmentationThreshold(self, val: int) -> None: ... def getCrossSegmentationThreshold(self) -> int: ... def setMaxLevel(self, val: int) -> None: ... def getMaxLevel(self) -> int: ... def setUseInitialFlow(self, val: bool) -> None: ... def getUseInitialFlow(self) -> bool: ... def setUseIlluminationModel(self, val: bool) -> None: ... def getUseIlluminationModel(self) -> bool: ... def setUseGlobalMotionPrior(self, val: bool) -> None: ... def getUseGlobalMotionPrior(self) -> bool: ... def setMaxIteration(self, val: int) -> None: ... def getMaxIteration(self) -> int: ... def setMinEigenValue(self, val: float) -> None: ... def getMinEigenValue(self) -> float: ... def setGlobalMotionRansacThreshold(self, val: float) -> None: ... def getGlobalMotionRansacThreshold(self) -> float: ... @classmethod def create(cls) -> RLOFOpticalFlowParameter: ... class DenseRLOFOpticalFlow(cv2.DenseOpticalFlow): # Functions def setRLOFOpticalFlowParameter(self, val: RLOFOpticalFlowParameter) -> None: ... def getRLOFOpticalFlowParameter(self) -> RLOFOpticalFlowParameter: ... def setForwardBackward(self, val: float) -> None: ... def getForwardBackward(self) -> float: ... def getGridStep(self) -> cv2.typing.Size: ... def setGridStep(self, val: cv2.typing.Size) -> None: ... def setInterpolation(self, val: InterpolationType) -> None: ... def getInterpolation(self) -> InterpolationType: ... def getEPICK(self) -> int: ... def setEPICK(self, val: int) -> None: ... def getEPICSigma(self) -> float: ... def setEPICSigma(self, val: float) -> None: ... def getEPICLambda(self) -> float: ... def setEPICLambda(self, val: float) -> None: ... def getFgsLambda(self) -> float: ... def setFgsLambda(self, val: float) -> None: ... def getFgsSigma(self) -> float: ... def setFgsSigma(self, val: float) -> None: ... def setUsePostProc(self, val: bool) -> None: ... def getUsePostProc(self) -> bool: ... def setUseVariationalRefinement(self, val: bool) -> None: ... def getUseVariationalRefinement(self) -> bool: ... def setRICSPSize(self, val: int) -> None: ... def getRICSPSize(self) -> int: ... def setRICSLICType(self, val: int) -> None: ... def getRICSLICType(self) -> int: ... @classmethod def create(cls, rlofParam: RLOFOpticalFlowParameter = ..., forwardBackwardThreshold: float = ..., gridStep: cv2.typing.Size = ..., interp_type: InterpolationType = ..., epicK: int = ..., epicSigma: float = ..., epicLambda: float = ..., ricSPSize: int = ..., ricSLICType: int = ..., use_post_proc: bool = ..., fgsLambda: float = ..., fgsSigma: float = ..., use_variational_refinement: bool = ...) -> DenseRLOFOpticalFlow: ... class SparseRLOFOpticalFlow(cv2.SparseOpticalFlow): # Functions def setRLOFOpticalFlowParameter(self, val: RLOFOpticalFlowParameter) -> None: ... def getRLOFOpticalFlowParameter(self) -> RLOFOpticalFlowParameter: ... def setForwardBackward(self, val: float) -> None: ... def getForwardBackward(self) -> float: ... @classmethod def create(cls, rlofParam: RLOFOpticalFlowParameter = ..., forwardBackwardThreshold: float = ...) -> SparseRLOFOpticalFlow: ... class GPCPatchDescriptor: ... class GPCPatchSample: ... class GPCTrainingSamples: ... class GPCTree(cv2.Algorithm): ... class GPCDetails: ... # Functions @_typing.overload def calcOpticalFlowDenseRLOF(I0: cv2.typing.MatLike, I1: cv2.typing.MatLike, flow: cv2.typing.MatLike, rlofParam: RLOFOpticalFlowParameter = ..., forwardBackwardThreshold: float = ..., gridStep: cv2.typing.Size = ..., interp_type: InterpolationType = ..., epicK: int = ..., epicSigma: float = ..., epicLambda: float = ..., ricSPSize: int = ..., ricSLICType: int = ..., use_post_proc: bool = ..., fgsLambda: float = ..., fgsSigma: float = ..., use_variational_refinement: bool = ...) -> cv2.typing.MatLike: ... @_typing.overload def calcOpticalFlowDenseRLOF(I0: cv2.UMat, I1: cv2.UMat, flow: cv2.UMat, rlofParam: RLOFOpticalFlowParameter = ..., forwardBackwardThreshold: float = ..., gridStep: cv2.typing.Size = ..., interp_type: InterpolationType = ..., epicK: int = ..., epicSigma: float = ..., epicLambda: float = ..., ricSPSize: int = ..., ricSLICType: int = ..., use_post_proc: bool = ..., fgsLambda: float = ..., fgsSigma: float = ..., use_variational_refinement: bool = ...) -> cv2.UMat: ... @_typing.overload def calcOpticalFlowSF(from_: cv2.typing.MatLike, to: cv2.typing.MatLike, layers: int, averaging_block_size: int, max_flow: int, flow: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def calcOpticalFlowSF(from_: cv2.UMat, to: cv2.UMat, layers: int, averaging_block_size: int, max_flow: int, flow: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def calcOpticalFlowSF(from_: cv2.typing.MatLike, to: cv2.typing.MatLike, layers: int, averaging_block_size: int, max_flow: int, sigma_dist: float, sigma_color: float, postprocess_window: int, sigma_dist_fix: float, sigma_color_fix: float, occ_thr: float, upscale_averaging_radius: int, upscale_sigma_dist: float, upscale_sigma_color: float, speed_up_thr: float, flow: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def calcOpticalFlowSF(from_: cv2.UMat, to: cv2.UMat, layers: int, averaging_block_size: int, max_flow: int, sigma_dist: float, sigma_color: float, postprocess_window: int, sigma_dist_fix: float, sigma_color_fix: float, occ_thr: float, upscale_averaging_radius: int, upscale_sigma_dist: float, upscale_sigma_color: float, speed_up_thr: float, flow: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def calcOpticalFlowSparseRLOF(prevImg: cv2.typing.MatLike, nextImg: cv2.typing.MatLike, prevPts: cv2.typing.MatLike, nextPts: cv2.typing.MatLike, status: cv2.typing.MatLike | None = ..., err: cv2.typing.MatLike | None = ..., rlofParam: RLOFOpticalFlowParameter = ..., forwardBackwardThreshold: float = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def calcOpticalFlowSparseRLOF(prevImg: cv2.UMat, nextImg: cv2.UMat, prevPts: cv2.UMat, nextPts: cv2.UMat, status: cv2.UMat | None = ..., err: cv2.UMat | None = ..., rlofParam: RLOFOpticalFlowParameter = ..., forwardBackwardThreshold: float = ...) -> tuple[cv2.UMat, cv2.UMat, cv2.UMat]: ... @_typing.overload def calcOpticalFlowSparseToDense(from_: cv2.typing.MatLike, to: cv2.typing.MatLike, flow: cv2.typing.MatLike | None = ..., grid_step: int = ..., k: int = ..., sigma: float = ..., use_post_proc: bool = ..., fgs_lambda: float = ..., fgs_sigma: float = ...) -> cv2.typing.MatLike: ... @_typing.overload def calcOpticalFlowSparseToDense(from_: cv2.UMat, to: cv2.UMat, flow: cv2.UMat | None = ..., grid_step: int = ..., k: int = ..., sigma: float = ..., use_post_proc: bool = ..., fgs_lambda: float = ..., fgs_sigma: float = ...) -> cv2.UMat: ... def createOptFlow_DeepFlow() -> cv2.DenseOpticalFlow: ... def createOptFlow_DenseRLOF() -> cv2.DenseOpticalFlow: ... def createOptFlow_DualTVL1() -> DualTVL1OpticalFlow: ... def createOptFlow_Farneback() -> cv2.DenseOpticalFlow: ... def createOptFlow_PCAFlow() -> cv2.DenseOpticalFlow: ... def createOptFlow_SimpleFlow() -> cv2.DenseOpticalFlow: ... def createOptFlow_SparseRLOF() -> cv2.SparseOpticalFlow: ... def createOptFlow_SparseToDense() -> cv2.DenseOpticalFlow: ...