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rattatwinko
286
venv/lib/python3.12/site-packages/cv2/optflow/__init__.pyi
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286
venv/lib/python3.12/site-packages/cv2/optflow/__init__.pyi
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__all__: list[str] = []
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import cv2
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import cv2.typing
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import typing as _typing
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# Enumerations
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SR_FIXED: int
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SR_CROSS: int
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SupportRegionType = int
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"""One of [SR_FIXED, SR_CROSS]"""
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ST_STANDART: int
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ST_BILINEAR: int
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SolverType = int
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"""One of [ST_STANDART, ST_BILINEAR]"""
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INTERP_GEO: int
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INTERP_EPIC: int
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INTERP_RIC: int
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InterpolationType = int
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"""One of [INTERP_GEO, INTERP_EPIC, INTERP_RIC]"""
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GPC_DESCRIPTOR_DCT: int
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GPC_DESCRIPTOR_WHT: int
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GPCDescType = int
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"""One of [GPC_DESCRIPTOR_DCT, GPC_DESCRIPTOR_WHT]"""
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# Classes
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class DualTVL1OpticalFlow(cv2.DenseOpticalFlow):
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# Functions
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def getTau(self) -> float: ...
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def setTau(self, val: float) -> None: ...
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def getLambda(self) -> float: ...
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def setLambda(self, val: float) -> None: ...
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def getTheta(self) -> float: ...
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def setTheta(self, val: float) -> None: ...
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def getGamma(self) -> float: ...
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def setGamma(self, val: float) -> None: ...
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def getScalesNumber(self) -> int: ...
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def setScalesNumber(self, val: int) -> None: ...
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def getWarpingsNumber(self) -> int: ...
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def setWarpingsNumber(self, val: int) -> None: ...
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def getEpsilon(self) -> float: ...
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def setEpsilon(self, val: float) -> None: ...
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def getInnerIterations(self) -> int: ...
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def setInnerIterations(self, val: int) -> None: ...
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def getOuterIterations(self) -> int: ...
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def setOuterIterations(self, val: int) -> None: ...
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def getUseInitialFlow(self) -> bool: ...
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def setUseInitialFlow(self, val: bool) -> None: ...
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def getScaleStep(self) -> float: ...
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def setScaleStep(self, val: float) -> None: ...
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def getMedianFiltering(self) -> int: ...
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def setMedianFiltering(self, val: int) -> None: ...
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@classmethod
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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: ...
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class PCAPrior:
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...
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class OpticalFlowPCAFlow(cv2.DenseOpticalFlow):
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...
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class RLOFOpticalFlowParameter:
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# Functions
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def setUseMEstimator(self, val: bool) -> None: ...
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def setSolverType(self, val: SolverType) -> None: ...
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def getSolverType(self) -> SolverType: ...
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def setSupportRegionType(self, val: SupportRegionType) -> None: ...
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def getSupportRegionType(self) -> SupportRegionType: ...
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def setNormSigma0(self, val: float) -> None: ...
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def getNormSigma0(self) -> float: ...
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def setNormSigma1(self, val: float) -> None: ...
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def getNormSigma1(self) -> float: ...
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def setSmallWinSize(self, val: int) -> None: ...
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def getSmallWinSize(self) -> int: ...
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def setLargeWinSize(self, val: int) -> None: ...
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def getLargeWinSize(self) -> int: ...
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def setCrossSegmentationThreshold(self, val: int) -> None: ...
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def getCrossSegmentationThreshold(self) -> int: ...
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def setMaxLevel(self, val: int) -> None: ...
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def getMaxLevel(self) -> int: ...
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def setUseInitialFlow(self, val: bool) -> None: ...
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def getUseInitialFlow(self) -> bool: ...
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def setUseIlluminationModel(self, val: bool) -> None: ...
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def getUseIlluminationModel(self) -> bool: ...
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def setUseGlobalMotionPrior(self, val: bool) -> None: ...
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def getUseGlobalMotionPrior(self) -> bool: ...
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def setMaxIteration(self, val: int) -> None: ...
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def getMaxIteration(self) -> int: ...
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def setMinEigenValue(self, val: float) -> None: ...
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def getMinEigenValue(self) -> float: ...
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def setGlobalMotionRansacThreshold(self, val: float) -> None: ...
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def getGlobalMotionRansacThreshold(self) -> float: ...
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@classmethod
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def create(cls) -> RLOFOpticalFlowParameter: ...
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class DenseRLOFOpticalFlow(cv2.DenseOpticalFlow):
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# Functions
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def setRLOFOpticalFlowParameter(self, val: RLOFOpticalFlowParameter) -> None: ...
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def getRLOFOpticalFlowParameter(self) -> RLOFOpticalFlowParameter: ...
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def setForwardBackward(self, val: float) -> None: ...
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def getForwardBackward(self) -> float: ...
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def getGridStep(self) -> cv2.typing.Size: ...
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def setGridStep(self, val: cv2.typing.Size) -> None: ...
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def setInterpolation(self, val: InterpolationType) -> None: ...
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def getInterpolation(self) -> InterpolationType: ...
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def getEPICK(self) -> int: ...
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def setEPICK(self, val: int) -> None: ...
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def getEPICSigma(self) -> float: ...
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def setEPICSigma(self, val: float) -> None: ...
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def getEPICLambda(self) -> float: ...
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def setEPICLambda(self, val: float) -> None: ...
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def getFgsLambda(self) -> float: ...
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def setFgsLambda(self, val: float) -> None: ...
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def getFgsSigma(self) -> float: ...
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def setFgsSigma(self, val: float) -> None: ...
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def setUsePostProc(self, val: bool) -> None: ...
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def getUsePostProc(self) -> bool: ...
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def setUseVariationalRefinement(self, val: bool) -> None: ...
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def getUseVariationalRefinement(self) -> bool: ...
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def setRICSPSize(self, val: int) -> None: ...
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def getRICSPSize(self) -> int: ...
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def setRICSLICType(self, val: int) -> None: ...
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def getRICSLICType(self) -> int: ...
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@classmethod
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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: ...
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class SparseRLOFOpticalFlow(cv2.SparseOpticalFlow):
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# Functions
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def setRLOFOpticalFlowParameter(self, val: RLOFOpticalFlowParameter) -> None: ...
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def getRLOFOpticalFlowParameter(self) -> RLOFOpticalFlowParameter: ...
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def setForwardBackward(self, val: float) -> None: ...
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def getForwardBackward(self) -> float: ...
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@classmethod
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def create(cls, rlofParam: RLOFOpticalFlowParameter = ..., forwardBackwardThreshold: float = ...) -> SparseRLOFOpticalFlow: ...
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class GPCPatchDescriptor:
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...
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class GPCPatchSample:
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...
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class GPCTrainingSamples:
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...
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class GPCTree(cv2.Algorithm):
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...
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class GPCDetails:
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...
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# Functions
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@_typing.overload
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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: ...
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@_typing.overload
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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: ...
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@_typing.overload
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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: ...
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@_typing.overload
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def calcOpticalFlowSF(from_: cv2.UMat, to: cv2.UMat, layers: int, averaging_block_size: int, max_flow: int, flow: cv2.UMat | None = ...) -> cv2.UMat: ...
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@_typing.overload
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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: ...
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@_typing.overload
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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: ...
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@_typing.overload
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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]: ...
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@_typing.overload
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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]: ...
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@_typing.overload
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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: ...
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@_typing.overload
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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: ...
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def createOptFlow_DeepFlow() -> cv2.DenseOpticalFlow: ...
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def createOptFlow_DenseRLOF() -> cv2.DenseOpticalFlow: ...
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def createOptFlow_DualTVL1() -> DualTVL1OpticalFlow: ...
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def createOptFlow_Farneback() -> cv2.DenseOpticalFlow: ...
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def createOptFlow_PCAFlow() -> cv2.DenseOpticalFlow: ...
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def createOptFlow_SimpleFlow() -> cv2.DenseOpticalFlow: ...
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def createOptFlow_SparseRLOF() -> cv2.SparseOpticalFlow: ...
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def createOptFlow_SparseToDense() -> cv2.DenseOpticalFlow: ...
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