__all__: list[str] = [] import cv2 import cv2.typing import typing as _typing from cv2.ximgproc import segmentation as segmentation # Enumerations THINNING_ZHANGSUEN: int THINNING_GUOHALL: int ThinningTypes = int """One of [THINNING_ZHANGSUEN, THINNING_GUOHALL]""" BINARIZATION_NIBLACK: int BINARIZATION_SAUVOLA: int BINARIZATION_WOLF: int BINARIZATION_NICK: int LocalBinarizationMethods = int """One of [BINARIZATION_NIBLACK, BINARIZATION_SAUVOLA, BINARIZATION_WOLF, BINARIZATION_NICK]""" DTF_NC: int DTF_IC: int DTF_RF: int GUIDED_FILTER: int AM_FILTER: int EdgeAwareFiltersList = int """One of [DTF_NC, DTF_IC, DTF_RF, GUIDED_FILTER, AM_FILTER]""" ARO_0_45: int ARO_45_90: int ARO_90_135: int ARO_315_0: int ARO_315_45: int ARO_45_135: int ARO_315_135: int ARO_CTR_HOR: int ARO_CTR_VER: int AngleRangeOption = int """One of [ARO_0_45, ARO_45_90, ARO_90_135, ARO_315_0, ARO_315_45, ARO_45_135, ARO_315_135, ARO_CTR_HOR, ARO_CTR_VER]""" FHT_MIN: int FHT_MAX: int FHT_ADD: int FHT_AVE: int HoughOp = int """One of [FHT_MIN, FHT_MAX, FHT_ADD, FHT_AVE]""" HDO_RAW: int HDO_DESKEW: int HoughDeskewOption = int """One of [HDO_RAW, HDO_DESKEW]""" SLIC: int SLICO: int MSLIC: int SLICType = int """One of [SLIC, SLICO, MSLIC]""" WMF_EXP: int WMF_IV1: int WMF_IV2: int WMF_COS: int WMF_JAC: int WMF_OFF: int WMFWeightType = int """One of [WMF_EXP, WMF_IV1, WMF_IV2, WMF_COS, WMF_JAC, WMF_OFF]""" EdgeDrawing_PREWITT: int EDGE_DRAWING_PREWITT: int EdgeDrawing_SOBEL: int EDGE_DRAWING_SOBEL: int EdgeDrawing_SCHARR: int EDGE_DRAWING_SCHARR: int EdgeDrawing_LSD: int EDGE_DRAWING_LSD: int EdgeDrawing_GradientOperator = int """One of [EdgeDrawing_PREWITT, EDGE_DRAWING_PREWITT, EdgeDrawing_SOBEL, EDGE_DRAWING_SOBEL, EdgeDrawing_SCHARR, EDGE_DRAWING_SCHARR, EdgeDrawing_LSD, EDGE_DRAWING_LSD]""" # Classes class DisparityFilter(cv2.Algorithm): # Functions @_typing.overload def filter(self, disparity_map_left: cv2.typing.MatLike, left_view: cv2.typing.MatLike, filtered_disparity_map: cv2.typing.MatLike | None = ..., disparity_map_right: cv2.typing.MatLike | None = ..., ROI: cv2.typing.Rect = ..., right_view: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def filter(self, disparity_map_left: cv2.UMat, left_view: cv2.UMat, filtered_disparity_map: cv2.UMat | None = ..., disparity_map_right: cv2.UMat | None = ..., ROI: cv2.typing.Rect = ..., right_view: cv2.UMat | None = ...) -> cv2.UMat: ... class DisparityWLSFilter(DisparityFilter): # Functions def getLambda(self) -> float: ... def setLambda(self, _lambda: float) -> None: ... def getSigmaColor(self) -> float: ... def setSigmaColor(self, _sigma_color: float) -> None: ... def getLRCthresh(self) -> int: ... def setLRCthresh(self, _LRC_thresh: int) -> None: ... def getDepthDiscontinuityRadius(self) -> int: ... def setDepthDiscontinuityRadius(self, _disc_radius: int) -> None: ... def getConfidenceMap(self) -> cv2.typing.MatLike: ... def getROI(self) -> cv2.typing.Rect: ... class EdgeDrawing(cv2.Algorithm): # Classes class Params: PFmode: bool EdgeDetectionOperator: int GradientThresholdValue: int AnchorThresholdValue: int ScanInterval: int MinPathLength: int Sigma: float SumFlag: bool NFAValidation: bool MinLineLength: int MaxDistanceBetweenTwoLines: float LineFitErrorThreshold: float MaxErrorThreshold: float # Functions def __init__(self) -> None: ... def read(self, fn: cv2.FileNode) -> None: ... def write(self, fs: cv2.FileStorage) -> None: ... # Functions @_typing.overload def detectEdges(self, src: cv2.typing.MatLike) -> None: ... @_typing.overload def detectEdges(self, src: cv2.UMat) -> None: ... @_typing.overload def getEdgeImage(self, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def getEdgeImage(self, dst: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def getGradientImage(self, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def getGradientImage(self, dst: cv2.UMat | None = ...) -> cv2.UMat: ... def getSegments(self) -> _typing.Sequence[_typing.Sequence[cv2.typing.Point]]: ... def getSegmentIndicesOfLines(self) -> _typing.Sequence[int]: ... @_typing.overload def detectLines(self, lines: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def detectLines(self, lines: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def detectEllipses(self, ellipses: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def detectEllipses(self, ellipses: cv2.UMat | None = ...) -> cv2.UMat: ... def setParams(self, parameters: EdgeDrawing.Params) -> None: ... class DTFilter(cv2.Algorithm): # Functions @_typing.overload def filter(self, src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., dDepth: int = ...) -> cv2.typing.MatLike: ... @_typing.overload def filter(self, src: cv2.UMat, dst: cv2.UMat | None = ..., dDepth: int = ...) -> cv2.UMat: ... class GuidedFilter(cv2.Algorithm): # Functions @_typing.overload def filter(self, src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., dDepth: int = ...) -> cv2.typing.MatLike: ... @_typing.overload def filter(self, src: cv2.UMat, dst: cv2.UMat | None = ..., dDepth: int = ...) -> cv2.UMat: ... class AdaptiveManifoldFilter(cv2.Algorithm): # Functions @_typing.overload def filter(self, src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., joint: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def filter(self, src: cv2.UMat, dst: cv2.UMat | None = ..., joint: cv2.UMat | None = ...) -> cv2.UMat: ... def collectGarbage(self) -> None: ... @classmethod def create(cls) -> AdaptiveManifoldFilter: ... class FastBilateralSolverFilter(cv2.Algorithm): # Functions @_typing.overload def filter(self, src: cv2.typing.MatLike, confidence: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def filter(self, src: cv2.UMat, confidence: cv2.UMat, dst: cv2.UMat | None = ...) -> cv2.UMat: ... class FastGlobalSmootherFilter(cv2.Algorithm): # Functions @_typing.overload def filter(self, src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def filter(self, src: cv2.UMat, dst: cv2.UMat | None = ...) -> cv2.UMat: ... class EdgeBoxes(cv2.Algorithm): # Functions @_typing.overload def getBoundingBoxes(self, edge_map: cv2.typing.MatLike, orientation_map: cv2.typing.MatLike, scores: cv2.typing.MatLike | None = ...) -> tuple[_typing.Sequence[cv2.typing.Rect], cv2.typing.MatLike]: ... @_typing.overload def getBoundingBoxes(self, edge_map: cv2.UMat, orientation_map: cv2.UMat, scores: cv2.UMat | None = ...) -> tuple[_typing.Sequence[cv2.typing.Rect], cv2.UMat]: ... def getAlpha(self) -> float: ... def setAlpha(self, value: float) -> None: ... def getBeta(self) -> float: ... def setBeta(self, value: float) -> None: ... def getEta(self) -> float: ... def setEta(self, value: float) -> None: ... def getMinScore(self) -> float: ... def setMinScore(self, value: float) -> None: ... def getMaxBoxes(self) -> int: ... def setMaxBoxes(self, value: int) -> None: ... def getEdgeMinMag(self) -> float: ... def setEdgeMinMag(self, value: float) -> None: ... def getEdgeMergeThr(self) -> float: ... def setEdgeMergeThr(self, value: float) -> None: ... def getClusterMinMag(self) -> float: ... def setClusterMinMag(self, value: float) -> None: ... def getMaxAspectRatio(self) -> float: ... def setMaxAspectRatio(self, value: float) -> None: ... def getMinBoxArea(self) -> float: ... def setMinBoxArea(self, value: float) -> None: ... def getGamma(self) -> float: ... def setGamma(self, value: float) -> None: ... def getKappa(self) -> float: ... def setKappa(self, value: float) -> None: ... class FastLineDetector(cv2.Algorithm): # Functions @_typing.overload def detect(self, image: cv2.typing.MatLike, lines: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def detect(self, image: cv2.UMat, lines: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def drawSegments(self, image: cv2.typing.MatLike, lines: cv2.typing.MatLike, draw_arrow: bool = ..., linecolor: cv2.typing.Scalar = ..., linethickness: int = ...) -> cv2.typing.MatLike: ... @_typing.overload def drawSegments(self, image: cv2.UMat, lines: cv2.UMat, draw_arrow: bool = ..., linecolor: cv2.typing.Scalar = ..., linethickness: int = ...) -> cv2.UMat: ... class ContourFitting(cv2.Algorithm): # Functions @_typing.overload def estimateTransformation(self, src: cv2.typing.MatLike, dst: cv2.typing.MatLike, alphaPhiST: cv2.typing.MatLike | None = ..., fdContour: bool = ...) -> tuple[cv2.typing.MatLike, float]: ... @_typing.overload def estimateTransformation(self, src: cv2.UMat, dst: cv2.UMat, alphaPhiST: cv2.UMat | None = ..., fdContour: bool = ...) -> tuple[cv2.UMat, float]: ... def setCtrSize(self, n: int) -> None: ... def setFDSize(self, n: int) -> None: ... def getCtrSize(self) -> int: ... def getFDSize(self) -> int: ... class SuperpixelLSC(cv2.Algorithm): # Functions def getNumberOfSuperpixels(self) -> int: ... def iterate(self, num_iterations: int = ...) -> None: ... @_typing.overload def getLabels(self, labels_out: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def getLabels(self, labels_out: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def getLabelContourMask(self, image: cv2.typing.MatLike | None = ..., thick_line: bool = ...) -> cv2.typing.MatLike: ... @_typing.overload def getLabelContourMask(self, image: cv2.UMat | None = ..., thick_line: bool = ...) -> cv2.UMat: ... def enforceLabelConnectivity(self, min_element_size: int = ...) -> None: ... class RidgeDetectionFilter(cv2.Algorithm): # Functions @classmethod def create(cls, ddepth: int = ..., dx: int = ..., dy: int = ..., ksize: int = ..., out_dtype: int = ..., scale: float = ..., delta: float = ..., borderType: int = ...) -> RidgeDetectionFilter: ... @_typing.overload def getRidgeFilteredImage(self, _img: cv2.typing.MatLike, out: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def getRidgeFilteredImage(self, _img: cv2.UMat, out: cv2.UMat | None = ...) -> cv2.UMat: ... class ScanSegment(cv2.Algorithm): # Functions def getNumberOfSuperpixels(self) -> int: ... @_typing.overload def iterate(self, img: cv2.typing.MatLike) -> None: ... @_typing.overload def iterate(self, img: cv2.UMat) -> None: ... @_typing.overload def getLabels(self, labels_out: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def getLabels(self, labels_out: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def getLabelContourMask(self, image: cv2.typing.MatLike | None = ..., thick_line: bool = ...) -> cv2.typing.MatLike: ... @_typing.overload def getLabelContourMask(self, image: cv2.UMat | None = ..., thick_line: bool = ...) -> cv2.UMat: ... class SuperpixelSEEDS(cv2.Algorithm): # Functions def getNumberOfSuperpixels(self) -> int: ... @_typing.overload def iterate(self, img: cv2.typing.MatLike, num_iterations: int = ...) -> None: ... @_typing.overload def iterate(self, img: cv2.UMat, num_iterations: int = ...) -> None: ... @_typing.overload def getLabels(self, labels_out: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def getLabels(self, labels_out: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def getLabelContourMask(self, image: cv2.typing.MatLike | None = ..., thick_line: bool = ...) -> cv2.typing.MatLike: ... @_typing.overload def getLabelContourMask(self, image: cv2.UMat | None = ..., thick_line: bool = ...) -> cv2.UMat: ... class SuperpixelSLIC(cv2.Algorithm): # Functions def getNumberOfSuperpixels(self) -> int: ... def iterate(self, num_iterations: int = ...) -> None: ... @_typing.overload def getLabels(self, labels_out: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def getLabels(self, labels_out: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def getLabelContourMask(self, image: cv2.typing.MatLike | None = ..., thick_line: bool = ...) -> cv2.typing.MatLike: ... @_typing.overload def getLabelContourMask(self, image: cv2.UMat | None = ..., thick_line: bool = ...) -> cv2.UMat: ... def enforceLabelConnectivity(self, min_element_size: int = ...) -> None: ... class SparseMatchInterpolator(cv2.Algorithm): # Functions @_typing.overload def interpolate(self, from_image: cv2.typing.MatLike, from_points: cv2.typing.MatLike, to_image: cv2.typing.MatLike, to_points: cv2.typing.MatLike, dense_flow: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def interpolate(self, from_image: cv2.UMat, from_points: cv2.UMat, to_image: cv2.UMat, to_points: cv2.UMat, dense_flow: cv2.UMat | None = ...) -> cv2.UMat: ... class EdgeAwareInterpolator(SparseMatchInterpolator): # Functions def setCostMap(self, _costMap: cv2.typing.MatLike) -> None: ... def setK(self, _k: int) -> None: ... def getK(self) -> int: ... def setSigma(self, _sigma: float) -> None: ... def getSigma(self) -> float: ... def setLambda(self, _lambda: float) -> None: ... def getLambda(self) -> float: ... def setUsePostProcessing(self, _use_post_proc: bool) -> None: ... def getUsePostProcessing(self) -> bool: ... def setFGSLambda(self, _lambda: float) -> None: ... def getFGSLambda(self) -> float: ... def setFGSSigma(self, _sigma: float) -> None: ... def getFGSSigma(self) -> float: ... class RICInterpolator(SparseMatchInterpolator): # Functions def setK(self, k: int = ...) -> None: ... def getK(self) -> int: ... def setCostMap(self, costMap: cv2.typing.MatLike) -> None: ... def setSuperpixelSize(self, spSize: int = ...) -> None: ... def getSuperpixelSize(self) -> int: ... def setSuperpixelNNCnt(self, spNN: int = ...) -> None: ... def getSuperpixelNNCnt(self) -> int: ... def setSuperpixelRuler(self, ruler: float = ...) -> None: ... def getSuperpixelRuler(self) -> float: ... def setSuperpixelMode(self, mode: int = ...) -> None: ... def getSuperpixelMode(self) -> int: ... def setAlpha(self, alpha: float = ...) -> None: ... def getAlpha(self) -> float: ... def setModelIter(self, modelIter: int = ...) -> None: ... def getModelIter(self) -> int: ... def setRefineModels(self, refineModles: bool = ...) -> None: ... def getRefineModels(self) -> bool: ... def setMaxFlow(self, maxFlow: float = ...) -> None: ... def getMaxFlow(self) -> float: ... def setUseVariationalRefinement(self, use_variational_refinement: bool = ...) -> None: ... def getUseVariationalRefinement(self) -> bool: ... def setUseGlobalSmootherFilter(self, use_FGS: bool = ...) -> None: ... def getUseGlobalSmootherFilter(self) -> bool: ... def setFGSLambda(self, lambda_: float = ...) -> None: ... def getFGSLambda(self) -> float: ... def setFGSSigma(self, sigma: float = ...) -> None: ... def getFGSSigma(self) -> float: ... class RFFeatureGetter(cv2.Algorithm): # Functions def getFeatures(self, src: cv2.typing.MatLike, features: cv2.typing.MatLike, gnrmRad: int, gsmthRad: int, shrink: int, outNum: int, gradNum: int) -> None: ... class StructuredEdgeDetection(cv2.Algorithm): # Functions @_typing.overload def detectEdges(self, src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def detectEdges(self, src: cv2.UMat, dst: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def computeOrientation(self, src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def computeOrientation(self, src: cv2.UMat, dst: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def edgesNms(self, edge_image: cv2.typing.MatLike, orientation_image: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., r: int = ..., s: int = ..., m: float = ..., isParallel: bool = ...) -> cv2.typing.MatLike: ... @_typing.overload def edgesNms(self, edge_image: cv2.UMat, orientation_image: cv2.UMat, dst: cv2.UMat | None = ..., r: int = ..., s: int = ..., m: float = ..., isParallel: bool = ...) -> cv2.UMat: ... # Functions @_typing.overload def FastHoughTransform(src: cv2.typing.MatLike, dstMatDepth: int, dst: cv2.typing.MatLike | None = ..., angleRange: int = ..., op: int = ..., makeSkew: int = ...) -> cv2.typing.MatLike: ... @_typing.overload def FastHoughTransform(src: cv2.UMat, dstMatDepth: int, dst: cv2.UMat | None = ..., angleRange: int = ..., op: int = ..., makeSkew: int = ...) -> cv2.UMat: ... @_typing.overload def GradientDericheX(op: cv2.typing.MatLike, alpha: float, omega: float, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def GradientDericheX(op: cv2.UMat, alpha: float, omega: float, dst: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def GradientDericheY(op: cv2.typing.MatLike, alpha: float, omega: float, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def GradientDericheY(op: cv2.UMat, alpha: float, omega: float, dst: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def HoughPoint2Line(houghPoint: cv2.typing.Point, srcImgInfo: cv2.typing.MatLike, angleRange: int = ..., makeSkew: int = ..., rules: int = ...) -> cv2.typing.Vec4i: ... @_typing.overload def HoughPoint2Line(houghPoint: cv2.typing.Point, srcImgInfo: cv2.UMat, angleRange: int = ..., makeSkew: int = ..., rules: int = ...) -> cv2.typing.Vec4i: ... @_typing.overload def PeiLinNormalization(I: cv2.typing.MatLike, T: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def PeiLinNormalization(I: cv2.UMat, T: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def RadonTransform(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., theta: float = ..., start_angle: float = ..., end_angle: float = ..., crop: bool = ..., norm: bool = ...) -> cv2.typing.MatLike: ... @_typing.overload def RadonTransform(src: cv2.UMat, dst: cv2.UMat | None = ..., theta: float = ..., start_angle: float = ..., end_angle: float = ..., crop: bool = ..., norm: bool = ...) -> cv2.UMat: ... @_typing.overload def amFilter(joint: cv2.typing.MatLike, src: cv2.typing.MatLike, sigma_s: float, sigma_r: float, dst: cv2.typing.MatLike | None = ..., adjust_outliers: bool = ...) -> cv2.typing.MatLike: ... @_typing.overload def amFilter(joint: cv2.UMat, src: cv2.UMat, sigma_s: float, sigma_r: float, dst: cv2.UMat | None = ..., adjust_outliers: bool = ...) -> cv2.UMat: ... @_typing.overload def anisotropicDiffusion(src: cv2.typing.MatLike, alpha: float, K: float, niters: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def anisotropicDiffusion(src: cv2.UMat, alpha: float, K: float, niters: int, dst: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def bilateralTextureFilter(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., fr: int = ..., numIter: int = ..., sigmaAlpha: float = ..., sigmaAvg: float = ...) -> cv2.typing.MatLike: ... @_typing.overload def bilateralTextureFilter(src: cv2.UMat, dst: cv2.UMat | None = ..., fr: int = ..., numIter: int = ..., sigmaAlpha: float = ..., sigmaAvg: float = ...) -> cv2.UMat: ... @_typing.overload def colorMatchTemplate(img: cv2.typing.MatLike, templ: cv2.typing.MatLike, result: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def colorMatchTemplate(img: cv2.UMat, templ: cv2.UMat, result: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def computeBadPixelPercent(GT: cv2.typing.MatLike, src: cv2.typing.MatLike, ROI: cv2.typing.Rect, thresh: int = ...) -> float: ... @_typing.overload def computeBadPixelPercent(GT: cv2.UMat, src: cv2.UMat, ROI: cv2.typing.Rect, thresh: int = ...) -> float: ... @_typing.overload def computeMSE(GT: cv2.typing.MatLike, src: cv2.typing.MatLike, ROI: cv2.typing.Rect) -> float: ... @_typing.overload def computeMSE(GT: cv2.UMat, src: cv2.UMat, ROI: cv2.typing.Rect) -> float: ... @_typing.overload def contourSampling(src: cv2.typing.MatLike, nbElt: int, out: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def contourSampling(src: cv2.UMat, nbElt: int, out: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def covarianceEstimation(src: cv2.typing.MatLike, windowRows: int, windowCols: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def covarianceEstimation(src: cv2.UMat, windowRows: int, windowCols: int, dst: cv2.UMat | None = ...) -> cv2.UMat: ... def createAMFilter(sigma_s: float, sigma_r: float, adjust_outliers: bool = ...) -> AdaptiveManifoldFilter: ... def createContourFitting(ctr: int = ..., fd: int = ...) -> ContourFitting: ... @_typing.overload def createDTFilter(guide: cv2.typing.MatLike, sigmaSpatial: float, sigmaColor: float, mode: int = ..., numIters: int = ...) -> DTFilter: ... @_typing.overload def createDTFilter(guide: cv2.UMat, sigmaSpatial: float, sigmaColor: float, mode: int = ..., numIters: int = ...) -> DTFilter: ... def createDisparityWLSFilter(matcher_left: cv2.StereoMatcher) -> DisparityWLSFilter: ... def createDisparityWLSFilterGeneric(use_confidence: bool) -> DisparityWLSFilter: ... def createEdgeAwareInterpolator() -> EdgeAwareInterpolator: ... def createEdgeBoxes(alpha: float = ..., beta: float = ..., eta: float = ..., minScore: float = ..., maxBoxes: int = ..., edgeMinMag: float = ..., edgeMergeThr: float = ..., clusterMinMag: float = ..., maxAspectRatio: float = ..., minBoxArea: float = ..., gamma: float = ..., kappa: float = ...) -> EdgeBoxes: ... def createEdgeDrawing() -> EdgeDrawing: ... @_typing.overload def createFastBilateralSolverFilter(guide: cv2.typing.MatLike, sigma_spatial: float, sigma_luma: float, sigma_chroma: float, lambda_: float = ..., num_iter: int = ..., max_tol: float = ...) -> FastBilateralSolverFilter: ... @_typing.overload def createFastBilateralSolverFilter(guide: cv2.UMat, sigma_spatial: float, sigma_luma: float, sigma_chroma: float, lambda_: float = ..., num_iter: int = ..., max_tol: float = ...) -> FastBilateralSolverFilter: ... @_typing.overload def createFastGlobalSmootherFilter(guide: cv2.typing.MatLike, lambda_: float, sigma_color: float, lambda_attenuation: float = ..., num_iter: int = ...) -> FastGlobalSmootherFilter: ... @_typing.overload def createFastGlobalSmootherFilter(guide: cv2.UMat, lambda_: float, sigma_color: float, lambda_attenuation: float = ..., num_iter: int = ...) -> FastGlobalSmootherFilter: ... def createFastLineDetector(length_threshold: int = ..., distance_threshold: float = ..., canny_th1: float = ..., canny_th2: float = ..., canny_aperture_size: int = ..., do_merge: bool = ...) -> FastLineDetector: ... @_typing.overload def createGuidedFilter(guide: cv2.typing.MatLike, radius: int, eps: float, scale: float = ...) -> GuidedFilter: ... @_typing.overload def createGuidedFilter(guide: cv2.UMat, radius: int, eps: float, scale: float = ...) -> GuidedFilter: ... @_typing.overload def createQuaternionImage(img: cv2.typing.MatLike, qimg: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def createQuaternionImage(img: cv2.UMat, qimg: cv2.UMat | None = ...) -> cv2.UMat: ... def createRFFeatureGetter() -> RFFeatureGetter: ... def createRICInterpolator() -> RICInterpolator: ... def createRightMatcher(matcher_left: cv2.StereoMatcher) -> cv2.StereoMatcher: ... def createScanSegment(image_width: int, image_height: int, num_superpixels: int, slices: int = ..., merge_small: bool = ...) -> ScanSegment: ... def createStructuredEdgeDetection(model: str, howToGetFeatures: RFFeatureGetter = ...) -> StructuredEdgeDetection: ... @_typing.overload def createSuperpixelLSC(image: cv2.typing.MatLike, region_size: int = ..., ratio: float = ...) -> SuperpixelLSC: ... @_typing.overload def createSuperpixelLSC(image: cv2.UMat, region_size: int = ..., ratio: float = ...) -> SuperpixelLSC: ... def createSuperpixelSEEDS(image_width: int, image_height: int, image_channels: int, num_superpixels: int, num_levels: int, prior: int = ..., histogram_bins: int = ..., double_step: bool = ...) -> SuperpixelSEEDS: ... @_typing.overload def createSuperpixelSLIC(image: cv2.typing.MatLike, algorithm: int = ..., region_size: int = ..., ruler: float = ...) -> SuperpixelSLIC: ... @_typing.overload def createSuperpixelSLIC(image: cv2.UMat, algorithm: int = ..., region_size: int = ..., ruler: float = ...) -> SuperpixelSLIC: ... @_typing.overload def dtFilter(guide: cv2.typing.MatLike, src: cv2.typing.MatLike, sigmaSpatial: float, sigmaColor: float, dst: cv2.typing.MatLike | None = ..., mode: int = ..., numIters: int = ...) -> cv2.typing.MatLike: ... @_typing.overload def dtFilter(guide: cv2.UMat, src: cv2.UMat, sigmaSpatial: float, sigmaColor: float, dst: cv2.UMat | None = ..., mode: int = ..., numIters: int = ...) -> cv2.UMat: ... @_typing.overload def edgePreservingFilter(src: cv2.typing.MatLike, d: int, threshold: float, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def edgePreservingFilter(src: cv2.UMat, d: int, threshold: float, dst: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def fastBilateralSolverFilter(guide: cv2.typing.MatLike, src: cv2.typing.MatLike, confidence: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., sigma_spatial: float = ..., sigma_luma: float = ..., sigma_chroma: float = ..., lambda_: float = ..., num_iter: int = ..., max_tol: float = ...) -> cv2.typing.MatLike: ... @_typing.overload def fastBilateralSolverFilter(guide: cv2.UMat, src: cv2.UMat, confidence: cv2.UMat, dst: cv2.UMat | None = ..., sigma_spatial: float = ..., sigma_luma: float = ..., sigma_chroma: float = ..., lambda_: float = ..., num_iter: int = ..., max_tol: float = ...) -> cv2.UMat: ... @_typing.overload def fastGlobalSmootherFilter(guide: cv2.typing.MatLike, src: cv2.typing.MatLike, lambda_: float, sigma_color: float, dst: cv2.typing.MatLike | None = ..., lambda_attenuation: float = ..., num_iter: int = ...) -> cv2.typing.MatLike: ... @_typing.overload def fastGlobalSmootherFilter(guide: cv2.UMat, src: cv2.UMat, lambda_: float, sigma_color: float, dst: cv2.UMat | None = ..., lambda_attenuation: float = ..., num_iter: int = ...) -> cv2.UMat: ... @_typing.overload def findEllipses(image: cv2.typing.MatLike, ellipses: cv2.typing.MatLike | None = ..., scoreThreshold: float = ..., reliabilityThreshold: float = ..., centerDistanceThreshold: float = ...) -> cv2.typing.MatLike: ... @_typing.overload def findEllipses(image: cv2.UMat, ellipses: cv2.UMat | None = ..., scoreThreshold: float = ..., reliabilityThreshold: float = ..., centerDistanceThreshold: float = ...) -> cv2.UMat: ... @_typing.overload def fourierDescriptor(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., nbElt: int = ..., nbFD: int = ...) -> cv2.typing.MatLike: ... @_typing.overload def fourierDescriptor(src: cv2.UMat, dst: cv2.UMat | None = ..., nbElt: int = ..., nbFD: int = ...) -> cv2.UMat: ... @_typing.overload def getDisparityVis(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., scale: float = ...) -> cv2.typing.MatLike: ... @_typing.overload def getDisparityVis(src: cv2.UMat, dst: cv2.UMat | None = ..., scale: float = ...) -> cv2.UMat: ... @_typing.overload def guidedFilter(guide: cv2.typing.MatLike, src: cv2.typing.MatLike, radius: int, eps: float, dst: cv2.typing.MatLike | None = ..., dDepth: int = ..., scale: float = ...) -> cv2.typing.MatLike: ... @_typing.overload def guidedFilter(guide: cv2.UMat, src: cv2.UMat, radius: int, eps: float, dst: cv2.UMat | None = ..., dDepth: int = ..., scale: float = ...) -> cv2.UMat: ... @_typing.overload def jointBilateralFilter(joint: cv2.typing.MatLike, src: cv2.typing.MatLike, d: int, sigmaColor: float, sigmaSpace: float, dst: cv2.typing.MatLike | None = ..., borderType: int = ...) -> cv2.typing.MatLike: ... @_typing.overload def jointBilateralFilter(joint: cv2.UMat, src: cv2.UMat, d: int, sigmaColor: float, sigmaSpace: float, dst: cv2.UMat | None = ..., borderType: int = ...) -> cv2.UMat: ... @_typing.overload def l0Smooth(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., lambda_: float = ..., kappa: float = ...) -> cv2.typing.MatLike: ... @_typing.overload def l0Smooth(src: cv2.UMat, dst: cv2.UMat | None = ..., lambda_: float = ..., kappa: float = ...) -> cv2.UMat: ... @_typing.overload def niBlackThreshold(_src: cv2.typing.MatLike, maxValue: float, type: int, blockSize: int, k: float, _dst: cv2.typing.MatLike | None = ..., binarizationMethod: int = ..., r: float = ...) -> cv2.typing.MatLike: ... @_typing.overload def niBlackThreshold(_src: cv2.UMat, maxValue: float, type: int, blockSize: int, k: float, _dst: cv2.UMat | None = ..., binarizationMethod: int = ..., r: float = ...) -> cv2.UMat: ... @_typing.overload def qconj(qimg: cv2.typing.MatLike, qcimg: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def qconj(qimg: cv2.UMat, qcimg: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def qdft(img: cv2.typing.MatLike, flags: int, sideLeft: bool, qimg: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def qdft(img: cv2.UMat, flags: int, sideLeft: bool, qimg: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def qmultiply(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def qmultiply(src1: cv2.UMat, src2: cv2.UMat, dst: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def qunitary(qimg: cv2.typing.MatLike, qnimg: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def qunitary(qimg: cv2.UMat, qnimg: cv2.UMat | None = ...) -> cv2.UMat: ... @_typing.overload def readGT(src_path: str, dst: cv2.typing.MatLike | None = ...) -> tuple[int, cv2.typing.MatLike]: ... @_typing.overload def readGT(src_path: str, dst: cv2.UMat | None = ...) -> tuple[int, cv2.UMat]: ... @_typing.overload def rollingGuidanceFilter(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., d: int = ..., sigmaColor: float = ..., sigmaSpace: float = ..., numOfIter: int = ..., borderType: int = ...) -> cv2.typing.MatLike: ... @_typing.overload def rollingGuidanceFilter(src: cv2.UMat, dst: cv2.UMat | None = ..., d: int = ..., sigmaColor: float = ..., sigmaSpace: float = ..., numOfIter: int = ..., borderType: int = ...) -> cv2.UMat: ... @_typing.overload def thinning(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., thinningType: int = ...) -> cv2.typing.MatLike: ... @_typing.overload def thinning(src: cv2.UMat, dst: cv2.UMat | None = ..., thinningType: int = ...) -> cv2.UMat: ... @_typing.overload def transformFD(src: cv2.typing.MatLike, t: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., fdContour: bool = ...) -> cv2.typing.MatLike: ... @_typing.overload def transformFD(src: cv2.UMat, t: cv2.UMat, dst: cv2.UMat | None = ..., fdContour: bool = ...) -> cv2.UMat: ... @_typing.overload def weightedMedianFilter(joint: cv2.typing.MatLike, src: cv2.typing.MatLike, r: int, dst: cv2.typing.MatLike | None = ..., sigma: float = ..., weightType: int = ..., mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ... @_typing.overload def weightedMedianFilter(joint: cv2.UMat, src: cv2.UMat, r: int, dst: cv2.UMat | None = ..., sigma: float = ..., weightType: int = ..., mask: cv2.UMat | None = ...) -> cv2.UMat: ...