__all__: list[str] = [] import cv2 import cv2.gapi import cv2.gapi.ie import cv2.gapi.onnx import cv2.gapi.ov import cv2.typing import numpy import typing as _typing # Enumerations TEST_CUSTOM: int TEST_EQ: int TEST_NE: int TEST_LE: int TEST_LT: int TEST_GE: int TEST_GT: int TestOp = int """One of [TEST_CUSTOM, TEST_EQ, TEST_NE, TEST_LE, TEST_LT, TEST_GE, TEST_GT]""" WAVE_CORRECT_HORIZ: int WAVE_CORRECT_VERT: int WAVE_CORRECT_AUTO: int WaveCorrectKind = int """One of [WAVE_CORRECT_HORIZ, WAVE_CORRECT_VERT, WAVE_CORRECT_AUTO]""" OpaqueKind_CV_UNKNOWN: int OPAQUE_KIND_CV_UNKNOWN: int OpaqueKind_CV_BOOL: int OPAQUE_KIND_CV_BOOL: int OpaqueKind_CV_INT: int OPAQUE_KIND_CV_INT: int OpaqueKind_CV_INT64: int OPAQUE_KIND_CV_INT64: int OpaqueKind_CV_DOUBLE: int OPAQUE_KIND_CV_DOUBLE: int OpaqueKind_CV_FLOAT: int OPAQUE_KIND_CV_FLOAT: int OpaqueKind_CV_UINT64: int OPAQUE_KIND_CV_UINT64: int OpaqueKind_CV_STRING: int OPAQUE_KIND_CV_STRING: int OpaqueKind_CV_POINT: int OPAQUE_KIND_CV_POINT: int OpaqueKind_CV_POINT2F: int OPAQUE_KIND_CV_POINT2F: int OpaqueKind_CV_POINT3F: int OPAQUE_KIND_CV_POINT3F: int OpaqueKind_CV_SIZE: int OPAQUE_KIND_CV_SIZE: int OpaqueKind_CV_RECT: int OPAQUE_KIND_CV_RECT: int OpaqueKind_CV_SCALAR: int OPAQUE_KIND_CV_SCALAR: int OpaqueKind_CV_MAT: int OPAQUE_KIND_CV_MAT: int OpaqueKind_CV_DRAW_PRIM: int OPAQUE_KIND_CV_DRAW_PRIM: int OpaqueKind = int """One of [OpaqueKind_CV_UNKNOWN, OPAQUE_KIND_CV_UNKNOWN, OpaqueKind_CV_BOOL, OPAQUE_KIND_CV_BOOL, OpaqueKind_CV_INT, OPAQUE_KIND_CV_INT, OpaqueKind_CV_INT64, OPAQUE_KIND_CV_INT64, OpaqueKind_CV_DOUBLE, OPAQUE_KIND_CV_DOUBLE, OpaqueKind_CV_FLOAT, OPAQUE_KIND_CV_FLOAT, OpaqueKind_CV_UINT64, OPAQUE_KIND_CV_UINT64, OpaqueKind_CV_STRING, OPAQUE_KIND_CV_STRING, OpaqueKind_CV_POINT, OPAQUE_KIND_CV_POINT, OpaqueKind_CV_POINT2F, OPAQUE_KIND_CV_POINT2F, OpaqueKind_CV_POINT3F, OPAQUE_KIND_CV_POINT3F, OpaqueKind_CV_SIZE, OPAQUE_KIND_CV_SIZE, OpaqueKind_CV_RECT, OPAQUE_KIND_CV_RECT, OpaqueKind_CV_SCALAR, OPAQUE_KIND_CV_SCALAR, OpaqueKind_CV_MAT, OPAQUE_KIND_CV_MAT, OpaqueKind_CV_DRAW_PRIM, OPAQUE_KIND_CV_DRAW_PRIM]""" ArgKind_OPAQUE_VAL: int ARG_KIND_OPAQUE_VAL: int ArgKind_OPAQUE: int ARG_KIND_OPAQUE: int ArgKind_GOBJREF: int ARG_KIND_GOBJREF: int ArgKind_GMAT: int ARG_KIND_GMAT: int ArgKind_GMATP: int ARG_KIND_GMATP: int ArgKind_GFRAME: int ARG_KIND_GFRAME: int ArgKind_GSCALAR: int ARG_KIND_GSCALAR: int ArgKind_GARRAY: int ARG_KIND_GARRAY: int ArgKind_GOPAQUE: int ARG_KIND_GOPAQUE: int ArgKind = int """One of [ArgKind_OPAQUE_VAL, ARG_KIND_OPAQUE_VAL, ArgKind_OPAQUE, ARG_KIND_OPAQUE, ArgKind_GOBJREF, ARG_KIND_GOBJREF, ArgKind_GMAT, ARG_KIND_GMAT, ArgKind_GMATP, ARG_KIND_GMATP, ArgKind_GFRAME, ARG_KIND_GFRAME, ArgKind_GSCALAR, ARG_KIND_GSCALAR, ArgKind_GARRAY, ARG_KIND_GARRAY, ArgKind_GOPAQUE, ARG_KIND_GOPAQUE]""" Blender_NO: int BLENDER_NO: int Blender_FEATHER: int BLENDER_FEATHER: int Blender_MULTI_BAND: int BLENDER_MULTI_BAND: int ExposureCompensator_NO: int EXPOSURE_COMPENSATOR_NO: int ExposureCompensator_GAIN: int EXPOSURE_COMPENSATOR_GAIN: int ExposureCompensator_GAIN_BLOCKS: int EXPOSURE_COMPENSATOR_GAIN_BLOCKS: int ExposureCompensator_CHANNELS: int EXPOSURE_COMPENSATOR_CHANNELS: int ExposureCompensator_CHANNELS_BLOCKS: int EXPOSURE_COMPENSATOR_CHANNELS_BLOCKS: int SeamFinder_NO: int SEAM_FINDER_NO: int SeamFinder_VORONOI_SEAM: int SEAM_FINDER_VORONOI_SEAM: int SeamFinder_DP_SEAM: int SEAM_FINDER_DP_SEAM: int DpSeamFinder_COLOR: int DP_SEAM_FINDER_COLOR: int DpSeamFinder_COLOR_GRAD: int DP_SEAM_FINDER_COLOR_GRAD: int DpSeamFinder_CostFunction = int """One of [DpSeamFinder_COLOR, DP_SEAM_FINDER_COLOR, DpSeamFinder_COLOR_GRAD, DP_SEAM_FINDER_COLOR_GRAD]""" Timelapser_AS_IS: int TIMELAPSER_AS_IS: int Timelapser_CROP: int TIMELAPSER_CROP: int GraphCutSeamFinderBase_COST_COLOR: int GRAPH_CUT_SEAM_FINDER_BASE_COST_COLOR: int GraphCutSeamFinderBase_COST_COLOR_GRAD: int GRAPH_CUT_SEAM_FINDER_BASE_COST_COLOR_GRAD: int GraphCutSeamFinderBase_CostType = int """One of [GraphCutSeamFinderBase_COST_COLOR, GRAPH_CUT_SEAM_FINDER_BASE_COST_COLOR, GraphCutSeamFinderBase_COST_COLOR_GRAD, GRAPH_CUT_SEAM_FINDER_BASE_COST_COLOR_GRAD]""" TrackerSamplerCSC_MODE_INIT_POS: int TRACKER_SAMPLER_CSC_MODE_INIT_POS: int TrackerSamplerCSC_MODE_INIT_NEG: int TRACKER_SAMPLER_CSC_MODE_INIT_NEG: int TrackerSamplerCSC_MODE_TRACK_POS: int TRACKER_SAMPLER_CSC_MODE_TRACK_POS: int TrackerSamplerCSC_MODE_TRACK_NEG: int TRACKER_SAMPLER_CSC_MODE_TRACK_NEG: int TrackerSamplerCSC_MODE_DETECT: int TRACKER_SAMPLER_CSC_MODE_DETECT: int TrackerSamplerCSC_MODE = int """One of [TrackerSamplerCSC_MODE_INIT_POS, TRACKER_SAMPLER_CSC_MODE_INIT_POS, TrackerSamplerCSC_MODE_INIT_NEG, TRACKER_SAMPLER_CSC_MODE_INIT_NEG, TrackerSamplerCSC_MODE_TRACK_POS, TRACKER_SAMPLER_CSC_MODE_TRACK_POS, TrackerSamplerCSC_MODE_TRACK_NEG, TRACKER_SAMPLER_CSC_MODE_TRACK_NEG, TrackerSamplerCSC_MODE_DETECT, TRACKER_SAMPLER_CSC_MODE_DETECT]""" # Classes class Blender: # Functions @classmethod def createDefault(cls, type: int, try_gpu: bool = ...) -> Blender: ... @_typing.overload def prepare(self, corners: _typing.Sequence[cv2.typing.Point], sizes: _typing.Sequence[cv2.typing.Size]) -> None: ... @_typing.overload def prepare(self, dst_roi: cv2.typing.Rect) -> None: ... @_typing.overload def feed(self, img: cv2.typing.MatLike, mask: cv2.typing.MatLike, tl: cv2.typing.Point) -> None: ... @_typing.overload def feed(self, img: cv2.UMat, mask: cv2.UMat, tl: cv2.typing.Point) -> None: ... @_typing.overload def blend(self, dst: cv2.typing.MatLike, dst_mask: cv2.typing.MatLike) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def blend(self, dst: cv2.UMat, dst_mask: cv2.UMat) -> tuple[cv2.UMat, cv2.UMat]: ... class FeatherBlender(Blender): # Functions def __init__(self, sharpness: float = ...) -> None: ... def sharpness(self) -> float: ... def setSharpness(self, val: float) -> None: ... def prepare(self, dst_roi: cv2.typing.Rect) -> None: ... @_typing.overload def feed(self, img: cv2.typing.MatLike, mask: cv2.typing.MatLike, tl: cv2.typing.Point) -> None: ... @_typing.overload def feed(self, img: cv2.UMat, mask: cv2.UMat, tl: cv2.typing.Point) -> None: ... @_typing.overload def blend(self, dst: cv2.typing.MatLike, dst_mask: cv2.typing.MatLike) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def blend(self, dst: cv2.UMat, dst_mask: cv2.UMat) -> tuple[cv2.UMat, cv2.UMat]: ... def createWeightMaps(self, masks: _typing.Sequence[cv2.UMat], corners: _typing.Sequence[cv2.typing.Point], weight_maps: _typing.Sequence[cv2.UMat]) -> tuple[cv2.typing.Rect, _typing.Sequence[cv2.UMat]]: ... class MultiBandBlender(Blender): # Functions def __init__(self, try_gpu: int = ..., num_bands: int = ..., weight_type: int = ...) -> None: ... def numBands(self) -> int: ... def setNumBands(self, val: int) -> None: ... def prepare(self, dst_roi: cv2.typing.Rect) -> None: ... @_typing.overload def feed(self, img: cv2.typing.MatLike, mask: cv2.typing.MatLike, tl: cv2.typing.Point) -> None: ... @_typing.overload def feed(self, img: cv2.UMat, mask: cv2.UMat, tl: cv2.typing.Point) -> None: ... @_typing.overload def blend(self, dst: cv2.typing.MatLike, dst_mask: cv2.typing.MatLike) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ... @_typing.overload def blend(self, dst: cv2.UMat, dst_mask: cv2.UMat) -> tuple[cv2.UMat, cv2.UMat]: ... class CameraParams: focal: float aspect: float ppx: float ppy: float R: cv2.typing.MatLike t: cv2.typing.MatLike # Functions def K(self) -> cv2.typing.MatLike: ... class ExposureCompensator: # Functions @classmethod def createDefault(cls, type: int) -> ExposureCompensator: ... def feed(self, corners: _typing.Sequence[cv2.typing.Point], images: _typing.Sequence[cv2.UMat], masks: _typing.Sequence[cv2.UMat]) -> None: ... @_typing.overload def apply(self, index: int, corner: cv2.typing.Point, image: cv2.typing.MatLike, mask: cv2.typing.MatLike) -> cv2.typing.MatLike: ... @_typing.overload def apply(self, index: int, corner: cv2.typing.Point, image: cv2.UMat, mask: cv2.UMat) -> cv2.UMat: ... def getMatGains(self, arg1: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ... def setMatGains(self, arg1: _typing.Sequence[cv2.typing.MatLike]) -> None: ... def setUpdateGain(self, b: bool) -> None: ... def getUpdateGain(self) -> bool: ... class NoExposureCompensator(ExposureCompensator): # Functions @_typing.overload def apply(self, arg1: int, arg2: cv2.typing.Point, arg3: cv2.typing.MatLike, arg4: cv2.typing.MatLike) -> cv2.typing.MatLike: ... @_typing.overload def apply(self, arg1: int, arg2: cv2.typing.Point, arg3: cv2.UMat, arg4: cv2.UMat) -> cv2.UMat: ... def getMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ... def setMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike]) -> None: ... class GainCompensator(ExposureCompensator): # Functions @_typing.overload def __init__(self) -> None: ... @_typing.overload def __init__(self, nr_feeds: int) -> None: ... @_typing.overload def apply(self, index: int, corner: cv2.typing.Point, image: cv2.typing.MatLike, mask: cv2.typing.MatLike) -> cv2.typing.MatLike: ... @_typing.overload def apply(self, index: int, corner: cv2.typing.Point, image: cv2.UMat, mask: cv2.UMat) -> cv2.UMat: ... def getMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ... def setMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike]) -> None: ... def setNrFeeds(self, nr_feeds: int) -> None: ... def getNrFeeds(self) -> int: ... def setSimilarityThreshold(self, similarity_threshold: float) -> None: ... def getSimilarityThreshold(self) -> float: ... class ChannelsCompensator(ExposureCompensator): # Functions def __init__(self, nr_feeds: int = ...) -> None: ... @_typing.overload def apply(self, index: int, corner: cv2.typing.Point, image: cv2.typing.MatLike, mask: cv2.typing.MatLike) -> cv2.typing.MatLike: ... @_typing.overload def apply(self, index: int, corner: cv2.typing.Point, image: cv2.UMat, mask: cv2.UMat) -> cv2.UMat: ... def getMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ... def setMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike]) -> None: ... def setNrFeeds(self, nr_feeds: int) -> None: ... def getNrFeeds(self) -> int: ... def setSimilarityThreshold(self, similarity_threshold: float) -> None: ... def getSimilarityThreshold(self) -> float: ... class BlocksCompensator(ExposureCompensator): # Functions @_typing.overload def apply(self, index: int, corner: cv2.typing.Point, image: cv2.typing.MatLike, mask: cv2.typing.MatLike) -> cv2.typing.MatLike: ... @_typing.overload def apply(self, index: int, corner: cv2.typing.Point, image: cv2.UMat, mask: cv2.UMat) -> cv2.UMat: ... def getMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ... def setMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike]) -> None: ... def setNrFeeds(self, nr_feeds: int) -> None: ... def getNrFeeds(self) -> int: ... def setSimilarityThreshold(self, similarity_threshold: float) -> None: ... def getSimilarityThreshold(self) -> float: ... @_typing.overload def setBlockSize(self, width: int, height: int) -> None: ... @_typing.overload def setBlockSize(self, size: cv2.typing.Size) -> None: ... def getBlockSize(self) -> cv2.typing.Size: ... def setNrGainsFilteringIterations(self, nr_iterations: int) -> None: ... def getNrGainsFilteringIterations(self) -> int: ... class BlocksGainCompensator(BlocksCompensator): # Functions @_typing.overload def __init__(self, bl_width: int = ..., bl_height: int = ...) -> None: ... @_typing.overload def __init__(self, bl_width: int, bl_height: int, nr_feeds: int) -> None: ... @_typing.overload def apply(self, index: int, corner: cv2.typing.Point, image: cv2.typing.MatLike, mask: cv2.typing.MatLike) -> cv2.typing.MatLike: ... @_typing.overload def apply(self, index: int, corner: cv2.typing.Point, image: cv2.UMat, mask: cv2.UMat) -> cv2.UMat: ... def getMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ... def setMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike]) -> None: ... class BlocksChannelsCompensator(BlocksCompensator): # Functions def __init__(self, bl_width: int = ..., bl_height: int = ..., nr_feeds: int = ...) -> None: ... class ImageFeatures: img_idx: int img_size: cv2.typing.Size keypoints: _typing.Sequence[cv2.KeyPoint] descriptors: cv2.UMat # Functions def getKeypoints(self) -> _typing.Sequence[cv2.KeyPoint]: ... class MatchesInfo: src_img_idx: int dst_img_idx: int matches: _typing.Sequence[cv2.DMatch] inliers_mask: numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]] num_inliers: int H: cv2.typing.MatLike confidence: float # Functions def getMatches(self) -> _typing.Sequence[cv2.DMatch]: ... def getInliers(self) -> numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]]: ... class FeaturesMatcher: # Functions def apply(self, features1: ImageFeatures, features2: ImageFeatures) -> MatchesInfo: ... def apply2(self, features: _typing.Sequence[ImageFeatures], mask: cv2.UMat | None = ...) -> _typing.Sequence[MatchesInfo]: ... def isThreadSafe(self) -> bool: ... def collectGarbage(self) -> None: ... class BestOf2NearestMatcher(FeaturesMatcher): # Functions def __init__(self, try_use_gpu: bool = ..., match_conf: float = ..., num_matches_thresh1: int = ..., num_matches_thresh2: int = ..., matches_confindece_thresh: float = ...) -> None: ... def collectGarbage(self) -> None: ... @classmethod def create(cls, try_use_gpu: bool = ..., match_conf: float = ..., num_matches_thresh1: int = ..., num_matches_thresh2: int = ..., matches_confindece_thresh: float = ...) -> BestOf2NearestMatcher: ... class BestOf2NearestRangeMatcher(BestOf2NearestMatcher): # Functions def __init__(self, range_width: int = ..., try_use_gpu: bool = ..., match_conf: float = ..., num_matches_thresh1: int = ..., num_matches_thresh2: int = ...) -> None: ... class AffineBestOf2NearestMatcher(BestOf2NearestMatcher): # Functions def __init__(self, full_affine: bool = ..., try_use_gpu: bool = ..., match_conf: float = ..., num_matches_thresh1: int = ...) -> None: ... class Estimator: # Functions def apply(self, features: _typing.Sequence[ImageFeatures], pairwise_matches: _typing.Sequence[MatchesInfo], cameras: _typing.Sequence[CameraParams]) -> tuple[bool, _typing.Sequence[CameraParams]]: ... class HomographyBasedEstimator(Estimator): # Functions def __init__(self, is_focals_estimated: bool = ...) -> None: ... class AffineBasedEstimator(Estimator): # Functions def __init__(self) -> None: ... class BundleAdjusterBase(Estimator): # Functions def refinementMask(self) -> cv2.typing.MatLike: ... def setRefinementMask(self, mask: cv2.typing.MatLike) -> None: ... def confThresh(self) -> float: ... def setConfThresh(self, conf_thresh: float) -> None: ... def termCriteria(self) -> cv2.typing.TermCriteria: ... def setTermCriteria(self, term_criteria: cv2.typing.TermCriteria) -> None: ... class NoBundleAdjuster(BundleAdjusterBase): # Functions def __init__(self) -> None: ... class BundleAdjusterReproj(BundleAdjusterBase): # Functions def __init__(self) -> None: ... class BundleAdjusterRay(BundleAdjusterBase): # Functions def __init__(self) -> None: ... class BundleAdjusterAffine(BundleAdjusterBase): # Functions def __init__(self) -> None: ... class BundleAdjusterAffinePartial(BundleAdjusterBase): # Functions def __init__(self) -> None: ... class SeamFinder: # Functions def find(self, src: _typing.Sequence[cv2.UMat], corners: _typing.Sequence[cv2.typing.Point], masks: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ... @classmethod def createDefault(cls, type: int) -> SeamFinder: ... class NoSeamFinder(SeamFinder): # Functions def find(self, arg1: _typing.Sequence[cv2.UMat], arg2: _typing.Sequence[cv2.typing.Point], arg3: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ... class PairwiseSeamFinder(SeamFinder): # Functions def find(self, src: _typing.Sequence[cv2.UMat], corners: _typing.Sequence[cv2.typing.Point], masks: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ... class VoronoiSeamFinder(PairwiseSeamFinder): # Functions def find(self, src: _typing.Sequence[cv2.UMat], corners: _typing.Sequence[cv2.typing.Point], masks: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ... class DpSeamFinder(SeamFinder): # Functions def __init__(self, costFunc: str) -> None: ... def setCostFunction(self, val: str) -> None: ... class GraphCutSeamFinder: # Functions def __init__(self, cost_type: str, terminal_cost: float = ..., bad_region_penalty: float = ...) -> None: ... def find(self, src: _typing.Sequence[cv2.UMat], corners: _typing.Sequence[cv2.typing.Point], masks: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ... class Timelapser: # Functions @classmethod def createDefault(cls, type: int) -> Timelapser: ... def initialize(self, corners: _typing.Sequence[cv2.typing.Point], sizes: _typing.Sequence[cv2.typing.Size]) -> None: ... @_typing.overload def process(self, img: cv2.typing.MatLike, mask: cv2.typing.MatLike, tl: cv2.typing.Point) -> None: ... @_typing.overload def process(self, img: cv2.UMat, mask: cv2.UMat, tl: cv2.typing.Point) -> None: ... def getDst(self) -> cv2.UMat: ... class TimelapserCrop(Timelapser): ... class ProjectorBase: ... class SphericalProjector(ProjectorBase): # Functions def mapForward(self, x: float, y: float, u: float, v: float) -> None: ... def mapBackward(self, u: float, v: float, x: float, y: float) -> None: ... # Functions def calibrateRotatingCamera(Hs: _typing.Sequence[cv2.typing.MatLike], K: cv2.typing.MatLike | None = ...) -> tuple[bool, cv2.typing.MatLike]: ... @_typing.overload def computeImageFeatures(featuresFinder: cv2.Feature2D, images: _typing.Sequence[cv2.typing.MatLike], masks: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[ImageFeatures]: ... @_typing.overload def computeImageFeatures(featuresFinder: cv2.Feature2D, images: _typing.Sequence[cv2.UMat], masks: _typing.Sequence[cv2.UMat] | None = ...) -> _typing.Sequence[ImageFeatures]: ... @_typing.overload def computeImageFeatures2(featuresFinder: cv2.Feature2D, image: cv2.typing.MatLike, mask: cv2.typing.MatLike | None = ...) -> ImageFeatures: ... @_typing.overload def computeImageFeatures2(featuresFinder: cv2.Feature2D, image: cv2.UMat, mask: cv2.UMat | None = ...) -> ImageFeatures: ... @_typing.overload def createLaplacePyr(img: cv2.typing.MatLike, num_levels: int, pyr: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ... @_typing.overload def createLaplacePyr(img: cv2.UMat, num_levels: int, pyr: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ... @_typing.overload def createLaplacePyrGpu(img: cv2.typing.MatLike, num_levels: int, pyr: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ... @_typing.overload def createLaplacePyrGpu(img: cv2.UMat, num_levels: int, pyr: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ... @_typing.overload def createWeightMap(mask: cv2.typing.MatLike, sharpness: float, weight: cv2.typing.MatLike) -> cv2.typing.MatLike: ... @_typing.overload def createWeightMap(mask: cv2.UMat, sharpness: float, weight: cv2.UMat) -> cv2.UMat: ... def focalsFromHomography(H: cv2.typing.MatLike, f0: float, f1: float, f0_ok: bool, f1_ok: bool) -> None: ... def leaveBiggestComponent(features: _typing.Sequence[ImageFeatures], pairwise_matches: _typing.Sequence[MatchesInfo], conf_threshold: float) -> _typing.Sequence[int]: ... def matchesGraphAsString(paths: _typing.Sequence[str], pairwise_matches: _typing.Sequence[MatchesInfo], conf_threshold: float) -> str: ... @_typing.overload def normalizeUsingWeightMap(weight: cv2.typing.MatLike, src: cv2.typing.MatLike) -> cv2.typing.MatLike: ... @_typing.overload def normalizeUsingWeightMap(weight: cv2.UMat, src: cv2.UMat) -> cv2.UMat: ... def overlapRoi(tl1: cv2.typing.Point, tl2: cv2.typing.Point, sz1: cv2.typing.Size, sz2: cv2.typing.Size, roi: cv2.typing.Rect) -> bool: ... def restoreImageFromLaplacePyr(pyr: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ... def restoreImageFromLaplacePyrGpu(pyr: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ... @_typing.overload def resultRoi(corners: _typing.Sequence[cv2.typing.Point], images: _typing.Sequence[cv2.UMat]) -> cv2.typing.Rect: ... @_typing.overload def resultRoi(corners: _typing.Sequence[cv2.typing.Point], sizes: _typing.Sequence[cv2.typing.Size]) -> cv2.typing.Rect: ... def resultRoiIntersection(corners: _typing.Sequence[cv2.typing.Point], sizes: _typing.Sequence[cv2.typing.Size]) -> cv2.typing.Rect: ... def resultTl(corners: _typing.Sequence[cv2.typing.Point]) -> cv2.typing.Point: ... def selectRandomSubset(count: int, size: int, subset: _typing.Sequence[int]) -> None: ... def stitchingLogLevel() -> int: ... @_typing.overload def strip(params: cv2.gapi.ie.PyParams) -> cv2.gapi.GNetParam: ... @_typing.overload def strip(params: cv2.gapi.onnx.PyParams) -> cv2.gapi.GNetParam: ... @_typing.overload def strip(params: cv2.gapi.ov.PyParams) -> cv2.gapi.GNetParam: ... def waveCorrect(rmats: _typing.Sequence[cv2.typing.MatLike], kind: WaveCorrectKind) -> _typing.Sequence[cv2.typing.MatLike]: ...