| __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]: ... |
|
|
|
|
|
|
