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6306 lines
291 KiB
6306 lines
291 KiB
__all__: list[str] = []
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import cv2.aruco
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import cv2.cuda
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import cv2.dnn
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import cv2.gapi
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import cv2.gapi.ot
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import cv2.gapi.streaming
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import cv2.typing
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import numpy
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import typing as _typing
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from cv2 import Error as Error
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from cv2 import aruco as aruco
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from cv2 import barcode as barcode
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from cv2 import cuda as cuda
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from cv2 import detail as detail
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from cv2 import dnn as dnn
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from cv2 import fisheye as fisheye
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from cv2 import flann as flann
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from cv2 import gapi as gapi
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from cv2 import ipp as ipp
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from cv2 import ml as ml
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from cv2 import ocl as ocl
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from cv2 import ogl as ogl
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from cv2 import parallel as parallel
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from cv2 import samples as samples
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from cv2 import segmentation as segmentation
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from cv2 import typing as typing
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from cv2 import utils as utils
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from cv2 import videoio_registry as videoio_registry
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from cv2.mat_wrapper import Mat as Mat
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# Enumerations
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SORT_EVERY_ROW: int
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SORT_EVERY_COLUMN: int
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SORT_ASCENDING: int
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SORT_DESCENDING: int
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SortFlags = int
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"""One of [SORT_EVERY_ROW, SORT_EVERY_COLUMN, SORT_ASCENDING, SORT_DESCENDING]"""
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COVAR_SCRAMBLED: int
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COVAR_NORMAL: int
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COVAR_USE_AVG: int
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COVAR_SCALE: int
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COVAR_ROWS: int
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COVAR_COLS: int
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CovarFlags = int
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"""One of [COVAR_SCRAMBLED, COVAR_NORMAL, COVAR_USE_AVG, COVAR_SCALE, COVAR_ROWS, COVAR_COLS]"""
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KMEANS_RANDOM_CENTERS: int
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KMEANS_PP_CENTERS: int
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KMEANS_USE_INITIAL_LABELS: int
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KmeansFlags = int
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"""One of [KMEANS_RANDOM_CENTERS, KMEANS_PP_CENTERS, KMEANS_USE_INITIAL_LABELS]"""
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REDUCE_SUM: int
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REDUCE_AVG: int
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REDUCE_MAX: int
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REDUCE_MIN: int
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REDUCE_SUM2: int
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ReduceTypes = int
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"""One of [REDUCE_SUM, REDUCE_AVG, REDUCE_MAX, REDUCE_MIN, REDUCE_SUM2]"""
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ROTATE_90_CLOCKWISE: int
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ROTATE_180: int
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ROTATE_90_COUNTERCLOCKWISE: int
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RotateFlags = int
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"""One of [ROTATE_90_CLOCKWISE, ROTATE_180, ROTATE_90_COUNTERCLOCKWISE]"""
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Param_INT: int
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PARAM_INT: int
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Param_BOOLEAN: int
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PARAM_BOOLEAN: int
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Param_REAL: int
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PARAM_REAL: int
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Param_STRING: int
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PARAM_STRING: int
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Param_MAT: int
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PARAM_MAT: int
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Param_MAT_VECTOR: int
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PARAM_MAT_VECTOR: int
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Param_ALGORITHM: int
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PARAM_ALGORITHM: int
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Param_FLOAT: int
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PARAM_FLOAT: int
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Param_UNSIGNED_INT: int
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PARAM_UNSIGNED_INT: int
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Param_UINT64: int
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PARAM_UINT64: int
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Param_UCHAR: int
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PARAM_UCHAR: int
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Param_SCALAR: int
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PARAM_SCALAR: int
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Param = int
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"""One of [Param_INT, PARAM_INT, Param_BOOLEAN, PARAM_BOOLEAN, Param_REAL, PARAM_REAL, Param_STRING, PARAM_STRING, Param_MAT, PARAM_MAT, Param_MAT_VECTOR, PARAM_MAT_VECTOR, Param_ALGORITHM, PARAM_ALGORITHM, Param_FLOAT, PARAM_FLOAT, Param_UNSIGNED_INT, PARAM_UNSIGNED_INT, Param_UINT64, PARAM_UINT64, Param_UCHAR, PARAM_UCHAR, Param_SCALAR, PARAM_SCALAR]"""
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DECOMP_LU: int
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DECOMP_SVD: int
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DECOMP_EIG: int
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DECOMP_CHOLESKY: int
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DECOMP_QR: int
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DECOMP_NORMAL: int
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DecompTypes = int
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"""One of [DECOMP_LU, DECOMP_SVD, DECOMP_EIG, DECOMP_CHOLESKY, DECOMP_QR, DECOMP_NORMAL]"""
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NORM_INF: int
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NORM_L1: int
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NORM_L2: int
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NORM_L2SQR: int
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NORM_HAMMING: int
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NORM_HAMMING2: int
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NORM_TYPE_MASK: int
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NORM_RELATIVE: int
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NORM_MINMAX: int
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NormTypes = int
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"""One of [NORM_INF, NORM_L1, NORM_L2, NORM_L2SQR, NORM_HAMMING, NORM_HAMMING2, NORM_TYPE_MASK, NORM_RELATIVE, NORM_MINMAX]"""
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CMP_EQ: int
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CMP_GT: int
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CMP_GE: int
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CMP_LT: int
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CMP_LE: int
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CMP_NE: int
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CmpTypes = int
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"""One of [CMP_EQ, CMP_GT, CMP_GE, CMP_LT, CMP_LE, CMP_NE]"""
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GEMM_1_T: int
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GEMM_2_T: int
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GEMM_3_T: int
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GemmFlags = int
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"""One of [GEMM_1_T, GEMM_2_T, GEMM_3_T]"""
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DFT_INVERSE: int
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DFT_SCALE: int
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DFT_ROWS: int
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DFT_COMPLEX_OUTPUT: int
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DFT_REAL_OUTPUT: int
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DFT_COMPLEX_INPUT: int
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DCT_INVERSE: int
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DCT_ROWS: int
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DftFlags = int
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"""One of [DFT_INVERSE, DFT_SCALE, DFT_ROWS, DFT_COMPLEX_OUTPUT, DFT_REAL_OUTPUT, DFT_COMPLEX_INPUT, DCT_INVERSE, DCT_ROWS]"""
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BORDER_CONSTANT: int
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BORDER_REPLICATE: int
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BORDER_REFLECT: int
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BORDER_WRAP: int
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BORDER_REFLECT_101: int
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BORDER_TRANSPARENT: int
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BORDER_REFLECT101: int
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BORDER_DEFAULT: int
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BORDER_ISOLATED: int
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BorderTypes = int
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"""One of [BORDER_CONSTANT, BORDER_REPLICATE, BORDER_REFLECT, BORDER_WRAP, BORDER_REFLECT_101, BORDER_TRANSPARENT, BORDER_REFLECT101, BORDER_DEFAULT, BORDER_ISOLATED]"""
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ACCESS_READ: int
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ACCESS_WRITE: int
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ACCESS_RW: int
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ACCESS_MASK: int
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ACCESS_FAST: int
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AccessFlag = int
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"""One of [ACCESS_READ, ACCESS_WRITE, ACCESS_RW, ACCESS_MASK, ACCESS_FAST]"""
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USAGE_DEFAULT: int
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USAGE_ALLOCATE_HOST_MEMORY: int
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USAGE_ALLOCATE_DEVICE_MEMORY: int
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USAGE_ALLOCATE_SHARED_MEMORY: int
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__UMAT_USAGE_FLAGS_32BIT: int
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UMatUsageFlags = int
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"""One of [USAGE_DEFAULT, USAGE_ALLOCATE_HOST_MEMORY, USAGE_ALLOCATE_DEVICE_MEMORY, USAGE_ALLOCATE_SHARED_MEMORY, __UMAT_USAGE_FLAGS_32BIT]"""
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SOLVELP_LOST: int
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SOLVELP_UNBOUNDED: int
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SOLVELP_UNFEASIBLE: int
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SOLVELP_SINGLE: int
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SOLVELP_MULTI: int
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SolveLPResult = int
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"""One of [SOLVELP_LOST, SOLVELP_UNBOUNDED, SOLVELP_UNFEASIBLE, SOLVELP_SINGLE, SOLVELP_MULTI]"""
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QUAT_ASSUME_NOT_UNIT: int
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QUAT_ASSUME_UNIT: int
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QuatAssumeType = int
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"""One of [QUAT_ASSUME_NOT_UNIT, QUAT_ASSUME_UNIT]"""
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FILTER_SCHARR: int
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SpecialFilter = int
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"""One of [FILTER_SCHARR]"""
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MORPH_ERODE: int
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MORPH_DILATE: int
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MORPH_OPEN: int
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MORPH_CLOSE: int
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MORPH_GRADIENT: int
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MORPH_TOPHAT: int
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MORPH_BLACKHAT: int
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MORPH_HITMISS: int
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MorphTypes = int
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"""One of [MORPH_ERODE, MORPH_DILATE, MORPH_OPEN, MORPH_CLOSE, MORPH_GRADIENT, MORPH_TOPHAT, MORPH_BLACKHAT, MORPH_HITMISS]"""
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MORPH_RECT: int
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MORPH_CROSS: int
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MORPH_ELLIPSE: int
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MorphShapes = int
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"""One of [MORPH_RECT, MORPH_CROSS, MORPH_ELLIPSE]"""
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INTER_NEAREST: int
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INTER_LINEAR: int
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INTER_CUBIC: int
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INTER_AREA: int
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INTER_LANCZOS4: int
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INTER_LINEAR_EXACT: int
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INTER_NEAREST_EXACT: int
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INTER_MAX: int
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WARP_FILL_OUTLIERS: int
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WARP_INVERSE_MAP: int
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WARP_RELATIVE_MAP: int
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InterpolationFlags = int
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"""One of [INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_AREA, INTER_LANCZOS4, INTER_LINEAR_EXACT, INTER_NEAREST_EXACT, INTER_MAX, WARP_FILL_OUTLIERS, WARP_INVERSE_MAP, WARP_RELATIVE_MAP]"""
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WARP_POLAR_LINEAR: int
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WARP_POLAR_LOG: int
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WarpPolarMode = int
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"""One of [WARP_POLAR_LINEAR, WARP_POLAR_LOG]"""
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INTER_BITS: int
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INTER_BITS2: int
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INTER_TAB_SIZE: int
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INTER_TAB_SIZE2: int
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InterpolationMasks = int
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"""One of [INTER_BITS, INTER_BITS2, INTER_TAB_SIZE, INTER_TAB_SIZE2]"""
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DIST_USER: int
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DIST_L1: int
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DIST_L2: int
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DIST_C: int
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DIST_L12: int
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DIST_FAIR: int
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DIST_WELSCH: int
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DIST_HUBER: int
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DistanceTypes = int
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"""One of [DIST_USER, DIST_L1, DIST_L2, DIST_C, DIST_L12, DIST_FAIR, DIST_WELSCH, DIST_HUBER]"""
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DIST_MASK_3: int
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DIST_MASK_5: int
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DIST_MASK_PRECISE: int
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DistanceTransformMasks = int
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"""One of [DIST_MASK_3, DIST_MASK_5, DIST_MASK_PRECISE]"""
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THRESH_BINARY: int
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THRESH_BINARY_INV: int
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THRESH_TRUNC: int
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THRESH_TOZERO: int
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THRESH_TOZERO_INV: int
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THRESH_MASK: int
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THRESH_OTSU: int
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THRESH_TRIANGLE: int
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ThresholdTypes = int
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"""One of [THRESH_BINARY, THRESH_BINARY_INV, THRESH_TRUNC, THRESH_TOZERO, THRESH_TOZERO_INV, THRESH_MASK, THRESH_OTSU, THRESH_TRIANGLE]"""
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ADAPTIVE_THRESH_MEAN_C: int
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ADAPTIVE_THRESH_GAUSSIAN_C: int
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AdaptiveThresholdTypes = int
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"""One of [ADAPTIVE_THRESH_MEAN_C, ADAPTIVE_THRESH_GAUSSIAN_C]"""
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GC_BGD: int
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GC_FGD: int
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GC_PR_BGD: int
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GC_PR_FGD: int
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GrabCutClasses = int
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"""One of [GC_BGD, GC_FGD, GC_PR_BGD, GC_PR_FGD]"""
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GC_INIT_WITH_RECT: int
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GC_INIT_WITH_MASK: int
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GC_EVAL: int
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GC_EVAL_FREEZE_MODEL: int
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GrabCutModes = int
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"""One of [GC_INIT_WITH_RECT, GC_INIT_WITH_MASK, GC_EVAL, GC_EVAL_FREEZE_MODEL]"""
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DIST_LABEL_CCOMP: int
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DIST_LABEL_PIXEL: int
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DistanceTransformLabelTypes = int
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"""One of [DIST_LABEL_CCOMP, DIST_LABEL_PIXEL]"""
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FLOODFILL_FIXED_RANGE: int
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FLOODFILL_MASK_ONLY: int
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FloodFillFlags = int
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"""One of [FLOODFILL_FIXED_RANGE, FLOODFILL_MASK_ONLY]"""
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CC_STAT_LEFT: int
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CC_STAT_TOP: int
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CC_STAT_WIDTH: int
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CC_STAT_HEIGHT: int
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CC_STAT_AREA: int
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CC_STAT_MAX: int
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ConnectedComponentsTypes = int
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"""One of [CC_STAT_LEFT, CC_STAT_TOP, CC_STAT_WIDTH, CC_STAT_HEIGHT, CC_STAT_AREA, CC_STAT_MAX]"""
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CCL_DEFAULT: int
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CCL_WU: int
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CCL_GRANA: int
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CCL_BOLELLI: int
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CCL_SAUF: int
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CCL_BBDT: int
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CCL_SPAGHETTI: int
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ConnectedComponentsAlgorithmsTypes = int
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"""One of [CCL_DEFAULT, CCL_WU, CCL_GRANA, CCL_BOLELLI, CCL_SAUF, CCL_BBDT, CCL_SPAGHETTI]"""
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RETR_EXTERNAL: int
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RETR_LIST: int
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RETR_CCOMP: int
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RETR_TREE: int
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RETR_FLOODFILL: int
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RetrievalModes = int
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"""One of [RETR_EXTERNAL, RETR_LIST, RETR_CCOMP, RETR_TREE, RETR_FLOODFILL]"""
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CHAIN_APPROX_NONE: int
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CHAIN_APPROX_SIMPLE: int
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CHAIN_APPROX_TC89_L1: int
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CHAIN_APPROX_TC89_KCOS: int
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ContourApproximationModes = int
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"""One of [CHAIN_APPROX_NONE, CHAIN_APPROX_SIMPLE, CHAIN_APPROX_TC89_L1, CHAIN_APPROX_TC89_KCOS]"""
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CONTOURS_MATCH_I1: int
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CONTOURS_MATCH_I2: int
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CONTOURS_MATCH_I3: int
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ShapeMatchModes = int
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"""One of [CONTOURS_MATCH_I1, CONTOURS_MATCH_I2, CONTOURS_MATCH_I3]"""
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HOUGH_STANDARD: int
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HOUGH_PROBABILISTIC: int
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HOUGH_MULTI_SCALE: int
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HOUGH_GRADIENT: int
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HOUGH_GRADIENT_ALT: int
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HoughModes = int
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"""One of [HOUGH_STANDARD, HOUGH_PROBABILISTIC, HOUGH_MULTI_SCALE, HOUGH_GRADIENT, HOUGH_GRADIENT_ALT]"""
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LSD_REFINE_NONE: int
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LSD_REFINE_STD: int
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LSD_REFINE_ADV: int
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LineSegmentDetectorModes = int
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"""One of [LSD_REFINE_NONE, LSD_REFINE_STD, LSD_REFINE_ADV]"""
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HISTCMP_CORREL: int
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HISTCMP_CHISQR: int
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HISTCMP_INTERSECT: int
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HISTCMP_BHATTACHARYYA: int
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HISTCMP_HELLINGER: int
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HISTCMP_CHISQR_ALT: int
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HISTCMP_KL_DIV: int
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HistCompMethods = int
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"""One of [HISTCMP_CORREL, HISTCMP_CHISQR, HISTCMP_INTERSECT, HISTCMP_BHATTACHARYYA, HISTCMP_HELLINGER, HISTCMP_CHISQR_ALT, HISTCMP_KL_DIV]"""
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COLOR_BGR2BGRA: int
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COLOR_RGB2RGBA: int
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COLOR_BGRA2BGR: int
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COLOR_RGBA2RGB: int
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COLOR_BGR2RGBA: int
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COLOR_RGB2BGRA: int
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COLOR_RGBA2BGR: int
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COLOR_BGRA2RGB: int
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COLOR_BGR2RGB: int
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COLOR_RGB2BGR: int
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COLOR_BGRA2RGBA: int
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COLOR_RGBA2BGRA: int
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COLOR_BGR2GRAY: int
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COLOR_RGB2GRAY: int
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COLOR_GRAY2BGR: int
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COLOR_GRAY2RGB: int
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COLOR_GRAY2BGRA: int
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COLOR_GRAY2RGBA: int
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COLOR_BGRA2GRAY: int
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COLOR_RGBA2GRAY: int
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COLOR_BGR2BGR565: int
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COLOR_RGB2BGR565: int
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COLOR_BGR5652BGR: int
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COLOR_BGR5652RGB: int
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COLOR_BGRA2BGR565: int
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COLOR_RGBA2BGR565: int
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COLOR_BGR5652BGRA: int
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COLOR_BGR5652RGBA: int
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COLOR_GRAY2BGR565: int
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COLOR_BGR5652GRAY: int
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COLOR_BGR2BGR555: int
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COLOR_RGB2BGR555: int
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COLOR_BGR5552BGR: int
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COLOR_BGR5552RGB: int
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COLOR_BGRA2BGR555: int
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COLOR_RGBA2BGR555: int
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COLOR_BGR5552BGRA: int
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COLOR_BGR5552RGBA: int
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COLOR_GRAY2BGR555: int
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COLOR_BGR5552GRAY: int
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COLOR_BGR2XYZ: int
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COLOR_RGB2XYZ: int
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COLOR_XYZ2BGR: int
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COLOR_XYZ2RGB: int
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COLOR_BGR2YCrCb: int
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COLOR_BGR2YCR_CB: int
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COLOR_RGB2YCrCb: int
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COLOR_RGB2YCR_CB: int
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COLOR_YCrCb2BGR: int
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COLOR_YCR_CB2BGR: int
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COLOR_YCrCb2RGB: int
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COLOR_YCR_CB2RGB: int
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COLOR_BGR2HSV: int
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COLOR_RGB2HSV: int
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COLOR_BGR2Lab: int
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COLOR_BGR2LAB: int
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COLOR_RGB2Lab: int
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COLOR_RGB2LAB: int
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COLOR_BGR2Luv: int
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COLOR_BGR2LUV: int
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COLOR_RGB2Luv: int
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COLOR_RGB2LUV: int
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COLOR_BGR2HLS: int
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COLOR_RGB2HLS: int
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COLOR_HSV2BGR: int
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COLOR_HSV2RGB: int
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COLOR_Lab2BGR: int
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COLOR_LAB2BGR: int
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COLOR_Lab2RGB: int
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COLOR_LAB2RGB: int
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COLOR_Luv2BGR: int
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COLOR_LUV2BGR: int
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COLOR_Luv2RGB: int
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COLOR_LUV2RGB: int
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COLOR_HLS2BGR: int
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COLOR_HLS2RGB: int
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COLOR_BGR2HSV_FULL: int
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COLOR_RGB2HSV_FULL: int
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COLOR_BGR2HLS_FULL: int
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COLOR_RGB2HLS_FULL: int
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COLOR_HSV2BGR_FULL: int
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COLOR_HSV2RGB_FULL: int
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COLOR_HLS2BGR_FULL: int
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COLOR_HLS2RGB_FULL: int
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COLOR_LBGR2Lab: int
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COLOR_LBGR2LAB: int
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COLOR_LRGB2Lab: int
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COLOR_LRGB2LAB: int
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COLOR_LBGR2Luv: int
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COLOR_LBGR2LUV: int
|
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COLOR_LRGB2Luv: int
|
|
COLOR_LRGB2LUV: int
|
|
COLOR_Lab2LBGR: int
|
|
COLOR_LAB2LBGR: int
|
|
COLOR_Lab2LRGB: int
|
|
COLOR_LAB2LRGB: int
|
|
COLOR_Luv2LBGR: int
|
|
COLOR_LUV2LBGR: int
|
|
COLOR_Luv2LRGB: int
|
|
COLOR_LUV2LRGB: int
|
|
COLOR_BGR2YUV: int
|
|
COLOR_RGB2YUV: int
|
|
COLOR_YUV2BGR: int
|
|
COLOR_YUV2RGB: int
|
|
COLOR_YUV2RGB_NV12: int
|
|
COLOR_YUV2BGR_NV12: int
|
|
COLOR_YUV2RGB_NV21: int
|
|
COLOR_YUV2BGR_NV21: int
|
|
COLOR_YUV420sp2RGB: int
|
|
COLOR_YUV420SP2RGB: int
|
|
COLOR_YUV420sp2BGR: int
|
|
COLOR_YUV420SP2BGR: int
|
|
COLOR_YUV2RGBA_NV12: int
|
|
COLOR_YUV2BGRA_NV12: int
|
|
COLOR_YUV2RGBA_NV21: int
|
|
COLOR_YUV2BGRA_NV21: int
|
|
COLOR_YUV420sp2RGBA: int
|
|
COLOR_YUV420SP2RGBA: int
|
|
COLOR_YUV420sp2BGRA: int
|
|
COLOR_YUV420SP2BGRA: int
|
|
COLOR_YUV2RGB_YV12: int
|
|
COLOR_YUV2BGR_YV12: int
|
|
COLOR_YUV2RGB_IYUV: int
|
|
COLOR_YUV2BGR_IYUV: int
|
|
COLOR_YUV2RGB_I420: int
|
|
COLOR_YUV2BGR_I420: int
|
|
COLOR_YUV420p2RGB: int
|
|
COLOR_YUV420P2RGB: int
|
|
COLOR_YUV420p2BGR: int
|
|
COLOR_YUV420P2BGR: int
|
|
COLOR_YUV2RGBA_YV12: int
|
|
COLOR_YUV2BGRA_YV12: int
|
|
COLOR_YUV2RGBA_IYUV: int
|
|
COLOR_YUV2BGRA_IYUV: int
|
|
COLOR_YUV2RGBA_I420: int
|
|
COLOR_YUV2BGRA_I420: int
|
|
COLOR_YUV420p2RGBA: int
|
|
COLOR_YUV420P2RGBA: int
|
|
COLOR_YUV420p2BGRA: int
|
|
COLOR_YUV420P2BGRA: int
|
|
COLOR_YUV2GRAY_420: int
|
|
COLOR_YUV2GRAY_NV21: int
|
|
COLOR_YUV2GRAY_NV12: int
|
|
COLOR_YUV2GRAY_YV12: int
|
|
COLOR_YUV2GRAY_IYUV: int
|
|
COLOR_YUV2GRAY_I420: int
|
|
COLOR_YUV420sp2GRAY: int
|
|
COLOR_YUV420SP2GRAY: int
|
|
COLOR_YUV420p2GRAY: int
|
|
COLOR_YUV420P2GRAY: int
|
|
COLOR_YUV2RGB_UYVY: int
|
|
COLOR_YUV2BGR_UYVY: int
|
|
COLOR_YUV2RGB_Y422: int
|
|
COLOR_YUV2BGR_Y422: int
|
|
COLOR_YUV2RGB_UYNV: int
|
|
COLOR_YUV2BGR_UYNV: int
|
|
COLOR_YUV2RGBA_UYVY: int
|
|
COLOR_YUV2BGRA_UYVY: int
|
|
COLOR_YUV2RGBA_Y422: int
|
|
COLOR_YUV2BGRA_Y422: int
|
|
COLOR_YUV2RGBA_UYNV: int
|
|
COLOR_YUV2BGRA_UYNV: int
|
|
COLOR_YUV2RGB_YUY2: int
|
|
COLOR_YUV2BGR_YUY2: int
|
|
COLOR_YUV2RGB_YVYU: int
|
|
COLOR_YUV2BGR_YVYU: int
|
|
COLOR_YUV2RGB_YUYV: int
|
|
COLOR_YUV2BGR_YUYV: int
|
|
COLOR_YUV2RGB_YUNV: int
|
|
COLOR_YUV2BGR_YUNV: int
|
|
COLOR_YUV2RGBA_YUY2: int
|
|
COLOR_YUV2BGRA_YUY2: int
|
|
COLOR_YUV2RGBA_YVYU: int
|
|
COLOR_YUV2BGRA_YVYU: int
|
|
COLOR_YUV2RGBA_YUYV: int
|
|
COLOR_YUV2BGRA_YUYV: int
|
|
COLOR_YUV2RGBA_YUNV: int
|
|
COLOR_YUV2BGRA_YUNV: int
|
|
COLOR_YUV2GRAY_UYVY: int
|
|
COLOR_YUV2GRAY_YUY2: int
|
|
COLOR_YUV2GRAY_Y422: int
|
|
COLOR_YUV2GRAY_UYNV: int
|
|
COLOR_YUV2GRAY_YVYU: int
|
|
COLOR_YUV2GRAY_YUYV: int
|
|
COLOR_YUV2GRAY_YUNV: int
|
|
COLOR_RGBA2mRGBA: int
|
|
COLOR_RGBA2M_RGBA: int
|
|
COLOR_mRGBA2RGBA: int
|
|
COLOR_M_RGBA2RGBA: int
|
|
COLOR_RGB2YUV_I420: int
|
|
COLOR_BGR2YUV_I420: int
|
|
COLOR_RGB2YUV_IYUV: int
|
|
COLOR_BGR2YUV_IYUV: int
|
|
COLOR_RGBA2YUV_I420: int
|
|
COLOR_BGRA2YUV_I420: int
|
|
COLOR_RGBA2YUV_IYUV: int
|
|
COLOR_BGRA2YUV_IYUV: int
|
|
COLOR_RGB2YUV_YV12: int
|
|
COLOR_BGR2YUV_YV12: int
|
|
COLOR_RGBA2YUV_YV12: int
|
|
COLOR_BGRA2YUV_YV12: int
|
|
COLOR_BayerBG2BGR: int
|
|
COLOR_BAYER_BG2BGR: int
|
|
COLOR_BayerGB2BGR: int
|
|
COLOR_BAYER_GB2BGR: int
|
|
COLOR_BayerRG2BGR: int
|
|
COLOR_BAYER_RG2BGR: int
|
|
COLOR_BayerGR2BGR: int
|
|
COLOR_BAYER_GR2BGR: int
|
|
COLOR_BayerRGGB2BGR: int
|
|
COLOR_BAYER_RGGB2BGR: int
|
|
COLOR_BayerGRBG2BGR: int
|
|
COLOR_BAYER_GRBG2BGR: int
|
|
COLOR_BayerBGGR2BGR: int
|
|
COLOR_BAYER_BGGR2BGR: int
|
|
COLOR_BayerGBRG2BGR: int
|
|
COLOR_BAYER_GBRG2BGR: int
|
|
COLOR_BayerRGGB2RGB: int
|
|
COLOR_BAYER_RGGB2RGB: int
|
|
COLOR_BayerGRBG2RGB: int
|
|
COLOR_BAYER_GRBG2RGB: int
|
|
COLOR_BayerBGGR2RGB: int
|
|
COLOR_BAYER_BGGR2RGB: int
|
|
COLOR_BayerGBRG2RGB: int
|
|
COLOR_BAYER_GBRG2RGB: int
|
|
COLOR_BayerBG2RGB: int
|
|
COLOR_BAYER_BG2RGB: int
|
|
COLOR_BayerGB2RGB: int
|
|
COLOR_BAYER_GB2RGB: int
|
|
COLOR_BayerRG2RGB: int
|
|
COLOR_BAYER_RG2RGB: int
|
|
COLOR_BayerGR2RGB: int
|
|
COLOR_BAYER_GR2RGB: int
|
|
COLOR_BayerBG2GRAY: int
|
|
COLOR_BAYER_BG2GRAY: int
|
|
COLOR_BayerGB2GRAY: int
|
|
COLOR_BAYER_GB2GRAY: int
|
|
COLOR_BayerRG2GRAY: int
|
|
COLOR_BAYER_RG2GRAY: int
|
|
COLOR_BayerGR2GRAY: int
|
|
COLOR_BAYER_GR2GRAY: int
|
|
COLOR_BayerRGGB2GRAY: int
|
|
COLOR_BAYER_RGGB2GRAY: int
|
|
COLOR_BayerGRBG2GRAY: int
|
|
COLOR_BAYER_GRBG2GRAY: int
|
|
COLOR_BayerBGGR2GRAY: int
|
|
COLOR_BAYER_BGGR2GRAY: int
|
|
COLOR_BayerGBRG2GRAY: int
|
|
COLOR_BAYER_GBRG2GRAY: int
|
|
COLOR_BayerBG2BGR_VNG: int
|
|
COLOR_BAYER_BG2BGR_VNG: int
|
|
COLOR_BayerGB2BGR_VNG: int
|
|
COLOR_BAYER_GB2BGR_VNG: int
|
|
COLOR_BayerRG2BGR_VNG: int
|
|
COLOR_BAYER_RG2BGR_VNG: int
|
|
COLOR_BayerGR2BGR_VNG: int
|
|
COLOR_BAYER_GR2BGR_VNG: int
|
|
COLOR_BayerRGGB2BGR_VNG: int
|
|
COLOR_BAYER_RGGB2BGR_VNG: int
|
|
COLOR_BayerGRBG2BGR_VNG: int
|
|
COLOR_BAYER_GRBG2BGR_VNG: int
|
|
COLOR_BayerBGGR2BGR_VNG: int
|
|
COLOR_BAYER_BGGR2BGR_VNG: int
|
|
COLOR_BayerGBRG2BGR_VNG: int
|
|
COLOR_BAYER_GBRG2BGR_VNG: int
|
|
COLOR_BayerRGGB2RGB_VNG: int
|
|
COLOR_BAYER_RGGB2RGB_VNG: int
|
|
COLOR_BayerGRBG2RGB_VNG: int
|
|
COLOR_BAYER_GRBG2RGB_VNG: int
|
|
COLOR_BayerBGGR2RGB_VNG: int
|
|
COLOR_BAYER_BGGR2RGB_VNG: int
|
|
COLOR_BayerGBRG2RGB_VNG: int
|
|
COLOR_BAYER_GBRG2RGB_VNG: int
|
|
COLOR_BayerBG2RGB_VNG: int
|
|
COLOR_BAYER_BG2RGB_VNG: int
|
|
COLOR_BayerGB2RGB_VNG: int
|
|
COLOR_BAYER_GB2RGB_VNG: int
|
|
COLOR_BayerRG2RGB_VNG: int
|
|
COLOR_BAYER_RG2RGB_VNG: int
|
|
COLOR_BayerGR2RGB_VNG: int
|
|
COLOR_BAYER_GR2RGB_VNG: int
|
|
COLOR_BayerBG2BGR_EA: int
|
|
COLOR_BAYER_BG2BGR_EA: int
|
|
COLOR_BayerGB2BGR_EA: int
|
|
COLOR_BAYER_GB2BGR_EA: int
|
|
COLOR_BayerRG2BGR_EA: int
|
|
COLOR_BAYER_RG2BGR_EA: int
|
|
COLOR_BayerGR2BGR_EA: int
|
|
COLOR_BAYER_GR2BGR_EA: int
|
|
COLOR_BayerRGGB2BGR_EA: int
|
|
COLOR_BAYER_RGGB2BGR_EA: int
|
|
COLOR_BayerGRBG2BGR_EA: int
|
|
COLOR_BAYER_GRBG2BGR_EA: int
|
|
COLOR_BayerBGGR2BGR_EA: int
|
|
COLOR_BAYER_BGGR2BGR_EA: int
|
|
COLOR_BayerGBRG2BGR_EA: int
|
|
COLOR_BAYER_GBRG2BGR_EA: int
|
|
COLOR_BayerRGGB2RGB_EA: int
|
|
COLOR_BAYER_RGGB2RGB_EA: int
|
|
COLOR_BayerGRBG2RGB_EA: int
|
|
COLOR_BAYER_GRBG2RGB_EA: int
|
|
COLOR_BayerBGGR2RGB_EA: int
|
|
COLOR_BAYER_BGGR2RGB_EA: int
|
|
COLOR_BayerGBRG2RGB_EA: int
|
|
COLOR_BAYER_GBRG2RGB_EA: int
|
|
COLOR_BayerBG2RGB_EA: int
|
|
COLOR_BAYER_BG2RGB_EA: int
|
|
COLOR_BayerGB2RGB_EA: int
|
|
COLOR_BAYER_GB2RGB_EA: int
|
|
COLOR_BayerRG2RGB_EA: int
|
|
COLOR_BAYER_RG2RGB_EA: int
|
|
COLOR_BayerGR2RGB_EA: int
|
|
COLOR_BAYER_GR2RGB_EA: int
|
|
COLOR_BayerBG2BGRA: int
|
|
COLOR_BAYER_BG2BGRA: int
|
|
COLOR_BayerGB2BGRA: int
|
|
COLOR_BAYER_GB2BGRA: int
|
|
COLOR_BayerRG2BGRA: int
|
|
COLOR_BAYER_RG2BGRA: int
|
|
COLOR_BayerGR2BGRA: int
|
|
COLOR_BAYER_GR2BGRA: int
|
|
COLOR_BayerRGGB2BGRA: int
|
|
COLOR_BAYER_RGGB2BGRA: int
|
|
COLOR_BayerGRBG2BGRA: int
|
|
COLOR_BAYER_GRBG2BGRA: int
|
|
COLOR_BayerBGGR2BGRA: int
|
|
COLOR_BAYER_BGGR2BGRA: int
|
|
COLOR_BayerGBRG2BGRA: int
|
|
COLOR_BAYER_GBRG2BGRA: int
|
|
COLOR_BayerRGGB2RGBA: int
|
|
COLOR_BAYER_RGGB2RGBA: int
|
|
COLOR_BayerGRBG2RGBA: int
|
|
COLOR_BAYER_GRBG2RGBA: int
|
|
COLOR_BayerBGGR2RGBA: int
|
|
COLOR_BAYER_BGGR2RGBA: int
|
|
COLOR_BayerGBRG2RGBA: int
|
|
COLOR_BAYER_GBRG2RGBA: int
|
|
COLOR_BayerBG2RGBA: int
|
|
COLOR_BAYER_BG2RGBA: int
|
|
COLOR_BayerGB2RGBA: int
|
|
COLOR_BAYER_GB2RGBA: int
|
|
COLOR_BayerRG2RGBA: int
|
|
COLOR_BAYER_RG2RGBA: int
|
|
COLOR_BayerGR2RGBA: int
|
|
COLOR_BAYER_GR2RGBA: int
|
|
COLOR_RGB2YUV_UYVY: int
|
|
COLOR_BGR2YUV_UYVY: int
|
|
COLOR_RGB2YUV_Y422: int
|
|
COLOR_BGR2YUV_Y422: int
|
|
COLOR_RGB2YUV_UYNV: int
|
|
COLOR_BGR2YUV_UYNV: int
|
|
COLOR_RGBA2YUV_UYVY: int
|
|
COLOR_BGRA2YUV_UYVY: int
|
|
COLOR_RGBA2YUV_Y422: int
|
|
COLOR_BGRA2YUV_Y422: int
|
|
COLOR_RGBA2YUV_UYNV: int
|
|
COLOR_BGRA2YUV_UYNV: int
|
|
COLOR_RGB2YUV_YUY2: int
|
|
COLOR_BGR2YUV_YUY2: int
|
|
COLOR_RGB2YUV_YVYU: int
|
|
COLOR_BGR2YUV_YVYU: int
|
|
COLOR_RGB2YUV_YUYV: int
|
|
COLOR_BGR2YUV_YUYV: int
|
|
COLOR_RGB2YUV_YUNV: int
|
|
COLOR_BGR2YUV_YUNV: int
|
|
COLOR_RGBA2YUV_YUY2: int
|
|
COLOR_BGRA2YUV_YUY2: int
|
|
COLOR_RGBA2YUV_YVYU: int
|
|
COLOR_BGRA2YUV_YVYU: int
|
|
COLOR_RGBA2YUV_YUYV: int
|
|
COLOR_BGRA2YUV_YUYV: int
|
|
COLOR_RGBA2YUV_YUNV: int
|
|
COLOR_BGRA2YUV_YUNV: int
|
|
COLOR_COLORCVT_MAX: int
|
|
ColorConversionCodes = int
|
|
"""One of [COLOR_BGR2BGRA, COLOR_RGB2RGBA, COLOR_BGRA2BGR, COLOR_RGBA2RGB, COLOR_BGR2RGBA, COLOR_RGB2BGRA, COLOR_RGBA2BGR, COLOR_BGRA2RGB, COLOR_BGR2RGB, COLOR_RGB2BGR, COLOR_BGRA2RGBA, COLOR_RGBA2BGRA, COLOR_BGR2GRAY, COLOR_RGB2GRAY, COLOR_GRAY2BGR, COLOR_GRAY2RGB, COLOR_GRAY2BGRA, COLOR_GRAY2RGBA, COLOR_BGRA2GRAY, COLOR_RGBA2GRAY, COLOR_BGR2BGR565, COLOR_RGB2BGR565, COLOR_BGR5652BGR, COLOR_BGR5652RGB, COLOR_BGRA2BGR565, COLOR_RGBA2BGR565, COLOR_BGR5652BGRA, COLOR_BGR5652RGBA, COLOR_GRAY2BGR565, COLOR_BGR5652GRAY, COLOR_BGR2BGR555, COLOR_RGB2BGR555, COLOR_BGR5552BGR, COLOR_BGR5552RGB, COLOR_BGRA2BGR555, COLOR_RGBA2BGR555, COLOR_BGR5552BGRA, COLOR_BGR5552RGBA, COLOR_GRAY2BGR555, COLOR_BGR5552GRAY, COLOR_BGR2XYZ, COLOR_RGB2XYZ, COLOR_XYZ2BGR, COLOR_XYZ2RGB, COLOR_BGR2YCrCb, COLOR_BGR2YCR_CB, COLOR_RGB2YCrCb, COLOR_RGB2YCR_CB, COLOR_YCrCb2BGR, COLOR_YCR_CB2BGR, COLOR_YCrCb2RGB, COLOR_YCR_CB2RGB, COLOR_BGR2HSV, COLOR_RGB2HSV, COLOR_BGR2Lab, COLOR_BGR2LAB, COLOR_RGB2Lab, COLOR_RGB2LAB, COLOR_BGR2Luv, COLOR_BGR2LUV, COLOR_RGB2Luv, COLOR_RGB2LUV, COLOR_BGR2HLS, COLOR_RGB2HLS, COLOR_HSV2BGR, COLOR_HSV2RGB, COLOR_Lab2BGR, COLOR_LAB2BGR, COLOR_Lab2RGB, COLOR_LAB2RGB, COLOR_Luv2BGR, COLOR_LUV2BGR, COLOR_Luv2RGB, COLOR_LUV2RGB, COLOR_HLS2BGR, COLOR_HLS2RGB, COLOR_BGR2HSV_FULL, COLOR_RGB2HSV_FULL, COLOR_BGR2HLS_FULL, COLOR_RGB2HLS_FULL, COLOR_HSV2BGR_FULL, COLOR_HSV2RGB_FULL, COLOR_HLS2BGR_FULL, COLOR_HLS2RGB_FULL, COLOR_LBGR2Lab, COLOR_LBGR2LAB, COLOR_LRGB2Lab, COLOR_LRGB2LAB, COLOR_LBGR2Luv, COLOR_LBGR2LUV, COLOR_LRGB2Luv, COLOR_LRGB2LUV, COLOR_Lab2LBGR, COLOR_LAB2LBGR, COLOR_Lab2LRGB, COLOR_LAB2LRGB, COLOR_Luv2LBGR, COLOR_LUV2LBGR, COLOR_Luv2LRGB, COLOR_LUV2LRGB, COLOR_BGR2YUV, COLOR_RGB2YUV, COLOR_YUV2BGR, COLOR_YUV2RGB, COLOR_YUV2RGB_NV12, COLOR_YUV2BGR_NV12, COLOR_YUV2RGB_NV21, COLOR_YUV2BGR_NV21, COLOR_YUV420sp2RGB, COLOR_YUV420SP2RGB, COLOR_YUV420sp2BGR, COLOR_YUV420SP2BGR, COLOR_YUV2RGBA_NV12, COLOR_YUV2BGRA_NV12, COLOR_YUV2RGBA_NV21, COLOR_YUV2BGRA_NV21, COLOR_YUV420sp2RGBA, COLOR_YUV420SP2RGBA, COLOR_YUV420sp2BGRA, COLOR_YUV420SP2BGRA, COLOR_YUV2RGB_YV12, COLOR_YUV2BGR_YV12, COLOR_YUV2RGB_IYUV, COLOR_YUV2BGR_IYUV, COLOR_YUV2RGB_I420, COLOR_YUV2BGR_I420, COLOR_YUV420p2RGB, COLOR_YUV420P2RGB, COLOR_YUV420p2BGR, COLOR_YUV420P2BGR, COLOR_YUV2RGBA_YV12, COLOR_YUV2BGRA_YV12, COLOR_YUV2RGBA_IYUV, COLOR_YUV2BGRA_IYUV, COLOR_YUV2RGBA_I420, COLOR_YUV2BGRA_I420, COLOR_YUV420p2RGBA, COLOR_YUV420P2RGBA, COLOR_YUV420p2BGRA, COLOR_YUV420P2BGRA, COLOR_YUV2GRAY_420, COLOR_YUV2GRAY_NV21, COLOR_YUV2GRAY_NV12, COLOR_YUV2GRAY_YV12, COLOR_YUV2GRAY_IYUV, COLOR_YUV2GRAY_I420, COLOR_YUV420sp2GRAY, COLOR_YUV420SP2GRAY, COLOR_YUV420p2GRAY, COLOR_YUV420P2GRAY, COLOR_YUV2RGB_UYVY, COLOR_YUV2BGR_UYVY, COLOR_YUV2RGB_Y422, COLOR_YUV2BGR_Y422, COLOR_YUV2RGB_UYNV, COLOR_YUV2BGR_UYNV, COLOR_YUV2RGBA_UYVY, COLOR_YUV2BGRA_UYVY, COLOR_YUV2RGBA_Y422, COLOR_YUV2BGRA_Y422, COLOR_YUV2RGBA_UYNV, COLOR_YUV2BGRA_UYNV, COLOR_YUV2RGB_YUY2, COLOR_YUV2BGR_YUY2, COLOR_YUV2RGB_YVYU, COLOR_YUV2BGR_YVYU, COLOR_YUV2RGB_YUYV, COLOR_YUV2BGR_YUYV, COLOR_YUV2RGB_YUNV, COLOR_YUV2BGR_YUNV, COLOR_YUV2RGBA_YUY2, COLOR_YUV2BGRA_YUY2, COLOR_YUV2RGBA_YVYU, COLOR_YUV2BGRA_YVYU, COLOR_YUV2RGBA_YUYV, COLOR_YUV2BGRA_YUYV, COLOR_YUV2RGBA_YUNV, COLOR_YUV2BGRA_YUNV, COLOR_YUV2GRAY_UYVY, COLOR_YUV2GRAY_YUY2, COLOR_YUV2GRAY_Y422, COLOR_YUV2GRAY_UYNV, COLOR_YUV2GRAY_YVYU, COLOR_YUV2GRAY_YUYV, COLOR_YUV2GRAY_YUNV, COLOR_RGBA2mRGBA, COLOR_RGBA2M_RGBA, COLOR_mRGBA2RGBA, COLOR_M_RGBA2RGBA, COLOR_RGB2YUV_I420, COLOR_BGR2YUV_I420, COLOR_RGB2YUV_IYUV, COLOR_BGR2YUV_IYUV, COLOR_RGBA2YUV_I420, COLOR_BGRA2YUV_I420, COLOR_RGBA2YUV_IYUV, COLOR_BGRA2YUV_IYUV, COLOR_RGB2YUV_YV12, COLOR_BGR2YUV_YV12, COLOR_RGBA2YUV_YV12, COLOR_BGRA2YUV_YV12, COLOR_BayerBG2BGR, COLOR_BAYER_BG2BGR, COLOR_BayerGB2BGR, COLOR_BAYER_GB2BGR, COLOR_BayerRG2BGR, COLOR_BAYER_RG2BGR, COLOR_BayerGR2BGR, COLOR_BAYER_GR2BGR, COLOR_BayerRGGB2BGR, COLOR_BAYER_RGGB2BGR, COLOR_BayerGRBG2BGR, COLOR_BAYER_GRBG2BGR, COLOR_BayerBGGR2BGR, COLOR_BAYER_BGGR2BGR, COLOR_BayerGBRG2BGR, COLOR_BAYER_GBRG2BGR, COLOR_BayerRGGB2RGB, COLOR_BAYER_RGGB2RGB, COLOR_BayerGRBG2RGB, COLOR_BAYER_GRBG2RGB, COLOR_BayerBGGR2RGB, COLOR_BAYER_BGGR2RGB, COLOR_BayerGBRG2RGB, COLOR_BAYER_GBRG2RGB, COLOR_BayerBG2RGB, COLOR_BAYER_BG2RGB, COLOR_BayerGB2RGB, COLOR_BAYER_GB2RGB, COLOR_BayerRG2RGB, COLOR_BAYER_RG2RGB, COLOR_BayerGR2RGB, COLOR_BAYER_GR2RGB, COLOR_BayerBG2GRAY, COLOR_BAYER_BG2GRAY, COLOR_BayerGB2GRAY, COLOR_BAYER_GB2GRAY, COLOR_BayerRG2GRAY, COLOR_BAYER_RG2GRAY, COLOR_BayerGR2GRAY, COLOR_BAYER_GR2GRAY, COLOR_BayerRGGB2GRAY, COLOR_BAYER_RGGB2GRAY, COLOR_BayerGRBG2GRAY, COLOR_BAYER_GRBG2GRAY, COLOR_BayerBGGR2GRAY, COLOR_BAYER_BGGR2GRAY, COLOR_BayerGBRG2GRAY, COLOR_BAYER_GBRG2GRAY, COLOR_BayerBG2BGR_VNG, COLOR_BAYER_BG2BGR_VNG, COLOR_BayerGB2BGR_VNG, COLOR_BAYER_GB2BGR_VNG, COLOR_BayerRG2BGR_VNG, COLOR_BAYER_RG2BGR_VNG, COLOR_BayerGR2BGR_VNG, COLOR_BAYER_GR2BGR_VNG, COLOR_BayerRGGB2BGR_VNG, COLOR_BAYER_RGGB2BGR_VNG, COLOR_BayerGRBG2BGR_VNG, COLOR_BAYER_GRBG2BGR_VNG, COLOR_BayerBGGR2BGR_VNG, COLOR_BAYER_BGGR2BGR_VNG, COLOR_BayerGBRG2BGR_VNG, COLOR_BAYER_GBRG2BGR_VNG, COLOR_BayerRGGB2RGB_VNG, COLOR_BAYER_RGGB2RGB_VNG, COLOR_BayerGRBG2RGB_VNG, COLOR_BAYER_GRBG2RGB_VNG, COLOR_BayerBGGR2RGB_VNG, COLOR_BAYER_BGGR2RGB_VNG, COLOR_BayerGBRG2RGB_VNG, COLOR_BAYER_GBRG2RGB_VNG, COLOR_BayerBG2RGB_VNG, COLOR_BAYER_BG2RGB_VNG, COLOR_BayerGB2RGB_VNG, COLOR_BAYER_GB2RGB_VNG, COLOR_BayerRG2RGB_VNG, COLOR_BAYER_RG2RGB_VNG, COLOR_BayerGR2RGB_VNG, COLOR_BAYER_GR2RGB_VNG, COLOR_BayerBG2BGR_EA, COLOR_BAYER_BG2BGR_EA, COLOR_BayerGB2BGR_EA, COLOR_BAYER_GB2BGR_EA, COLOR_BayerRG2BGR_EA, COLOR_BAYER_RG2BGR_EA, COLOR_BayerGR2BGR_EA, COLOR_BAYER_GR2BGR_EA, COLOR_BayerRGGB2BGR_EA, COLOR_BAYER_RGGB2BGR_EA, COLOR_BayerGRBG2BGR_EA, COLOR_BAYER_GRBG2BGR_EA, COLOR_BayerBGGR2BGR_EA, COLOR_BAYER_BGGR2BGR_EA, COLOR_BayerGBRG2BGR_EA, COLOR_BAYER_GBRG2BGR_EA, COLOR_BayerRGGB2RGB_EA, COLOR_BAYER_RGGB2RGB_EA, COLOR_BayerGRBG2RGB_EA, COLOR_BAYER_GRBG2RGB_EA, COLOR_BayerBGGR2RGB_EA, COLOR_BAYER_BGGR2RGB_EA, COLOR_BayerGBRG2RGB_EA, COLOR_BAYER_GBRG2RGB_EA, COLOR_BayerBG2RGB_EA, COLOR_BAYER_BG2RGB_EA, COLOR_BayerGB2RGB_EA, COLOR_BAYER_GB2RGB_EA, COLOR_BayerRG2RGB_EA, COLOR_BAYER_RG2RGB_EA, COLOR_BayerGR2RGB_EA, COLOR_BAYER_GR2RGB_EA, COLOR_BayerBG2BGRA, COLOR_BAYER_BG2BGRA, COLOR_BayerGB2BGRA, COLOR_BAYER_GB2BGRA, COLOR_BayerRG2BGRA, COLOR_BAYER_RG2BGRA, COLOR_BayerGR2BGRA, COLOR_BAYER_GR2BGRA, COLOR_BayerRGGB2BGRA, COLOR_BAYER_RGGB2BGRA, COLOR_BayerGRBG2BGRA, COLOR_BAYER_GRBG2BGRA, COLOR_BayerBGGR2BGRA, COLOR_BAYER_BGGR2BGRA, COLOR_BayerGBRG2BGRA, COLOR_BAYER_GBRG2BGRA, COLOR_BayerRGGB2RGBA, COLOR_BAYER_RGGB2RGBA, COLOR_BayerGRBG2RGBA, COLOR_BAYER_GRBG2RGBA, COLOR_BayerBGGR2RGBA, COLOR_BAYER_BGGR2RGBA, COLOR_BayerGBRG2RGBA, COLOR_BAYER_GBRG2RGBA, COLOR_BayerBG2RGBA, COLOR_BAYER_BG2RGBA, COLOR_BayerGB2RGBA, COLOR_BAYER_GB2RGBA, COLOR_BayerRG2RGBA, COLOR_BAYER_RG2RGBA, COLOR_BayerGR2RGBA, COLOR_BAYER_GR2RGBA, COLOR_RGB2YUV_UYVY, COLOR_BGR2YUV_UYVY, COLOR_RGB2YUV_Y422, COLOR_BGR2YUV_Y422, COLOR_RGB2YUV_UYNV, COLOR_BGR2YUV_UYNV, COLOR_RGBA2YUV_UYVY, COLOR_BGRA2YUV_UYVY, COLOR_RGBA2YUV_Y422, COLOR_BGRA2YUV_Y422, COLOR_RGBA2YUV_UYNV, COLOR_BGRA2YUV_UYNV, COLOR_RGB2YUV_YUY2, COLOR_BGR2YUV_YUY2, COLOR_RGB2YUV_YVYU, COLOR_BGR2YUV_YVYU, COLOR_RGB2YUV_YUYV, COLOR_BGR2YUV_YUYV, COLOR_RGB2YUV_YUNV, COLOR_BGR2YUV_YUNV, COLOR_RGBA2YUV_YUY2, COLOR_BGRA2YUV_YUY2, COLOR_RGBA2YUV_YVYU, COLOR_BGRA2YUV_YVYU, COLOR_RGBA2YUV_YUYV, COLOR_BGRA2YUV_YUYV, COLOR_RGBA2YUV_YUNV, COLOR_BGRA2YUV_YUNV, COLOR_COLORCVT_MAX]"""
|
|
|
|
INTERSECT_NONE: int
|
|
INTERSECT_PARTIAL: int
|
|
INTERSECT_FULL: int
|
|
RectanglesIntersectTypes = int
|
|
"""One of [INTERSECT_NONE, INTERSECT_PARTIAL, INTERSECT_FULL]"""
|
|
|
|
FILLED: int
|
|
LINE_4: int
|
|
LINE_8: int
|
|
LINE_AA: int
|
|
LineTypes = int
|
|
"""One of [FILLED, LINE_4, LINE_8, LINE_AA]"""
|
|
|
|
FONT_HERSHEY_SIMPLEX: int
|
|
FONT_HERSHEY_PLAIN: int
|
|
FONT_HERSHEY_DUPLEX: int
|
|
FONT_HERSHEY_COMPLEX: int
|
|
FONT_HERSHEY_TRIPLEX: int
|
|
FONT_HERSHEY_COMPLEX_SMALL: int
|
|
FONT_HERSHEY_SCRIPT_SIMPLEX: int
|
|
FONT_HERSHEY_SCRIPT_COMPLEX: int
|
|
FONT_ITALIC: int
|
|
HersheyFonts = int
|
|
"""One of [FONT_HERSHEY_SIMPLEX, FONT_HERSHEY_PLAIN, FONT_HERSHEY_DUPLEX, FONT_HERSHEY_COMPLEX, FONT_HERSHEY_TRIPLEX, FONT_HERSHEY_COMPLEX_SMALL, FONT_HERSHEY_SCRIPT_SIMPLEX, FONT_HERSHEY_SCRIPT_COMPLEX, FONT_ITALIC]"""
|
|
|
|
MARKER_CROSS: int
|
|
MARKER_TILTED_CROSS: int
|
|
MARKER_STAR: int
|
|
MARKER_DIAMOND: int
|
|
MARKER_SQUARE: int
|
|
MARKER_TRIANGLE_UP: int
|
|
MARKER_TRIANGLE_DOWN: int
|
|
MarkerTypes = int
|
|
"""One of [MARKER_CROSS, MARKER_TILTED_CROSS, MARKER_STAR, MARKER_DIAMOND, MARKER_SQUARE, MARKER_TRIANGLE_UP, MARKER_TRIANGLE_DOWN]"""
|
|
|
|
TM_SQDIFF: int
|
|
TM_SQDIFF_NORMED: int
|
|
TM_CCORR: int
|
|
TM_CCORR_NORMED: int
|
|
TM_CCOEFF: int
|
|
TM_CCOEFF_NORMED: int
|
|
TemplateMatchModes = int
|
|
"""One of [TM_SQDIFF, TM_SQDIFF_NORMED, TM_CCORR, TM_CCORR_NORMED, TM_CCOEFF, TM_CCOEFF_NORMED]"""
|
|
|
|
COLORMAP_AUTUMN: int
|
|
COLORMAP_BONE: int
|
|
COLORMAP_JET: int
|
|
COLORMAP_WINTER: int
|
|
COLORMAP_RAINBOW: int
|
|
COLORMAP_OCEAN: int
|
|
COLORMAP_SUMMER: int
|
|
COLORMAP_SPRING: int
|
|
COLORMAP_COOL: int
|
|
COLORMAP_HSV: int
|
|
COLORMAP_PINK: int
|
|
COLORMAP_HOT: int
|
|
COLORMAP_PARULA: int
|
|
COLORMAP_MAGMA: int
|
|
COLORMAP_INFERNO: int
|
|
COLORMAP_PLASMA: int
|
|
COLORMAP_VIRIDIS: int
|
|
COLORMAP_CIVIDIS: int
|
|
COLORMAP_TWILIGHT: int
|
|
COLORMAP_TWILIGHT_SHIFTED: int
|
|
COLORMAP_TURBO: int
|
|
COLORMAP_DEEPGREEN: int
|
|
ColormapTypes = int
|
|
"""One of [COLORMAP_AUTUMN, COLORMAP_BONE, COLORMAP_JET, COLORMAP_WINTER, COLORMAP_RAINBOW, COLORMAP_OCEAN, COLORMAP_SUMMER, COLORMAP_SPRING, COLORMAP_COOL, COLORMAP_HSV, COLORMAP_PINK, COLORMAP_HOT, COLORMAP_PARULA, COLORMAP_MAGMA, COLORMAP_INFERNO, COLORMAP_PLASMA, COLORMAP_VIRIDIS, COLORMAP_CIVIDIS, COLORMAP_TWILIGHT, COLORMAP_TWILIGHT_SHIFTED, COLORMAP_TURBO, COLORMAP_DEEPGREEN]"""
|
|
|
|
INPAINT_NS: int
|
|
INPAINT_TELEA: int
|
|
LDR_SIZE: int
|
|
NORMAL_CLONE: int
|
|
MIXED_CLONE: int
|
|
MONOCHROME_TRANSFER: int
|
|
RECURS_FILTER: int
|
|
NORMCONV_FILTER: int
|
|
CAP_PROP_DC1394_OFF: int
|
|
CAP_PROP_DC1394_MODE_MANUAL: int
|
|
CAP_PROP_DC1394_MODE_AUTO: int
|
|
CAP_PROP_DC1394_MODE_ONE_PUSH_AUTO: int
|
|
CAP_PROP_DC1394_MAX: int
|
|
CAP_OPENNI_DEPTH_GENERATOR: int
|
|
CAP_OPENNI_IMAGE_GENERATOR: int
|
|
CAP_OPENNI_IR_GENERATOR: int
|
|
CAP_OPENNI_GENERATORS_MASK: int
|
|
CAP_PROP_OPENNI_OUTPUT_MODE: int
|
|
CAP_PROP_OPENNI_FRAME_MAX_DEPTH: int
|
|
CAP_PROP_OPENNI_BASELINE: int
|
|
CAP_PROP_OPENNI_FOCAL_LENGTH: int
|
|
CAP_PROP_OPENNI_REGISTRATION: int
|
|
CAP_PROP_OPENNI_REGISTRATION_ON: int
|
|
CAP_PROP_OPENNI_APPROX_FRAME_SYNC: int
|
|
CAP_PROP_OPENNI_MAX_BUFFER_SIZE: int
|
|
CAP_PROP_OPENNI_CIRCLE_BUFFER: int
|
|
CAP_PROP_OPENNI_MAX_TIME_DURATION: int
|
|
CAP_PROP_OPENNI_GENERATOR_PRESENT: int
|
|
CAP_PROP_OPENNI2_SYNC: int
|
|
CAP_PROP_OPENNI2_MIRROR: int
|
|
CAP_OPENNI_IMAGE_GENERATOR_PRESENT: int
|
|
CAP_OPENNI_IMAGE_GENERATOR_OUTPUT_MODE: int
|
|
CAP_OPENNI_DEPTH_GENERATOR_PRESENT: int
|
|
CAP_OPENNI_DEPTH_GENERATOR_BASELINE: int
|
|
CAP_OPENNI_DEPTH_GENERATOR_FOCAL_LENGTH: int
|
|
CAP_OPENNI_DEPTH_GENERATOR_REGISTRATION: int
|
|
CAP_OPENNI_DEPTH_GENERATOR_REGISTRATION_ON: int
|
|
CAP_OPENNI_IR_GENERATOR_PRESENT: int
|
|
CAP_OPENNI_DEPTH_MAP: int
|
|
CAP_OPENNI_POINT_CLOUD_MAP: int
|
|
CAP_OPENNI_DISPARITY_MAP: int
|
|
CAP_OPENNI_DISPARITY_MAP_32F: int
|
|
CAP_OPENNI_VALID_DEPTH_MASK: int
|
|
CAP_OPENNI_BGR_IMAGE: int
|
|
CAP_OPENNI_GRAY_IMAGE: int
|
|
CAP_OPENNI_IR_IMAGE: int
|
|
CAP_OPENNI_VGA_30HZ: int
|
|
CAP_OPENNI_SXGA_15HZ: int
|
|
CAP_OPENNI_SXGA_30HZ: int
|
|
CAP_OPENNI_QVGA_30HZ: int
|
|
CAP_OPENNI_QVGA_60HZ: int
|
|
CAP_PROP_GSTREAMER_QUEUE_LENGTH: int
|
|
CAP_PROP_PVAPI_MULTICASTIP: int
|
|
CAP_PROP_PVAPI_FRAMESTARTTRIGGERMODE: int
|
|
CAP_PROP_PVAPI_DECIMATIONHORIZONTAL: int
|
|
CAP_PROP_PVAPI_DECIMATIONVERTICAL: int
|
|
CAP_PROP_PVAPI_BINNINGX: int
|
|
CAP_PROP_PVAPI_BINNINGY: int
|
|
CAP_PROP_PVAPI_PIXELFORMAT: int
|
|
CAP_PVAPI_FSTRIGMODE_FREERUN: int
|
|
CAP_PVAPI_FSTRIGMODE_SYNCIN1: int
|
|
CAP_PVAPI_FSTRIGMODE_SYNCIN2: int
|
|
CAP_PVAPI_FSTRIGMODE_FIXEDRATE: int
|
|
CAP_PVAPI_FSTRIGMODE_SOFTWARE: int
|
|
CAP_PVAPI_DECIMATION_OFF: int
|
|
CAP_PVAPI_DECIMATION_2OUTOF4: int
|
|
CAP_PVAPI_DECIMATION_2OUTOF8: int
|
|
CAP_PVAPI_DECIMATION_2OUTOF16: int
|
|
CAP_PVAPI_PIXELFORMAT_MONO8: int
|
|
CAP_PVAPI_PIXELFORMAT_MONO16: int
|
|
CAP_PVAPI_PIXELFORMAT_BAYER8: int
|
|
CAP_PVAPI_PIXELFORMAT_BAYER16: int
|
|
CAP_PVAPI_PIXELFORMAT_RGB24: int
|
|
CAP_PVAPI_PIXELFORMAT_BGR24: int
|
|
CAP_PVAPI_PIXELFORMAT_RGBA32: int
|
|
CAP_PVAPI_PIXELFORMAT_BGRA32: int
|
|
CAP_PROP_XI_DOWNSAMPLING: int
|
|
CAP_PROP_XI_DATA_FORMAT: int
|
|
CAP_PROP_XI_OFFSET_X: int
|
|
CAP_PROP_XI_OFFSET_Y: int
|
|
CAP_PROP_XI_TRG_SOURCE: int
|
|
CAP_PROP_XI_TRG_SOFTWARE: int
|
|
CAP_PROP_XI_GPI_SELECTOR: int
|
|
CAP_PROP_XI_GPI_MODE: int
|
|
CAP_PROP_XI_GPI_LEVEL: int
|
|
CAP_PROP_XI_GPO_SELECTOR: int
|
|
CAP_PROP_XI_GPO_MODE: int
|
|
CAP_PROP_XI_LED_SELECTOR: int
|
|
CAP_PROP_XI_LED_MODE: int
|
|
CAP_PROP_XI_MANUAL_WB: int
|
|
CAP_PROP_XI_AUTO_WB: int
|
|
CAP_PROP_XI_AEAG: int
|
|
CAP_PROP_XI_EXP_PRIORITY: int
|
|
CAP_PROP_XI_AE_MAX_LIMIT: int
|
|
CAP_PROP_XI_AG_MAX_LIMIT: int
|
|
CAP_PROP_XI_AEAG_LEVEL: int
|
|
CAP_PROP_XI_TIMEOUT: int
|
|
CAP_PROP_XI_EXPOSURE: int
|
|
CAP_PROP_XI_EXPOSURE_BURST_COUNT: int
|
|
CAP_PROP_XI_GAIN_SELECTOR: int
|
|
CAP_PROP_XI_GAIN: int
|
|
CAP_PROP_XI_DOWNSAMPLING_TYPE: int
|
|
CAP_PROP_XI_BINNING_SELECTOR: int
|
|
CAP_PROP_XI_BINNING_VERTICAL: int
|
|
CAP_PROP_XI_BINNING_HORIZONTAL: int
|
|
CAP_PROP_XI_BINNING_PATTERN: int
|
|
CAP_PROP_XI_DECIMATION_SELECTOR: int
|
|
CAP_PROP_XI_DECIMATION_VERTICAL: int
|
|
CAP_PROP_XI_DECIMATION_HORIZONTAL: int
|
|
CAP_PROP_XI_DECIMATION_PATTERN: int
|
|
CAP_PROP_XI_TEST_PATTERN_GENERATOR_SELECTOR: int
|
|
CAP_PROP_XI_TEST_PATTERN: int
|
|
CAP_PROP_XI_IMAGE_DATA_FORMAT: int
|
|
CAP_PROP_XI_SHUTTER_TYPE: int
|
|
CAP_PROP_XI_SENSOR_TAPS: int
|
|
CAP_PROP_XI_AEAG_ROI_OFFSET_X: int
|
|
CAP_PROP_XI_AEAG_ROI_OFFSET_Y: int
|
|
CAP_PROP_XI_AEAG_ROI_WIDTH: int
|
|
CAP_PROP_XI_AEAG_ROI_HEIGHT: int
|
|
CAP_PROP_XI_BPC: int
|
|
CAP_PROP_XI_WB_KR: int
|
|
CAP_PROP_XI_WB_KG: int
|
|
CAP_PROP_XI_WB_KB: int
|
|
CAP_PROP_XI_WIDTH: int
|
|
CAP_PROP_XI_HEIGHT: int
|
|
CAP_PROP_XI_REGION_SELECTOR: int
|
|
CAP_PROP_XI_REGION_MODE: int
|
|
CAP_PROP_XI_LIMIT_BANDWIDTH: int
|
|
CAP_PROP_XI_SENSOR_DATA_BIT_DEPTH: int
|
|
CAP_PROP_XI_OUTPUT_DATA_BIT_DEPTH: int
|
|
CAP_PROP_XI_IMAGE_DATA_BIT_DEPTH: int
|
|
CAP_PROP_XI_OUTPUT_DATA_PACKING: int
|
|
CAP_PROP_XI_OUTPUT_DATA_PACKING_TYPE: int
|
|
CAP_PROP_XI_IS_COOLED: int
|
|
CAP_PROP_XI_COOLING: int
|
|
CAP_PROP_XI_TARGET_TEMP: int
|
|
CAP_PROP_XI_CHIP_TEMP: int
|
|
CAP_PROP_XI_HOUS_TEMP: int
|
|
CAP_PROP_XI_HOUS_BACK_SIDE_TEMP: int
|
|
CAP_PROP_XI_SENSOR_BOARD_TEMP: int
|
|
CAP_PROP_XI_CMS: int
|
|
CAP_PROP_XI_APPLY_CMS: int
|
|
CAP_PROP_XI_IMAGE_IS_COLOR: int
|
|
CAP_PROP_XI_COLOR_FILTER_ARRAY: int
|
|
CAP_PROP_XI_GAMMAY: int
|
|
CAP_PROP_XI_GAMMAC: int
|
|
CAP_PROP_XI_SHARPNESS: int
|
|
CAP_PROP_XI_CC_MATRIX_00: int
|
|
CAP_PROP_XI_CC_MATRIX_01: int
|
|
CAP_PROP_XI_CC_MATRIX_02: int
|
|
CAP_PROP_XI_CC_MATRIX_03: int
|
|
CAP_PROP_XI_CC_MATRIX_10: int
|
|
CAP_PROP_XI_CC_MATRIX_11: int
|
|
CAP_PROP_XI_CC_MATRIX_12: int
|
|
CAP_PROP_XI_CC_MATRIX_13: int
|
|
CAP_PROP_XI_CC_MATRIX_20: int
|
|
CAP_PROP_XI_CC_MATRIX_21: int
|
|
CAP_PROP_XI_CC_MATRIX_22: int
|
|
CAP_PROP_XI_CC_MATRIX_23: int
|
|
CAP_PROP_XI_CC_MATRIX_30: int
|
|
CAP_PROP_XI_CC_MATRIX_31: int
|
|
CAP_PROP_XI_CC_MATRIX_32: int
|
|
CAP_PROP_XI_CC_MATRIX_33: int
|
|
CAP_PROP_XI_DEFAULT_CC_MATRIX: int
|
|
CAP_PROP_XI_TRG_SELECTOR: int
|
|
CAP_PROP_XI_ACQ_FRAME_BURST_COUNT: int
|
|
CAP_PROP_XI_DEBOUNCE_EN: int
|
|
CAP_PROP_XI_DEBOUNCE_T0: int
|
|
CAP_PROP_XI_DEBOUNCE_T1: int
|
|
CAP_PROP_XI_DEBOUNCE_POL: int
|
|
CAP_PROP_XI_LENS_MODE: int
|
|
CAP_PROP_XI_LENS_APERTURE_VALUE: int
|
|
CAP_PROP_XI_LENS_FOCUS_MOVEMENT_VALUE: int
|
|
CAP_PROP_XI_LENS_FOCUS_MOVE: int
|
|
CAP_PROP_XI_LENS_FOCUS_DISTANCE: int
|
|
CAP_PROP_XI_LENS_FOCAL_LENGTH: int
|
|
CAP_PROP_XI_LENS_FEATURE_SELECTOR: int
|
|
CAP_PROP_XI_LENS_FEATURE: int
|
|
CAP_PROP_XI_DEVICE_MODEL_ID: int
|
|
CAP_PROP_XI_DEVICE_SN: int
|
|
CAP_PROP_XI_IMAGE_DATA_FORMAT_RGB32_ALPHA: int
|
|
CAP_PROP_XI_IMAGE_PAYLOAD_SIZE: int
|
|
CAP_PROP_XI_TRANSPORT_PIXEL_FORMAT: int
|
|
CAP_PROP_XI_SENSOR_CLOCK_FREQ_HZ: int
|
|
CAP_PROP_XI_SENSOR_CLOCK_FREQ_INDEX: int
|
|
CAP_PROP_XI_SENSOR_OUTPUT_CHANNEL_COUNT: int
|
|
CAP_PROP_XI_FRAMERATE: int
|
|
CAP_PROP_XI_COUNTER_SELECTOR: int
|
|
CAP_PROP_XI_COUNTER_VALUE: int
|
|
CAP_PROP_XI_ACQ_TIMING_MODE: int
|
|
CAP_PROP_XI_AVAILABLE_BANDWIDTH: int
|
|
CAP_PROP_XI_BUFFER_POLICY: int
|
|
CAP_PROP_XI_LUT_EN: int
|
|
CAP_PROP_XI_LUT_INDEX: int
|
|
CAP_PROP_XI_LUT_VALUE: int
|
|
CAP_PROP_XI_TRG_DELAY: int
|
|
CAP_PROP_XI_TS_RST_MODE: int
|
|
CAP_PROP_XI_TS_RST_SOURCE: int
|
|
CAP_PROP_XI_IS_DEVICE_EXIST: int
|
|
CAP_PROP_XI_ACQ_BUFFER_SIZE: int
|
|
CAP_PROP_XI_ACQ_BUFFER_SIZE_UNIT: int
|
|
CAP_PROP_XI_ACQ_TRANSPORT_BUFFER_SIZE: int
|
|
CAP_PROP_XI_BUFFERS_QUEUE_SIZE: int
|
|
CAP_PROP_XI_ACQ_TRANSPORT_BUFFER_COMMIT: int
|
|
CAP_PROP_XI_RECENT_FRAME: int
|
|
CAP_PROP_XI_DEVICE_RESET: int
|
|
CAP_PROP_XI_COLUMN_FPN_CORRECTION: int
|
|
CAP_PROP_XI_ROW_FPN_CORRECTION: int
|
|
CAP_PROP_XI_SENSOR_MODE: int
|
|
CAP_PROP_XI_HDR: int
|
|
CAP_PROP_XI_HDR_KNEEPOINT_COUNT: int
|
|
CAP_PROP_XI_HDR_T1: int
|
|
CAP_PROP_XI_HDR_T2: int
|
|
CAP_PROP_XI_KNEEPOINT1: int
|
|
CAP_PROP_XI_KNEEPOINT2: int
|
|
CAP_PROP_XI_IMAGE_BLACK_LEVEL: int
|
|
CAP_PROP_XI_HW_REVISION: int
|
|
CAP_PROP_XI_DEBUG_LEVEL: int
|
|
CAP_PROP_XI_AUTO_BANDWIDTH_CALCULATION: int
|
|
CAP_PROP_XI_FFS_FILE_ID: int
|
|
CAP_PROP_XI_FFS_FILE_SIZE: int
|
|
CAP_PROP_XI_FREE_FFS_SIZE: int
|
|
CAP_PROP_XI_USED_FFS_SIZE: int
|
|
CAP_PROP_XI_FFS_ACCESS_KEY: int
|
|
CAP_PROP_XI_SENSOR_FEATURE_SELECTOR: int
|
|
CAP_PROP_XI_SENSOR_FEATURE_VALUE: int
|
|
CAP_PROP_ARAVIS_AUTOTRIGGER: int
|
|
CAP_PROP_IOS_DEVICE_FOCUS: int
|
|
CAP_PROP_IOS_DEVICE_EXPOSURE: int
|
|
CAP_PROP_IOS_DEVICE_FLASH: int
|
|
CAP_PROP_IOS_DEVICE_WHITEBALANCE: int
|
|
CAP_PROP_IOS_DEVICE_TORCH: int
|
|
CAP_PROP_GIGA_FRAME_OFFSET_X: int
|
|
CAP_PROP_GIGA_FRAME_OFFSET_Y: int
|
|
CAP_PROP_GIGA_FRAME_WIDTH_MAX: int
|
|
CAP_PROP_GIGA_FRAME_HEIGH_MAX: int
|
|
CAP_PROP_GIGA_FRAME_SENS_WIDTH: int
|
|
CAP_PROP_GIGA_FRAME_SENS_HEIGH: int
|
|
CAP_PROP_INTELPERC_PROFILE_COUNT: int
|
|
CAP_PROP_INTELPERC_PROFILE_IDX: int
|
|
CAP_PROP_INTELPERC_DEPTH_LOW_CONFIDENCE_VALUE: int
|
|
CAP_PROP_INTELPERC_DEPTH_SATURATION_VALUE: int
|
|
CAP_PROP_INTELPERC_DEPTH_CONFIDENCE_THRESHOLD: int
|
|
CAP_PROP_INTELPERC_DEPTH_FOCAL_LENGTH_HORZ: int
|
|
CAP_PROP_INTELPERC_DEPTH_FOCAL_LENGTH_VERT: int
|
|
CAP_INTELPERC_DEPTH_GENERATOR: int
|
|
CAP_INTELPERC_IMAGE_GENERATOR: int
|
|
CAP_INTELPERC_IR_GENERATOR: int
|
|
CAP_INTELPERC_GENERATORS_MASK: int
|
|
CAP_INTELPERC_DEPTH_MAP: int
|
|
CAP_INTELPERC_UVDEPTH_MAP: int
|
|
CAP_INTELPERC_IR_MAP: int
|
|
CAP_INTELPERC_IMAGE: int
|
|
CAP_PROP_GPHOTO2_PREVIEW: int
|
|
CAP_PROP_GPHOTO2_WIDGET_ENUMERATE: int
|
|
CAP_PROP_GPHOTO2_RELOAD_CONFIG: int
|
|
CAP_PROP_GPHOTO2_RELOAD_ON_CHANGE: int
|
|
CAP_PROP_GPHOTO2_COLLECT_MSGS: int
|
|
CAP_PROP_GPHOTO2_FLUSH_MSGS: int
|
|
CAP_PROP_SPEED: int
|
|
CAP_PROP_APERTURE: int
|
|
CAP_PROP_EXPOSUREPROGRAM: int
|
|
CAP_PROP_VIEWFINDER: int
|
|
CAP_PROP_IMAGES_BASE: int
|
|
CAP_PROP_IMAGES_LAST: int
|
|
LMEDS: int
|
|
RANSAC: int
|
|
RHO: int
|
|
USAC_DEFAULT: int
|
|
USAC_PARALLEL: int
|
|
USAC_FM_8PTS: int
|
|
USAC_FAST: int
|
|
USAC_ACCURATE: int
|
|
USAC_PROSAC: int
|
|
USAC_MAGSAC: int
|
|
CALIB_CB_ADAPTIVE_THRESH: int
|
|
CALIB_CB_NORMALIZE_IMAGE: int
|
|
CALIB_CB_FILTER_QUADS: int
|
|
CALIB_CB_FAST_CHECK: int
|
|
CALIB_CB_EXHAUSTIVE: int
|
|
CALIB_CB_ACCURACY: int
|
|
CALIB_CB_LARGER: int
|
|
CALIB_CB_MARKER: int
|
|
CALIB_CB_PLAIN: int
|
|
CALIB_CB_SYMMETRIC_GRID: int
|
|
CALIB_CB_ASYMMETRIC_GRID: int
|
|
CALIB_CB_CLUSTERING: int
|
|
CALIB_NINTRINSIC: int
|
|
CALIB_USE_INTRINSIC_GUESS: int
|
|
CALIB_FIX_ASPECT_RATIO: int
|
|
CALIB_FIX_PRINCIPAL_POINT: int
|
|
CALIB_ZERO_TANGENT_DIST: int
|
|
CALIB_FIX_FOCAL_LENGTH: int
|
|
CALIB_FIX_K1: int
|
|
CALIB_FIX_K2: int
|
|
CALIB_FIX_K3: int
|
|
CALIB_FIX_K4: int
|
|
CALIB_FIX_K5: int
|
|
CALIB_FIX_K6: int
|
|
CALIB_RATIONAL_MODEL: int
|
|
CALIB_THIN_PRISM_MODEL: int
|
|
CALIB_FIX_S1_S2_S3_S4: int
|
|
CALIB_TILTED_MODEL: int
|
|
CALIB_FIX_TAUX_TAUY: int
|
|
CALIB_USE_QR: int
|
|
CALIB_FIX_TANGENT_DIST: int
|
|
CALIB_FIX_INTRINSIC: int
|
|
CALIB_SAME_FOCAL_LENGTH: int
|
|
CALIB_ZERO_DISPARITY: int
|
|
CALIB_USE_LU: int
|
|
CALIB_USE_EXTRINSIC_GUESS: int
|
|
FM_7POINT: int
|
|
FM_8POINT: int
|
|
FM_LMEDS: int
|
|
FM_RANSAC: int
|
|
CASCADE_DO_CANNY_PRUNING: int
|
|
CASCADE_SCALE_IMAGE: int
|
|
CASCADE_FIND_BIGGEST_OBJECT: int
|
|
CASCADE_DO_ROUGH_SEARCH: int
|
|
OPTFLOW_USE_INITIAL_FLOW: int
|
|
OPTFLOW_LK_GET_MIN_EIGENVALS: int
|
|
OPTFLOW_FARNEBACK_GAUSSIAN: int
|
|
MOTION_TRANSLATION: int
|
|
MOTION_EUCLIDEAN: int
|
|
MOTION_AFFINE: int
|
|
MOTION_HOMOGRAPHY: int
|
|
|
|
DrawMatchesFlags_DEFAULT: int
|
|
DRAW_MATCHES_FLAGS_DEFAULT: int
|
|
DrawMatchesFlags_DRAW_OVER_OUTIMG: int
|
|
DRAW_MATCHES_FLAGS_DRAW_OVER_OUTIMG: int
|
|
DrawMatchesFlags_NOT_DRAW_SINGLE_POINTS: int
|
|
DRAW_MATCHES_FLAGS_NOT_DRAW_SINGLE_POINTS: int
|
|
DrawMatchesFlags_DRAW_RICH_KEYPOINTS: int
|
|
DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS: int
|
|
DrawMatchesFlags = int
|
|
"""One of [DrawMatchesFlags_DEFAULT, DRAW_MATCHES_FLAGS_DEFAULT, DrawMatchesFlags_DRAW_OVER_OUTIMG, DRAW_MATCHES_FLAGS_DRAW_OVER_OUTIMG, DrawMatchesFlags_NOT_DRAW_SINGLE_POINTS, DRAW_MATCHES_FLAGS_NOT_DRAW_SINGLE_POINTS, DrawMatchesFlags_DRAW_RICH_KEYPOINTS, DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS]"""
|
|
|
|
IMREAD_UNCHANGED: int
|
|
IMREAD_GRAYSCALE: int
|
|
IMREAD_COLOR: int
|
|
IMREAD_ANYDEPTH: int
|
|
IMREAD_ANYCOLOR: int
|
|
IMREAD_LOAD_GDAL: int
|
|
IMREAD_REDUCED_GRAYSCALE_2: int
|
|
IMREAD_REDUCED_COLOR_2: int
|
|
IMREAD_REDUCED_GRAYSCALE_4: int
|
|
IMREAD_REDUCED_COLOR_4: int
|
|
IMREAD_REDUCED_GRAYSCALE_8: int
|
|
IMREAD_REDUCED_COLOR_8: int
|
|
IMREAD_IGNORE_ORIENTATION: int
|
|
ImreadModes = int
|
|
"""One of [IMREAD_UNCHANGED, IMREAD_GRAYSCALE, IMREAD_COLOR, IMREAD_ANYDEPTH, IMREAD_ANYCOLOR, IMREAD_LOAD_GDAL, IMREAD_REDUCED_GRAYSCALE_2, IMREAD_REDUCED_COLOR_2, IMREAD_REDUCED_GRAYSCALE_4, IMREAD_REDUCED_COLOR_4, IMREAD_REDUCED_GRAYSCALE_8, IMREAD_REDUCED_COLOR_8, IMREAD_IGNORE_ORIENTATION]"""
|
|
|
|
IMWRITE_JPEG_QUALITY: int
|
|
IMWRITE_JPEG_PROGRESSIVE: int
|
|
IMWRITE_JPEG_OPTIMIZE: int
|
|
IMWRITE_JPEG_RST_INTERVAL: int
|
|
IMWRITE_JPEG_LUMA_QUALITY: int
|
|
IMWRITE_JPEG_CHROMA_QUALITY: int
|
|
IMWRITE_JPEG_SAMPLING_FACTOR: int
|
|
IMWRITE_PNG_COMPRESSION: int
|
|
IMWRITE_PNG_STRATEGY: int
|
|
IMWRITE_PNG_BILEVEL: int
|
|
IMWRITE_PXM_BINARY: int
|
|
IMWRITE_EXR_TYPE: int
|
|
IMWRITE_EXR_COMPRESSION: int
|
|
IMWRITE_EXR_DWA_COMPRESSION_LEVEL: int
|
|
IMWRITE_WEBP_QUALITY: int
|
|
IMWRITE_HDR_COMPRESSION: int
|
|
IMWRITE_PAM_TUPLETYPE: int
|
|
IMWRITE_TIFF_RESUNIT: int
|
|
IMWRITE_TIFF_XDPI: int
|
|
IMWRITE_TIFF_YDPI: int
|
|
IMWRITE_TIFF_COMPRESSION: int
|
|
IMWRITE_TIFF_ROWSPERSTRIP: int
|
|
IMWRITE_TIFF_PREDICTOR: int
|
|
IMWRITE_JPEG2000_COMPRESSION_X1000: int
|
|
IMWRITE_AVIF_QUALITY: int
|
|
IMWRITE_AVIF_DEPTH: int
|
|
IMWRITE_AVIF_SPEED: int
|
|
ImwriteFlags = int
|
|
"""One of [IMWRITE_JPEG_QUALITY, IMWRITE_JPEG_PROGRESSIVE, IMWRITE_JPEG_OPTIMIZE, IMWRITE_JPEG_RST_INTERVAL, IMWRITE_JPEG_LUMA_QUALITY, IMWRITE_JPEG_CHROMA_QUALITY, IMWRITE_JPEG_SAMPLING_FACTOR, IMWRITE_PNG_COMPRESSION, IMWRITE_PNG_STRATEGY, IMWRITE_PNG_BILEVEL, IMWRITE_PXM_BINARY, IMWRITE_EXR_TYPE, IMWRITE_EXR_COMPRESSION, IMWRITE_EXR_DWA_COMPRESSION_LEVEL, IMWRITE_WEBP_QUALITY, IMWRITE_HDR_COMPRESSION, IMWRITE_PAM_TUPLETYPE, IMWRITE_TIFF_RESUNIT, IMWRITE_TIFF_XDPI, IMWRITE_TIFF_YDPI, IMWRITE_TIFF_COMPRESSION, IMWRITE_TIFF_ROWSPERSTRIP, IMWRITE_TIFF_PREDICTOR, IMWRITE_JPEG2000_COMPRESSION_X1000, IMWRITE_AVIF_QUALITY, IMWRITE_AVIF_DEPTH, IMWRITE_AVIF_SPEED]"""
|
|
|
|
IMWRITE_JPEG_SAMPLING_FACTOR_411: int
|
|
IMWRITE_JPEG_SAMPLING_FACTOR_420: int
|
|
IMWRITE_JPEG_SAMPLING_FACTOR_422: int
|
|
IMWRITE_JPEG_SAMPLING_FACTOR_440: int
|
|
IMWRITE_JPEG_SAMPLING_FACTOR_444: int
|
|
ImwriteJPEGSamplingFactorParams = int
|
|
"""One of [IMWRITE_JPEG_SAMPLING_FACTOR_411, IMWRITE_JPEG_SAMPLING_FACTOR_420, IMWRITE_JPEG_SAMPLING_FACTOR_422, IMWRITE_JPEG_SAMPLING_FACTOR_440, IMWRITE_JPEG_SAMPLING_FACTOR_444]"""
|
|
|
|
IMWRITE_TIFF_COMPRESSION_NONE: int
|
|
IMWRITE_TIFF_COMPRESSION_CCITTRLE: int
|
|
IMWRITE_TIFF_COMPRESSION_CCITTFAX3: int
|
|
IMWRITE_TIFF_COMPRESSION_CCITT_T4: int
|
|
IMWRITE_TIFF_COMPRESSION_CCITTFAX4: int
|
|
IMWRITE_TIFF_COMPRESSION_CCITT_T6: int
|
|
IMWRITE_TIFF_COMPRESSION_LZW: int
|
|
IMWRITE_TIFF_COMPRESSION_OJPEG: int
|
|
IMWRITE_TIFF_COMPRESSION_JPEG: int
|
|
IMWRITE_TIFF_COMPRESSION_T85: int
|
|
IMWRITE_TIFF_COMPRESSION_T43: int
|
|
IMWRITE_TIFF_COMPRESSION_NEXT: int
|
|
IMWRITE_TIFF_COMPRESSION_CCITTRLEW: int
|
|
IMWRITE_TIFF_COMPRESSION_PACKBITS: int
|
|
IMWRITE_TIFF_COMPRESSION_THUNDERSCAN: int
|
|
IMWRITE_TIFF_COMPRESSION_IT8CTPAD: int
|
|
IMWRITE_TIFF_COMPRESSION_IT8LW: int
|
|
IMWRITE_TIFF_COMPRESSION_IT8MP: int
|
|
IMWRITE_TIFF_COMPRESSION_IT8BL: int
|
|
IMWRITE_TIFF_COMPRESSION_PIXARFILM: int
|
|
IMWRITE_TIFF_COMPRESSION_PIXARLOG: int
|
|
IMWRITE_TIFF_COMPRESSION_DEFLATE: int
|
|
IMWRITE_TIFF_COMPRESSION_ADOBE_DEFLATE: int
|
|
IMWRITE_TIFF_COMPRESSION_DCS: int
|
|
IMWRITE_TIFF_COMPRESSION_JBIG: int
|
|
IMWRITE_TIFF_COMPRESSION_SGILOG: int
|
|
IMWRITE_TIFF_COMPRESSION_SGILOG24: int
|
|
IMWRITE_TIFF_COMPRESSION_JP2000: int
|
|
IMWRITE_TIFF_COMPRESSION_LERC: int
|
|
IMWRITE_TIFF_COMPRESSION_LZMA: int
|
|
IMWRITE_TIFF_COMPRESSION_ZSTD: int
|
|
IMWRITE_TIFF_COMPRESSION_WEBP: int
|
|
IMWRITE_TIFF_COMPRESSION_JXL: int
|
|
ImwriteTiffCompressionFlags = int
|
|
"""One of [IMWRITE_TIFF_COMPRESSION_NONE, IMWRITE_TIFF_COMPRESSION_CCITTRLE, IMWRITE_TIFF_COMPRESSION_CCITTFAX3, IMWRITE_TIFF_COMPRESSION_CCITT_T4, IMWRITE_TIFF_COMPRESSION_CCITTFAX4, IMWRITE_TIFF_COMPRESSION_CCITT_T6, IMWRITE_TIFF_COMPRESSION_LZW, IMWRITE_TIFF_COMPRESSION_OJPEG, IMWRITE_TIFF_COMPRESSION_JPEG, IMWRITE_TIFF_COMPRESSION_T85, IMWRITE_TIFF_COMPRESSION_T43, IMWRITE_TIFF_COMPRESSION_NEXT, IMWRITE_TIFF_COMPRESSION_CCITTRLEW, IMWRITE_TIFF_COMPRESSION_PACKBITS, IMWRITE_TIFF_COMPRESSION_THUNDERSCAN, IMWRITE_TIFF_COMPRESSION_IT8CTPAD, IMWRITE_TIFF_COMPRESSION_IT8LW, IMWRITE_TIFF_COMPRESSION_IT8MP, IMWRITE_TIFF_COMPRESSION_IT8BL, IMWRITE_TIFF_COMPRESSION_PIXARFILM, IMWRITE_TIFF_COMPRESSION_PIXARLOG, IMWRITE_TIFF_COMPRESSION_DEFLATE, IMWRITE_TIFF_COMPRESSION_ADOBE_DEFLATE, IMWRITE_TIFF_COMPRESSION_DCS, IMWRITE_TIFF_COMPRESSION_JBIG, IMWRITE_TIFF_COMPRESSION_SGILOG, IMWRITE_TIFF_COMPRESSION_SGILOG24, IMWRITE_TIFF_COMPRESSION_JP2000, IMWRITE_TIFF_COMPRESSION_LERC, IMWRITE_TIFF_COMPRESSION_LZMA, IMWRITE_TIFF_COMPRESSION_ZSTD, IMWRITE_TIFF_COMPRESSION_WEBP, IMWRITE_TIFF_COMPRESSION_JXL]"""
|
|
|
|
IMWRITE_TIFF_PREDICTOR_NONE: int
|
|
IMWRITE_TIFF_PREDICTOR_HORIZONTAL: int
|
|
IMWRITE_TIFF_PREDICTOR_FLOATINGPOINT: int
|
|
ImwriteTiffPredictorFlags = int
|
|
"""One of [IMWRITE_TIFF_PREDICTOR_NONE, IMWRITE_TIFF_PREDICTOR_HORIZONTAL, IMWRITE_TIFF_PREDICTOR_FLOATINGPOINT]"""
|
|
|
|
IMWRITE_EXR_TYPE_HALF: int
|
|
IMWRITE_EXR_TYPE_FLOAT: int
|
|
ImwriteEXRTypeFlags = int
|
|
"""One of [IMWRITE_EXR_TYPE_HALF, IMWRITE_EXR_TYPE_FLOAT]"""
|
|
|
|
IMWRITE_EXR_COMPRESSION_NO: int
|
|
IMWRITE_EXR_COMPRESSION_RLE: int
|
|
IMWRITE_EXR_COMPRESSION_ZIPS: int
|
|
IMWRITE_EXR_COMPRESSION_ZIP: int
|
|
IMWRITE_EXR_COMPRESSION_PIZ: int
|
|
IMWRITE_EXR_COMPRESSION_PXR24: int
|
|
IMWRITE_EXR_COMPRESSION_B44: int
|
|
IMWRITE_EXR_COMPRESSION_B44A: int
|
|
IMWRITE_EXR_COMPRESSION_DWAA: int
|
|
IMWRITE_EXR_COMPRESSION_DWAB: int
|
|
ImwriteEXRCompressionFlags = int
|
|
"""One of [IMWRITE_EXR_COMPRESSION_NO, IMWRITE_EXR_COMPRESSION_RLE, IMWRITE_EXR_COMPRESSION_ZIPS, IMWRITE_EXR_COMPRESSION_ZIP, IMWRITE_EXR_COMPRESSION_PIZ, IMWRITE_EXR_COMPRESSION_PXR24, IMWRITE_EXR_COMPRESSION_B44, IMWRITE_EXR_COMPRESSION_B44A, IMWRITE_EXR_COMPRESSION_DWAA, IMWRITE_EXR_COMPRESSION_DWAB]"""
|
|
|
|
IMWRITE_PNG_STRATEGY_DEFAULT: int
|
|
IMWRITE_PNG_STRATEGY_FILTERED: int
|
|
IMWRITE_PNG_STRATEGY_HUFFMAN_ONLY: int
|
|
IMWRITE_PNG_STRATEGY_RLE: int
|
|
IMWRITE_PNG_STRATEGY_FIXED: int
|
|
ImwritePNGFlags = int
|
|
"""One of [IMWRITE_PNG_STRATEGY_DEFAULT, IMWRITE_PNG_STRATEGY_FILTERED, IMWRITE_PNG_STRATEGY_HUFFMAN_ONLY, IMWRITE_PNG_STRATEGY_RLE, IMWRITE_PNG_STRATEGY_FIXED]"""
|
|
|
|
IMWRITE_PAM_FORMAT_NULL: int
|
|
IMWRITE_PAM_FORMAT_BLACKANDWHITE: int
|
|
IMWRITE_PAM_FORMAT_GRAYSCALE: int
|
|
IMWRITE_PAM_FORMAT_GRAYSCALE_ALPHA: int
|
|
IMWRITE_PAM_FORMAT_RGB: int
|
|
IMWRITE_PAM_FORMAT_RGB_ALPHA: int
|
|
ImwritePAMFlags = int
|
|
"""One of [IMWRITE_PAM_FORMAT_NULL, IMWRITE_PAM_FORMAT_BLACKANDWHITE, IMWRITE_PAM_FORMAT_GRAYSCALE, IMWRITE_PAM_FORMAT_GRAYSCALE_ALPHA, IMWRITE_PAM_FORMAT_RGB, IMWRITE_PAM_FORMAT_RGB_ALPHA]"""
|
|
|
|
IMWRITE_HDR_COMPRESSION_NONE: int
|
|
IMWRITE_HDR_COMPRESSION_RLE: int
|
|
ImwriteHDRCompressionFlags = int
|
|
"""One of [IMWRITE_HDR_COMPRESSION_NONE, IMWRITE_HDR_COMPRESSION_RLE]"""
|
|
|
|
CAP_ANY: int
|
|
CAP_VFW: int
|
|
CAP_V4L: int
|
|
CAP_V4L2: int
|
|
CAP_FIREWIRE: int
|
|
CAP_FIREWARE: int
|
|
CAP_IEEE1394: int
|
|
CAP_DC1394: int
|
|
CAP_CMU1394: int
|
|
CAP_QT: int
|
|
CAP_UNICAP: int
|
|
CAP_DSHOW: int
|
|
CAP_PVAPI: int
|
|
CAP_OPENNI: int
|
|
CAP_OPENNI_ASUS: int
|
|
CAP_ANDROID: int
|
|
CAP_XIAPI: int
|
|
CAP_AVFOUNDATION: int
|
|
CAP_GIGANETIX: int
|
|
CAP_MSMF: int
|
|
CAP_WINRT: int
|
|
CAP_INTELPERC: int
|
|
CAP_REALSENSE: int
|
|
CAP_OPENNI2: int
|
|
CAP_OPENNI2_ASUS: int
|
|
CAP_OPENNI2_ASTRA: int
|
|
CAP_GPHOTO2: int
|
|
CAP_GSTREAMER: int
|
|
CAP_FFMPEG: int
|
|
CAP_IMAGES: int
|
|
CAP_ARAVIS: int
|
|
CAP_OPENCV_MJPEG: int
|
|
CAP_INTEL_MFX: int
|
|
CAP_XINE: int
|
|
CAP_UEYE: int
|
|
CAP_OBSENSOR: int
|
|
VideoCaptureAPIs = int
|
|
"""One of [CAP_ANY, CAP_VFW, CAP_V4L, CAP_V4L2, CAP_FIREWIRE, CAP_FIREWARE, CAP_IEEE1394, CAP_DC1394, CAP_CMU1394, CAP_QT, CAP_UNICAP, CAP_DSHOW, CAP_PVAPI, CAP_OPENNI, CAP_OPENNI_ASUS, CAP_ANDROID, CAP_XIAPI, CAP_AVFOUNDATION, CAP_GIGANETIX, CAP_MSMF, CAP_WINRT, CAP_INTELPERC, CAP_REALSENSE, CAP_OPENNI2, CAP_OPENNI2_ASUS, CAP_OPENNI2_ASTRA, CAP_GPHOTO2, CAP_GSTREAMER, CAP_FFMPEG, CAP_IMAGES, CAP_ARAVIS, CAP_OPENCV_MJPEG, CAP_INTEL_MFX, CAP_XINE, CAP_UEYE, CAP_OBSENSOR]"""
|
|
|
|
CAP_PROP_POS_MSEC: int
|
|
CAP_PROP_POS_FRAMES: int
|
|
CAP_PROP_POS_AVI_RATIO: int
|
|
CAP_PROP_FRAME_WIDTH: int
|
|
CAP_PROP_FRAME_HEIGHT: int
|
|
CAP_PROP_FPS: int
|
|
CAP_PROP_FOURCC: int
|
|
CAP_PROP_FRAME_COUNT: int
|
|
CAP_PROP_FORMAT: int
|
|
CAP_PROP_MODE: int
|
|
CAP_PROP_BRIGHTNESS: int
|
|
CAP_PROP_CONTRAST: int
|
|
CAP_PROP_SATURATION: int
|
|
CAP_PROP_HUE: int
|
|
CAP_PROP_GAIN: int
|
|
CAP_PROP_EXPOSURE: int
|
|
CAP_PROP_CONVERT_RGB: int
|
|
CAP_PROP_WHITE_BALANCE_BLUE_U: int
|
|
CAP_PROP_RECTIFICATION: int
|
|
CAP_PROP_MONOCHROME: int
|
|
CAP_PROP_SHARPNESS: int
|
|
CAP_PROP_AUTO_EXPOSURE: int
|
|
CAP_PROP_GAMMA: int
|
|
CAP_PROP_TEMPERATURE: int
|
|
CAP_PROP_TRIGGER: int
|
|
CAP_PROP_TRIGGER_DELAY: int
|
|
CAP_PROP_WHITE_BALANCE_RED_V: int
|
|
CAP_PROP_ZOOM: int
|
|
CAP_PROP_FOCUS: int
|
|
CAP_PROP_GUID: int
|
|
CAP_PROP_ISO_SPEED: int
|
|
CAP_PROP_BACKLIGHT: int
|
|
CAP_PROP_PAN: int
|
|
CAP_PROP_TILT: int
|
|
CAP_PROP_ROLL: int
|
|
CAP_PROP_IRIS: int
|
|
CAP_PROP_SETTINGS: int
|
|
CAP_PROP_BUFFERSIZE: int
|
|
CAP_PROP_AUTOFOCUS: int
|
|
CAP_PROP_SAR_NUM: int
|
|
CAP_PROP_SAR_DEN: int
|
|
CAP_PROP_BACKEND: int
|
|
CAP_PROP_CHANNEL: int
|
|
CAP_PROP_AUTO_WB: int
|
|
CAP_PROP_WB_TEMPERATURE: int
|
|
CAP_PROP_CODEC_PIXEL_FORMAT: int
|
|
CAP_PROP_BITRATE: int
|
|
CAP_PROP_ORIENTATION_META: int
|
|
CAP_PROP_ORIENTATION_AUTO: int
|
|
CAP_PROP_HW_ACCELERATION: int
|
|
CAP_PROP_HW_DEVICE: int
|
|
CAP_PROP_HW_ACCELERATION_USE_OPENCL: int
|
|
CAP_PROP_OPEN_TIMEOUT_MSEC: int
|
|
CAP_PROP_READ_TIMEOUT_MSEC: int
|
|
CAP_PROP_STREAM_OPEN_TIME_USEC: int
|
|
CAP_PROP_VIDEO_TOTAL_CHANNELS: int
|
|
CAP_PROP_VIDEO_STREAM: int
|
|
CAP_PROP_AUDIO_STREAM: int
|
|
CAP_PROP_AUDIO_POS: int
|
|
CAP_PROP_AUDIO_SHIFT_NSEC: int
|
|
CAP_PROP_AUDIO_DATA_DEPTH: int
|
|
CAP_PROP_AUDIO_SAMPLES_PER_SECOND: int
|
|
CAP_PROP_AUDIO_BASE_INDEX: int
|
|
CAP_PROP_AUDIO_TOTAL_CHANNELS: int
|
|
CAP_PROP_AUDIO_TOTAL_STREAMS: int
|
|
CAP_PROP_AUDIO_SYNCHRONIZE: int
|
|
CAP_PROP_LRF_HAS_KEY_FRAME: int
|
|
CAP_PROP_CODEC_EXTRADATA_INDEX: int
|
|
CAP_PROP_FRAME_TYPE: int
|
|
CAP_PROP_N_THREADS: int
|
|
VideoCaptureProperties = int
|
|
"""One of [CAP_PROP_POS_MSEC, CAP_PROP_POS_FRAMES, CAP_PROP_POS_AVI_RATIO, CAP_PROP_FRAME_WIDTH, CAP_PROP_FRAME_HEIGHT, CAP_PROP_FPS, CAP_PROP_FOURCC, CAP_PROP_FRAME_COUNT, CAP_PROP_FORMAT, CAP_PROP_MODE, CAP_PROP_BRIGHTNESS, CAP_PROP_CONTRAST, CAP_PROP_SATURATION, CAP_PROP_HUE, CAP_PROP_GAIN, CAP_PROP_EXPOSURE, CAP_PROP_CONVERT_RGB, CAP_PROP_WHITE_BALANCE_BLUE_U, CAP_PROP_RECTIFICATION, CAP_PROP_MONOCHROME, CAP_PROP_SHARPNESS, CAP_PROP_AUTO_EXPOSURE, CAP_PROP_GAMMA, CAP_PROP_TEMPERATURE, CAP_PROP_TRIGGER, CAP_PROP_TRIGGER_DELAY, CAP_PROP_WHITE_BALANCE_RED_V, CAP_PROP_ZOOM, CAP_PROP_FOCUS, CAP_PROP_GUID, CAP_PROP_ISO_SPEED, CAP_PROP_BACKLIGHT, CAP_PROP_PAN, CAP_PROP_TILT, CAP_PROP_ROLL, CAP_PROP_IRIS, CAP_PROP_SETTINGS, CAP_PROP_BUFFERSIZE, CAP_PROP_AUTOFOCUS, CAP_PROP_SAR_NUM, CAP_PROP_SAR_DEN, CAP_PROP_BACKEND, CAP_PROP_CHANNEL, CAP_PROP_AUTO_WB, CAP_PROP_WB_TEMPERATURE, CAP_PROP_CODEC_PIXEL_FORMAT, CAP_PROP_BITRATE, CAP_PROP_ORIENTATION_META, CAP_PROP_ORIENTATION_AUTO, CAP_PROP_HW_ACCELERATION, CAP_PROP_HW_DEVICE, CAP_PROP_HW_ACCELERATION_USE_OPENCL, CAP_PROP_OPEN_TIMEOUT_MSEC, CAP_PROP_READ_TIMEOUT_MSEC, CAP_PROP_STREAM_OPEN_TIME_USEC, CAP_PROP_VIDEO_TOTAL_CHANNELS, CAP_PROP_VIDEO_STREAM, CAP_PROP_AUDIO_STREAM, CAP_PROP_AUDIO_POS, CAP_PROP_AUDIO_SHIFT_NSEC, CAP_PROP_AUDIO_DATA_DEPTH, CAP_PROP_AUDIO_SAMPLES_PER_SECOND, CAP_PROP_AUDIO_BASE_INDEX, CAP_PROP_AUDIO_TOTAL_CHANNELS, CAP_PROP_AUDIO_TOTAL_STREAMS, CAP_PROP_AUDIO_SYNCHRONIZE, CAP_PROP_LRF_HAS_KEY_FRAME, CAP_PROP_CODEC_EXTRADATA_INDEX, CAP_PROP_FRAME_TYPE, CAP_PROP_N_THREADS]"""
|
|
|
|
VIDEOWRITER_PROP_QUALITY: int
|
|
VIDEOWRITER_PROP_FRAMEBYTES: int
|
|
VIDEOWRITER_PROP_NSTRIPES: int
|
|
VIDEOWRITER_PROP_IS_COLOR: int
|
|
VIDEOWRITER_PROP_DEPTH: int
|
|
VIDEOWRITER_PROP_HW_ACCELERATION: int
|
|
VIDEOWRITER_PROP_HW_DEVICE: int
|
|
VIDEOWRITER_PROP_HW_ACCELERATION_USE_OPENCL: int
|
|
VIDEOWRITER_PROP_RAW_VIDEO: int
|
|
VIDEOWRITER_PROP_KEY_INTERVAL: int
|
|
VIDEOWRITER_PROP_KEY_FLAG: int
|
|
VideoWriterProperties = int
|
|
"""One of [VIDEOWRITER_PROP_QUALITY, VIDEOWRITER_PROP_FRAMEBYTES, VIDEOWRITER_PROP_NSTRIPES, VIDEOWRITER_PROP_IS_COLOR, VIDEOWRITER_PROP_DEPTH, VIDEOWRITER_PROP_HW_ACCELERATION, VIDEOWRITER_PROP_HW_DEVICE, VIDEOWRITER_PROP_HW_ACCELERATION_USE_OPENCL, VIDEOWRITER_PROP_RAW_VIDEO, VIDEOWRITER_PROP_KEY_INTERVAL, VIDEOWRITER_PROP_KEY_FLAG]"""
|
|
|
|
VIDEO_ACCELERATION_NONE: int
|
|
VIDEO_ACCELERATION_ANY: int
|
|
VIDEO_ACCELERATION_D3D11: int
|
|
VIDEO_ACCELERATION_VAAPI: int
|
|
VIDEO_ACCELERATION_MFX: int
|
|
VideoAccelerationType = int
|
|
"""One of [VIDEO_ACCELERATION_NONE, VIDEO_ACCELERATION_ANY, VIDEO_ACCELERATION_D3D11, VIDEO_ACCELERATION_VAAPI, VIDEO_ACCELERATION_MFX]"""
|
|
|
|
CAP_OBSENSOR_DEPTH_MAP: int
|
|
CAP_OBSENSOR_BGR_IMAGE: int
|
|
CAP_OBSENSOR_IR_IMAGE: int
|
|
VideoCaptureOBSensorDataType = int
|
|
"""One of [CAP_OBSENSOR_DEPTH_MAP, CAP_OBSENSOR_BGR_IMAGE, CAP_OBSENSOR_IR_IMAGE]"""
|
|
|
|
CAP_OBSENSOR_DEPTH_GENERATOR: int
|
|
CAP_OBSENSOR_IMAGE_GENERATOR: int
|
|
CAP_OBSENSOR_IR_GENERATOR: int
|
|
CAP_OBSENSOR_GENERATORS_MASK: int
|
|
VideoCaptureOBSensorGenerators = int
|
|
"""One of [CAP_OBSENSOR_DEPTH_GENERATOR, CAP_OBSENSOR_IMAGE_GENERATOR, CAP_OBSENSOR_IR_GENERATOR, CAP_OBSENSOR_GENERATORS_MASK]"""
|
|
|
|
CAP_PROP_OBSENSOR_INTRINSIC_FX: int
|
|
CAP_PROP_OBSENSOR_INTRINSIC_FY: int
|
|
CAP_PROP_OBSENSOR_INTRINSIC_CX: int
|
|
CAP_PROP_OBSENSOR_INTRINSIC_CY: int
|
|
VideoCaptureOBSensorProperties = int
|
|
"""One of [CAP_PROP_OBSENSOR_INTRINSIC_FX, CAP_PROP_OBSENSOR_INTRINSIC_FY, CAP_PROP_OBSENSOR_INTRINSIC_CX, CAP_PROP_OBSENSOR_INTRINSIC_CY]"""
|
|
|
|
SOLVEPNP_ITERATIVE: int
|
|
SOLVEPNP_EPNP: int
|
|
SOLVEPNP_P3P: int
|
|
SOLVEPNP_DLS: int
|
|
SOLVEPNP_UPNP: int
|
|
SOLVEPNP_AP3P: int
|
|
SOLVEPNP_IPPE: int
|
|
SOLVEPNP_IPPE_SQUARE: int
|
|
SOLVEPNP_SQPNP: int
|
|
SOLVEPNP_MAX_COUNT: int
|
|
SolvePnPMethod = int
|
|
"""One of [SOLVEPNP_ITERATIVE, SOLVEPNP_EPNP, SOLVEPNP_P3P, SOLVEPNP_DLS, SOLVEPNP_UPNP, SOLVEPNP_AP3P, SOLVEPNP_IPPE, SOLVEPNP_IPPE_SQUARE, SOLVEPNP_SQPNP, SOLVEPNP_MAX_COUNT]"""
|
|
|
|
CALIB_HAND_EYE_TSAI: int
|
|
CALIB_HAND_EYE_PARK: int
|
|
CALIB_HAND_EYE_HORAUD: int
|
|
CALIB_HAND_EYE_ANDREFF: int
|
|
CALIB_HAND_EYE_DANIILIDIS: int
|
|
HandEyeCalibrationMethod = int
|
|
"""One of [CALIB_HAND_EYE_TSAI, CALIB_HAND_EYE_PARK, CALIB_HAND_EYE_HORAUD, CALIB_HAND_EYE_ANDREFF, CALIB_HAND_EYE_DANIILIDIS]"""
|
|
|
|
CALIB_ROBOT_WORLD_HAND_EYE_SHAH: int
|
|
CALIB_ROBOT_WORLD_HAND_EYE_LI: int
|
|
RobotWorldHandEyeCalibrationMethod = int
|
|
"""One of [CALIB_ROBOT_WORLD_HAND_EYE_SHAH, CALIB_ROBOT_WORLD_HAND_EYE_LI]"""
|
|
|
|
SAMPLING_UNIFORM: int
|
|
SAMPLING_PROGRESSIVE_NAPSAC: int
|
|
SAMPLING_NAPSAC: int
|
|
SAMPLING_PROSAC: int
|
|
SamplingMethod = int
|
|
"""One of [SAMPLING_UNIFORM, SAMPLING_PROGRESSIVE_NAPSAC, SAMPLING_NAPSAC, SAMPLING_PROSAC]"""
|
|
|
|
LOCAL_OPTIM_NULL: int
|
|
LOCAL_OPTIM_INNER_LO: int
|
|
LOCAL_OPTIM_INNER_AND_ITER_LO: int
|
|
LOCAL_OPTIM_GC: int
|
|
LOCAL_OPTIM_SIGMA: int
|
|
LocalOptimMethod = int
|
|
"""One of [LOCAL_OPTIM_NULL, LOCAL_OPTIM_INNER_LO, LOCAL_OPTIM_INNER_AND_ITER_LO, LOCAL_OPTIM_GC, LOCAL_OPTIM_SIGMA]"""
|
|
|
|
SCORE_METHOD_RANSAC: int
|
|
SCORE_METHOD_MSAC: int
|
|
SCORE_METHOD_MAGSAC: int
|
|
SCORE_METHOD_LMEDS: int
|
|
ScoreMethod = int
|
|
"""One of [SCORE_METHOD_RANSAC, SCORE_METHOD_MSAC, SCORE_METHOD_MAGSAC, SCORE_METHOD_LMEDS]"""
|
|
|
|
NEIGH_FLANN_KNN: int
|
|
NEIGH_GRID: int
|
|
NEIGH_FLANN_RADIUS: int
|
|
NeighborSearchMethod = int
|
|
"""One of [NEIGH_FLANN_KNN, NEIGH_GRID, NEIGH_FLANN_RADIUS]"""
|
|
|
|
NONE_POLISHER: int
|
|
LSQ_POLISHER: int
|
|
MAGSAC: int
|
|
COV_POLISHER: int
|
|
PolishingMethod = int
|
|
"""One of [NONE_POLISHER, LSQ_POLISHER, MAGSAC, COV_POLISHER]"""
|
|
|
|
PROJ_SPHERICAL_ORTHO: int
|
|
PROJ_SPHERICAL_EQRECT: int
|
|
UndistortTypes = int
|
|
"""One of [PROJ_SPHERICAL_ORTHO, PROJ_SPHERICAL_EQRECT]"""
|
|
|
|
WINDOW_NORMAL: int
|
|
WINDOW_AUTOSIZE: int
|
|
WINDOW_OPENGL: int
|
|
WINDOW_FULLSCREEN: int
|
|
WINDOW_FREERATIO: int
|
|
WINDOW_KEEPRATIO: int
|
|
WINDOW_GUI_EXPANDED: int
|
|
WINDOW_GUI_NORMAL: int
|
|
WindowFlags = int
|
|
"""One of [WINDOW_NORMAL, WINDOW_AUTOSIZE, WINDOW_OPENGL, WINDOW_FULLSCREEN, WINDOW_FREERATIO, WINDOW_KEEPRATIO, WINDOW_GUI_EXPANDED, WINDOW_GUI_NORMAL]"""
|
|
|
|
WND_PROP_FULLSCREEN: int
|
|
WND_PROP_AUTOSIZE: int
|
|
WND_PROP_ASPECT_RATIO: int
|
|
WND_PROP_OPENGL: int
|
|
WND_PROP_VISIBLE: int
|
|
WND_PROP_TOPMOST: int
|
|
WND_PROP_VSYNC: int
|
|
WindowPropertyFlags = int
|
|
"""One of [WND_PROP_FULLSCREEN, WND_PROP_AUTOSIZE, WND_PROP_ASPECT_RATIO, WND_PROP_OPENGL, WND_PROP_VISIBLE, WND_PROP_TOPMOST, WND_PROP_VSYNC]"""
|
|
|
|
EVENT_MOUSEMOVE: int
|
|
EVENT_LBUTTONDOWN: int
|
|
EVENT_RBUTTONDOWN: int
|
|
EVENT_MBUTTONDOWN: int
|
|
EVENT_LBUTTONUP: int
|
|
EVENT_RBUTTONUP: int
|
|
EVENT_MBUTTONUP: int
|
|
EVENT_LBUTTONDBLCLK: int
|
|
EVENT_RBUTTONDBLCLK: int
|
|
EVENT_MBUTTONDBLCLK: int
|
|
EVENT_MOUSEWHEEL: int
|
|
EVENT_MOUSEHWHEEL: int
|
|
MouseEventTypes = int
|
|
"""One of [EVENT_MOUSEMOVE, EVENT_LBUTTONDOWN, EVENT_RBUTTONDOWN, EVENT_MBUTTONDOWN, EVENT_LBUTTONUP, EVENT_RBUTTONUP, EVENT_MBUTTONUP, EVENT_LBUTTONDBLCLK, EVENT_RBUTTONDBLCLK, EVENT_MBUTTONDBLCLK, EVENT_MOUSEWHEEL, EVENT_MOUSEHWHEEL]"""
|
|
|
|
EVENT_FLAG_LBUTTON: int
|
|
EVENT_FLAG_RBUTTON: int
|
|
EVENT_FLAG_MBUTTON: int
|
|
EVENT_FLAG_CTRLKEY: int
|
|
EVENT_FLAG_SHIFTKEY: int
|
|
EVENT_FLAG_ALTKEY: int
|
|
MouseEventFlags = int
|
|
"""One of [EVENT_FLAG_LBUTTON, EVENT_FLAG_RBUTTON, EVENT_FLAG_MBUTTON, EVENT_FLAG_CTRLKEY, EVENT_FLAG_SHIFTKEY, EVENT_FLAG_ALTKEY]"""
|
|
|
|
QT_FONT_LIGHT: int
|
|
QT_FONT_NORMAL: int
|
|
QT_FONT_DEMIBOLD: int
|
|
QT_FONT_BOLD: int
|
|
QT_FONT_BLACK: int
|
|
QtFontWeights = int
|
|
"""One of [QT_FONT_LIGHT, QT_FONT_NORMAL, QT_FONT_DEMIBOLD, QT_FONT_BOLD, QT_FONT_BLACK]"""
|
|
|
|
QT_STYLE_NORMAL: int
|
|
QT_STYLE_ITALIC: int
|
|
QT_STYLE_OBLIQUE: int
|
|
QtFontStyles = int
|
|
"""One of [QT_STYLE_NORMAL, QT_STYLE_ITALIC, QT_STYLE_OBLIQUE]"""
|
|
|
|
QT_PUSH_BUTTON: int
|
|
QT_CHECKBOX: int
|
|
QT_RADIOBOX: int
|
|
QT_NEW_BUTTONBAR: int
|
|
QtButtonTypes = int
|
|
"""One of [QT_PUSH_BUTTON, QT_CHECKBOX, QT_RADIOBOX, QT_NEW_BUTTONBAR]"""
|
|
|
|
GShape_GMAT: int
|
|
GSHAPE_GMAT: int
|
|
GShape_GSCALAR: int
|
|
GSHAPE_GSCALAR: int
|
|
GShape_GARRAY: int
|
|
GSHAPE_GARRAY: int
|
|
GShape_GOPAQUE: int
|
|
GSHAPE_GOPAQUE: int
|
|
GShape_GFRAME: int
|
|
GSHAPE_GFRAME: int
|
|
GShape = int
|
|
"""One of [GShape_GMAT, GSHAPE_GMAT, GShape_GSCALAR, GSHAPE_GSCALAR, GShape_GARRAY, GSHAPE_GARRAY, GShape_GOPAQUE, GSHAPE_GOPAQUE, GShape_GFRAME, GSHAPE_GFRAME]"""
|
|
|
|
MediaFormat_BGR: int
|
|
MEDIA_FORMAT_BGR: int
|
|
MediaFormat_NV12: int
|
|
MEDIA_FORMAT_NV12: int
|
|
MediaFormat_GRAY: int
|
|
MEDIA_FORMAT_GRAY: int
|
|
MediaFormat = int
|
|
"""One of [MediaFormat_BGR, MEDIA_FORMAT_BGR, MediaFormat_NV12, MEDIA_FORMAT_NV12, MediaFormat_GRAY, MEDIA_FORMAT_GRAY]"""
|
|
|
|
|
|
FileStorage_READ: int
|
|
FILE_STORAGE_READ: int
|
|
FileStorage_WRITE: int
|
|
FILE_STORAGE_WRITE: int
|
|
FileStorage_APPEND: int
|
|
FILE_STORAGE_APPEND: int
|
|
FileStorage_MEMORY: int
|
|
FILE_STORAGE_MEMORY: int
|
|
FileStorage_FORMAT_MASK: int
|
|
FILE_STORAGE_FORMAT_MASK: int
|
|
FileStorage_FORMAT_AUTO: int
|
|
FILE_STORAGE_FORMAT_AUTO: int
|
|
FileStorage_FORMAT_XML: int
|
|
FILE_STORAGE_FORMAT_XML: int
|
|
FileStorage_FORMAT_YAML: int
|
|
FILE_STORAGE_FORMAT_YAML: int
|
|
FileStorage_FORMAT_JSON: int
|
|
FILE_STORAGE_FORMAT_JSON: int
|
|
FileStorage_BASE64: int
|
|
FILE_STORAGE_BASE64: int
|
|
FileStorage_WRITE_BASE64: int
|
|
FILE_STORAGE_WRITE_BASE64: int
|
|
FileStorage_Mode = int
|
|
"""One of [FileStorage_READ, FILE_STORAGE_READ, FileStorage_WRITE, FILE_STORAGE_WRITE, FileStorage_APPEND, FILE_STORAGE_APPEND, FileStorage_MEMORY, FILE_STORAGE_MEMORY, FileStorage_FORMAT_MASK, FILE_STORAGE_FORMAT_MASK, FileStorage_FORMAT_AUTO, FILE_STORAGE_FORMAT_AUTO, FileStorage_FORMAT_XML, FILE_STORAGE_FORMAT_XML, FileStorage_FORMAT_YAML, FILE_STORAGE_FORMAT_YAML, FileStorage_FORMAT_JSON, FILE_STORAGE_FORMAT_JSON, FileStorage_BASE64, FILE_STORAGE_BASE64, FileStorage_WRITE_BASE64, FILE_STORAGE_WRITE_BASE64]"""
|
|
|
|
FileStorage_UNDEFINED: int
|
|
FILE_STORAGE_UNDEFINED: int
|
|
FileStorage_VALUE_EXPECTED: int
|
|
FILE_STORAGE_VALUE_EXPECTED: int
|
|
FileStorage_NAME_EXPECTED: int
|
|
FILE_STORAGE_NAME_EXPECTED: int
|
|
FileStorage_INSIDE_MAP: int
|
|
FILE_STORAGE_INSIDE_MAP: int
|
|
FileStorage_State = int
|
|
"""One of [FileStorage_UNDEFINED, FILE_STORAGE_UNDEFINED, FileStorage_VALUE_EXPECTED, FILE_STORAGE_VALUE_EXPECTED, FileStorage_NAME_EXPECTED, FILE_STORAGE_NAME_EXPECTED, FileStorage_INSIDE_MAP, FILE_STORAGE_INSIDE_MAP]"""
|
|
|
|
FileNode_NONE: int
|
|
FILE_NODE_NONE: int
|
|
FileNode_INT: int
|
|
FILE_NODE_INT: int
|
|
FileNode_REAL: int
|
|
FILE_NODE_REAL: int
|
|
FileNode_FLOAT: int
|
|
FILE_NODE_FLOAT: int
|
|
FileNode_STR: int
|
|
FILE_NODE_STR: int
|
|
FileNode_STRING: int
|
|
FILE_NODE_STRING: int
|
|
FileNode_SEQ: int
|
|
FILE_NODE_SEQ: int
|
|
FileNode_MAP: int
|
|
FILE_NODE_MAP: int
|
|
FileNode_TYPE_MASK: int
|
|
FILE_NODE_TYPE_MASK: int
|
|
FileNode_FLOW: int
|
|
FILE_NODE_FLOW: int
|
|
FileNode_UNIFORM: int
|
|
FILE_NODE_UNIFORM: int
|
|
FileNode_EMPTY: int
|
|
FILE_NODE_EMPTY: int
|
|
FileNode_NAMED: int
|
|
FILE_NODE_NAMED: int
|
|
|
|
UMat_MAGIC_VAL: int
|
|
UMAT_MAGIC_VAL: int
|
|
UMat_AUTO_STEP: int
|
|
UMAT_AUTO_STEP: int
|
|
UMat_CONTINUOUS_FLAG: int
|
|
UMAT_CONTINUOUS_FLAG: int
|
|
UMat_SUBMATRIX_FLAG: int
|
|
UMAT_SUBMATRIX_FLAG: int
|
|
UMat_MAGIC_MASK: int
|
|
UMAT_MAGIC_MASK: int
|
|
UMat_TYPE_MASK: int
|
|
UMAT_TYPE_MASK: int
|
|
UMat_DEPTH_MASK: int
|
|
UMAT_DEPTH_MASK: int
|
|
|
|
Subdiv2D_PTLOC_ERROR: int
|
|
SUBDIV2D_PTLOC_ERROR: int
|
|
Subdiv2D_PTLOC_OUTSIDE_RECT: int
|
|
SUBDIV2D_PTLOC_OUTSIDE_RECT: int
|
|
Subdiv2D_PTLOC_INSIDE: int
|
|
SUBDIV2D_PTLOC_INSIDE: int
|
|
Subdiv2D_PTLOC_VERTEX: int
|
|
SUBDIV2D_PTLOC_VERTEX: int
|
|
Subdiv2D_PTLOC_ON_EDGE: int
|
|
SUBDIV2D_PTLOC_ON_EDGE: int
|
|
Subdiv2D_NEXT_AROUND_ORG: int
|
|
SUBDIV2D_NEXT_AROUND_ORG: int
|
|
Subdiv2D_NEXT_AROUND_DST: int
|
|
SUBDIV2D_NEXT_AROUND_DST: int
|
|
Subdiv2D_PREV_AROUND_ORG: int
|
|
SUBDIV2D_PREV_AROUND_ORG: int
|
|
Subdiv2D_PREV_AROUND_DST: int
|
|
SUBDIV2D_PREV_AROUND_DST: int
|
|
Subdiv2D_NEXT_AROUND_LEFT: int
|
|
SUBDIV2D_NEXT_AROUND_LEFT: int
|
|
Subdiv2D_NEXT_AROUND_RIGHT: int
|
|
SUBDIV2D_NEXT_AROUND_RIGHT: int
|
|
Subdiv2D_PREV_AROUND_LEFT: int
|
|
SUBDIV2D_PREV_AROUND_LEFT: int
|
|
Subdiv2D_PREV_AROUND_RIGHT: int
|
|
SUBDIV2D_PREV_AROUND_RIGHT: int
|
|
|
|
ORB_HARRIS_SCORE: int
|
|
ORB_FAST_SCORE: int
|
|
ORB_ScoreType = int
|
|
"""One of [ORB_HARRIS_SCORE, ORB_FAST_SCORE]"""
|
|
|
|
FastFeatureDetector_TYPE_5_8: int
|
|
FAST_FEATURE_DETECTOR_TYPE_5_8: int
|
|
FastFeatureDetector_TYPE_7_12: int
|
|
FAST_FEATURE_DETECTOR_TYPE_7_12: int
|
|
FastFeatureDetector_TYPE_9_16: int
|
|
FAST_FEATURE_DETECTOR_TYPE_9_16: int
|
|
FastFeatureDetector_DetectorType = int
|
|
"""One of [FastFeatureDetector_TYPE_5_8, FAST_FEATURE_DETECTOR_TYPE_5_8, FastFeatureDetector_TYPE_7_12, FAST_FEATURE_DETECTOR_TYPE_7_12, FastFeatureDetector_TYPE_9_16, FAST_FEATURE_DETECTOR_TYPE_9_16]"""
|
|
|
|
FastFeatureDetector_THRESHOLD: int
|
|
FAST_FEATURE_DETECTOR_THRESHOLD: int
|
|
FastFeatureDetector_NONMAX_SUPPRESSION: int
|
|
FAST_FEATURE_DETECTOR_NONMAX_SUPPRESSION: int
|
|
FastFeatureDetector_FAST_N: int
|
|
FAST_FEATURE_DETECTOR_FAST_N: int
|
|
|
|
AgastFeatureDetector_AGAST_5_8: int
|
|
AGAST_FEATURE_DETECTOR_AGAST_5_8: int
|
|
AgastFeatureDetector_AGAST_7_12d: int
|
|
AGAST_FEATURE_DETECTOR_AGAST_7_12D: int
|
|
AgastFeatureDetector_AGAST_7_12s: int
|
|
AGAST_FEATURE_DETECTOR_AGAST_7_12S: int
|
|
AgastFeatureDetector_OAST_9_16: int
|
|
AGAST_FEATURE_DETECTOR_OAST_9_16: int
|
|
AgastFeatureDetector_DetectorType = int
|
|
"""One of [AgastFeatureDetector_AGAST_5_8, AGAST_FEATURE_DETECTOR_AGAST_5_8, AgastFeatureDetector_AGAST_7_12d, AGAST_FEATURE_DETECTOR_AGAST_7_12D, AgastFeatureDetector_AGAST_7_12s, AGAST_FEATURE_DETECTOR_AGAST_7_12S, AgastFeatureDetector_OAST_9_16, AGAST_FEATURE_DETECTOR_OAST_9_16]"""
|
|
|
|
AgastFeatureDetector_THRESHOLD: int
|
|
AGAST_FEATURE_DETECTOR_THRESHOLD: int
|
|
AgastFeatureDetector_NONMAX_SUPPRESSION: int
|
|
AGAST_FEATURE_DETECTOR_NONMAX_SUPPRESSION: int
|
|
|
|
KAZE_DIFF_PM_G1: int
|
|
KAZE_DIFF_PM_G2: int
|
|
KAZE_DIFF_WEICKERT: int
|
|
KAZE_DIFF_CHARBONNIER: int
|
|
KAZE_DiffusivityType = int
|
|
"""One of [KAZE_DIFF_PM_G1, KAZE_DIFF_PM_G2, KAZE_DIFF_WEICKERT, KAZE_DIFF_CHARBONNIER]"""
|
|
|
|
AKAZE_DESCRIPTOR_KAZE_UPRIGHT: int
|
|
AKAZE_DESCRIPTOR_KAZE: int
|
|
AKAZE_DESCRIPTOR_MLDB_UPRIGHT: int
|
|
AKAZE_DESCRIPTOR_MLDB: int
|
|
AKAZE_DescriptorType = int
|
|
"""One of [AKAZE_DESCRIPTOR_KAZE_UPRIGHT, AKAZE_DESCRIPTOR_KAZE, AKAZE_DESCRIPTOR_MLDB_UPRIGHT, AKAZE_DESCRIPTOR_MLDB]"""
|
|
|
|
DescriptorMatcher_FLANNBASED: int
|
|
DESCRIPTOR_MATCHER_FLANNBASED: int
|
|
DescriptorMatcher_BRUTEFORCE: int
|
|
DESCRIPTOR_MATCHER_BRUTEFORCE: int
|
|
DescriptorMatcher_BRUTEFORCE_L1: int
|
|
DESCRIPTOR_MATCHER_BRUTEFORCE_L1: int
|
|
DescriptorMatcher_BRUTEFORCE_HAMMING: int
|
|
DESCRIPTOR_MATCHER_BRUTEFORCE_HAMMING: int
|
|
DescriptorMatcher_BRUTEFORCE_HAMMINGLUT: int
|
|
DESCRIPTOR_MATCHER_BRUTEFORCE_HAMMINGLUT: int
|
|
DescriptorMatcher_BRUTEFORCE_SL2: int
|
|
DESCRIPTOR_MATCHER_BRUTEFORCE_SL2: int
|
|
DescriptorMatcher_MatcherType = int
|
|
"""One of [DescriptorMatcher_FLANNBASED, DESCRIPTOR_MATCHER_FLANNBASED, DescriptorMatcher_BRUTEFORCE, DESCRIPTOR_MATCHER_BRUTEFORCE, DescriptorMatcher_BRUTEFORCE_L1, DESCRIPTOR_MATCHER_BRUTEFORCE_L1, DescriptorMatcher_BRUTEFORCE_HAMMING, DESCRIPTOR_MATCHER_BRUTEFORCE_HAMMING, DescriptorMatcher_BRUTEFORCE_HAMMINGLUT, DESCRIPTOR_MATCHER_BRUTEFORCE_HAMMINGLUT, DescriptorMatcher_BRUTEFORCE_SL2, DESCRIPTOR_MATCHER_BRUTEFORCE_SL2]"""
|
|
|
|
CirclesGridFinderParameters_SYMMETRIC_GRID: int
|
|
CIRCLES_GRID_FINDER_PARAMETERS_SYMMETRIC_GRID: int
|
|
CirclesGridFinderParameters_ASYMMETRIC_GRID: int
|
|
CIRCLES_GRID_FINDER_PARAMETERS_ASYMMETRIC_GRID: int
|
|
CirclesGridFinderParameters_GridType = int
|
|
"""One of [CirclesGridFinderParameters_SYMMETRIC_GRID, CIRCLES_GRID_FINDER_PARAMETERS_SYMMETRIC_GRID, CirclesGridFinderParameters_ASYMMETRIC_GRID, CIRCLES_GRID_FINDER_PARAMETERS_ASYMMETRIC_GRID]"""
|
|
|
|
StereoMatcher_DISP_SHIFT: int
|
|
STEREO_MATCHER_DISP_SHIFT: int
|
|
StereoMatcher_DISP_SCALE: int
|
|
STEREO_MATCHER_DISP_SCALE: int
|
|
|
|
StereoBM_PREFILTER_NORMALIZED_RESPONSE: int
|
|
STEREO_BM_PREFILTER_NORMALIZED_RESPONSE: int
|
|
StereoBM_PREFILTER_XSOBEL: int
|
|
STEREO_BM_PREFILTER_XSOBEL: int
|
|
|
|
StereoSGBM_MODE_SGBM: int
|
|
STEREO_SGBM_MODE_SGBM: int
|
|
StereoSGBM_MODE_HH: int
|
|
STEREO_SGBM_MODE_HH: int
|
|
StereoSGBM_MODE_SGBM_3WAY: int
|
|
STEREO_SGBM_MODE_SGBM_3WAY: int
|
|
StereoSGBM_MODE_HH4: int
|
|
STEREO_SGBM_MODE_HH4: int
|
|
|
|
HOGDescriptor_L2Hys: int
|
|
HOGDESCRIPTOR_L2HYS: int
|
|
HOGDescriptor_HistogramNormType = int
|
|
"""One of [HOGDescriptor_L2Hys, HOGDESCRIPTOR_L2HYS]"""
|
|
|
|
HOGDescriptor_DEFAULT_NLEVELS: int
|
|
HOGDESCRIPTOR_DEFAULT_NLEVELS: int
|
|
|
|
HOGDescriptor_DESCR_FORMAT_COL_BY_COL: int
|
|
HOGDESCRIPTOR_DESCR_FORMAT_COL_BY_COL: int
|
|
HOGDescriptor_DESCR_FORMAT_ROW_BY_ROW: int
|
|
HOGDESCRIPTOR_DESCR_FORMAT_ROW_BY_ROW: int
|
|
HOGDescriptor_DescriptorStorageFormat = int
|
|
"""One of [HOGDescriptor_DESCR_FORMAT_COL_BY_COL, HOGDESCRIPTOR_DESCR_FORMAT_COL_BY_COL, HOGDescriptor_DESCR_FORMAT_ROW_BY_ROW, HOGDESCRIPTOR_DESCR_FORMAT_ROW_BY_ROW]"""
|
|
|
|
QRCodeEncoder_MODE_AUTO: int
|
|
QRCODE_ENCODER_MODE_AUTO: int
|
|
QRCodeEncoder_MODE_NUMERIC: int
|
|
QRCODE_ENCODER_MODE_NUMERIC: int
|
|
QRCodeEncoder_MODE_ALPHANUMERIC: int
|
|
QRCODE_ENCODER_MODE_ALPHANUMERIC: int
|
|
QRCodeEncoder_MODE_BYTE: int
|
|
QRCODE_ENCODER_MODE_BYTE: int
|
|
QRCodeEncoder_MODE_ECI: int
|
|
QRCODE_ENCODER_MODE_ECI: int
|
|
QRCodeEncoder_MODE_KANJI: int
|
|
QRCODE_ENCODER_MODE_KANJI: int
|
|
QRCodeEncoder_MODE_STRUCTURED_APPEND: int
|
|
QRCODE_ENCODER_MODE_STRUCTURED_APPEND: int
|
|
QRCodeEncoder_EncodeMode = int
|
|
"""One of [QRCodeEncoder_MODE_AUTO, QRCODE_ENCODER_MODE_AUTO, QRCodeEncoder_MODE_NUMERIC, QRCODE_ENCODER_MODE_NUMERIC, QRCodeEncoder_MODE_ALPHANUMERIC, QRCODE_ENCODER_MODE_ALPHANUMERIC, QRCodeEncoder_MODE_BYTE, QRCODE_ENCODER_MODE_BYTE, QRCodeEncoder_MODE_ECI, QRCODE_ENCODER_MODE_ECI, QRCodeEncoder_MODE_KANJI, QRCODE_ENCODER_MODE_KANJI, QRCodeEncoder_MODE_STRUCTURED_APPEND, QRCODE_ENCODER_MODE_STRUCTURED_APPEND]"""
|
|
|
|
QRCodeEncoder_CORRECT_LEVEL_L: int
|
|
QRCODE_ENCODER_CORRECT_LEVEL_L: int
|
|
QRCodeEncoder_CORRECT_LEVEL_M: int
|
|
QRCODE_ENCODER_CORRECT_LEVEL_M: int
|
|
QRCodeEncoder_CORRECT_LEVEL_Q: int
|
|
QRCODE_ENCODER_CORRECT_LEVEL_Q: int
|
|
QRCodeEncoder_CORRECT_LEVEL_H: int
|
|
QRCODE_ENCODER_CORRECT_LEVEL_H: int
|
|
QRCodeEncoder_CorrectionLevel = int
|
|
"""One of [QRCodeEncoder_CORRECT_LEVEL_L, QRCODE_ENCODER_CORRECT_LEVEL_L, QRCodeEncoder_CORRECT_LEVEL_M, QRCODE_ENCODER_CORRECT_LEVEL_M, QRCodeEncoder_CORRECT_LEVEL_Q, QRCODE_ENCODER_CORRECT_LEVEL_Q, QRCodeEncoder_CORRECT_LEVEL_H, QRCODE_ENCODER_CORRECT_LEVEL_H]"""
|
|
|
|
QRCodeEncoder_ECI_UTF8: int
|
|
QRCODE_ENCODER_ECI_UTF8: int
|
|
QRCodeEncoder_ECIEncodings = int
|
|
"""One of [QRCodeEncoder_ECI_UTF8, QRCODE_ENCODER_ECI_UTF8]"""
|
|
|
|
FaceRecognizerSF_FR_COSINE: int
|
|
FACE_RECOGNIZER_SF_FR_COSINE: int
|
|
FaceRecognizerSF_FR_NORM_L2: int
|
|
FACE_RECOGNIZER_SF_FR_NORM_L2: int
|
|
FaceRecognizerSF_DisType = int
|
|
"""One of [FaceRecognizerSF_FR_COSINE, FACE_RECOGNIZER_SF_FR_COSINE, FaceRecognizerSF_FR_NORM_L2, FACE_RECOGNIZER_SF_FR_NORM_L2]"""
|
|
|
|
Stitcher_OK: int
|
|
STITCHER_OK: int
|
|
Stitcher_ERR_NEED_MORE_IMGS: int
|
|
STITCHER_ERR_NEED_MORE_IMGS: int
|
|
Stitcher_ERR_HOMOGRAPHY_EST_FAIL: int
|
|
STITCHER_ERR_HOMOGRAPHY_EST_FAIL: int
|
|
Stitcher_ERR_CAMERA_PARAMS_ADJUST_FAIL: int
|
|
STITCHER_ERR_CAMERA_PARAMS_ADJUST_FAIL: int
|
|
Stitcher_Status = int
|
|
"""One of [Stitcher_OK, STITCHER_OK, Stitcher_ERR_NEED_MORE_IMGS, STITCHER_ERR_NEED_MORE_IMGS, Stitcher_ERR_HOMOGRAPHY_EST_FAIL, STITCHER_ERR_HOMOGRAPHY_EST_FAIL, Stitcher_ERR_CAMERA_PARAMS_ADJUST_FAIL, STITCHER_ERR_CAMERA_PARAMS_ADJUST_FAIL]"""
|
|
|
|
Stitcher_PANORAMA: int
|
|
STITCHER_PANORAMA: int
|
|
Stitcher_SCANS: int
|
|
STITCHER_SCANS: int
|
|
Stitcher_Mode = int
|
|
"""One of [Stitcher_PANORAMA, STITCHER_PANORAMA, Stitcher_SCANS, STITCHER_SCANS]"""
|
|
|
|
DISOpticalFlow_PRESET_ULTRAFAST: int
|
|
DISOPTICAL_FLOW_PRESET_ULTRAFAST: int
|
|
DISOpticalFlow_PRESET_FAST: int
|
|
DISOPTICAL_FLOW_PRESET_FAST: int
|
|
DISOpticalFlow_PRESET_MEDIUM: int
|
|
DISOPTICAL_FLOW_PRESET_MEDIUM: int
|
|
|
|
PCA_DATA_AS_ROW: int
|
|
PCA_DATA_AS_COL: int
|
|
PCA_USE_AVG: int
|
|
PCA_Flags = int
|
|
"""One of [PCA_DATA_AS_ROW, PCA_DATA_AS_COL, PCA_USE_AVG]"""
|
|
|
|
SVD_MODIFY_A: int
|
|
SVD_NO_UV: int
|
|
SVD_FULL_UV: int
|
|
SVD_Flags = int
|
|
"""One of [SVD_MODIFY_A, SVD_NO_UV, SVD_FULL_UV]"""
|
|
|
|
RNG_UNIFORM: int
|
|
RNG_NORMAL: int
|
|
|
|
Formatter_FMT_DEFAULT: int
|
|
FORMATTER_FMT_DEFAULT: int
|
|
Formatter_FMT_MATLAB: int
|
|
FORMATTER_FMT_MATLAB: int
|
|
Formatter_FMT_CSV: int
|
|
FORMATTER_FMT_CSV: int
|
|
Formatter_FMT_PYTHON: int
|
|
FORMATTER_FMT_PYTHON: int
|
|
Formatter_FMT_NUMPY: int
|
|
FORMATTER_FMT_NUMPY: int
|
|
Formatter_FMT_C: int
|
|
FORMATTER_FMT_C: int
|
|
Formatter_FormatType = int
|
|
"""One of [Formatter_FMT_DEFAULT, FORMATTER_FMT_DEFAULT, Formatter_FMT_MATLAB, FORMATTER_FMT_MATLAB, Formatter_FMT_CSV, FORMATTER_FMT_CSV, Formatter_FMT_PYTHON, FORMATTER_FMT_PYTHON, Formatter_FMT_NUMPY, FORMATTER_FMT_NUMPY, Formatter_FMT_C, FORMATTER_FMT_C]"""
|
|
|
|
_InputArray_KIND_SHIFT: int
|
|
_INPUT_ARRAY_KIND_SHIFT: int
|
|
_InputArray_FIXED_TYPE: int
|
|
_INPUT_ARRAY_FIXED_TYPE: int
|
|
_InputArray_FIXED_SIZE: int
|
|
_INPUT_ARRAY_FIXED_SIZE: int
|
|
_InputArray_KIND_MASK: int
|
|
_INPUT_ARRAY_KIND_MASK: int
|
|
_InputArray_NONE: int
|
|
_INPUT_ARRAY_NONE: int
|
|
_InputArray_MAT: int
|
|
_INPUT_ARRAY_MAT: int
|
|
_InputArray_MATX: int
|
|
_INPUT_ARRAY_MATX: int
|
|
_InputArray_STD_VECTOR: int
|
|
_INPUT_ARRAY_STD_VECTOR: int
|
|
_InputArray_STD_VECTOR_VECTOR: int
|
|
_INPUT_ARRAY_STD_VECTOR_VECTOR: int
|
|
_InputArray_STD_VECTOR_MAT: int
|
|
_INPUT_ARRAY_STD_VECTOR_MAT: int
|
|
_InputArray_EXPR: int
|
|
_INPUT_ARRAY_EXPR: int
|
|
_InputArray_OPENGL_BUFFER: int
|
|
_INPUT_ARRAY_OPENGL_BUFFER: int
|
|
_InputArray_CUDA_HOST_MEM: int
|
|
_INPUT_ARRAY_CUDA_HOST_MEM: int
|
|
_InputArray_CUDA_GPU_MAT: int
|
|
_INPUT_ARRAY_CUDA_GPU_MAT: int
|
|
_InputArray_UMAT: int
|
|
_INPUT_ARRAY_UMAT: int
|
|
_InputArray_STD_VECTOR_UMAT: int
|
|
_INPUT_ARRAY_STD_VECTOR_UMAT: int
|
|
_InputArray_STD_BOOL_VECTOR: int
|
|
_INPUT_ARRAY_STD_BOOL_VECTOR: int
|
|
_InputArray_STD_VECTOR_CUDA_GPU_MAT: int
|
|
_INPUT_ARRAY_STD_VECTOR_CUDA_GPU_MAT: int
|
|
_InputArray_STD_ARRAY: int
|
|
_INPUT_ARRAY_STD_ARRAY: int
|
|
_InputArray_STD_ARRAY_MAT: int
|
|
_INPUT_ARRAY_STD_ARRAY_MAT: int
|
|
_InputArray_KindFlag = int
|
|
"""One of [_InputArray_KIND_SHIFT, _INPUT_ARRAY_KIND_SHIFT, _InputArray_FIXED_TYPE, _INPUT_ARRAY_FIXED_TYPE, _InputArray_FIXED_SIZE, _INPUT_ARRAY_FIXED_SIZE, _InputArray_KIND_MASK, _INPUT_ARRAY_KIND_MASK, _InputArray_NONE, _INPUT_ARRAY_NONE, _InputArray_MAT, _INPUT_ARRAY_MAT, _InputArray_MATX, _INPUT_ARRAY_MATX, _InputArray_STD_VECTOR, _INPUT_ARRAY_STD_VECTOR, _InputArray_STD_VECTOR_VECTOR, _INPUT_ARRAY_STD_VECTOR_VECTOR, _InputArray_STD_VECTOR_MAT, _INPUT_ARRAY_STD_VECTOR_MAT, _InputArray_EXPR, _INPUT_ARRAY_EXPR, _InputArray_OPENGL_BUFFER, _INPUT_ARRAY_OPENGL_BUFFER, _InputArray_CUDA_HOST_MEM, _INPUT_ARRAY_CUDA_HOST_MEM, _InputArray_CUDA_GPU_MAT, _INPUT_ARRAY_CUDA_GPU_MAT, _InputArray_UMAT, _INPUT_ARRAY_UMAT, _InputArray_STD_VECTOR_UMAT, _INPUT_ARRAY_STD_VECTOR_UMAT, _InputArray_STD_BOOL_VECTOR, _INPUT_ARRAY_STD_BOOL_VECTOR, _InputArray_STD_VECTOR_CUDA_GPU_MAT, _INPUT_ARRAY_STD_VECTOR_CUDA_GPU_MAT, _InputArray_STD_ARRAY, _INPUT_ARRAY_STD_ARRAY, _InputArray_STD_ARRAY_MAT, _INPUT_ARRAY_STD_ARRAY_MAT]"""
|
|
|
|
_OutputArray_DEPTH_MASK_8U: int
|
|
_OUTPUT_ARRAY_DEPTH_MASK_8U: int
|
|
_OutputArray_DEPTH_MASK_8S: int
|
|
_OUTPUT_ARRAY_DEPTH_MASK_8S: int
|
|
_OutputArray_DEPTH_MASK_16U: int
|
|
_OUTPUT_ARRAY_DEPTH_MASK_16U: int
|
|
_OutputArray_DEPTH_MASK_16S: int
|
|
_OUTPUT_ARRAY_DEPTH_MASK_16S: int
|
|
_OutputArray_DEPTH_MASK_32S: int
|
|
_OUTPUT_ARRAY_DEPTH_MASK_32S: int
|
|
_OutputArray_DEPTH_MASK_32F: int
|
|
_OUTPUT_ARRAY_DEPTH_MASK_32F: int
|
|
_OutputArray_DEPTH_MASK_64F: int
|
|
_OUTPUT_ARRAY_DEPTH_MASK_64F: int
|
|
_OutputArray_DEPTH_MASK_16F: int
|
|
_OUTPUT_ARRAY_DEPTH_MASK_16F: int
|
|
_OutputArray_DEPTH_MASK_ALL: int
|
|
_OUTPUT_ARRAY_DEPTH_MASK_ALL: int
|
|
_OutputArray_DEPTH_MASK_ALL_BUT_8S: int
|
|
_OUTPUT_ARRAY_DEPTH_MASK_ALL_BUT_8S: int
|
|
_OutputArray_DEPTH_MASK_ALL_16F: int
|
|
_OUTPUT_ARRAY_DEPTH_MASK_ALL_16F: int
|
|
_OutputArray_DEPTH_MASK_FLT: int
|
|
_OUTPUT_ARRAY_DEPTH_MASK_FLT: int
|
|
_OutputArray_DepthMask = int
|
|
"""One of [_OutputArray_DEPTH_MASK_8U, _OUTPUT_ARRAY_DEPTH_MASK_8U, _OutputArray_DEPTH_MASK_8S, _OUTPUT_ARRAY_DEPTH_MASK_8S, _OutputArray_DEPTH_MASK_16U, _OUTPUT_ARRAY_DEPTH_MASK_16U, _OutputArray_DEPTH_MASK_16S, _OUTPUT_ARRAY_DEPTH_MASK_16S, _OutputArray_DEPTH_MASK_32S, _OUTPUT_ARRAY_DEPTH_MASK_32S, _OutputArray_DEPTH_MASK_32F, _OUTPUT_ARRAY_DEPTH_MASK_32F, _OutputArray_DEPTH_MASK_64F, _OUTPUT_ARRAY_DEPTH_MASK_64F, _OutputArray_DEPTH_MASK_16F, _OUTPUT_ARRAY_DEPTH_MASK_16F, _OutputArray_DEPTH_MASK_ALL, _OUTPUT_ARRAY_DEPTH_MASK_ALL, _OutputArray_DEPTH_MASK_ALL_BUT_8S, _OUTPUT_ARRAY_DEPTH_MASK_ALL_BUT_8S, _OutputArray_DEPTH_MASK_ALL_16F, _OUTPUT_ARRAY_DEPTH_MASK_ALL_16F, _OutputArray_DEPTH_MASK_FLT, _OUTPUT_ARRAY_DEPTH_MASK_FLT]"""
|
|
|
|
UMatData_COPY_ON_MAP: int
|
|
UMAT_DATA_COPY_ON_MAP: int
|
|
UMatData_HOST_COPY_OBSOLETE: int
|
|
UMAT_DATA_HOST_COPY_OBSOLETE: int
|
|
UMatData_DEVICE_COPY_OBSOLETE: int
|
|
UMAT_DATA_DEVICE_COPY_OBSOLETE: int
|
|
UMatData_TEMP_UMAT: int
|
|
UMAT_DATA_TEMP_UMAT: int
|
|
UMatData_TEMP_COPIED_UMAT: int
|
|
UMAT_DATA_TEMP_COPIED_UMAT: int
|
|
UMatData_USER_ALLOCATED: int
|
|
UMAT_DATA_USER_ALLOCATED: int
|
|
UMatData_DEVICE_MEM_MAPPED: int
|
|
UMAT_DATA_DEVICE_MEM_MAPPED: int
|
|
UMatData_ASYNC_CLEANUP: int
|
|
UMAT_DATA_ASYNC_CLEANUP: int
|
|
UMatData_MemoryFlag = int
|
|
"""One of [UMatData_COPY_ON_MAP, UMAT_DATA_COPY_ON_MAP, UMatData_HOST_COPY_OBSOLETE, UMAT_DATA_HOST_COPY_OBSOLETE, UMatData_DEVICE_COPY_OBSOLETE, UMAT_DATA_DEVICE_COPY_OBSOLETE, UMatData_TEMP_UMAT, UMAT_DATA_TEMP_UMAT, UMatData_TEMP_COPIED_UMAT, UMAT_DATA_TEMP_COPIED_UMAT, UMatData_USER_ALLOCATED, UMAT_DATA_USER_ALLOCATED, UMatData_DEVICE_MEM_MAPPED, UMAT_DATA_DEVICE_MEM_MAPPED, UMatData_ASYNC_CLEANUP, UMAT_DATA_ASYNC_CLEANUP]"""
|
|
|
|
Mat_MAGIC_VAL: int
|
|
MAT_MAGIC_VAL: int
|
|
Mat_AUTO_STEP: int
|
|
MAT_AUTO_STEP: int
|
|
Mat_CONTINUOUS_FLAG: int
|
|
MAT_CONTINUOUS_FLAG: int
|
|
Mat_SUBMATRIX_FLAG: int
|
|
MAT_SUBMATRIX_FLAG: int
|
|
Mat_MAGIC_MASK: int
|
|
MAT_MAGIC_MASK: int
|
|
Mat_TYPE_MASK: int
|
|
MAT_TYPE_MASK: int
|
|
Mat_DEPTH_MASK: int
|
|
MAT_DEPTH_MASK: int
|
|
|
|
SparseMat_MAGIC_VAL: int
|
|
SPARSE_MAT_MAGIC_VAL: int
|
|
SparseMat_MAX_DIM: int
|
|
SPARSE_MAT_MAX_DIM: int
|
|
SparseMat_HASH_SCALE: int
|
|
SPARSE_MAT_HASH_SCALE: int
|
|
SparseMat_HASH_BIT: int
|
|
SPARSE_MAT_HASH_BIT: int
|
|
|
|
QuatEnum_INT_XYZ: int
|
|
QUAT_ENUM_INT_XYZ: int
|
|
QuatEnum_INT_XZY: int
|
|
QUAT_ENUM_INT_XZY: int
|
|
QuatEnum_INT_YXZ: int
|
|
QUAT_ENUM_INT_YXZ: int
|
|
QuatEnum_INT_YZX: int
|
|
QUAT_ENUM_INT_YZX: int
|
|
QuatEnum_INT_ZXY: int
|
|
QUAT_ENUM_INT_ZXY: int
|
|
QuatEnum_INT_ZYX: int
|
|
QUAT_ENUM_INT_ZYX: int
|
|
QuatEnum_INT_XYX: int
|
|
QUAT_ENUM_INT_XYX: int
|
|
QuatEnum_INT_XZX: int
|
|
QUAT_ENUM_INT_XZX: int
|
|
QuatEnum_INT_YXY: int
|
|
QUAT_ENUM_INT_YXY: int
|
|
QuatEnum_INT_YZY: int
|
|
QUAT_ENUM_INT_YZY: int
|
|
QuatEnum_INT_ZXZ: int
|
|
QUAT_ENUM_INT_ZXZ: int
|
|
QuatEnum_INT_ZYZ: int
|
|
QUAT_ENUM_INT_ZYZ: int
|
|
QuatEnum_EXT_XYZ: int
|
|
QUAT_ENUM_EXT_XYZ: int
|
|
QuatEnum_EXT_XZY: int
|
|
QUAT_ENUM_EXT_XZY: int
|
|
QuatEnum_EXT_YXZ: int
|
|
QUAT_ENUM_EXT_YXZ: int
|
|
QuatEnum_EXT_YZX: int
|
|
QUAT_ENUM_EXT_YZX: int
|
|
QuatEnum_EXT_ZXY: int
|
|
QUAT_ENUM_EXT_ZXY: int
|
|
QuatEnum_EXT_ZYX: int
|
|
QUAT_ENUM_EXT_ZYX: int
|
|
QuatEnum_EXT_XYX: int
|
|
QUAT_ENUM_EXT_XYX: int
|
|
QuatEnum_EXT_XZX: int
|
|
QUAT_ENUM_EXT_XZX: int
|
|
QuatEnum_EXT_YXY: int
|
|
QUAT_ENUM_EXT_YXY: int
|
|
QuatEnum_EXT_YZY: int
|
|
QUAT_ENUM_EXT_YZY: int
|
|
QuatEnum_EXT_ZXZ: int
|
|
QUAT_ENUM_EXT_ZXZ: int
|
|
QuatEnum_EXT_ZYZ: int
|
|
QUAT_ENUM_EXT_ZYZ: int
|
|
QuatEnum_EULER_ANGLES_MAX_VALUE: int
|
|
QUAT_ENUM_EULER_ANGLES_MAX_VALUE: int
|
|
QuatEnum_EulerAnglesType = int
|
|
"""One of [QuatEnum_INT_XYZ, QUAT_ENUM_INT_XYZ, QuatEnum_INT_XZY, QUAT_ENUM_INT_XZY, QuatEnum_INT_YXZ, QUAT_ENUM_INT_YXZ, QuatEnum_INT_YZX, QUAT_ENUM_INT_YZX, QuatEnum_INT_ZXY, QUAT_ENUM_INT_ZXY, QuatEnum_INT_ZYX, QUAT_ENUM_INT_ZYX, QuatEnum_INT_XYX, QUAT_ENUM_INT_XYX, QuatEnum_INT_XZX, QUAT_ENUM_INT_XZX, QuatEnum_INT_YXY, QUAT_ENUM_INT_YXY, QuatEnum_INT_YZY, QUAT_ENUM_INT_YZY, QuatEnum_INT_ZXZ, QUAT_ENUM_INT_ZXZ, QuatEnum_INT_ZYZ, QUAT_ENUM_INT_ZYZ, QuatEnum_EXT_XYZ, QUAT_ENUM_EXT_XYZ, QuatEnum_EXT_XZY, QUAT_ENUM_EXT_XZY, QuatEnum_EXT_YXZ, QUAT_ENUM_EXT_YXZ, QuatEnum_EXT_YZX, QUAT_ENUM_EXT_YZX, QuatEnum_EXT_ZXY, QUAT_ENUM_EXT_ZXY, QuatEnum_EXT_ZYX, QUAT_ENUM_EXT_ZYX, QuatEnum_EXT_XYX, QUAT_ENUM_EXT_XYX, QuatEnum_EXT_XZX, QUAT_ENUM_EXT_XZX, QuatEnum_EXT_YXY, QUAT_ENUM_EXT_YXY, QuatEnum_EXT_YZY, QUAT_ENUM_EXT_YZY, QuatEnum_EXT_ZXZ, QUAT_ENUM_EXT_ZXZ, QuatEnum_EXT_ZYZ, QUAT_ENUM_EXT_ZYZ, QuatEnum_EULER_ANGLES_MAX_VALUE, QUAT_ENUM_EULER_ANGLES_MAX_VALUE]"""
|
|
|
|
TermCriteria_COUNT: int
|
|
TERM_CRITERIA_COUNT: int
|
|
TermCriteria_MAX_ITER: int
|
|
TERM_CRITERIA_MAX_ITER: int
|
|
TermCriteria_EPS: int
|
|
TERM_CRITERIA_EPS: int
|
|
TermCriteria_Type = int
|
|
"""One of [TermCriteria_COUNT, TERM_CRITERIA_COUNT, TermCriteria_MAX_ITER, TERM_CRITERIA_MAX_ITER, TermCriteria_EPS, TERM_CRITERIA_EPS]"""
|
|
|
|
GFluidKernel_Kind_Filter: int
|
|
GFLUID_KERNEL_KIND_FILTER: int
|
|
GFluidKernel_Kind_Resize: int
|
|
GFLUID_KERNEL_KIND_RESIZE: int
|
|
GFluidKernel_Kind_YUV420toRGB: int
|
|
GFLUID_KERNEL_KIND_YUV420TO_RGB: int
|
|
GFluidKernel_Kind = int
|
|
"""One of [GFluidKernel_Kind_Filter, GFLUID_KERNEL_KIND_FILTER, GFluidKernel_Kind_Resize, GFLUID_KERNEL_KIND_RESIZE, GFluidKernel_Kind_YUV420toRGB, GFLUID_KERNEL_KIND_YUV420TO_RGB]"""
|
|
|
|
MediaFrame_Access_R: int
|
|
MEDIA_FRAME_ACCESS_R: int
|
|
MediaFrame_Access_W: int
|
|
MEDIA_FRAME_ACCESS_W: int
|
|
MediaFrame_Access = int
|
|
"""One of [MediaFrame_Access_R, MEDIA_FRAME_ACCESS_R, MediaFrame_Access_W, MEDIA_FRAME_ACCESS_W]"""
|
|
|
|
RMat_Access_R: int
|
|
RMAT_ACCESS_R: int
|
|
RMat_Access_W: int
|
|
RMAT_ACCESS_W: int
|
|
RMat_Access = int
|
|
"""One of [RMat_Access_R, RMAT_ACCESS_R, RMat_Access_W, RMAT_ACCESS_W]"""
|
|
|
|
|
|
# Constants
|
|
CV_8U: int
|
|
CV_8UC1: int
|
|
CV_8UC2: int
|
|
CV_8UC3: int
|
|
CV_8UC4: int
|
|
CV_8S: int
|
|
CV_8SC1: int
|
|
CV_8SC2: int
|
|
CV_8SC3: int
|
|
CV_8SC4: int
|
|
CV_16U: int
|
|
CV_16UC1: int
|
|
CV_16UC2: int
|
|
CV_16UC3: int
|
|
CV_16UC4: int
|
|
CV_16S: int
|
|
CV_16SC1: int
|
|
CV_16SC2: int
|
|
CV_16SC3: int
|
|
CV_16SC4: int
|
|
CV_32S: int
|
|
CV_32SC1: int
|
|
CV_32SC2: int
|
|
CV_32SC3: int
|
|
CV_32SC4: int
|
|
CV_32F: int
|
|
CV_32FC1: int
|
|
CV_32FC2: int
|
|
CV_32FC3: int
|
|
CV_32FC4: int
|
|
CV_64F: int
|
|
CV_64FC1: int
|
|
CV_64FC2: int
|
|
CV_64FC3: int
|
|
CV_64FC4: int
|
|
CV_16F: int
|
|
CV_16FC1: int
|
|
CV_16FC2: int
|
|
CV_16FC3: int
|
|
CV_16FC4: int
|
|
__version__: str
|
|
|
|
# Classes
|
|
class Algorithm:
|
|
# Functions
|
|
def clear(self) -> None: ...
|
|
|
|
@_typing.overload
|
|
def write(self, fs: FileStorage) -> None: ...
|
|
@_typing.overload
|
|
def write(self, fs: FileStorage, name: str) -> None: ...
|
|
|
|
def read(self, fn: FileNode) -> None: ...
|
|
|
|
def empty(self) -> bool: ...
|
|
|
|
def save(self, filename: str) -> None: ...
|
|
|
|
def getDefaultName(self) -> str: ...
|
|
|
|
|
|
class AsyncArray:
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
def release(self) -> None: ...
|
|
|
|
@_typing.overload
|
|
def get(self, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def get(self, dst: UMat | None = ...) -> UMat: ...
|
|
@_typing.overload
|
|
def get(self, timeoutNs: float, dst: cv2.typing.MatLike | None = ...) -> tuple[bool, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def get(self, timeoutNs: float, dst: UMat | None = ...) -> tuple[bool, UMat]: ...
|
|
|
|
def wait_for(self, timeoutNs: float) -> bool: ...
|
|
|
|
def valid(self) -> bool: ...
|
|
|
|
|
|
class FileStorage:
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, filename: str, flags: int, encoding: str = ...) -> None: ...
|
|
|
|
def open(self, filename: str, flags: int, encoding: str = ...) -> bool: ...
|
|
|
|
def isOpened(self) -> bool: ...
|
|
|
|
def release(self) -> None: ...
|
|
|
|
def releaseAndGetString(self) -> str: ...
|
|
|
|
def getFirstTopLevelNode(self) -> FileNode: ...
|
|
|
|
def root(self, streamidx: int = ...) -> FileNode: ...
|
|
|
|
def getNode(self, nodename: str) -> FileNode: ...
|
|
|
|
@_typing.overload
|
|
def write(self, name: str, val: int) -> None: ...
|
|
@_typing.overload
|
|
def write(self, name: str, val: float) -> None: ...
|
|
@_typing.overload
|
|
def write(self, name: str, val: str) -> None: ...
|
|
@_typing.overload
|
|
def write(self, name: str, val: cv2.typing.MatLike) -> None: ...
|
|
@_typing.overload
|
|
def write(self, name: str, val: _typing.Sequence[str]) -> None: ...
|
|
|
|
def writeComment(self, comment: str, append: bool = ...) -> None: ...
|
|
|
|
def startWriteStruct(self, name: str, flags: int, typeName: str = ...) -> None: ...
|
|
|
|
def endWriteStruct(self) -> None: ...
|
|
|
|
def getFormat(self) -> int: ...
|
|
|
|
|
|
class FileNode:
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
def getNode(self, nodename: str) -> FileNode: ...
|
|
|
|
def at(self, i: int) -> FileNode: ...
|
|
|
|
def keys(self) -> _typing.Sequence[str]: ...
|
|
|
|
def type(self) -> int: ...
|
|
|
|
def empty(self) -> bool: ...
|
|
|
|
def isNone(self) -> bool: ...
|
|
|
|
def isSeq(self) -> bool: ...
|
|
|
|
def isMap(self) -> bool: ...
|
|
|
|
def isInt(self) -> bool: ...
|
|
|
|
def isReal(self) -> bool: ...
|
|
|
|
def isString(self) -> bool: ...
|
|
|
|
def isNamed(self) -> bool: ...
|
|
|
|
def name(self) -> str: ...
|
|
|
|
def size(self) -> int: ...
|
|
|
|
def rawSize(self) -> int: ...
|
|
|
|
def real(self) -> float: ...
|
|
|
|
def string(self) -> str: ...
|
|
|
|
def mat(self) -> cv2.typing.MatLike: ...
|
|
|
|
|
|
class RotatedRect:
|
|
center: cv2.typing.Point2f
|
|
size: cv2.typing.Size2f
|
|
angle: float
|
|
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, center: cv2.typing.Point2f, size: cv2.typing.Size2f, angle: float) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, point1: cv2.typing.Point2f, point2: cv2.typing.Point2f, point3: cv2.typing.Point2f) -> None: ...
|
|
|
|
def points(self) -> _typing.Sequence[cv2.typing.Point2f]: ...
|
|
|
|
def boundingRect(self) -> cv2.typing.Rect: ...
|
|
|
|
def boundingRect2f(self) -> cv2.typing.Rect2f: ...
|
|
|
|
|
|
class KeyPoint:
|
|
pt: cv2.typing.Point2f
|
|
size: float
|
|
angle: float
|
|
response: float
|
|
octave: int
|
|
class_id: int
|
|
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, x: float, y: float, size: float, angle: float = ..., response: float = ..., octave: int = ..., class_id: int = ...) -> None: ...
|
|
|
|
@staticmethod
|
|
@_typing.overload
|
|
def convert(keypoints: _typing.Sequence[KeyPoint], keypointIndexes: _typing.Sequence[int] = ...) -> _typing.Sequence[cv2.typing.Point2f]: ...
|
|
@staticmethod
|
|
@_typing.overload
|
|
def convert(points2f: _typing.Sequence[cv2.typing.Point2f], size: float = ..., response: float = ..., octave: int = ..., class_id: int = ...) -> _typing.Sequence[KeyPoint]: ...
|
|
|
|
@staticmethod
|
|
def overlap(kp1: KeyPoint, kp2: KeyPoint) -> float: ...
|
|
|
|
|
|
class DMatch:
|
|
queryIdx: int
|
|
trainIdx: int
|
|
imgIdx: int
|
|
distance: float
|
|
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, _queryIdx: int, _trainIdx: int, _distance: float) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, _queryIdx: int, _trainIdx: int, _imgIdx: int, _distance: float) -> None: ...
|
|
|
|
|
|
class TickMeter:
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
def start(self) -> None: ...
|
|
|
|
def stop(self) -> None: ...
|
|
|
|
def getTimeTicks(self) -> int: ...
|
|
|
|
def getTimeMicro(self) -> float: ...
|
|
|
|
def getTimeMilli(self) -> float: ...
|
|
|
|
def getTimeSec(self) -> float: ...
|
|
|
|
def getCounter(self) -> int: ...
|
|
|
|
def getFPS(self) -> float: ...
|
|
|
|
def getAvgTimeSec(self) -> float: ...
|
|
|
|
def getAvgTimeMilli(self) -> float: ...
|
|
|
|
def reset(self) -> None: ...
|
|
|
|
|
|
class UMat:
|
|
offset: int
|
|
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self, usageFlags: UMatUsageFlags = ...) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, rows: int, cols: int, type: int, usageFlags: UMatUsageFlags = ...) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, size: cv2.typing.Size, type: int, usageFlags: UMatUsageFlags = ...) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, rows: int, cols: int, type: int, s: cv2.typing.Scalar, usageFlags: UMatUsageFlags = ...) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, size: cv2.typing.Size, type: int, s: cv2.typing.Scalar, usageFlags: UMatUsageFlags = ...) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, m: UMat) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, m: UMat, rowRange: cv2.typing.Range, colRange: cv2.typing.Range = ...) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, m: UMat, roi: cv2.typing.Rect) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, m: UMat, ranges: _typing.Sequence[cv2.typing.Range]) -> None: ...
|
|
|
|
@staticmethod
|
|
def queue() -> cv2.typing.IntPointer: ...
|
|
|
|
@staticmethod
|
|
def context() -> cv2.typing.IntPointer: ...
|
|
|
|
def get(self) -> cv2.typing.MatLike: ...
|
|
|
|
def isContinuous(self) -> bool: ...
|
|
|
|
def isSubmatrix(self) -> bool: ...
|
|
|
|
def handle(self, accessFlags: AccessFlag) -> cv2.typing.IntPointer: ...
|
|
|
|
|
|
class GeneralizedHough(Algorithm):
|
|
# Functions
|
|
@_typing.overload
|
|
def setTemplate(self, templ: cv2.typing.MatLike, templCenter: cv2.typing.Point = ...) -> None: ...
|
|
@_typing.overload
|
|
def setTemplate(self, templ: UMat, templCenter: cv2.typing.Point = ...) -> None: ...
|
|
@_typing.overload
|
|
def setTemplate(self, edges: cv2.typing.MatLike, dx: cv2.typing.MatLike, dy: cv2.typing.MatLike, templCenter: cv2.typing.Point = ...) -> None: ...
|
|
@_typing.overload
|
|
def setTemplate(self, edges: UMat, dx: UMat, dy: UMat, templCenter: cv2.typing.Point = ...) -> None: ...
|
|
|
|
@_typing.overload
|
|
def detect(self, image: cv2.typing.MatLike, positions: cv2.typing.MatLike | None = ..., votes: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def detect(self, image: UMat, positions: UMat | None = ..., votes: UMat | None = ...) -> tuple[UMat, UMat]: ...
|
|
@_typing.overload
|
|
def detect(self, edges: cv2.typing.MatLike, dx: cv2.typing.MatLike, dy: cv2.typing.MatLike, positions: cv2.typing.MatLike | None = ..., votes: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def detect(self, edges: UMat, dx: UMat, dy: UMat, positions: UMat | None = ..., votes: UMat | None = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
def setCannyLowThresh(self, cannyLowThresh: int) -> None: ...
|
|
|
|
def getCannyLowThresh(self) -> int: ...
|
|
|
|
def setCannyHighThresh(self, cannyHighThresh: int) -> None: ...
|
|
|
|
def getCannyHighThresh(self) -> int: ...
|
|
|
|
def setMinDist(self, minDist: float) -> None: ...
|
|
|
|
def getMinDist(self) -> float: ...
|
|
|
|
def setDp(self, dp: float) -> None: ...
|
|
|
|
def getDp(self) -> float: ...
|
|
|
|
def setMaxBufferSize(self, maxBufferSize: int) -> None: ...
|
|
|
|
def getMaxBufferSize(self) -> int: ...
|
|
|
|
|
|
class GeneralizedHoughBallard(GeneralizedHough):
|
|
# Functions
|
|
def setLevels(self, levels: int) -> None: ...
|
|
|
|
def getLevels(self) -> int: ...
|
|
|
|
def setVotesThreshold(self, votesThreshold: int) -> None: ...
|
|
|
|
def getVotesThreshold(self) -> int: ...
|
|
|
|
|
|
class GeneralizedHoughGuil(GeneralizedHough):
|
|
# Functions
|
|
def setXi(self, xi: float) -> None: ...
|
|
|
|
def getXi(self) -> float: ...
|
|
|
|
def setLevels(self, levels: int) -> None: ...
|
|
|
|
def getLevels(self) -> int: ...
|
|
|
|
def setAngleEpsilon(self, angleEpsilon: float) -> None: ...
|
|
|
|
def getAngleEpsilon(self) -> float: ...
|
|
|
|
def setMinAngle(self, minAngle: float) -> None: ...
|
|
|
|
def getMinAngle(self) -> float: ...
|
|
|
|
def setMaxAngle(self, maxAngle: float) -> None: ...
|
|
|
|
def getMaxAngle(self) -> float: ...
|
|
|
|
def setAngleStep(self, angleStep: float) -> None: ...
|
|
|
|
def getAngleStep(self) -> float: ...
|
|
|
|
def setAngleThresh(self, angleThresh: int) -> None: ...
|
|
|
|
def getAngleThresh(self) -> int: ...
|
|
|
|
def setMinScale(self, minScale: float) -> None: ...
|
|
|
|
def getMinScale(self) -> float: ...
|
|
|
|
def setMaxScale(self, maxScale: float) -> None: ...
|
|
|
|
def getMaxScale(self) -> float: ...
|
|
|
|
def setScaleStep(self, scaleStep: float) -> None: ...
|
|
|
|
def getScaleStep(self) -> float: ...
|
|
|
|
def setScaleThresh(self, scaleThresh: int) -> None: ...
|
|
|
|
def getScaleThresh(self) -> int: ...
|
|
|
|
def setPosThresh(self, posThresh: int) -> None: ...
|
|
|
|
def getPosThresh(self) -> int: ...
|
|
|
|
|
|
class CLAHE(Algorithm):
|
|
# Functions
|
|
@_typing.overload
|
|
def apply(self, src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def apply(self, src: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
def setClipLimit(self, clipLimit: float) -> None: ...
|
|
|
|
def getClipLimit(self) -> float: ...
|
|
|
|
def setTilesGridSize(self, tileGridSize: cv2.typing.Size) -> None: ...
|
|
|
|
def getTilesGridSize(self) -> cv2.typing.Size: ...
|
|
|
|
def collectGarbage(self) -> None: ...
|
|
|
|
|
|
class Subdiv2D:
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, rect: cv2.typing.Rect) -> None: ...
|
|
|
|
def initDelaunay(self, rect: cv2.typing.Rect) -> None: ...
|
|
|
|
@_typing.overload
|
|
def insert(self, pt: cv2.typing.Point2f) -> int: ...
|
|
@_typing.overload
|
|
def insert(self, ptvec: _typing.Sequence[cv2.typing.Point2f]) -> None: ...
|
|
|
|
def locate(self, pt: cv2.typing.Point2f) -> tuple[int, int, int]: ...
|
|
|
|
def findNearest(self, pt: cv2.typing.Point2f) -> tuple[int, cv2.typing.Point2f]: ...
|
|
|
|
def getEdgeList(self) -> _typing.Sequence[cv2.typing.Vec4f]: ...
|
|
|
|
def getLeadingEdgeList(self) -> _typing.Sequence[int]: ...
|
|
|
|
def getTriangleList(self) -> _typing.Sequence[cv2.typing.Vec6f]: ...
|
|
|
|
def getVoronoiFacetList(self, idx: _typing.Sequence[int]) -> tuple[_typing.Sequence[_typing.Sequence[cv2.typing.Point2f]], _typing.Sequence[cv2.typing.Point2f]]: ...
|
|
|
|
def getVertex(self, vertex: int) -> tuple[cv2.typing.Point2f, int]: ...
|
|
|
|
def getEdge(self, edge: int, nextEdgeType: int) -> int: ...
|
|
|
|
def nextEdge(self, edge: int) -> int: ...
|
|
|
|
def rotateEdge(self, edge: int, rotate: int) -> int: ...
|
|
|
|
def symEdge(self, edge: int) -> int: ...
|
|
|
|
def edgeOrg(self, edge: int) -> tuple[int, cv2.typing.Point2f]: ...
|
|
|
|
def edgeDst(self, edge: int) -> tuple[int, cv2.typing.Point2f]: ...
|
|
|
|
|
|
class LineSegmentDetector(Algorithm):
|
|
# Functions
|
|
@_typing.overload
|
|
def detect(self, image: cv2.typing.MatLike, lines: cv2.typing.MatLike | None = ..., width: cv2.typing.MatLike | None = ..., prec: cv2.typing.MatLike | None = ..., nfa: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def detect(self, image: UMat, lines: UMat | None = ..., width: UMat | None = ..., prec: UMat | None = ..., nfa: UMat | None = ...) -> tuple[UMat, UMat, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def drawSegments(self, image: cv2.typing.MatLike, lines: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def drawSegments(self, image: UMat, lines: UMat) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def compareSegments(self, size: cv2.typing.Size, lines1: cv2.typing.MatLike, lines2: cv2.typing.MatLike, image: cv2.typing.MatLike | None = ...) -> tuple[int, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def compareSegments(self, size: cv2.typing.Size, lines1: UMat, lines2: UMat, image: UMat | None = ...) -> tuple[int, UMat]: ...
|
|
|
|
|
|
class Tonemap(Algorithm):
|
|
# Functions
|
|
@_typing.overload
|
|
def process(self, src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def process(self, src: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
def getGamma(self) -> float: ...
|
|
|
|
def setGamma(self, gamma: float) -> None: ...
|
|
|
|
|
|
class TonemapDrago(Tonemap):
|
|
# Functions
|
|
def getSaturation(self) -> float: ...
|
|
|
|
def setSaturation(self, saturation: float) -> None: ...
|
|
|
|
def getBias(self) -> float: ...
|
|
|
|
def setBias(self, bias: float) -> None: ...
|
|
|
|
|
|
class TonemapReinhard(Tonemap):
|
|
# Functions
|
|
def getIntensity(self) -> float: ...
|
|
|
|
def setIntensity(self, intensity: float) -> None: ...
|
|
|
|
def getLightAdaptation(self) -> float: ...
|
|
|
|
def setLightAdaptation(self, light_adapt: float) -> None: ...
|
|
|
|
def getColorAdaptation(self) -> float: ...
|
|
|
|
def setColorAdaptation(self, color_adapt: float) -> None: ...
|
|
|
|
|
|
class TonemapMantiuk(Tonemap):
|
|
# Functions
|
|
def getScale(self) -> float: ...
|
|
|
|
def setScale(self, scale: float) -> None: ...
|
|
|
|
def getSaturation(self) -> float: ...
|
|
|
|
def setSaturation(self, saturation: float) -> None: ...
|
|
|
|
|
|
class AlignExposures(Algorithm):
|
|
# Functions
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[cv2.typing.MatLike], dst: _typing.Sequence[cv2.typing.MatLike], times: cv2.typing.MatLike, response: cv2.typing.MatLike) -> None: ...
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[UMat], dst: _typing.Sequence[cv2.typing.MatLike], times: UMat, response: UMat) -> None: ...
|
|
|
|
|
|
class AlignMTB(AlignExposures):
|
|
# Functions
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[cv2.typing.MatLike], dst: _typing.Sequence[cv2.typing.MatLike], times: cv2.typing.MatLike, response: cv2.typing.MatLike) -> None: ...
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[UMat], dst: _typing.Sequence[cv2.typing.MatLike], times: UMat, response: UMat) -> None: ...
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[cv2.typing.MatLike], dst: _typing.Sequence[cv2.typing.MatLike]) -> None: ...
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[UMat], dst: _typing.Sequence[cv2.typing.MatLike]) -> None: ...
|
|
|
|
@_typing.overload
|
|
def calculateShift(self, img0: cv2.typing.MatLike, img1: cv2.typing.MatLike) -> cv2.typing.Point: ...
|
|
@_typing.overload
|
|
def calculateShift(self, img0: UMat, img1: UMat) -> cv2.typing.Point: ...
|
|
|
|
@_typing.overload
|
|
def shiftMat(self, src: cv2.typing.MatLike, shift: cv2.typing.Point, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def shiftMat(self, src: UMat, shift: cv2.typing.Point, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def computeBitmaps(self, img: cv2.typing.MatLike, tb: cv2.typing.MatLike | None = ..., eb: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def computeBitmaps(self, img: UMat, tb: UMat | None = ..., eb: UMat | None = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
def getMaxBits(self) -> int: ...
|
|
|
|
def setMaxBits(self, max_bits: int) -> None: ...
|
|
|
|
def getExcludeRange(self) -> int: ...
|
|
|
|
def setExcludeRange(self, exclude_range: int) -> None: ...
|
|
|
|
def getCut(self) -> bool: ...
|
|
|
|
def setCut(self, value: bool) -> None: ...
|
|
|
|
|
|
class CalibrateCRF(Algorithm):
|
|
# Functions
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[cv2.typing.MatLike], times: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[UMat], times: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
|
|
class CalibrateDebevec(CalibrateCRF):
|
|
# Functions
|
|
def getLambda(self) -> float: ...
|
|
|
|
def setLambda(self, lambda_: float) -> None: ...
|
|
|
|
def getSamples(self) -> int: ...
|
|
|
|
def setSamples(self, samples: int) -> None: ...
|
|
|
|
def getRandom(self) -> bool: ...
|
|
|
|
def setRandom(self, random: bool) -> None: ...
|
|
|
|
|
|
class CalibrateRobertson(CalibrateCRF):
|
|
# Functions
|
|
def getMaxIter(self) -> int: ...
|
|
|
|
def setMaxIter(self, max_iter: int) -> None: ...
|
|
|
|
def getThreshold(self) -> float: ...
|
|
|
|
def setThreshold(self, threshold: float) -> None: ...
|
|
|
|
def getRadiance(self) -> cv2.typing.MatLike: ...
|
|
|
|
|
|
class MergeExposures(Algorithm):
|
|
# Functions
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[cv2.typing.MatLike], times: cv2.typing.MatLike, response: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[UMat], times: UMat, response: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
|
|
class MergeDebevec(MergeExposures):
|
|
# Functions
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[cv2.typing.MatLike], times: cv2.typing.MatLike, response: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[UMat], times: UMat, response: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[cv2.typing.MatLike], times: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[UMat], times: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
|
|
class MergeMertens(MergeExposures):
|
|
# Functions
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[cv2.typing.MatLike], times: cv2.typing.MatLike, response: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[UMat], times: UMat, response: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[cv2.typing.MatLike], dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[UMat], dst: UMat | None = ...) -> UMat: ...
|
|
|
|
def getContrastWeight(self) -> float: ...
|
|
|
|
def setContrastWeight(self, contrast_weiht: float) -> None: ...
|
|
|
|
def getSaturationWeight(self) -> float: ...
|
|
|
|
def setSaturationWeight(self, saturation_weight: float) -> None: ...
|
|
|
|
def getExposureWeight(self) -> float: ...
|
|
|
|
def setExposureWeight(self, exposure_weight: float) -> None: ...
|
|
|
|
|
|
class MergeRobertson(MergeExposures):
|
|
# Functions
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[cv2.typing.MatLike], times: cv2.typing.MatLike, response: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[UMat], times: UMat, response: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[cv2.typing.MatLike], times: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def process(self, src: _typing.Sequence[UMat], times: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
|
|
class Feature2D:
|
|
# Functions
|
|
@_typing.overload
|
|
def detect(self, image: cv2.typing.MatLike, mask: cv2.typing.MatLike | None = ...) -> _typing.Sequence[KeyPoint]: ...
|
|
@_typing.overload
|
|
def detect(self, image: UMat, mask: UMat | None = ...) -> _typing.Sequence[KeyPoint]: ...
|
|
@_typing.overload
|
|
def detect(self, images: _typing.Sequence[cv2.typing.MatLike], masks: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[_typing.Sequence[KeyPoint]]: ...
|
|
@_typing.overload
|
|
def detect(self, images: _typing.Sequence[UMat], masks: _typing.Sequence[UMat] | None = ...) -> _typing.Sequence[_typing.Sequence[KeyPoint]]: ...
|
|
|
|
@_typing.overload
|
|
def compute(self, image: cv2.typing.MatLike, keypoints: _typing.Sequence[KeyPoint], descriptors: cv2.typing.MatLike | None = ...) -> tuple[_typing.Sequence[KeyPoint], cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def compute(self, image: UMat, keypoints: _typing.Sequence[KeyPoint], descriptors: UMat | None = ...) -> tuple[_typing.Sequence[KeyPoint], UMat]: ...
|
|
@_typing.overload
|
|
def compute(self, images: _typing.Sequence[cv2.typing.MatLike], keypoints: _typing.Sequence[_typing.Sequence[KeyPoint]], descriptors: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> tuple[_typing.Sequence[_typing.Sequence[KeyPoint]], _typing.Sequence[cv2.typing.MatLike]]: ...
|
|
@_typing.overload
|
|
def compute(self, images: _typing.Sequence[UMat], keypoints: _typing.Sequence[_typing.Sequence[KeyPoint]], descriptors: _typing.Sequence[UMat] | None = ...) -> tuple[_typing.Sequence[_typing.Sequence[KeyPoint]], _typing.Sequence[UMat]]: ...
|
|
|
|
@_typing.overload
|
|
def detectAndCompute(self, image: cv2.typing.MatLike, mask: cv2.typing.MatLike, descriptors: cv2.typing.MatLike | None = ..., useProvidedKeypoints: bool = ...) -> tuple[_typing.Sequence[KeyPoint], cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def detectAndCompute(self, image: UMat, mask: UMat, descriptors: UMat | None = ..., useProvidedKeypoints: bool = ...) -> tuple[_typing.Sequence[KeyPoint], UMat]: ...
|
|
|
|
def descriptorSize(self) -> int: ...
|
|
|
|
def descriptorType(self) -> int: ...
|
|
|
|
def defaultNorm(self) -> int: ...
|
|
|
|
@_typing.overload
|
|
def write(self, fileName: str) -> None: ...
|
|
@_typing.overload
|
|
def write(self, fs: FileStorage, name: str) -> None: ...
|
|
|
|
@_typing.overload
|
|
def read(self, fileName: str) -> None: ...
|
|
@_typing.overload
|
|
def read(self, arg1: FileNode) -> None: ...
|
|
|
|
def empty(self) -> bool: ...
|
|
|
|
def getDefaultName(self) -> str: ...
|
|
|
|
|
|
class AffineFeature(Feature2D):
|
|
# Functions
|
|
@classmethod
|
|
def create(cls, backend: Feature2D, maxTilt: int = ..., minTilt: int = ..., tiltStep: float = ..., rotateStepBase: float = ...) -> AffineFeature: ...
|
|
|
|
def setViewParams(self, tilts: _typing.Sequence[float], rolls: _typing.Sequence[float]) -> None: ...
|
|
|
|
def getViewParams(self, tilts: _typing.Sequence[float], rolls: _typing.Sequence[float]) -> None: ...
|
|
|
|
def getDefaultName(self) -> str: ...
|
|
|
|
|
|
class SIFT(Feature2D):
|
|
# Functions
|
|
@classmethod
|
|
@_typing.overload
|
|
def create(cls, nfeatures: int = ..., nOctaveLayers: int = ..., contrastThreshold: float = ..., edgeThreshold: float = ..., sigma: float = ..., enable_precise_upscale: bool = ...) -> SIFT: ...
|
|
@classmethod
|
|
@_typing.overload
|
|
def create(cls, nfeatures: int, nOctaveLayers: int, contrastThreshold: float, edgeThreshold: float, sigma: float, descriptorType: int, enable_precise_upscale: bool = ...) -> SIFT: ...
|
|
|
|
def getDefaultName(self) -> str: ...
|
|
|
|
def setNFeatures(self, maxFeatures: int) -> None: ...
|
|
|
|
def getNFeatures(self) -> int: ...
|
|
|
|
def setNOctaveLayers(self, nOctaveLayers: int) -> None: ...
|
|
|
|
def getNOctaveLayers(self) -> int: ...
|
|
|
|
def setContrastThreshold(self, contrastThreshold: float) -> None: ...
|
|
|
|
def getContrastThreshold(self) -> float: ...
|
|
|
|
def setEdgeThreshold(self, edgeThreshold: float) -> None: ...
|
|
|
|
def getEdgeThreshold(self) -> float: ...
|
|
|
|
def setSigma(self, sigma: float) -> None: ...
|
|
|
|
def getSigma(self) -> float: ...
|
|
|
|
|
|
class BRISK(Feature2D):
|
|
# Functions
|
|
@classmethod
|
|
@_typing.overload
|
|
def create(cls, thresh: int = ..., octaves: int = ..., patternScale: float = ...) -> BRISK: ...
|
|
@classmethod
|
|
@_typing.overload
|
|
def create(cls, radiusList: _typing.Sequence[float], numberList: _typing.Sequence[int], dMax: float = ..., dMin: float = ..., indexChange: _typing.Sequence[int] = ...) -> BRISK: ...
|
|
@classmethod
|
|
@_typing.overload
|
|
def create(cls, thresh: int, octaves: int, radiusList: _typing.Sequence[float], numberList: _typing.Sequence[int], dMax: float = ..., dMin: float = ..., indexChange: _typing.Sequence[int] = ...) -> BRISK: ...
|
|
|
|
def getDefaultName(self) -> str: ...
|
|
|
|
def setThreshold(self, threshold: int) -> None: ...
|
|
|
|
def getThreshold(self) -> int: ...
|
|
|
|
def setOctaves(self, octaves: int) -> None: ...
|
|
|
|
def getOctaves(self) -> int: ...
|
|
|
|
def setPatternScale(self, patternScale: float) -> None: ...
|
|
|
|
def getPatternScale(self) -> float: ...
|
|
|
|
|
|
class ORB(Feature2D):
|
|
# Functions
|
|
@classmethod
|
|
def create(cls, nfeatures: int = ..., scaleFactor: float = ..., nlevels: int = ..., edgeThreshold: int = ..., firstLevel: int = ..., WTA_K: int = ..., scoreType: ORB_ScoreType = ..., patchSize: int = ..., fastThreshold: int = ...) -> ORB: ...
|
|
|
|
def setMaxFeatures(self, maxFeatures: int) -> None: ...
|
|
|
|
def getMaxFeatures(self) -> int: ...
|
|
|
|
def setScaleFactor(self, scaleFactor: float) -> None: ...
|
|
|
|
def getScaleFactor(self) -> float: ...
|
|
|
|
def setNLevels(self, nlevels: int) -> None: ...
|
|
|
|
def getNLevels(self) -> int: ...
|
|
|
|
def setEdgeThreshold(self, edgeThreshold: int) -> None: ...
|
|
|
|
def getEdgeThreshold(self) -> int: ...
|
|
|
|
def setFirstLevel(self, firstLevel: int) -> None: ...
|
|
|
|
def getFirstLevel(self) -> int: ...
|
|
|
|
def setWTA_K(self, wta_k: int) -> None: ...
|
|
|
|
def getWTA_K(self) -> int: ...
|
|
|
|
def setScoreType(self, scoreType: ORB_ScoreType) -> None: ...
|
|
|
|
def getScoreType(self) -> ORB_ScoreType: ...
|
|
|
|
def setPatchSize(self, patchSize: int) -> None: ...
|
|
|
|
def getPatchSize(self) -> int: ...
|
|
|
|
def setFastThreshold(self, fastThreshold: int) -> None: ...
|
|
|
|
def getFastThreshold(self) -> int: ...
|
|
|
|
def getDefaultName(self) -> str: ...
|
|
|
|
|
|
class MSER(Feature2D):
|
|
# Functions
|
|
@classmethod
|
|
def create(cls, delta: int = ..., min_area: int = ..., max_area: int = ..., max_variation: float = ..., min_diversity: float = ..., max_evolution: int = ..., area_threshold: float = ..., min_margin: float = ..., edge_blur_size: int = ...) -> MSER: ...
|
|
|
|
@_typing.overload
|
|
def detectRegions(self, image: cv2.typing.MatLike) -> tuple[_typing.Sequence[_typing.Sequence[cv2.typing.Point]], _typing.Sequence[cv2.typing.Rect]]: ...
|
|
@_typing.overload
|
|
def detectRegions(self, image: UMat) -> tuple[_typing.Sequence[_typing.Sequence[cv2.typing.Point]], _typing.Sequence[cv2.typing.Rect]]: ...
|
|
|
|
def setDelta(self, delta: int) -> None: ...
|
|
|
|
def getDelta(self) -> int: ...
|
|
|
|
def setMinArea(self, minArea: int) -> None: ...
|
|
|
|
def getMinArea(self) -> int: ...
|
|
|
|
def setMaxArea(self, maxArea: int) -> None: ...
|
|
|
|
def getMaxArea(self) -> int: ...
|
|
|
|
def setMaxVariation(self, maxVariation: float) -> None: ...
|
|
|
|
def getMaxVariation(self) -> float: ...
|
|
|
|
def setMinDiversity(self, minDiversity: float) -> None: ...
|
|
|
|
def getMinDiversity(self) -> float: ...
|
|
|
|
def setMaxEvolution(self, maxEvolution: int) -> None: ...
|
|
|
|
def getMaxEvolution(self) -> int: ...
|
|
|
|
def setAreaThreshold(self, areaThreshold: float) -> None: ...
|
|
|
|
def getAreaThreshold(self) -> float: ...
|
|
|
|
def setMinMargin(self, min_margin: float) -> None: ...
|
|
|
|
def getMinMargin(self) -> float: ...
|
|
|
|
def setEdgeBlurSize(self, edge_blur_size: int) -> None: ...
|
|
|
|
def getEdgeBlurSize(self) -> int: ...
|
|
|
|
def setPass2Only(self, f: bool) -> None: ...
|
|
|
|
def getPass2Only(self) -> bool: ...
|
|
|
|
def getDefaultName(self) -> str: ...
|
|
|
|
|
|
class FastFeatureDetector(Feature2D):
|
|
# Functions
|
|
@classmethod
|
|
def create(cls, threshold: int = ..., nonmaxSuppression: bool = ..., type: FastFeatureDetector_DetectorType = ...) -> FastFeatureDetector: ...
|
|
|
|
def setThreshold(self, threshold: int) -> None: ...
|
|
|
|
def getThreshold(self) -> int: ...
|
|
|
|
def setNonmaxSuppression(self, f: bool) -> None: ...
|
|
|
|
def getNonmaxSuppression(self) -> bool: ...
|
|
|
|
def setType(self, type: FastFeatureDetector_DetectorType) -> None: ...
|
|
|
|
def getType(self) -> FastFeatureDetector_DetectorType: ...
|
|
|
|
def getDefaultName(self) -> str: ...
|
|
|
|
|
|
class AgastFeatureDetector(Feature2D):
|
|
# Functions
|
|
@classmethod
|
|
def create(cls, threshold: int = ..., nonmaxSuppression: bool = ..., type: AgastFeatureDetector_DetectorType = ...) -> AgastFeatureDetector: ...
|
|
|
|
def setThreshold(self, threshold: int) -> None: ...
|
|
|
|
def getThreshold(self) -> int: ...
|
|
|
|
def setNonmaxSuppression(self, f: bool) -> None: ...
|
|
|
|
def getNonmaxSuppression(self) -> bool: ...
|
|
|
|
def setType(self, type: AgastFeatureDetector_DetectorType) -> None: ...
|
|
|
|
def getType(self) -> AgastFeatureDetector_DetectorType: ...
|
|
|
|
def getDefaultName(self) -> str: ...
|
|
|
|
|
|
class GFTTDetector(Feature2D):
|
|
# Functions
|
|
@classmethod
|
|
@_typing.overload
|
|
def create(cls, maxCorners: int = ..., qualityLevel: float = ..., minDistance: float = ..., blockSize: int = ..., useHarrisDetector: bool = ..., k: float = ...) -> GFTTDetector: ...
|
|
@classmethod
|
|
@_typing.overload
|
|
def create(cls, maxCorners: int, qualityLevel: float, minDistance: float, blockSize: int, gradiantSize: int, useHarrisDetector: bool = ..., k: float = ...) -> GFTTDetector: ...
|
|
|
|
def setMaxFeatures(self, maxFeatures: int) -> None: ...
|
|
|
|
def getMaxFeatures(self) -> int: ...
|
|
|
|
def setQualityLevel(self, qlevel: float) -> None: ...
|
|
|
|
def getQualityLevel(self) -> float: ...
|
|
|
|
def setMinDistance(self, minDistance: float) -> None: ...
|
|
|
|
def getMinDistance(self) -> float: ...
|
|
|
|
def setBlockSize(self, blockSize: int) -> None: ...
|
|
|
|
def getBlockSize(self) -> int: ...
|
|
|
|
def setGradientSize(self, gradientSize_: int) -> None: ...
|
|
|
|
def getGradientSize(self) -> int: ...
|
|
|
|
def setHarrisDetector(self, val: bool) -> None: ...
|
|
|
|
def getHarrisDetector(self) -> bool: ...
|
|
|
|
def setK(self, k: float) -> None: ...
|
|
|
|
def getK(self) -> float: ...
|
|
|
|
def getDefaultName(self) -> str: ...
|
|
|
|
|
|
class SimpleBlobDetector(Feature2D):
|
|
# Classes
|
|
class Params:
|
|
thresholdStep: float
|
|
minThreshold: float
|
|
maxThreshold: float
|
|
minRepeatability: int
|
|
minDistBetweenBlobs: float
|
|
filterByColor: bool
|
|
blobColor: int
|
|
filterByArea: bool
|
|
minArea: float
|
|
maxArea: float
|
|
filterByCircularity: bool
|
|
minCircularity: float
|
|
maxCircularity: float
|
|
filterByInertia: bool
|
|
minInertiaRatio: float
|
|
maxInertiaRatio: float
|
|
filterByConvexity: bool
|
|
minConvexity: float
|
|
maxConvexity: float
|
|
collectContours: bool
|
|
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
|
|
|
|
# Functions
|
|
@classmethod
|
|
def create(cls, parameters: SimpleBlobDetector.Params = ...) -> SimpleBlobDetector: ...
|
|
|
|
def setParams(self, params: SimpleBlobDetector.Params) -> None: ...
|
|
|
|
def getParams(self) -> SimpleBlobDetector.Params: ...
|
|
|
|
def getDefaultName(self) -> str: ...
|
|
|
|
def getBlobContours(self) -> _typing.Sequence[_typing.Sequence[cv2.typing.Point]]: ...
|
|
|
|
|
|
class KAZE(Feature2D):
|
|
# Functions
|
|
@classmethod
|
|
def create(cls, extended: bool = ..., upright: bool = ..., threshold: float = ..., nOctaves: int = ..., nOctaveLayers: int = ..., diffusivity: KAZE_DiffusivityType = ...) -> KAZE: ...
|
|
|
|
def setExtended(self, extended: bool) -> None: ...
|
|
|
|
def getExtended(self) -> bool: ...
|
|
|
|
def setUpright(self, upright: bool) -> None: ...
|
|
|
|
def getUpright(self) -> bool: ...
|
|
|
|
def setThreshold(self, threshold: float) -> None: ...
|
|
|
|
def getThreshold(self) -> float: ...
|
|
|
|
def setNOctaves(self, octaves: int) -> None: ...
|
|
|
|
def getNOctaves(self) -> int: ...
|
|
|
|
def setNOctaveLayers(self, octaveLayers: int) -> None: ...
|
|
|
|
def getNOctaveLayers(self) -> int: ...
|
|
|
|
def setDiffusivity(self, diff: KAZE_DiffusivityType) -> None: ...
|
|
|
|
def getDiffusivity(self) -> KAZE_DiffusivityType: ...
|
|
|
|
def getDefaultName(self) -> str: ...
|
|
|
|
|
|
class AKAZE(Feature2D):
|
|
# Functions
|
|
@classmethod
|
|
def create(cls, descriptor_type: AKAZE_DescriptorType = ..., descriptor_size: int = ..., descriptor_channels: int = ..., threshold: float = ..., nOctaves: int = ..., nOctaveLayers: int = ..., diffusivity: KAZE_DiffusivityType = ..., max_points: int = ...) -> AKAZE: ...
|
|
|
|
def setDescriptorType(self, dtype: AKAZE_DescriptorType) -> None: ...
|
|
|
|
def getDescriptorType(self) -> AKAZE_DescriptorType: ...
|
|
|
|
def setDescriptorSize(self, dsize: int) -> None: ...
|
|
|
|
def getDescriptorSize(self) -> int: ...
|
|
|
|
def setDescriptorChannels(self, dch: int) -> None: ...
|
|
|
|
def getDescriptorChannels(self) -> int: ...
|
|
|
|
def setThreshold(self, threshold: float) -> None: ...
|
|
|
|
def getThreshold(self) -> float: ...
|
|
|
|
def setNOctaves(self, octaves: int) -> None: ...
|
|
|
|
def getNOctaves(self) -> int: ...
|
|
|
|
def setNOctaveLayers(self, octaveLayers: int) -> None: ...
|
|
|
|
def getNOctaveLayers(self) -> int: ...
|
|
|
|
def setDiffusivity(self, diff: KAZE_DiffusivityType) -> None: ...
|
|
|
|
def getDiffusivity(self) -> KAZE_DiffusivityType: ...
|
|
|
|
def getDefaultName(self) -> str: ...
|
|
|
|
def setMaxPoints(self, max_points: int) -> None: ...
|
|
|
|
def getMaxPoints(self) -> int: ...
|
|
|
|
|
|
class DescriptorMatcher(Algorithm):
|
|
# Functions
|
|
@_typing.overload
|
|
def add(self, descriptors: _typing.Sequence[cv2.typing.MatLike]) -> None: ...
|
|
@_typing.overload
|
|
def add(self, descriptors: _typing.Sequence[UMat]) -> None: ...
|
|
|
|
def getTrainDescriptors(self) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
|
|
|
def clear(self) -> None: ...
|
|
|
|
def empty(self) -> bool: ...
|
|
|
|
def isMaskSupported(self) -> bool: ...
|
|
|
|
def train(self) -> None: ...
|
|
|
|
@_typing.overload
|
|
def match(self, queryDescriptors: cv2.typing.MatLike, trainDescriptors: cv2.typing.MatLike, mask: cv2.typing.MatLike | None = ...) -> _typing.Sequence[DMatch]: ...
|
|
@_typing.overload
|
|
def match(self, queryDescriptors: UMat, trainDescriptors: UMat, mask: UMat | None = ...) -> _typing.Sequence[DMatch]: ...
|
|
@_typing.overload
|
|
def match(self, queryDescriptors: cv2.typing.MatLike, masks: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[DMatch]: ...
|
|
@_typing.overload
|
|
def match(self, queryDescriptors: UMat, masks: _typing.Sequence[UMat] | None = ...) -> _typing.Sequence[DMatch]: ...
|
|
|
|
@_typing.overload
|
|
def knnMatch(self, queryDescriptors: cv2.typing.MatLike, trainDescriptors: cv2.typing.MatLike, k: int, mask: cv2.typing.MatLike | None = ..., compactResult: bool = ...) -> _typing.Sequence[_typing.Sequence[DMatch]]: ...
|
|
@_typing.overload
|
|
def knnMatch(self, queryDescriptors: UMat, trainDescriptors: UMat, k: int, mask: UMat | None = ..., compactResult: bool = ...) -> _typing.Sequence[_typing.Sequence[DMatch]]: ...
|
|
@_typing.overload
|
|
def knnMatch(self, queryDescriptors: cv2.typing.MatLike, k: int, masks: _typing.Sequence[cv2.typing.MatLike] | None = ..., compactResult: bool = ...) -> _typing.Sequence[_typing.Sequence[DMatch]]: ...
|
|
@_typing.overload
|
|
def knnMatch(self, queryDescriptors: UMat, k: int, masks: _typing.Sequence[UMat] | None = ..., compactResult: bool = ...) -> _typing.Sequence[_typing.Sequence[DMatch]]: ...
|
|
|
|
@_typing.overload
|
|
def radiusMatch(self, queryDescriptors: cv2.typing.MatLike, trainDescriptors: cv2.typing.MatLike, maxDistance: float, mask: cv2.typing.MatLike | None = ..., compactResult: bool = ...) -> _typing.Sequence[_typing.Sequence[DMatch]]: ...
|
|
@_typing.overload
|
|
def radiusMatch(self, queryDescriptors: UMat, trainDescriptors: UMat, maxDistance: float, mask: UMat | None = ..., compactResult: bool = ...) -> _typing.Sequence[_typing.Sequence[DMatch]]: ...
|
|
@_typing.overload
|
|
def radiusMatch(self, queryDescriptors: cv2.typing.MatLike, maxDistance: float, masks: _typing.Sequence[cv2.typing.MatLike] | None = ..., compactResult: bool = ...) -> _typing.Sequence[_typing.Sequence[DMatch]]: ...
|
|
@_typing.overload
|
|
def radiusMatch(self, queryDescriptors: UMat, maxDistance: float, masks: _typing.Sequence[UMat] | None = ..., compactResult: bool = ...) -> _typing.Sequence[_typing.Sequence[DMatch]]: ...
|
|
|
|
@_typing.overload
|
|
def write(self, fileName: str) -> None: ...
|
|
@_typing.overload
|
|
def write(self, fs: FileStorage, name: str) -> None: ...
|
|
|
|
@_typing.overload
|
|
def read(self, fileName: str) -> None: ...
|
|
@_typing.overload
|
|
def read(self, arg1: FileNode) -> None: ...
|
|
|
|
def clone(self, emptyTrainData: bool = ...) -> DescriptorMatcher: ...
|
|
|
|
@classmethod
|
|
@_typing.overload
|
|
def create(cls, descriptorMatcherType: str) -> DescriptorMatcher: ...
|
|
@classmethod
|
|
@_typing.overload
|
|
def create(cls, matcherType: DescriptorMatcher_MatcherType) -> DescriptorMatcher: ...
|
|
|
|
|
|
class BFMatcher(DescriptorMatcher):
|
|
# Functions
|
|
def __init__(self, normType: int = ..., crossCheck: bool = ...) -> None: ...
|
|
|
|
@classmethod
|
|
def create(cls, normType: int = ..., crossCheck: bool = ...) -> BFMatcher: ...
|
|
|
|
|
|
class FlannBasedMatcher(DescriptorMatcher):
|
|
# Functions
|
|
def __init__(self, indexParams: cv2.typing.IndexParams = ..., searchParams: cv2.typing.SearchParams = ...) -> None: ...
|
|
|
|
@classmethod
|
|
def create(cls) -> FlannBasedMatcher: ...
|
|
|
|
|
|
class BOWTrainer:
|
|
# Functions
|
|
def add(self, descriptors: cv2.typing.MatLike) -> None: ...
|
|
|
|
def getDescriptors(self) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
|
|
|
def descriptorsCount(self) -> int: ...
|
|
|
|
def clear(self) -> None: ...
|
|
|
|
@_typing.overload
|
|
def cluster(self) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def cluster(self, descriptors: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
|
|
|
|
|
class BOWKMeansTrainer(BOWTrainer):
|
|
# Functions
|
|
def __init__(self, clusterCount: int, termcrit: cv2.typing.TermCriteria = ..., attempts: int = ..., flags: int = ...) -> None: ...
|
|
|
|
@_typing.overload
|
|
def cluster(self) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def cluster(self, descriptors: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
|
|
|
|
|
class BOWImgDescriptorExtractor:
|
|
# Functions
|
|
def __init__(self, dextractor: Feature2D, dmatcher: DescriptorMatcher) -> None: ...
|
|
|
|
def setVocabulary(self, vocabulary: cv2.typing.MatLike) -> None: ...
|
|
|
|
def getVocabulary(self) -> cv2.typing.MatLike: ...
|
|
|
|
def compute(self, image: cv2.typing.MatLike, keypoints: _typing.Sequence[KeyPoint], imgDescriptor: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
|
|
def descriptorSize(self) -> int: ...
|
|
|
|
def descriptorType(self) -> int: ...
|
|
|
|
|
|
class VideoCapture:
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, filename: str, apiPreference: int = ...) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, filename: str, apiPreference: int, params: _typing.Sequence[int]) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, index: int, apiPreference: int = ...) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, index: int, apiPreference: int, params: _typing.Sequence[int]) -> None: ...
|
|
|
|
@_typing.overload
|
|
def open(self, filename: str, apiPreference: int = ...) -> bool: ...
|
|
@_typing.overload
|
|
def open(self, filename: str, apiPreference: int, params: _typing.Sequence[int]) -> bool: ...
|
|
@_typing.overload
|
|
def open(self, index: int, apiPreference: int = ...) -> bool: ...
|
|
@_typing.overload
|
|
def open(self, index: int, apiPreference: int, params: _typing.Sequence[int]) -> bool: ...
|
|
|
|
def isOpened(self) -> bool: ...
|
|
|
|
def release(self) -> None: ...
|
|
|
|
def grab(self) -> bool: ...
|
|
|
|
@_typing.overload
|
|
def retrieve(self, image: cv2.typing.MatLike | None = ..., flag: int = ...) -> tuple[bool, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def retrieve(self, image: UMat | None = ..., flag: int = ...) -> tuple[bool, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def read(self, image: cv2.typing.MatLike | None = ...) -> tuple[bool, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def read(self, image: UMat | None = ...) -> tuple[bool, UMat]: ...
|
|
|
|
def set(self, propId: int, value: float) -> bool: ...
|
|
|
|
def get(self, propId: int) -> float: ...
|
|
|
|
def getBackendName(self) -> str: ...
|
|
|
|
def setExceptionMode(self, enable: bool) -> None: ...
|
|
|
|
def getExceptionMode(self) -> bool: ...
|
|
|
|
@staticmethod
|
|
def waitAny(streams: _typing.Sequence[VideoCapture], timeoutNs: int = ...) -> tuple[bool, _typing.Sequence[int]]: ...
|
|
|
|
|
|
class VideoWriter:
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, filename: str, fourcc: int, fps: float, frameSize: cv2.typing.Size, isColor: bool = ...) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, filename: str, apiPreference: int, fourcc: int, fps: float, frameSize: cv2.typing.Size, isColor: bool = ...) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, filename: str, fourcc: int, fps: float, frameSize: cv2.typing.Size, params: _typing.Sequence[int]) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, filename: str, apiPreference: int, fourcc: int, fps: float, frameSize: cv2.typing.Size, params: _typing.Sequence[int]) -> None: ...
|
|
|
|
@_typing.overload
|
|
def open(self, filename: str, fourcc: int, fps: float, frameSize: cv2.typing.Size, isColor: bool = ...) -> bool: ...
|
|
@_typing.overload
|
|
def open(self, filename: str, apiPreference: int, fourcc: int, fps: float, frameSize: cv2.typing.Size, isColor: bool = ...) -> bool: ...
|
|
@_typing.overload
|
|
def open(self, filename: str, fourcc: int, fps: float, frameSize: cv2.typing.Size, params: _typing.Sequence[int]) -> bool: ...
|
|
@_typing.overload
|
|
def open(self, filename: str, apiPreference: int, fourcc: int, fps: float, frameSize: cv2.typing.Size, params: _typing.Sequence[int]) -> bool: ...
|
|
|
|
def isOpened(self) -> bool: ...
|
|
|
|
def release(self) -> None: ...
|
|
|
|
@_typing.overload
|
|
def write(self, image: cv2.typing.MatLike) -> None: ...
|
|
@_typing.overload
|
|
def write(self, image: UMat) -> None: ...
|
|
|
|
def set(self, propId: int, value: float) -> bool: ...
|
|
|
|
def get(self, propId: int) -> float: ...
|
|
|
|
@staticmethod
|
|
def fourcc(c1: str, c2: str, c3: str, c4: str) -> int: ...
|
|
|
|
def getBackendName(self) -> str: ...
|
|
|
|
|
|
class UsacParams:
|
|
confidence: float
|
|
isParallel: bool
|
|
loIterations: int
|
|
loMethod: LocalOptimMethod
|
|
loSampleSize: int
|
|
maxIterations: int
|
|
neighborsSearch: NeighborSearchMethod
|
|
randomGeneratorState: int
|
|
sampler: SamplingMethod
|
|
score: ScoreMethod
|
|
threshold: float
|
|
final_polisher: PolishingMethod
|
|
final_polisher_iterations: int
|
|
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
|
|
class CirclesGridFinderParameters:
|
|
densityNeighborhoodSize: cv2.typing.Size2f
|
|
minDensity: float
|
|
kmeansAttempts: int
|
|
minDistanceToAddKeypoint: int
|
|
keypointScale: int
|
|
minGraphConfidence: float
|
|
vertexGain: float
|
|
vertexPenalty: float
|
|
existingVertexGain: float
|
|
edgeGain: float
|
|
edgePenalty: float
|
|
convexHullFactor: float
|
|
minRNGEdgeSwitchDist: float
|
|
squareSize: float
|
|
maxRectifiedDistance: float
|
|
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
|
|
class StereoMatcher(Algorithm):
|
|
# Functions
|
|
@_typing.overload
|
|
def compute(self, left: cv2.typing.MatLike, right: cv2.typing.MatLike, disparity: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def compute(self, left: UMat, right: UMat, disparity: UMat | None = ...) -> UMat: ...
|
|
|
|
def getMinDisparity(self) -> int: ...
|
|
|
|
def setMinDisparity(self, minDisparity: int) -> None: ...
|
|
|
|
def getNumDisparities(self) -> int: ...
|
|
|
|
def setNumDisparities(self, numDisparities: int) -> None: ...
|
|
|
|
def getBlockSize(self) -> int: ...
|
|
|
|
def setBlockSize(self, blockSize: int) -> None: ...
|
|
|
|
def getSpeckleWindowSize(self) -> int: ...
|
|
|
|
def setSpeckleWindowSize(self, speckleWindowSize: int) -> None: ...
|
|
|
|
def getSpeckleRange(self) -> int: ...
|
|
|
|
def setSpeckleRange(self, speckleRange: int) -> None: ...
|
|
|
|
def getDisp12MaxDiff(self) -> int: ...
|
|
|
|
def setDisp12MaxDiff(self, disp12MaxDiff: int) -> None: ...
|
|
|
|
|
|
class StereoBM(StereoMatcher):
|
|
# Functions
|
|
def getPreFilterType(self) -> int: ...
|
|
|
|
def setPreFilterType(self, preFilterType: int) -> None: ...
|
|
|
|
def getPreFilterSize(self) -> int: ...
|
|
|
|
def setPreFilterSize(self, preFilterSize: int) -> None: ...
|
|
|
|
def getPreFilterCap(self) -> int: ...
|
|
|
|
def setPreFilterCap(self, preFilterCap: int) -> None: ...
|
|
|
|
def getTextureThreshold(self) -> int: ...
|
|
|
|
def setTextureThreshold(self, textureThreshold: int) -> None: ...
|
|
|
|
def getUniquenessRatio(self) -> int: ...
|
|
|
|
def setUniquenessRatio(self, uniquenessRatio: int) -> None: ...
|
|
|
|
def getSmallerBlockSize(self) -> int: ...
|
|
|
|
def setSmallerBlockSize(self, blockSize: int) -> None: ...
|
|
|
|
def getROI1(self) -> cv2.typing.Rect: ...
|
|
|
|
def setROI1(self, roi1: cv2.typing.Rect) -> None: ...
|
|
|
|
def getROI2(self) -> cv2.typing.Rect: ...
|
|
|
|
def setROI2(self, roi2: cv2.typing.Rect) -> None: ...
|
|
|
|
@classmethod
|
|
def create(cls, numDisparities: int = ..., blockSize: int = ...) -> StereoBM: ...
|
|
|
|
|
|
class StereoSGBM(StereoMatcher):
|
|
# Functions
|
|
def getPreFilterCap(self) -> int: ...
|
|
|
|
def setPreFilterCap(self, preFilterCap: int) -> None: ...
|
|
|
|
def getUniquenessRatio(self) -> int: ...
|
|
|
|
def setUniquenessRatio(self, uniquenessRatio: int) -> None: ...
|
|
|
|
def getP1(self) -> int: ...
|
|
|
|
def setP1(self, P1: int) -> None: ...
|
|
|
|
def getP2(self) -> int: ...
|
|
|
|
def setP2(self, P2: int) -> None: ...
|
|
|
|
def getMode(self) -> int: ...
|
|
|
|
def setMode(self, mode: int) -> None: ...
|
|
|
|
@classmethod
|
|
def create(cls, minDisparity: int = ..., numDisparities: int = ..., blockSize: int = ..., P1: int = ..., P2: int = ..., disp12MaxDiff: int = ..., preFilterCap: int = ..., uniquenessRatio: int = ..., speckleWindowSize: int = ..., speckleRange: int = ..., mode: int = ...) -> StereoSGBM: ...
|
|
|
|
|
|
class BaseCascadeClassifier(Algorithm):
|
|
...
|
|
|
|
class CascadeClassifier:
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, filename: str) -> None: ...
|
|
|
|
def empty(self) -> bool: ...
|
|
|
|
def load(self, filename: str) -> bool: ...
|
|
|
|
def read(self, node: FileNode) -> bool: ...
|
|
|
|
@_typing.overload
|
|
def detectMultiScale(self, image: cv2.typing.MatLike, scaleFactor: float = ..., minNeighbors: int = ..., flags: int = ..., minSize: cv2.typing.Size = ..., maxSize: cv2.typing.Size = ...) -> _typing.Sequence[cv2.typing.Rect]: ...
|
|
@_typing.overload
|
|
def detectMultiScale(self, image: UMat, scaleFactor: float = ..., minNeighbors: int = ..., flags: int = ..., minSize: cv2.typing.Size = ..., maxSize: cv2.typing.Size = ...) -> _typing.Sequence[cv2.typing.Rect]: ...
|
|
|
|
@_typing.overload
|
|
def detectMultiScale2(self, image: cv2.typing.MatLike, scaleFactor: float = ..., minNeighbors: int = ..., flags: int = ..., minSize: cv2.typing.Size = ..., maxSize: cv2.typing.Size = ...) -> tuple[_typing.Sequence[cv2.typing.Rect], _typing.Sequence[int]]: ...
|
|
@_typing.overload
|
|
def detectMultiScale2(self, image: UMat, scaleFactor: float = ..., minNeighbors: int = ..., flags: int = ..., minSize: cv2.typing.Size = ..., maxSize: cv2.typing.Size = ...) -> tuple[_typing.Sequence[cv2.typing.Rect], _typing.Sequence[int]]: ...
|
|
|
|
@_typing.overload
|
|
def detectMultiScale3(self, image: cv2.typing.MatLike, scaleFactor: float = ..., minNeighbors: int = ..., flags: int = ..., minSize: cv2.typing.Size = ..., maxSize: cv2.typing.Size = ..., outputRejectLevels: bool = ...) -> tuple[_typing.Sequence[cv2.typing.Rect], _typing.Sequence[int], _typing.Sequence[float]]: ...
|
|
@_typing.overload
|
|
def detectMultiScale3(self, image: UMat, scaleFactor: float = ..., minNeighbors: int = ..., flags: int = ..., minSize: cv2.typing.Size = ..., maxSize: cv2.typing.Size = ..., outputRejectLevels: bool = ...) -> tuple[_typing.Sequence[cv2.typing.Rect], _typing.Sequence[int], _typing.Sequence[float]]: ...
|
|
|
|
def isOldFormatCascade(self) -> bool: ...
|
|
|
|
def getOriginalWindowSize(self) -> cv2.typing.Size: ...
|
|
|
|
def getFeatureType(self) -> int: ...
|
|
|
|
@staticmethod
|
|
def convert(oldcascade: str, newcascade: str) -> bool: ...
|
|
|
|
|
|
class HOGDescriptor:
|
|
@property
|
|
def winSize(self) -> cv2.typing.Size: ...
|
|
@property
|
|
def blockSize(self) -> cv2.typing.Size: ...
|
|
@property
|
|
def blockStride(self) -> cv2.typing.Size: ...
|
|
@property
|
|
def cellSize(self) -> cv2.typing.Size: ...
|
|
@property
|
|
def nbins(self) -> int: ...
|
|
@property
|
|
def derivAperture(self) -> int: ...
|
|
@property
|
|
def winSigma(self) -> float: ...
|
|
@property
|
|
def histogramNormType(self) -> HOGDescriptor_HistogramNormType: ...
|
|
@property
|
|
def L2HysThreshold(self) -> float: ...
|
|
@property
|
|
def gammaCorrection(self) -> bool: ...
|
|
@property
|
|
def svmDetector(self) -> _typing.Sequence[float]: ...
|
|
@property
|
|
def nlevels(self) -> int: ...
|
|
@property
|
|
def signedGradient(self) -> bool: ...
|
|
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, _winSize: cv2.typing.Size, _blockSize: cv2.typing.Size, _blockStride: cv2.typing.Size, _cellSize: cv2.typing.Size, _nbins: int, _derivAperture: int = ..., _winSigma: float = ..., _histogramNormType: HOGDescriptor_HistogramNormType = ..., _L2HysThreshold: float = ..., _gammaCorrection: bool = ..., _nlevels: int = ..., _signedGradient: bool = ...) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, filename: str) -> None: ...
|
|
|
|
def getDescriptorSize(self) -> int: ...
|
|
|
|
def checkDetectorSize(self) -> bool: ...
|
|
|
|
def getWinSigma(self) -> float: ...
|
|
|
|
@_typing.overload
|
|
def setSVMDetector(self, svmdetector: cv2.typing.MatLike) -> None: ...
|
|
@_typing.overload
|
|
def setSVMDetector(self, svmdetector: UMat) -> None: ...
|
|
|
|
def load(self, filename: str, objname: str = ...) -> bool: ...
|
|
|
|
def save(self, filename: str, objname: str = ...) -> None: ...
|
|
|
|
@_typing.overload
|
|
def compute(self, img: cv2.typing.MatLike, winStride: cv2.typing.Size = ..., padding: cv2.typing.Size = ..., locations: _typing.Sequence[cv2.typing.Point] = ...) -> _typing.Sequence[float]: ...
|
|
@_typing.overload
|
|
def compute(self, img: UMat, winStride: cv2.typing.Size = ..., padding: cv2.typing.Size = ..., locations: _typing.Sequence[cv2.typing.Point] = ...) -> _typing.Sequence[float]: ...
|
|
|
|
@_typing.overload
|
|
def detect(self, img: cv2.typing.MatLike, hitThreshold: float = ..., winStride: cv2.typing.Size = ..., padding: cv2.typing.Size = ..., searchLocations: _typing.Sequence[cv2.typing.Point] = ...) -> tuple[_typing.Sequence[cv2.typing.Point], _typing.Sequence[float]]: ...
|
|
@_typing.overload
|
|
def detect(self, img: UMat, hitThreshold: float = ..., winStride: cv2.typing.Size = ..., padding: cv2.typing.Size = ..., searchLocations: _typing.Sequence[cv2.typing.Point] = ...) -> tuple[_typing.Sequence[cv2.typing.Point], _typing.Sequence[float]]: ...
|
|
|
|
@_typing.overload
|
|
def detectMultiScale(self, img: cv2.typing.MatLike, hitThreshold: float = ..., winStride: cv2.typing.Size = ..., padding: cv2.typing.Size = ..., scale: float = ..., groupThreshold: float = ..., useMeanshiftGrouping: bool = ...) -> tuple[_typing.Sequence[cv2.typing.Rect], _typing.Sequence[float]]: ...
|
|
@_typing.overload
|
|
def detectMultiScale(self, img: UMat, hitThreshold: float = ..., winStride: cv2.typing.Size = ..., padding: cv2.typing.Size = ..., scale: float = ..., groupThreshold: float = ..., useMeanshiftGrouping: bool = ...) -> tuple[_typing.Sequence[cv2.typing.Rect], _typing.Sequence[float]]: ...
|
|
|
|
@_typing.overload
|
|
def computeGradient(self, img: cv2.typing.MatLike, grad: cv2.typing.MatLike, angleOfs: cv2.typing.MatLike, paddingTL: cv2.typing.Size = ..., paddingBR: cv2.typing.Size = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def computeGradient(self, img: UMat, grad: UMat, angleOfs: UMat, paddingTL: cv2.typing.Size = ..., paddingBR: cv2.typing.Size = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@staticmethod
|
|
def getDefaultPeopleDetector() -> _typing.Sequence[float]: ...
|
|
|
|
@staticmethod
|
|
def getDaimlerPeopleDetector() -> _typing.Sequence[float]: ...
|
|
|
|
|
|
class QRCodeEncoder:
|
|
# Classes
|
|
class Params:
|
|
version: int
|
|
correction_level: QRCodeEncoder_CorrectionLevel
|
|
mode: QRCodeEncoder_EncodeMode
|
|
structure_number: int
|
|
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
|
|
|
|
# Functions
|
|
@classmethod
|
|
def create(cls, parameters: QRCodeEncoder.Params = ...) -> QRCodeEncoder: ...
|
|
|
|
@_typing.overload
|
|
def encode(self, encoded_info: str, qrcode: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def encode(self, encoded_info: str, qrcode: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def encodeStructuredAppend(self, encoded_info: str, qrcodes: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def encodeStructuredAppend(self, encoded_info: str, qrcodes: _typing.Sequence[UMat] | None = ...) -> _typing.Sequence[UMat]: ...
|
|
|
|
|
|
class QRCodeDetector(GraphicalCodeDetector):
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
def setEpsX(self, epsX: float) -> QRCodeDetector: ...
|
|
|
|
def setEpsY(self, epsY: float) -> QRCodeDetector: ...
|
|
|
|
def setUseAlignmentMarkers(self, useAlignmentMarkers: bool) -> QRCodeDetector: ...
|
|
|
|
@_typing.overload
|
|
def decodeCurved(self, img: cv2.typing.MatLike, points: cv2.typing.MatLike, straight_qrcode: cv2.typing.MatLike | None = ...) -> tuple[str, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def decodeCurved(self, img: UMat, points: UMat, straight_qrcode: UMat | None = ...) -> tuple[str, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def detectAndDecodeCurved(self, img: cv2.typing.MatLike, points: cv2.typing.MatLike | None = ..., straight_qrcode: cv2.typing.MatLike | None = ...) -> tuple[str, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def detectAndDecodeCurved(self, img: UMat, points: UMat | None = ..., straight_qrcode: UMat | None = ...) -> tuple[str, UMat, UMat]: ...
|
|
|
|
|
|
class GraphicalCodeDetector:
|
|
# Functions
|
|
@_typing.overload
|
|
def detect(self, img: cv2.typing.MatLike, points: cv2.typing.MatLike | None = ...) -> tuple[bool, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def detect(self, img: UMat, points: UMat | None = ...) -> tuple[bool, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def decode(self, img: cv2.typing.MatLike, points: cv2.typing.MatLike, straight_code: cv2.typing.MatLike | None = ...) -> tuple[str, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def decode(self, img: UMat, points: UMat, straight_code: UMat | None = ...) -> tuple[str, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def detectAndDecode(self, img: cv2.typing.MatLike, points: cv2.typing.MatLike | None = ..., straight_code: cv2.typing.MatLike | None = ...) -> tuple[str, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def detectAndDecode(self, img: UMat, points: UMat | None = ..., straight_code: UMat | None = ...) -> tuple[str, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def detectMulti(self, img: cv2.typing.MatLike, points: cv2.typing.MatLike | None = ...) -> tuple[bool, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def detectMulti(self, img: UMat, points: UMat | None = ...) -> tuple[bool, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def decodeMulti(self, img: cv2.typing.MatLike, points: cv2.typing.MatLike, straight_code: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> tuple[bool, _typing.Sequence[str], _typing.Sequence[cv2.typing.MatLike]]: ...
|
|
@_typing.overload
|
|
def decodeMulti(self, img: UMat, points: UMat, straight_code: _typing.Sequence[UMat] | None = ...) -> tuple[bool, _typing.Sequence[str], _typing.Sequence[UMat]]: ...
|
|
|
|
@_typing.overload
|
|
def detectAndDecodeMulti(self, img: cv2.typing.MatLike, points: cv2.typing.MatLike | None = ..., straight_code: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> tuple[bool, _typing.Sequence[str], cv2.typing.MatLike, _typing.Sequence[cv2.typing.MatLike]]: ...
|
|
@_typing.overload
|
|
def detectAndDecodeMulti(self, img: UMat, points: UMat | None = ..., straight_code: _typing.Sequence[UMat] | None = ...) -> tuple[bool, _typing.Sequence[str], UMat, _typing.Sequence[UMat]]: ...
|
|
|
|
|
|
class QRCodeDetectorAruco(GraphicalCodeDetector):
|
|
# Classes
|
|
class Params:
|
|
minModuleSizeInPyramid: float
|
|
maxRotation: float
|
|
maxModuleSizeMismatch: float
|
|
maxTimingPatternMismatch: float
|
|
maxPenalties: float
|
|
maxColorsMismatch: float
|
|
scaleTimingPatternScore: float
|
|
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
|
|
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, params: QRCodeDetectorAruco.Params) -> None: ...
|
|
|
|
def getDetectorParameters(self) -> QRCodeDetectorAruco.Params: ...
|
|
|
|
def setDetectorParameters(self, params: QRCodeDetectorAruco.Params) -> QRCodeDetectorAruco: ...
|
|
|
|
def getArucoParameters(self) -> cv2.aruco.DetectorParameters: ...
|
|
|
|
def setArucoParameters(self, params: cv2.aruco.DetectorParameters) -> None: ...
|
|
|
|
|
|
class FaceDetectorYN:
|
|
# Functions
|
|
def setInputSize(self, input_size: cv2.typing.Size) -> None: ...
|
|
|
|
def getInputSize(self) -> cv2.typing.Size: ...
|
|
|
|
def setScoreThreshold(self, score_threshold: float) -> None: ...
|
|
|
|
def getScoreThreshold(self) -> float: ...
|
|
|
|
def setNMSThreshold(self, nms_threshold: float) -> None: ...
|
|
|
|
def getNMSThreshold(self) -> float: ...
|
|
|
|
def setTopK(self, top_k: int) -> None: ...
|
|
|
|
def getTopK(self) -> int: ...
|
|
|
|
@_typing.overload
|
|
def detect(self, image: cv2.typing.MatLike, faces: cv2.typing.MatLike | None = ...) -> tuple[int, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def detect(self, image: UMat, faces: UMat | None = ...) -> tuple[int, UMat]: ...
|
|
|
|
@classmethod
|
|
@_typing.overload
|
|
def create(cls, model: str, config: str, input_size: cv2.typing.Size, score_threshold: float = ..., nms_threshold: float = ..., top_k: int = ..., backend_id: int = ..., target_id: int = ...) -> FaceDetectorYN: ...
|
|
@classmethod
|
|
@_typing.overload
|
|
def create(cls, framework: str, bufferModel: numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]], bufferConfig: numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]], input_size: cv2.typing.Size, score_threshold: float = ..., nms_threshold: float = ..., top_k: int = ..., backend_id: int = ..., target_id: int = ...) -> FaceDetectorYN: ...
|
|
|
|
|
|
class FaceRecognizerSF:
|
|
# Functions
|
|
@_typing.overload
|
|
def alignCrop(self, src_img: cv2.typing.MatLike, face_box: cv2.typing.MatLike, aligned_img: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def alignCrop(self, src_img: UMat, face_box: UMat, aligned_img: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def feature(self, aligned_img: cv2.typing.MatLike, face_feature: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def feature(self, aligned_img: UMat, face_feature: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def match(self, face_feature1: cv2.typing.MatLike, face_feature2: cv2.typing.MatLike, dis_type: int = ...) -> float: ...
|
|
@_typing.overload
|
|
def match(self, face_feature1: UMat, face_feature2: UMat, dis_type: int = ...) -> float: ...
|
|
|
|
@classmethod
|
|
def create(cls, model: str, config: str, backend_id: int = ..., target_id: int = ...) -> FaceRecognizerSF: ...
|
|
|
|
|
|
class Stitcher:
|
|
# Functions
|
|
@classmethod
|
|
def create(cls, mode: Stitcher_Mode = ...) -> Stitcher: ...
|
|
|
|
def registrationResol(self) -> float: ...
|
|
|
|
def setRegistrationResol(self, resol_mpx: float) -> None: ...
|
|
|
|
def seamEstimationResol(self) -> float: ...
|
|
|
|
def setSeamEstimationResol(self, resol_mpx: float) -> None: ...
|
|
|
|
def compositingResol(self) -> float: ...
|
|
|
|
def setCompositingResol(self, resol_mpx: float) -> None: ...
|
|
|
|
def panoConfidenceThresh(self) -> float: ...
|
|
|
|
def setPanoConfidenceThresh(self, conf_thresh: float) -> None: ...
|
|
|
|
def waveCorrection(self) -> bool: ...
|
|
|
|
def setWaveCorrection(self, flag: bool) -> None: ...
|
|
|
|
def interpolationFlags(self) -> InterpolationFlags: ...
|
|
|
|
def setInterpolationFlags(self, interp_flags: InterpolationFlags) -> None: ...
|
|
|
|
@_typing.overload
|
|
def estimateTransform(self, images: _typing.Sequence[cv2.typing.MatLike], masks: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> Stitcher_Status: ...
|
|
@_typing.overload
|
|
def estimateTransform(self, images: _typing.Sequence[UMat], masks: _typing.Sequence[UMat] | None = ...) -> Stitcher_Status: ...
|
|
|
|
@_typing.overload
|
|
def composePanorama(self, pano: cv2.typing.MatLike | None = ...) -> tuple[Stitcher_Status, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def composePanorama(self, pano: UMat | None = ...) -> tuple[Stitcher_Status, UMat]: ...
|
|
@_typing.overload
|
|
def composePanorama(self, images: _typing.Sequence[cv2.typing.MatLike], pano: cv2.typing.MatLike | None = ...) -> tuple[Stitcher_Status, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def composePanorama(self, images: _typing.Sequence[UMat], pano: UMat | None = ...) -> tuple[Stitcher_Status, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def stitch(self, images: _typing.Sequence[cv2.typing.MatLike], pano: cv2.typing.MatLike | None = ...) -> tuple[Stitcher_Status, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def stitch(self, images: _typing.Sequence[UMat], pano: UMat | None = ...) -> tuple[Stitcher_Status, UMat]: ...
|
|
@_typing.overload
|
|
def stitch(self, images: _typing.Sequence[cv2.typing.MatLike], masks: _typing.Sequence[cv2.typing.MatLike], pano: cv2.typing.MatLike | None = ...) -> tuple[Stitcher_Status, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def stitch(self, images: _typing.Sequence[UMat], masks: _typing.Sequence[UMat], pano: UMat | None = ...) -> tuple[Stitcher_Status, UMat]: ...
|
|
|
|
def workScale(self) -> float: ...
|
|
|
|
|
|
class PyRotationWarper:
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self, type: str, scale: float) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self) -> None: ...
|
|
|
|
@_typing.overload
|
|
def warpPoint(self, pt: cv2.typing.Point2f, K: cv2.typing.MatLike, R: cv2.typing.MatLike) -> cv2.typing.Point2f: ...
|
|
@_typing.overload
|
|
def warpPoint(self, pt: cv2.typing.Point2f, K: UMat, R: UMat) -> cv2.typing.Point2f: ...
|
|
|
|
@_typing.overload
|
|
def warpPointBackward(self, pt: cv2.typing.Point2f, K: cv2.typing.MatLike, R: cv2.typing.MatLike) -> cv2.typing.Point2f: ...
|
|
@_typing.overload
|
|
def warpPointBackward(self, pt: cv2.typing.Point2f, K: UMat, R: UMat) -> cv2.typing.Point2f: ...
|
|
@_typing.overload
|
|
def warpPointBackward(self, pt: cv2.typing.Point2f, K: cv2.typing.MatLike, R: cv2.typing.MatLike) -> cv2.typing.Point2f: ...
|
|
@_typing.overload
|
|
def warpPointBackward(self, pt: cv2.typing.Point2f, K: UMat, R: UMat) -> cv2.typing.Point2f: ...
|
|
|
|
@_typing.overload
|
|
def buildMaps(self, src_size: cv2.typing.Size, K: cv2.typing.MatLike, R: cv2.typing.MatLike, xmap: cv2.typing.MatLike | None = ..., ymap: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.Rect, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def buildMaps(self, src_size: cv2.typing.Size, K: UMat, R: UMat, xmap: UMat | None = ..., ymap: UMat | None = ...) -> tuple[cv2.typing.Rect, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def warp(self, src: cv2.typing.MatLike, K: cv2.typing.MatLike, R: cv2.typing.MatLike, interp_mode: int, border_mode: int, dst: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.Point, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def warp(self, src: UMat, K: UMat, R: UMat, interp_mode: int, border_mode: int, dst: UMat | None = ...) -> tuple[cv2.typing.Point, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def warpBackward(self, src: cv2.typing.MatLike, K: cv2.typing.MatLike, R: cv2.typing.MatLike, interp_mode: int, border_mode: int, dst_size: cv2.typing.Size, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def warpBackward(self, src: UMat, K: UMat, R: UMat, interp_mode: int, border_mode: int, dst_size: cv2.typing.Size, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def warpRoi(self, src_size: cv2.typing.Size, K: cv2.typing.MatLike, R: cv2.typing.MatLike) -> cv2.typing.Rect: ...
|
|
@_typing.overload
|
|
def warpRoi(self, src_size: cv2.typing.Size, K: UMat, R: UMat) -> cv2.typing.Rect: ...
|
|
|
|
def getScale(self) -> float: ...
|
|
|
|
def setScale(self, arg1: float) -> None: ...
|
|
|
|
|
|
class WarperCreator:
|
|
...
|
|
|
|
class BackgroundSubtractor(Algorithm):
|
|
# Functions
|
|
@_typing.overload
|
|
def apply(self, image: cv2.typing.MatLike, fgmask: cv2.typing.MatLike | None = ..., learningRate: float = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def apply(self, image: UMat, fgmask: UMat | None = ..., learningRate: float = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def getBackgroundImage(self, backgroundImage: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def getBackgroundImage(self, backgroundImage: UMat | None = ...) -> UMat: ...
|
|
|
|
|
|
class BackgroundSubtractorMOG2(BackgroundSubtractor):
|
|
# Functions
|
|
def getHistory(self) -> int: ...
|
|
|
|
def setHistory(self, history: int) -> None: ...
|
|
|
|
def getNMixtures(self) -> int: ...
|
|
|
|
def setNMixtures(self, nmixtures: int) -> None: ...
|
|
|
|
def getBackgroundRatio(self) -> float: ...
|
|
|
|
def setBackgroundRatio(self, ratio: float) -> None: ...
|
|
|
|
def getVarThreshold(self) -> float: ...
|
|
|
|
def setVarThreshold(self, varThreshold: float) -> None: ...
|
|
|
|
def getVarThresholdGen(self) -> float: ...
|
|
|
|
def setVarThresholdGen(self, varThresholdGen: float) -> None: ...
|
|
|
|
def getVarInit(self) -> float: ...
|
|
|
|
def setVarInit(self, varInit: float) -> None: ...
|
|
|
|
def getVarMin(self) -> float: ...
|
|
|
|
def setVarMin(self, varMin: float) -> None: ...
|
|
|
|
def getVarMax(self) -> float: ...
|
|
|
|
def setVarMax(self, varMax: float) -> None: ...
|
|
|
|
def getComplexityReductionThreshold(self) -> float: ...
|
|
|
|
def setComplexityReductionThreshold(self, ct: float) -> None: ...
|
|
|
|
def getDetectShadows(self) -> bool: ...
|
|
|
|
def setDetectShadows(self, detectShadows: bool) -> None: ...
|
|
|
|
def getShadowValue(self) -> int: ...
|
|
|
|
def setShadowValue(self, value: int) -> None: ...
|
|
|
|
def getShadowThreshold(self) -> float: ...
|
|
|
|
def setShadowThreshold(self, threshold: float) -> None: ...
|
|
|
|
@_typing.overload
|
|
def apply(self, image: cv2.typing.MatLike, fgmask: cv2.typing.MatLike | None = ..., learningRate: float = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def apply(self, image: UMat, fgmask: UMat | None = ..., learningRate: float = ...) -> UMat: ...
|
|
|
|
|
|
class BackgroundSubtractorKNN(BackgroundSubtractor):
|
|
# Functions
|
|
def getHistory(self) -> int: ...
|
|
|
|
def setHistory(self, history: int) -> None: ...
|
|
|
|
def getNSamples(self) -> int: ...
|
|
|
|
def setNSamples(self, _nN: int) -> None: ...
|
|
|
|
def getDist2Threshold(self) -> float: ...
|
|
|
|
def setDist2Threshold(self, _dist2Threshold: float) -> None: ...
|
|
|
|
def getkNNSamples(self) -> int: ...
|
|
|
|
def setkNNSamples(self, _nkNN: int) -> None: ...
|
|
|
|
def getDetectShadows(self) -> bool: ...
|
|
|
|
def setDetectShadows(self, detectShadows: bool) -> None: ...
|
|
|
|
def getShadowValue(self) -> int: ...
|
|
|
|
def setShadowValue(self, value: int) -> None: ...
|
|
|
|
def getShadowThreshold(self) -> float: ...
|
|
|
|
def setShadowThreshold(self, threshold: float) -> None: ...
|
|
|
|
|
|
class KalmanFilter:
|
|
statePre: cv2.typing.MatLike
|
|
statePost: cv2.typing.MatLike
|
|
transitionMatrix: cv2.typing.MatLike
|
|
controlMatrix: cv2.typing.MatLike
|
|
measurementMatrix: cv2.typing.MatLike
|
|
processNoiseCov: cv2.typing.MatLike
|
|
measurementNoiseCov: cv2.typing.MatLike
|
|
errorCovPre: cv2.typing.MatLike
|
|
gain: cv2.typing.MatLike
|
|
errorCovPost: cv2.typing.MatLike
|
|
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, dynamParams: int, measureParams: int, controlParams: int = ..., type: int = ...) -> None: ...
|
|
|
|
def predict(self, control: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
|
|
def correct(self, measurement: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
|
|
|
|
|
class DenseOpticalFlow(Algorithm):
|
|
# Functions
|
|
@_typing.overload
|
|
def calc(self, I0: cv2.typing.MatLike, I1: cv2.typing.MatLike, flow: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def calc(self, I0: UMat, I1: UMat, flow: UMat) -> UMat: ...
|
|
|
|
def collectGarbage(self) -> None: ...
|
|
|
|
|
|
class SparseOpticalFlow(Algorithm):
|
|
# Functions
|
|
@_typing.overload
|
|
def calc(self, 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 = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def calc(self, prevImg: UMat, nextImg: UMat, prevPts: UMat, nextPts: UMat, status: UMat | None = ..., err: UMat | None = ...) -> tuple[UMat, UMat, UMat]: ...
|
|
|
|
|
|
class FarnebackOpticalFlow(DenseOpticalFlow):
|
|
# Functions
|
|
def getNumLevels(self) -> int: ...
|
|
|
|
def setNumLevels(self, numLevels: int) -> None: ...
|
|
|
|
def getPyrScale(self) -> float: ...
|
|
|
|
def setPyrScale(self, pyrScale: float) -> None: ...
|
|
|
|
def getFastPyramids(self) -> bool: ...
|
|
|
|
def setFastPyramids(self, fastPyramids: bool) -> None: ...
|
|
|
|
def getWinSize(self) -> int: ...
|
|
|
|
def setWinSize(self, winSize: int) -> None: ...
|
|
|
|
def getNumIters(self) -> int: ...
|
|
|
|
def setNumIters(self, numIters: int) -> None: ...
|
|
|
|
def getPolyN(self) -> int: ...
|
|
|
|
def setPolyN(self, polyN: int) -> None: ...
|
|
|
|
def getPolySigma(self) -> float: ...
|
|
|
|
def setPolySigma(self, polySigma: float) -> None: ...
|
|
|
|
def getFlags(self) -> int: ...
|
|
|
|
def setFlags(self, flags: int) -> None: ...
|
|
|
|
@classmethod
|
|
def create(cls, numLevels: int = ..., pyrScale: float = ..., fastPyramids: bool = ..., winSize: int = ..., numIters: int = ..., polyN: int = ..., polySigma: float = ..., flags: int = ...) -> FarnebackOpticalFlow: ...
|
|
|
|
|
|
class VariationalRefinement(DenseOpticalFlow):
|
|
# Functions
|
|
@_typing.overload
|
|
def calcUV(self, I0: cv2.typing.MatLike, I1: cv2.typing.MatLike, flow_u: cv2.typing.MatLike, flow_v: cv2.typing.MatLike) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def calcUV(self, I0: UMat, I1: UMat, flow_u: UMat, flow_v: UMat) -> tuple[UMat, UMat]: ...
|
|
|
|
def getFixedPointIterations(self) -> int: ...
|
|
|
|
def setFixedPointIterations(self, val: int) -> None: ...
|
|
|
|
def getSorIterations(self) -> int: ...
|
|
|
|
def setSorIterations(self, val: int) -> None: ...
|
|
|
|
def getOmega(self) -> float: ...
|
|
|
|
def setOmega(self, val: float) -> None: ...
|
|
|
|
def getAlpha(self) -> float: ...
|
|
|
|
def setAlpha(self, val: float) -> None: ...
|
|
|
|
def getDelta(self) -> float: ...
|
|
|
|
def setDelta(self, val: float) -> None: ...
|
|
|
|
def getGamma(self) -> float: ...
|
|
|
|
def setGamma(self, val: float) -> None: ...
|
|
|
|
def getEpsilon(self) -> float: ...
|
|
|
|
def setEpsilon(self, val: float) -> None: ...
|
|
|
|
@classmethod
|
|
def create(cls) -> VariationalRefinement: ...
|
|
|
|
|
|
class DISOpticalFlow(DenseOpticalFlow):
|
|
# Functions
|
|
def getFinestScale(self) -> int: ...
|
|
|
|
def setFinestScale(self, val: int) -> None: ...
|
|
|
|
def getPatchSize(self) -> int: ...
|
|
|
|
def setPatchSize(self, val: int) -> None: ...
|
|
|
|
def getPatchStride(self) -> int: ...
|
|
|
|
def setPatchStride(self, val: int) -> None: ...
|
|
|
|
def getGradientDescentIterations(self) -> int: ...
|
|
|
|
def setGradientDescentIterations(self, val: int) -> None: ...
|
|
|
|
def getVariationalRefinementIterations(self) -> int: ...
|
|
|
|
def setVariationalRefinementIterations(self, val: int) -> None: ...
|
|
|
|
def getVariationalRefinementAlpha(self) -> float: ...
|
|
|
|
def setVariationalRefinementAlpha(self, val: float) -> None: ...
|
|
|
|
def getVariationalRefinementDelta(self) -> float: ...
|
|
|
|
def setVariationalRefinementDelta(self, val: float) -> None: ...
|
|
|
|
def getVariationalRefinementGamma(self) -> float: ...
|
|
|
|
def setVariationalRefinementGamma(self, val: float) -> None: ...
|
|
|
|
def getVariationalRefinementEpsilon(self) -> float: ...
|
|
|
|
def setVariationalRefinementEpsilon(self, val: float) -> None: ...
|
|
|
|
def getUseMeanNormalization(self) -> bool: ...
|
|
|
|
def setUseMeanNormalization(self, val: bool) -> None: ...
|
|
|
|
def getUseSpatialPropagation(self) -> bool: ...
|
|
|
|
def setUseSpatialPropagation(self, val: bool) -> None: ...
|
|
|
|
@classmethod
|
|
def create(cls, preset: int = ...) -> DISOpticalFlow: ...
|
|
|
|
|
|
class SparsePyrLKOpticalFlow(SparseOpticalFlow):
|
|
# Functions
|
|
def getWinSize(self) -> cv2.typing.Size: ...
|
|
|
|
def setWinSize(self, winSize: cv2.typing.Size) -> None: ...
|
|
|
|
def getMaxLevel(self) -> int: ...
|
|
|
|
def setMaxLevel(self, maxLevel: int) -> None: ...
|
|
|
|
def getTermCriteria(self) -> cv2.typing.TermCriteria: ...
|
|
|
|
def setTermCriteria(self, crit: cv2.typing.TermCriteria) -> None: ...
|
|
|
|
def getFlags(self) -> int: ...
|
|
|
|
def setFlags(self, flags: int) -> None: ...
|
|
|
|
def getMinEigThreshold(self) -> float: ...
|
|
|
|
def setMinEigThreshold(self, minEigThreshold: float) -> None: ...
|
|
|
|
@classmethod
|
|
def create(cls, winSize: cv2.typing.Size = ..., maxLevel: int = ..., crit: cv2.typing.TermCriteria = ..., flags: int = ..., minEigThreshold: float = ...) -> SparsePyrLKOpticalFlow: ...
|
|
|
|
|
|
class Tracker:
|
|
# Functions
|
|
@_typing.overload
|
|
def init(self, image: cv2.typing.MatLike, boundingBox: cv2.typing.Rect) -> None: ...
|
|
@_typing.overload
|
|
def init(self, image: UMat, boundingBox: cv2.typing.Rect) -> None: ...
|
|
|
|
@_typing.overload
|
|
def update(self, image: cv2.typing.MatLike) -> tuple[bool, cv2.typing.Rect]: ...
|
|
@_typing.overload
|
|
def update(self, image: UMat) -> tuple[bool, cv2.typing.Rect]: ...
|
|
|
|
|
|
class TrackerMIL(Tracker):
|
|
# Classes
|
|
class Params:
|
|
samplerInitInRadius: float
|
|
samplerInitMaxNegNum: int
|
|
samplerSearchWinSize: float
|
|
samplerTrackInRadius: float
|
|
samplerTrackMaxPosNum: int
|
|
samplerTrackMaxNegNum: int
|
|
featureSetNumFeatures: int
|
|
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
|
|
|
|
# Functions
|
|
@classmethod
|
|
def create(cls, parameters: TrackerMIL.Params = ...) -> TrackerMIL: ...
|
|
|
|
|
|
class TrackerGOTURN(Tracker):
|
|
# Classes
|
|
class Params:
|
|
modelTxt: str
|
|
modelBin: str
|
|
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
|
|
|
|
# Functions
|
|
@classmethod
|
|
def create(cls, parameters: TrackerGOTURN.Params = ...) -> TrackerGOTURN: ...
|
|
|
|
|
|
class TrackerDaSiamRPN(Tracker):
|
|
# Classes
|
|
class Params:
|
|
model: str
|
|
kernel_cls1: str
|
|
kernel_r1: str
|
|
backend: int
|
|
target: int
|
|
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
|
|
|
|
# Functions
|
|
@classmethod
|
|
def create(cls, parameters: TrackerDaSiamRPN.Params = ...) -> TrackerDaSiamRPN: ...
|
|
|
|
def getTrackingScore(self) -> float: ...
|
|
|
|
|
|
class TrackerNano(Tracker):
|
|
# Classes
|
|
class Params:
|
|
backbone: str
|
|
neckhead: str
|
|
backend: int
|
|
target: int
|
|
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
|
|
|
|
# Functions
|
|
@classmethod
|
|
def create(cls, parameters: TrackerNano.Params = ...) -> TrackerNano: ...
|
|
|
|
def getTrackingScore(self) -> float: ...
|
|
|
|
|
|
class TrackerVit(Tracker):
|
|
# Classes
|
|
class Params:
|
|
net: str
|
|
backend: int
|
|
target: int
|
|
meanvalue: cv2.typing.Scalar
|
|
stdvalue: cv2.typing.Scalar
|
|
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
|
|
|
|
# Functions
|
|
@classmethod
|
|
def create(cls, parameters: TrackerVit.Params = ...) -> TrackerVit: ...
|
|
|
|
def getTrackingScore(self) -> float: ...
|
|
|
|
|
|
class GArrayDesc:
|
|
...
|
|
|
|
class GComputation:
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self, ins: cv2.typing.GProtoInputArgs, outs: cv2.typing.GProtoOutputArgs) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, in_: GMat, out: GMat) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, in_: GMat, out: GScalar) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, in1: GMat, in2: GMat, out: GMat) -> None: ...
|
|
|
|
def apply(self, callback: cv2.typing.ExtractArgsCallback, args: _typing.Sequence[GCompileArg] = ...) -> _typing.Sequence[cv2.typing.GRunArg]: ...
|
|
|
|
@_typing.overload
|
|
def compileStreaming(self, in_metas: _typing.Sequence[cv2.typing.GMetaArg], args: _typing.Sequence[GCompileArg] = ...) -> GStreamingCompiled: ...
|
|
@_typing.overload
|
|
def compileStreaming(self, args: _typing.Sequence[GCompileArg] = ...) -> GStreamingCompiled: ...
|
|
@_typing.overload
|
|
def compileStreaming(self, callback: cv2.typing.ExtractMetaCallback, args: _typing.Sequence[GCompileArg] = ...) -> GStreamingCompiled: ...
|
|
|
|
|
|
class GFrame:
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
|
|
class GKernelPackage:
|
|
# Functions
|
|
def size(self) -> int: ...
|
|
|
|
|
|
class GMat:
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, m: cv2.typing.MatLike) -> None: ...
|
|
|
|
|
|
class GMatDesc:
|
|
@property
|
|
def depth(self) -> int: ...
|
|
@property
|
|
def chan(self) -> int: ...
|
|
@property
|
|
def size(self) -> cv2.typing.Size: ...
|
|
@property
|
|
def planar(self) -> bool: ...
|
|
@property
|
|
def dims(self) -> _typing.Sequence[int]: ...
|
|
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self, d: int, c: int, s: cv2.typing.Size, p: bool = ...) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, d: int, dd: _typing.Sequence[int]) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, d: int, dd: _typing.Sequence[int]) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self) -> None: ...
|
|
|
|
@_typing.overload
|
|
def withSizeDelta(self, delta: cv2.typing.Size) -> GMatDesc: ...
|
|
@_typing.overload
|
|
def withSizeDelta(self, dx: int, dy: int) -> GMatDesc: ...
|
|
|
|
def withSize(self, sz: cv2.typing.Size) -> GMatDesc: ...
|
|
|
|
def withDepth(self, ddepth: int) -> GMatDesc: ...
|
|
|
|
def withType(self, ddepth: int, dchan: int) -> GMatDesc: ...
|
|
|
|
@_typing.overload
|
|
def asPlanar(self) -> GMatDesc: ...
|
|
@_typing.overload
|
|
def asPlanar(self, planes: int) -> GMatDesc: ...
|
|
|
|
def asInterleaved(self) -> GMatDesc: ...
|
|
|
|
|
|
class GOpaqueDesc:
|
|
...
|
|
|
|
class GScalar:
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, s: cv2.typing.Scalar) -> None: ...
|
|
|
|
|
|
class GScalarDesc:
|
|
...
|
|
|
|
class GStreamingCompiled:
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
def setSource(self, callback: cv2.typing.ExtractArgsCallback) -> None: ...
|
|
|
|
def start(self) -> None: ...
|
|
|
|
def pull(self) -> tuple[bool, _typing.Sequence[cv2.typing.GRunArg] | _typing.Sequence[cv2.typing.GOptRunArg]]: ...
|
|
|
|
def stop(self) -> None: ...
|
|
|
|
def running(self) -> bool: ...
|
|
|
|
|
|
class GOpaqueT:
|
|
# Functions
|
|
def __init__(self, type: cv2.gapi.ArgType) -> None: ...
|
|
|
|
def type(self) -> cv2.gapi.ArgType: ...
|
|
|
|
|
|
class GArrayT:
|
|
# Functions
|
|
def __init__(self, type: cv2.gapi.ArgType) -> None: ...
|
|
|
|
def type(self) -> cv2.gapi.ArgType: ...
|
|
|
|
|
|
class GCompileArg:
|
|
# Functions
|
|
@_typing.overload
|
|
def __init__(self, arg: GKernelPackage) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, arg: cv2.gapi.GNetPackage) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, arg: cv2.gapi.streaming.queue_capacity) -> None: ...
|
|
@_typing.overload
|
|
def __init__(self, arg: cv2.gapi.ot.ObjectTrackerParams) -> None: ...
|
|
|
|
|
|
class GInferInputs:
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
@_typing.overload
|
|
def setInput(self, name: str, value: GMat) -> GInferInputs: ...
|
|
@_typing.overload
|
|
def setInput(self, name: str, value: GFrame) -> GInferInputs: ...
|
|
|
|
|
|
class GInferListInputs:
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
@_typing.overload
|
|
def setInput(self, name: str, value: GArrayT) -> GInferListInputs: ...
|
|
@_typing.overload
|
|
def setInput(self, name: str, value: GArrayT) -> GInferListInputs: ...
|
|
|
|
|
|
class GInferOutputs:
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
def at(self, name: str) -> GMat: ...
|
|
|
|
|
|
class GInferListOutputs:
|
|
# Functions
|
|
def __init__(self) -> None: ...
|
|
|
|
def at(self, name: str) -> GArrayT: ...
|
|
|
|
|
|
class error(Exception):
|
|
code: int
|
|
err: str
|
|
file: str
|
|
func: str
|
|
line: int
|
|
msg: str
|
|
|
|
|
|
# Functions
|
|
@_typing.overload
|
|
def CamShift(probImage: cv2.typing.MatLike, window: cv2.typing.Rect, criteria: cv2.typing.TermCriteria) -> tuple[cv2.typing.RotatedRect, cv2.typing.Rect]: ...
|
|
@_typing.overload
|
|
def CamShift(probImage: UMat, window: cv2.typing.Rect, criteria: cv2.typing.TermCriteria) -> tuple[cv2.typing.RotatedRect, cv2.typing.Rect]: ...
|
|
|
|
@_typing.overload
|
|
def Canny(image: cv2.typing.MatLike, threshold1: float, threshold2: float, edges: cv2.typing.MatLike | None = ..., apertureSize: int = ..., L2gradient: bool = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def Canny(image: UMat, threshold1: float, threshold2: float, edges: UMat | None = ..., apertureSize: int = ..., L2gradient: bool = ...) -> UMat: ...
|
|
@_typing.overload
|
|
def Canny(dx: cv2.typing.MatLike, dy: cv2.typing.MatLike, threshold1: float, threshold2: float, edges: cv2.typing.MatLike | None = ..., L2gradient: bool = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def Canny(dx: UMat, dy: UMat, threshold1: float, threshold2: float, edges: UMat | None = ..., L2gradient: bool = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def EMD(signature1: cv2.typing.MatLike, signature2: cv2.typing.MatLike, distType: int, cost: cv2.typing.MatLike | None = ..., lowerBound: float | None = ..., flow: cv2.typing.MatLike | None = ...) -> tuple[float, float, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def EMD(signature1: UMat, signature2: UMat, distType: int, cost: UMat | None = ..., lowerBound: float | None = ..., flow: UMat | None = ...) -> tuple[float, float, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def GaussianBlur(src: cv2.typing.MatLike, ksize: cv2.typing.Size, sigmaX: float, dst: cv2.typing.MatLike | None = ..., sigmaY: float = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def GaussianBlur(src: UMat, ksize: cv2.typing.Size, sigmaX: float, dst: UMat | None = ..., sigmaY: float = ..., borderType: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def HoughCircles(image: cv2.typing.MatLike, method: int, dp: float, minDist: float, circles: cv2.typing.MatLike | None = ..., param1: float = ..., param2: float = ..., minRadius: int = ..., maxRadius: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def HoughCircles(image: UMat, method: int, dp: float, minDist: float, circles: UMat | None = ..., param1: float = ..., param2: float = ..., minRadius: int = ..., maxRadius: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def HoughLines(image: cv2.typing.MatLike, rho: float, theta: float, threshold: int, lines: cv2.typing.MatLike | None = ..., srn: float = ..., stn: float = ..., min_theta: float = ..., max_theta: float = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def HoughLines(image: UMat, rho: float, theta: float, threshold: int, lines: UMat | None = ..., srn: float = ..., stn: float = ..., min_theta: float = ..., max_theta: float = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def HoughLinesP(image: cv2.typing.MatLike, rho: float, theta: float, threshold: int, lines: cv2.typing.MatLike | None = ..., minLineLength: float = ..., maxLineGap: float = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def HoughLinesP(image: UMat, rho: float, theta: float, threshold: int, lines: UMat | None = ..., minLineLength: float = ..., maxLineGap: float = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def HoughLinesPointSet(point: cv2.typing.MatLike, lines_max: int, threshold: int, min_rho: float, max_rho: float, rho_step: float, min_theta: float, max_theta: float, theta_step: float, lines: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def HoughLinesPointSet(point: UMat, lines_max: int, threshold: int, min_rho: float, max_rho: float, rho_step: float, min_theta: float, max_theta: float, theta_step: float, lines: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def HoughLinesWithAccumulator(image: cv2.typing.MatLike, rho: float, theta: float, threshold: int, lines: cv2.typing.MatLike | None = ..., srn: float = ..., stn: float = ..., min_theta: float = ..., max_theta: float = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def HoughLinesWithAccumulator(image: UMat, rho: float, theta: float, threshold: int, lines: UMat | None = ..., srn: float = ..., stn: float = ..., min_theta: float = ..., max_theta: float = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def HuMoments(m: cv2.typing.Moments, hu: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def HuMoments(m: cv2.typing.Moments, hu: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def LUT(src: cv2.typing.MatLike, lut: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def LUT(src: UMat, lut: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def Laplacian(src: cv2.typing.MatLike, ddepth: int, dst: cv2.typing.MatLike | None = ..., ksize: int = ..., scale: float = ..., delta: float = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def Laplacian(src: UMat, ddepth: int, dst: UMat | None = ..., ksize: int = ..., scale: float = ..., delta: float = ..., borderType: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def Mahalanobis(v1: cv2.typing.MatLike, v2: cv2.typing.MatLike, icovar: cv2.typing.MatLike) -> float: ...
|
|
@_typing.overload
|
|
def Mahalanobis(v1: UMat, v2: UMat, icovar: UMat) -> float: ...
|
|
|
|
@_typing.overload
|
|
def PCABackProject(data: cv2.typing.MatLike, mean: cv2.typing.MatLike, eigenvectors: cv2.typing.MatLike, result: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def PCABackProject(data: UMat, mean: UMat, eigenvectors: UMat, result: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def PCACompute(data: cv2.typing.MatLike, mean: cv2.typing.MatLike, eigenvectors: cv2.typing.MatLike | None = ..., maxComponents: int = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def PCACompute(data: UMat, mean: UMat, eigenvectors: UMat | None = ..., maxComponents: int = ...) -> tuple[UMat, UMat]: ...
|
|
@_typing.overload
|
|
def PCACompute(data: cv2.typing.MatLike, mean: cv2.typing.MatLike, retainedVariance: float, eigenvectors: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def PCACompute(data: UMat, mean: UMat, retainedVariance: float, eigenvectors: UMat | None = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def PCACompute2(data: cv2.typing.MatLike, mean: cv2.typing.MatLike, eigenvectors: cv2.typing.MatLike | None = ..., eigenvalues: cv2.typing.MatLike | None = ..., maxComponents: int = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def PCACompute2(data: UMat, mean: UMat, eigenvectors: UMat | None = ..., eigenvalues: UMat | None = ..., maxComponents: int = ...) -> tuple[UMat, UMat, UMat]: ...
|
|
@_typing.overload
|
|
def PCACompute2(data: cv2.typing.MatLike, mean: cv2.typing.MatLike, retainedVariance: float, eigenvectors: cv2.typing.MatLike | None = ..., eigenvalues: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def PCACompute2(data: UMat, mean: UMat, retainedVariance: float, eigenvectors: UMat | None = ..., eigenvalues: UMat | None = ...) -> tuple[UMat, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def PCAProject(data: cv2.typing.MatLike, mean: cv2.typing.MatLike, eigenvectors: cv2.typing.MatLike, result: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def PCAProject(data: UMat, mean: UMat, eigenvectors: UMat, result: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def PSNR(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, R: float = ...) -> float: ...
|
|
@_typing.overload
|
|
def PSNR(src1: UMat, src2: UMat, R: float = ...) -> float: ...
|
|
|
|
@_typing.overload
|
|
def RQDecomp3x3(src: cv2.typing.MatLike, mtxR: cv2.typing.MatLike | None = ..., mtxQ: cv2.typing.MatLike | None = ..., Qx: cv2.typing.MatLike | None = ..., Qy: cv2.typing.MatLike | None = ..., Qz: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.Vec3d, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
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@_typing.overload
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def RQDecomp3x3(src: UMat, mtxR: UMat | None = ..., mtxQ: UMat | None = ..., Qx: UMat | None = ..., Qy: UMat | None = ..., Qz: UMat | None = ...) -> tuple[cv2.typing.Vec3d, UMat, UMat, UMat, UMat, UMat]: ...
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|
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@_typing.overload
|
|
def Rodrigues(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., jacobian: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
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@_typing.overload
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def Rodrigues(src: UMat, dst: UMat | None = ..., jacobian: UMat | None = ...) -> tuple[UMat, UMat]: ...
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|
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@_typing.overload
|
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def SVBackSubst(w: cv2.typing.MatLike, u: cv2.typing.MatLike, vt: cv2.typing.MatLike, rhs: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
|
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def SVBackSubst(w: UMat, u: UMat, vt: UMat, rhs: UMat, dst: UMat | None = ...) -> UMat: ...
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@_typing.overload
|
|
def SVDecomp(src: cv2.typing.MatLike, w: cv2.typing.MatLike | None = ..., u: cv2.typing.MatLike | None = ..., vt: cv2.typing.MatLike | None = ..., flags: int = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
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@_typing.overload
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def SVDecomp(src: UMat, w: UMat | None = ..., u: UMat | None = ..., vt: UMat | None = ..., flags: int = ...) -> tuple[UMat, UMat, UMat]: ...
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@_typing.overload
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def Scharr(src: cv2.typing.MatLike, ddepth: int, dx: int, dy: int, dst: cv2.typing.MatLike | None = ..., scale: float = ..., delta: float = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
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def Scharr(src: UMat, ddepth: int, dx: int, dy: int, dst: UMat | None = ..., scale: float = ..., delta: float = ..., borderType: int = ...) -> UMat: ...
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@_typing.overload
|
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def Sobel(src: cv2.typing.MatLike, ddepth: int, dx: int, dy: int, dst: cv2.typing.MatLike | None = ..., ksize: int = ..., scale: float = ..., delta: float = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
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def Sobel(src: UMat, ddepth: int, dx: int, dy: int, dst: UMat | None = ..., ksize: int = ..., scale: float = ..., delta: float = ..., borderType: int = ...) -> UMat: ...
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@_typing.overload
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def absdiff(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
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def absdiff(src1: UMat, src2: UMat, dst: UMat | None = ...) -> UMat: ...
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@_typing.overload
|
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def accumulate(src: cv2.typing.MatLike, dst: cv2.typing.MatLike, mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
|
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def accumulate(src: UMat, dst: UMat, mask: UMat | None = ...) -> UMat: ...
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@_typing.overload
|
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def accumulateProduct(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike, mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
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def accumulateProduct(src1: UMat, src2: UMat, dst: UMat, mask: UMat | None = ...) -> UMat: ...
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@_typing.overload
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def accumulateSquare(src: cv2.typing.MatLike, dst: cv2.typing.MatLike, mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
|
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def accumulateSquare(src: UMat, dst: UMat, mask: UMat | None = ...) -> UMat: ...
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@_typing.overload
|
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def accumulateWeighted(src: cv2.typing.MatLike, dst: cv2.typing.MatLike, alpha: float, mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
|
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def accumulateWeighted(src: UMat, dst: UMat, alpha: float, mask: UMat | None = ...) -> UMat: ...
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@_typing.overload
|
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def adaptiveThreshold(src: cv2.typing.MatLike, maxValue: float, adaptiveMethod: int, thresholdType: int, blockSize: int, C: float, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
|
|
def adaptiveThreshold(src: UMat, maxValue: float, adaptiveMethod: int, thresholdType: int, blockSize: int, C: float, dst: UMat | None = ...) -> UMat: ...
|
|
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@_typing.overload
|
|
def add(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., mask: cv2.typing.MatLike | None = ..., dtype: int = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
|
|
def add(src1: UMat, src2: UMat, dst: UMat | None = ..., mask: UMat | None = ..., dtype: int = ...) -> UMat: ...
|
|
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|
def addText(img: cv2.typing.MatLike, text: str, org: cv2.typing.Point, nameFont: str, pointSize: int = ..., color: cv2.typing.Scalar = ..., weight: int = ..., style: int = ..., spacing: int = ...) -> None: ...
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@_typing.overload
|
|
def addWeighted(src1: cv2.typing.MatLike, alpha: float, src2: cv2.typing.MatLike, beta: float, gamma: float, dst: cv2.typing.MatLike | None = ..., dtype: int = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
|
|
def addWeighted(src1: UMat, alpha: float, src2: UMat, beta: float, gamma: float, dst: UMat | None = ..., dtype: int = ...) -> UMat: ...
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@_typing.overload
|
|
def applyColorMap(src: cv2.typing.MatLike, colormap: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
|
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def applyColorMap(src: UMat, colormap: int, dst: UMat | None = ...) -> UMat: ...
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@_typing.overload
|
|
def applyColorMap(src: cv2.typing.MatLike, userColor: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
|
|
def applyColorMap(src: UMat, userColor: UMat, dst: UMat | None = ...) -> UMat: ...
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@_typing.overload
|
|
def approxPolyDP(curve: cv2.typing.MatLike, epsilon: float, closed: bool, approxCurve: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
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@_typing.overload
|
|
def approxPolyDP(curve: UMat, epsilon: float, closed: bool, approxCurve: UMat | None = ...) -> UMat: ...
|
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@_typing.overload
|
|
def arcLength(curve: cv2.typing.MatLike, closed: bool) -> float: ...
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@_typing.overload
|
|
def arcLength(curve: UMat, closed: bool) -> float: ...
|
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@_typing.overload
|
|
def arrowedLine(img: cv2.typing.MatLike, pt1: cv2.typing.Point, pt2: cv2.typing.Point, color: cv2.typing.Scalar, thickness: int = ..., line_type: int = ..., shift: int = ..., tipLength: float = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
|
|
def arrowedLine(img: UMat, pt1: cv2.typing.Point, pt2: cv2.typing.Point, color: cv2.typing.Scalar, thickness: int = ..., line_type: int = ..., shift: int = ..., tipLength: float = ...) -> UMat: ...
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@_typing.overload
|
|
def batchDistance(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, dtype: int, dist: cv2.typing.MatLike | None = ..., nidx: cv2.typing.MatLike | None = ..., normType: int = ..., K: int = ..., mask: cv2.typing.MatLike | None = ..., update: int = ..., crosscheck: bool = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
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@_typing.overload
|
|
def batchDistance(src1: UMat, src2: UMat, dtype: int, dist: UMat | None = ..., nidx: UMat | None = ..., normType: int = ..., K: int = ..., mask: UMat | None = ..., update: int = ..., crosscheck: bool = ...) -> tuple[UMat, UMat]: ...
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@_typing.overload
|
|
def bilateralFilter(src: cv2.typing.MatLike, d: int, sigmaColor: float, sigmaSpace: float, dst: cv2.typing.MatLike | None = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
|
|
def bilateralFilter(src: UMat, d: int, sigmaColor: float, sigmaSpace: float, dst: UMat | None = ..., borderType: int = ...) -> UMat: ...
|
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@_typing.overload
|
|
def bitwise_and(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
|
|
def bitwise_and(src1: UMat, src2: UMat, dst: UMat | None = ..., mask: UMat | None = ...) -> UMat: ...
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@_typing.overload
|
|
def bitwise_not(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
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@_typing.overload
|
|
def bitwise_not(src: UMat, dst: UMat | None = ..., mask: UMat | None = ...) -> UMat: ...
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@_typing.overload
|
|
def bitwise_or(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
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@_typing.overload
|
|
def bitwise_or(src1: UMat, src2: UMat, dst: UMat | None = ..., mask: UMat | None = ...) -> UMat: ...
|
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@_typing.overload
|
|
def bitwise_xor(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
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@_typing.overload
|
|
def bitwise_xor(src1: UMat, src2: UMat, dst: UMat | None = ..., mask: UMat | None = ...) -> UMat: ...
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@_typing.overload
|
|
def blendLinear(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, weights1: cv2.typing.MatLike, weights2: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def blendLinear(src1: UMat, src2: UMat, weights1: UMat, weights2: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
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|
@_typing.overload
|
|
def blur(src: cv2.typing.MatLike, ksize: cv2.typing.Size, dst: cv2.typing.MatLike | None = ..., anchor: cv2.typing.Point = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def blur(src: UMat, ksize: cv2.typing.Size, dst: UMat | None = ..., anchor: cv2.typing.Point = ..., borderType: int = ...) -> UMat: ...
|
|
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|
def borderInterpolate(p: int, len: int, borderType: int) -> int: ...
|
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@_typing.overload
|
|
def boundingRect(array: cv2.typing.MatLike) -> cv2.typing.Rect: ...
|
|
@_typing.overload
|
|
def boundingRect(array: UMat) -> cv2.typing.Rect: ...
|
|
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|
@_typing.overload
|
|
def boxFilter(src: cv2.typing.MatLike, ddepth: int, ksize: cv2.typing.Size, dst: cv2.typing.MatLike | None = ..., anchor: cv2.typing.Point = ..., normalize: bool = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def boxFilter(src: UMat, ddepth: int, ksize: cv2.typing.Size, dst: UMat | None = ..., anchor: cv2.typing.Point = ..., normalize: bool = ..., borderType: int = ...) -> UMat: ...
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|
@_typing.overload
|
|
def boxPoints(box: cv2.typing.RotatedRect, points: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def boxPoints(box: cv2.typing.RotatedRect, points: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def broadcast(src: cv2.typing.MatLike, shape: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def broadcast(src: UMat, shape: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def buildOpticalFlowPyramid(img: cv2.typing.MatLike, winSize: cv2.typing.Size, maxLevel: int, pyramid: _typing.Sequence[cv2.typing.MatLike] | None = ..., withDerivatives: bool = ..., pyrBorder: int = ..., derivBorder: int = ..., tryReuseInputImage: bool = ...) -> tuple[int, _typing.Sequence[cv2.typing.MatLike]]: ...
|
|
@_typing.overload
|
|
def buildOpticalFlowPyramid(img: UMat, winSize: cv2.typing.Size, maxLevel: int, pyramid: _typing.Sequence[UMat] | None = ..., withDerivatives: bool = ..., pyrBorder: int = ..., derivBorder: int = ..., tryReuseInputImage: bool = ...) -> tuple[int, _typing.Sequence[UMat]]: ...
|
|
|
|
@_typing.overload
|
|
def calcBackProject(images: _typing.Sequence[cv2.typing.MatLike], channels: _typing.Sequence[int], hist: cv2.typing.MatLike, ranges: _typing.Sequence[float], scale: float, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def calcBackProject(images: _typing.Sequence[UMat], channels: _typing.Sequence[int], hist: UMat, ranges: _typing.Sequence[float], scale: float, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def calcCovarMatrix(samples: cv2.typing.MatLike, mean: cv2.typing.MatLike, flags: int, covar: cv2.typing.MatLike | None = ..., ctype: int = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def calcCovarMatrix(samples: UMat, mean: UMat, flags: int, covar: UMat | None = ..., ctype: int = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def calcHist(images: _typing.Sequence[cv2.typing.MatLike], channels: _typing.Sequence[int], mask: cv2.typing.MatLike | None, histSize: _typing.Sequence[int], ranges: _typing.Sequence[float], hist: cv2.typing.MatLike | None = ..., accumulate: bool = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def calcHist(images: _typing.Sequence[UMat], channels: _typing.Sequence[int], mask: UMat | None, histSize: _typing.Sequence[int], ranges: _typing.Sequence[float], hist: UMat | None = ..., accumulate: bool = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def calcOpticalFlowFarneback(prev: cv2.typing.MatLike, next: cv2.typing.MatLike, flow: cv2.typing.MatLike, pyr_scale: float, levels: int, winsize: int, iterations: int, poly_n: int, poly_sigma: float, flags: int) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def calcOpticalFlowFarneback(prev: UMat, next: UMat, flow: UMat, pyr_scale: float, levels: int, winsize: int, iterations: int, poly_n: int, poly_sigma: float, flags: int) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def calcOpticalFlowPyrLK(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 = ..., winSize: cv2.typing.Size = ..., maxLevel: int = ..., criteria: cv2.typing.TermCriteria = ..., flags: int = ..., minEigThreshold: float = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def calcOpticalFlowPyrLK(prevImg: UMat, nextImg: UMat, prevPts: UMat, nextPts: UMat, status: UMat | None = ..., err: UMat | None = ..., winSize: cv2.typing.Size = ..., maxLevel: int = ..., criteria: cv2.typing.TermCriteria = ..., flags: int = ..., minEigThreshold: float = ...) -> tuple[UMat, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def calibrateCamera(objectPoints: _typing.Sequence[cv2.typing.MatLike], imagePoints: _typing.Sequence[cv2.typing.MatLike], imageSize: cv2.typing.Size, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, rvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., tvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, cv2.typing.MatLike, cv2.typing.MatLike, _typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike]]: ...
|
|
@_typing.overload
|
|
def calibrateCamera(objectPoints: _typing.Sequence[UMat], imagePoints: _typing.Sequence[UMat], imageSize: cv2.typing.Size, cameraMatrix: UMat, distCoeffs: UMat, rvecs: _typing.Sequence[UMat] | None = ..., tvecs: _typing.Sequence[UMat] | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, UMat, UMat, _typing.Sequence[UMat], _typing.Sequence[UMat]]: ...
|
|
|
|
@_typing.overload
|
|
def calibrateCameraExtended(objectPoints: _typing.Sequence[cv2.typing.MatLike], imagePoints: _typing.Sequence[cv2.typing.MatLike], imageSize: cv2.typing.Size, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, rvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., tvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., stdDeviationsIntrinsics: cv2.typing.MatLike | None = ..., stdDeviationsExtrinsics: cv2.typing.MatLike | None = ..., perViewErrors: cv2.typing.MatLike | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, cv2.typing.MatLike, cv2.typing.MatLike, _typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike], cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def calibrateCameraExtended(objectPoints: _typing.Sequence[UMat], imagePoints: _typing.Sequence[UMat], imageSize: cv2.typing.Size, cameraMatrix: UMat, distCoeffs: UMat, rvecs: _typing.Sequence[UMat] | None = ..., tvecs: _typing.Sequence[UMat] | None = ..., stdDeviationsIntrinsics: UMat | None = ..., stdDeviationsExtrinsics: UMat | None = ..., perViewErrors: UMat | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, UMat, UMat, _typing.Sequence[UMat], _typing.Sequence[UMat], UMat, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def calibrateCameraRO(objectPoints: _typing.Sequence[cv2.typing.MatLike], imagePoints: _typing.Sequence[cv2.typing.MatLike], imageSize: cv2.typing.Size, iFixedPoint: int, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, rvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., tvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., newObjPoints: cv2.typing.MatLike | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, cv2.typing.MatLike, cv2.typing.MatLike, _typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike], cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def calibrateCameraRO(objectPoints: _typing.Sequence[UMat], imagePoints: _typing.Sequence[UMat], imageSize: cv2.typing.Size, iFixedPoint: int, cameraMatrix: UMat, distCoeffs: UMat, rvecs: _typing.Sequence[UMat] | None = ..., tvecs: _typing.Sequence[UMat] | None = ..., newObjPoints: UMat | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, UMat, UMat, _typing.Sequence[UMat], _typing.Sequence[UMat], UMat]: ...
|
|
|
|
@_typing.overload
|
|
def calibrateCameraROExtended(objectPoints: _typing.Sequence[cv2.typing.MatLike], imagePoints: _typing.Sequence[cv2.typing.MatLike], imageSize: cv2.typing.Size, iFixedPoint: int, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, rvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., tvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., newObjPoints: cv2.typing.MatLike | None = ..., stdDeviationsIntrinsics: cv2.typing.MatLike | None = ..., stdDeviationsExtrinsics: cv2.typing.MatLike | None = ..., stdDeviationsObjPoints: cv2.typing.MatLike | None = ..., perViewErrors: cv2.typing.MatLike | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, cv2.typing.MatLike, cv2.typing.MatLike, _typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike], cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def calibrateCameraROExtended(objectPoints: _typing.Sequence[UMat], imagePoints: _typing.Sequence[UMat], imageSize: cv2.typing.Size, iFixedPoint: int, cameraMatrix: UMat, distCoeffs: UMat, rvecs: _typing.Sequence[UMat] | None = ..., tvecs: _typing.Sequence[UMat] | None = ..., newObjPoints: UMat | None = ..., stdDeviationsIntrinsics: UMat | None = ..., stdDeviationsExtrinsics: UMat | None = ..., stdDeviationsObjPoints: UMat | None = ..., perViewErrors: UMat | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, UMat, UMat, _typing.Sequence[UMat], _typing.Sequence[UMat], UMat, UMat, UMat, UMat, UMat]: ...
|
|
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|
@_typing.overload
|
|
def calibrateHandEye(R_gripper2base: _typing.Sequence[cv2.typing.MatLike], t_gripper2base: _typing.Sequence[cv2.typing.MatLike], R_target2cam: _typing.Sequence[cv2.typing.MatLike], t_target2cam: _typing.Sequence[cv2.typing.MatLike], R_cam2gripper: cv2.typing.MatLike | None = ..., t_cam2gripper: cv2.typing.MatLike | None = ..., method: HandEyeCalibrationMethod = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
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@_typing.overload
|
|
def calibrateHandEye(R_gripper2base: _typing.Sequence[UMat], t_gripper2base: _typing.Sequence[UMat], R_target2cam: _typing.Sequence[UMat], t_target2cam: _typing.Sequence[UMat], R_cam2gripper: UMat | None = ..., t_cam2gripper: UMat | None = ..., method: HandEyeCalibrationMethod = ...) -> tuple[UMat, UMat]: ...
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@_typing.overload
|
|
def calibrateRobotWorldHandEye(R_world2cam: _typing.Sequence[cv2.typing.MatLike], t_world2cam: _typing.Sequence[cv2.typing.MatLike], R_base2gripper: _typing.Sequence[cv2.typing.MatLike], t_base2gripper: _typing.Sequence[cv2.typing.MatLike], R_base2world: cv2.typing.MatLike | None = ..., t_base2world: cv2.typing.MatLike | None = ..., R_gripper2cam: cv2.typing.MatLike | None = ..., t_gripper2cam: cv2.typing.MatLike | None = ..., method: RobotWorldHandEyeCalibrationMethod = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
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@_typing.overload
|
|
def calibrateRobotWorldHandEye(R_world2cam: _typing.Sequence[UMat], t_world2cam: _typing.Sequence[UMat], R_base2gripper: _typing.Sequence[UMat], t_base2gripper: _typing.Sequence[UMat], R_base2world: UMat | None = ..., t_base2world: UMat | None = ..., R_gripper2cam: UMat | None = ..., t_gripper2cam: UMat | None = ..., method: RobotWorldHandEyeCalibrationMethod = ...) -> tuple[UMat, UMat, UMat, UMat]: ...
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@_typing.overload
|
|
def calibrationMatrixValues(cameraMatrix: cv2.typing.MatLike, imageSize: cv2.typing.Size, apertureWidth: float, apertureHeight: float) -> tuple[float, float, float, cv2.typing.Point2d, float]: ...
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@_typing.overload
|
|
def calibrationMatrixValues(cameraMatrix: UMat, imageSize: cv2.typing.Size, apertureWidth: float, apertureHeight: float) -> tuple[float, float, float, cv2.typing.Point2d, float]: ...
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@_typing.overload
|
|
def cartToPolar(x: cv2.typing.MatLike, y: cv2.typing.MatLike, magnitude: cv2.typing.MatLike | None = ..., angle: cv2.typing.MatLike | None = ..., angleInDegrees: bool = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
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@_typing.overload
|
|
def cartToPolar(x: UMat, y: UMat, magnitude: UMat | None = ..., angle: UMat | None = ..., angleInDegrees: bool = ...) -> tuple[UMat, UMat]: ...
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@_typing.overload
|
|
def checkChessboard(img: cv2.typing.MatLike, size: cv2.typing.Size) -> bool: ...
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@_typing.overload
|
|
def checkChessboard(img: UMat, size: cv2.typing.Size) -> bool: ...
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|
def checkHardwareSupport(feature: int) -> bool: ...
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@_typing.overload
|
|
def checkRange(a: cv2.typing.MatLike, quiet: bool = ..., minVal: float = ..., maxVal: float = ...) -> tuple[bool, cv2.typing.Point]: ...
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@_typing.overload
|
|
def checkRange(a: UMat, quiet: bool = ..., minVal: float = ..., maxVal: float = ...) -> tuple[bool, cv2.typing.Point]: ...
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@_typing.overload
|
|
def circle(img: cv2.typing.MatLike, center: cv2.typing.Point, radius: int, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ..., shift: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def circle(img: UMat, center: cv2.typing.Point, radius: int, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ..., shift: int = ...) -> UMat: ...
|
|
|
|
def clipLine(imgRect: cv2.typing.Rect, pt1: cv2.typing.Point, pt2: cv2.typing.Point) -> tuple[bool, cv2.typing.Point, cv2.typing.Point]: ...
|
|
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|
@_typing.overload
|
|
def colorChange(src: cv2.typing.MatLike, mask: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., red_mul: float = ..., green_mul: float = ..., blue_mul: float = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def colorChange(src: UMat, mask: UMat, dst: UMat | None = ..., red_mul: float = ..., green_mul: float = ..., blue_mul: float = ...) -> UMat: ...
|
|
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|
@_typing.overload
|
|
def compare(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, cmpop: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def compare(src1: UMat, src2: UMat, cmpop: int, dst: UMat | None = ...) -> UMat: ...
|
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|
@_typing.overload
|
|
def compareHist(H1: cv2.typing.MatLike, H2: cv2.typing.MatLike, method: int) -> float: ...
|
|
@_typing.overload
|
|
def compareHist(H1: UMat, H2: UMat, method: int) -> float: ...
|
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|
@_typing.overload
|
|
def completeSymm(m: cv2.typing.MatLike, lowerToUpper: bool = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def completeSymm(m: UMat, lowerToUpper: bool = ...) -> UMat: ...
|
|
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|
@_typing.overload
|
|
def composeRT(rvec1: cv2.typing.MatLike, tvec1: cv2.typing.MatLike, rvec2: cv2.typing.MatLike, tvec2: cv2.typing.MatLike, rvec3: cv2.typing.MatLike | None = ..., tvec3: cv2.typing.MatLike | None = ..., dr3dr1: cv2.typing.MatLike | None = ..., dr3dt1: cv2.typing.MatLike | None = ..., dr3dr2: cv2.typing.MatLike | None = ..., dr3dt2: cv2.typing.MatLike | None = ..., dt3dr1: cv2.typing.MatLike | None = ..., dt3dt1: cv2.typing.MatLike | None = ..., dt3dr2: cv2.typing.MatLike | None = ..., dt3dt2: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
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|
@_typing.overload
|
|
def composeRT(rvec1: UMat, tvec1: UMat, rvec2: UMat, tvec2: UMat, rvec3: UMat | None = ..., tvec3: UMat | None = ..., dr3dr1: UMat | None = ..., dr3dt1: UMat | None = ..., dr3dr2: UMat | None = ..., dr3dt2: UMat | None = ..., dt3dr1: UMat | None = ..., dt3dt1: UMat | None = ..., dt3dr2: UMat | None = ..., dt3dt2: UMat | None = ...) -> tuple[UMat, UMat, UMat, UMat, UMat, UMat, UMat, UMat, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def computeCorrespondEpilines(points: cv2.typing.MatLike, whichImage: int, F: cv2.typing.MatLike, lines: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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|
@_typing.overload
|
|
def computeCorrespondEpilines(points: UMat, whichImage: int, F: UMat, lines: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def computeECC(templateImage: cv2.typing.MatLike, inputImage: cv2.typing.MatLike, inputMask: cv2.typing.MatLike | None = ...) -> float: ...
|
|
@_typing.overload
|
|
def computeECC(templateImage: UMat, inputImage: UMat, inputMask: UMat | None = ...) -> float: ...
|
|
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|
@_typing.overload
|
|
def connectedComponents(image: cv2.typing.MatLike, labels: cv2.typing.MatLike | None = ..., connectivity: int = ..., ltype: int = ...) -> tuple[int, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def connectedComponents(image: UMat, labels: UMat | None = ..., connectivity: int = ..., ltype: int = ...) -> tuple[int, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def connectedComponentsWithAlgorithm(image: cv2.typing.MatLike, connectivity: int, ltype: int, ccltype: int, labels: cv2.typing.MatLike | None = ...) -> tuple[int, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def connectedComponentsWithAlgorithm(image: UMat, connectivity: int, ltype: int, ccltype: int, labels: UMat | None = ...) -> tuple[int, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def connectedComponentsWithStats(image: cv2.typing.MatLike, labels: cv2.typing.MatLike | None = ..., stats: cv2.typing.MatLike | None = ..., centroids: cv2.typing.MatLike | None = ..., connectivity: int = ..., ltype: int = ...) -> tuple[int, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def connectedComponentsWithStats(image: UMat, labels: UMat | None = ..., stats: UMat | None = ..., centroids: UMat | None = ..., connectivity: int = ..., ltype: int = ...) -> tuple[int, UMat, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def connectedComponentsWithStatsWithAlgorithm(image: cv2.typing.MatLike, connectivity: int, ltype: int, ccltype: int, labels: cv2.typing.MatLike | None = ..., stats: cv2.typing.MatLike | None = ..., centroids: cv2.typing.MatLike | None = ...) -> tuple[int, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def connectedComponentsWithStatsWithAlgorithm(image: UMat, connectivity: int, ltype: int, ccltype: int, labels: UMat | None = ..., stats: UMat | None = ..., centroids: UMat | None = ...) -> tuple[int, UMat, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def contourArea(contour: cv2.typing.MatLike, oriented: bool = ...) -> float: ...
|
|
@_typing.overload
|
|
def contourArea(contour: UMat, oriented: bool = ...) -> float: ...
|
|
|
|
@_typing.overload
|
|
def convertFp16(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def convertFp16(src: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def convertMaps(map1: cv2.typing.MatLike, map2: cv2.typing.MatLike, dstmap1type: int, dstmap1: cv2.typing.MatLike | None = ..., dstmap2: cv2.typing.MatLike | None = ..., nninterpolation: bool = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def convertMaps(map1: UMat, map2: UMat, dstmap1type: int, dstmap1: UMat | None = ..., dstmap2: UMat | None = ..., nninterpolation: bool = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def convertPointsFromHomogeneous(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def convertPointsFromHomogeneous(src: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def convertPointsToHomogeneous(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def convertPointsToHomogeneous(src: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def convertScaleAbs(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., alpha: float = ..., beta: float = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def convertScaleAbs(src: UMat, dst: UMat | None = ..., alpha: float = ..., beta: float = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def convexHull(points: cv2.typing.MatLike, hull: cv2.typing.MatLike | None = ..., clockwise: bool = ..., returnPoints: bool = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def convexHull(points: UMat, hull: UMat | None = ..., clockwise: bool = ..., returnPoints: bool = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def convexityDefects(contour: cv2.typing.MatLike, convexhull: cv2.typing.MatLike, convexityDefects: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def convexityDefects(contour: UMat, convexhull: UMat, convexityDefects: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def copyMakeBorder(src: cv2.typing.MatLike, top: int, bottom: int, left: int, right: int, borderType: int, dst: cv2.typing.MatLike | None = ..., value: cv2.typing.Scalar = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def copyMakeBorder(src: UMat, top: int, bottom: int, left: int, right: int, borderType: int, dst: UMat | None = ..., value: cv2.typing.Scalar = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def copyTo(src: cv2.typing.MatLike, mask: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def copyTo(src: UMat, mask: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def cornerEigenValsAndVecs(src: cv2.typing.MatLike, blockSize: int, ksize: int, dst: cv2.typing.MatLike | None = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def cornerEigenValsAndVecs(src: UMat, blockSize: int, ksize: int, dst: UMat | None = ..., borderType: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def cornerHarris(src: cv2.typing.MatLike, blockSize: int, ksize: int, k: float, dst: cv2.typing.MatLike | None = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def cornerHarris(src: UMat, blockSize: int, ksize: int, k: float, dst: UMat | None = ..., borderType: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def cornerMinEigenVal(src: cv2.typing.MatLike, blockSize: int, dst: cv2.typing.MatLike | None = ..., ksize: int = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def cornerMinEigenVal(src: UMat, blockSize: int, dst: UMat | None = ..., ksize: int = ..., borderType: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def cornerSubPix(image: cv2.typing.MatLike, corners: cv2.typing.MatLike, winSize: cv2.typing.Size, zeroZone: cv2.typing.Size, criteria: cv2.typing.TermCriteria) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def cornerSubPix(image: UMat, corners: UMat, winSize: cv2.typing.Size, zeroZone: cv2.typing.Size, criteria: cv2.typing.TermCriteria) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def correctMatches(F: cv2.typing.MatLike, points1: cv2.typing.MatLike, points2: cv2.typing.MatLike, newPoints1: cv2.typing.MatLike | None = ..., newPoints2: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def correctMatches(F: UMat, points1: UMat, points2: UMat, newPoints1: UMat | None = ..., newPoints2: UMat | None = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def countNonZero(src: cv2.typing.MatLike) -> int: ...
|
|
@_typing.overload
|
|
def countNonZero(src: UMat) -> int: ...
|
|
|
|
def createAlignMTB(max_bits: int = ..., exclude_range: int = ..., cut: bool = ...) -> AlignMTB: ...
|
|
|
|
def createBackgroundSubtractorKNN(history: int = ..., dist2Threshold: float = ..., detectShadows: bool = ...) -> BackgroundSubtractorKNN: ...
|
|
|
|
def createBackgroundSubtractorMOG2(history: int = ..., varThreshold: float = ..., detectShadows: bool = ...) -> BackgroundSubtractorMOG2: ...
|
|
|
|
def createCLAHE(clipLimit: float = ..., tileGridSize: cv2.typing.Size = ...) -> CLAHE: ...
|
|
|
|
def createCalibrateDebevec(samples: int = ..., lambda_: float = ..., random: bool = ...) -> CalibrateDebevec: ...
|
|
|
|
def createCalibrateRobertson(max_iter: int = ..., threshold: float = ...) -> CalibrateRobertson: ...
|
|
|
|
def createGeneralizedHoughBallard() -> GeneralizedHoughBallard: ...
|
|
|
|
def createGeneralizedHoughGuil() -> GeneralizedHoughGuil: ...
|
|
|
|
@_typing.overload
|
|
def createHanningWindow(winSize: cv2.typing.Size, type: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def createHanningWindow(winSize: cv2.typing.Size, type: int, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
def createLineSegmentDetector(refine: int = ..., scale: float = ..., sigma_scale: float = ..., quant: float = ..., ang_th: float = ..., log_eps: float = ..., density_th: float = ..., n_bins: int = ...) -> LineSegmentDetector: ...
|
|
|
|
def createMergeDebevec() -> MergeDebevec: ...
|
|
|
|
def createMergeMertens(contrast_weight: float = ..., saturation_weight: float = ..., exposure_weight: float = ...) -> MergeMertens: ...
|
|
|
|
def createMergeRobertson() -> MergeRobertson: ...
|
|
|
|
def createTonemap(gamma: float = ...) -> Tonemap: ...
|
|
|
|
def createTonemapDrago(gamma: float = ..., saturation: float = ..., bias: float = ...) -> TonemapDrago: ...
|
|
|
|
def createTonemapMantiuk(gamma: float = ..., scale: float = ..., saturation: float = ...) -> TonemapMantiuk: ...
|
|
|
|
def createTonemapReinhard(gamma: float = ..., intensity: float = ..., light_adapt: float = ..., color_adapt: float = ...) -> TonemapReinhard: ...
|
|
|
|
def cubeRoot(val: float) -> float: ...
|
|
|
|
def currentUIFramework() -> str: ...
|
|
|
|
@_typing.overload
|
|
def cvtColor(src: cv2.typing.MatLike, code: int, dst: cv2.typing.MatLike | None = ..., dstCn: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def cvtColor(src: UMat, code: int, dst: UMat | None = ..., dstCn: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def cvtColorTwoPlane(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, code: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def cvtColorTwoPlane(src1: UMat, src2: UMat, code: int, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def dct(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., flags: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def dct(src: UMat, dst: UMat | None = ..., flags: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def decolor(src: cv2.typing.MatLike, grayscale: cv2.typing.MatLike | None = ..., color_boost: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def decolor(src: UMat, grayscale: UMat | None = ..., color_boost: UMat | None = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def decomposeEssentialMat(E: cv2.typing.MatLike, R1: cv2.typing.MatLike | None = ..., R2: cv2.typing.MatLike | None = ..., t: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def decomposeEssentialMat(E: UMat, R1: UMat | None = ..., R2: UMat | None = ..., t: UMat | None = ...) -> tuple[UMat, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def decomposeHomographyMat(H: cv2.typing.MatLike, K: cv2.typing.MatLike, rotations: _typing.Sequence[cv2.typing.MatLike] | None = ..., translations: _typing.Sequence[cv2.typing.MatLike] | None = ..., normals: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> tuple[int, _typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike]]: ...
|
|
@_typing.overload
|
|
def decomposeHomographyMat(H: UMat, K: UMat, rotations: _typing.Sequence[UMat] | None = ..., translations: _typing.Sequence[UMat] | None = ..., normals: _typing.Sequence[UMat] | None = ...) -> tuple[int, _typing.Sequence[UMat], _typing.Sequence[UMat], _typing.Sequence[UMat]]: ...
|
|
|
|
@_typing.overload
|
|
def decomposeProjectionMatrix(projMatrix: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike | None = ..., rotMatrix: cv2.typing.MatLike | None = ..., transVect: cv2.typing.MatLike | None = ..., rotMatrixX: cv2.typing.MatLike | None = ..., rotMatrixY: cv2.typing.MatLike | None = ..., rotMatrixZ: cv2.typing.MatLike | None = ..., eulerAngles: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
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|
@_typing.overload
|
|
def decomposeProjectionMatrix(projMatrix: UMat, cameraMatrix: UMat | None = ..., rotMatrix: UMat | None = ..., transVect: UMat | None = ..., rotMatrixX: UMat | None = ..., rotMatrixY: UMat | None = ..., rotMatrixZ: UMat | None = ..., eulerAngles: UMat | None = ...) -> tuple[UMat, UMat, UMat, UMat, UMat, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def demosaicing(src: cv2.typing.MatLike, code: int, dst: cv2.typing.MatLike | None = ..., dstCn: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def demosaicing(src: UMat, code: int, dst: UMat | None = ..., dstCn: int = ...) -> UMat: ...
|
|
|
|
def denoise_TVL1(observations: _typing.Sequence[cv2.typing.MatLike], result: cv2.typing.MatLike, lambda_: float = ..., niters: int = ...) -> None: ...
|
|
|
|
def destroyAllWindows() -> None: ...
|
|
|
|
def destroyWindow(winname: str) -> None: ...
|
|
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|
@_typing.overload
|
|
def detailEnhance(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., sigma_s: float = ..., sigma_r: float = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def detailEnhance(src: UMat, dst: UMat | None = ..., sigma_s: float = ..., sigma_r: float = ...) -> UMat: ...
|
|
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@_typing.overload
|
|
def determinant(mtx: cv2.typing.MatLike) -> float: ...
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@_typing.overload
|
|
def determinant(mtx: UMat) -> float: ...
|
|
|
|
@_typing.overload
|
|
def dft(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., flags: int = ..., nonzeroRows: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def dft(src: UMat, dst: UMat | None = ..., flags: int = ..., nonzeroRows: int = ...) -> UMat: ...
|
|
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|
@_typing.overload
|
|
def dilate(src: cv2.typing.MatLike, kernel: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., anchor: cv2.typing.Point = ..., iterations: int = ..., borderType: int = ..., borderValue: cv2.typing.Scalar = ...) -> cv2.typing.MatLike: ...
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|
@_typing.overload
|
|
def dilate(src: UMat, kernel: UMat, dst: UMat | None = ..., anchor: cv2.typing.Point = ..., iterations: int = ..., borderType: int = ..., borderValue: cv2.typing.Scalar = ...) -> UMat: ...
|
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def displayOverlay(winname: str, text: str, delayms: int = ...) -> None: ...
|
|
|
|
def displayStatusBar(winname: str, text: str, delayms: int = ...) -> None: ...
|
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@_typing.overload
|
|
def distanceTransform(src: cv2.typing.MatLike, distanceType: int, maskSize: int, dst: cv2.typing.MatLike | None = ..., dstType: int = ...) -> cv2.typing.MatLike: ...
|
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@_typing.overload
|
|
def distanceTransform(src: UMat, distanceType: int, maskSize: int, dst: UMat | None = ..., dstType: int = ...) -> UMat: ...
|
|
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@_typing.overload
|
|
def distanceTransformWithLabels(src: cv2.typing.MatLike, distanceType: int, maskSize: int, dst: cv2.typing.MatLike | None = ..., labels: cv2.typing.MatLike | None = ..., labelType: int = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def distanceTransformWithLabels(src: UMat, distanceType: int, maskSize: int, dst: UMat | None = ..., labels: UMat | None = ..., labelType: int = ...) -> tuple[UMat, UMat]: ...
|
|
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|
@_typing.overload
|
|
def divSpectrums(a: cv2.typing.MatLike, b: cv2.typing.MatLike, flags: int, c: cv2.typing.MatLike | None = ..., conjB: bool = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def divSpectrums(a: UMat, b: UMat, flags: int, c: UMat | None = ..., conjB: bool = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def divide(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., scale: float = ..., dtype: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def divide(src1: UMat, src2: UMat, dst: UMat | None = ..., scale: float = ..., dtype: int = ...) -> UMat: ...
|
|
@_typing.overload
|
|
def divide(scale: float, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., dtype: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def divide(scale: float, src2: UMat, dst: UMat | None = ..., dtype: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def drawChessboardCorners(image: cv2.typing.MatLike, patternSize: cv2.typing.Size, corners: cv2.typing.MatLike, patternWasFound: bool) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def drawChessboardCorners(image: UMat, patternSize: cv2.typing.Size, corners: UMat, patternWasFound: bool) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def drawContours(image: cv2.typing.MatLike, contours: _typing.Sequence[cv2.typing.MatLike], contourIdx: int, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ..., hierarchy: cv2.typing.MatLike | None = ..., maxLevel: int = ..., offset: cv2.typing.Point = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def drawContours(image: UMat, contours: _typing.Sequence[UMat], contourIdx: int, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ..., hierarchy: UMat | None = ..., maxLevel: int = ..., offset: cv2.typing.Point = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def drawFrameAxes(image: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, rvec: cv2.typing.MatLike, tvec: cv2.typing.MatLike, length: float, thickness: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def drawFrameAxes(image: UMat, cameraMatrix: UMat, distCoeffs: UMat, rvec: UMat, tvec: UMat, length: float, thickness: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def drawKeypoints(image: cv2.typing.MatLike, keypoints: _typing.Sequence[KeyPoint], outImage: cv2.typing.MatLike, color: cv2.typing.Scalar = ..., flags: DrawMatchesFlags = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def drawKeypoints(image: UMat, keypoints: _typing.Sequence[KeyPoint], outImage: UMat, color: cv2.typing.Scalar = ..., flags: DrawMatchesFlags = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def drawMarker(img: cv2.typing.MatLike, position: cv2.typing.Point, color: cv2.typing.Scalar, markerType: int = ..., markerSize: int = ..., thickness: int = ..., line_type: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def drawMarker(img: UMat, position: cv2.typing.Point, color: cv2.typing.Scalar, markerType: int = ..., markerSize: int = ..., thickness: int = ..., line_type: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def drawMatches(img1: cv2.typing.MatLike, keypoints1: _typing.Sequence[KeyPoint], img2: cv2.typing.MatLike, keypoints2: _typing.Sequence[KeyPoint], matches1to2: _typing.Sequence[DMatch], outImg: cv2.typing.MatLike, matchColor: cv2.typing.Scalar = ..., singlePointColor: cv2.typing.Scalar = ..., matchesMask: _typing.Sequence[str] = ..., flags: DrawMatchesFlags = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def drawMatches(img1: UMat, keypoints1: _typing.Sequence[KeyPoint], img2: UMat, keypoints2: _typing.Sequence[KeyPoint], matches1to2: _typing.Sequence[DMatch], outImg: UMat, matchColor: cv2.typing.Scalar = ..., singlePointColor: cv2.typing.Scalar = ..., matchesMask: _typing.Sequence[str] = ..., flags: DrawMatchesFlags = ...) -> UMat: ...
|
|
@_typing.overload
|
|
def drawMatches(img1: cv2.typing.MatLike, keypoints1: _typing.Sequence[KeyPoint], img2: cv2.typing.MatLike, keypoints2: _typing.Sequence[KeyPoint], matches1to2: _typing.Sequence[DMatch], outImg: cv2.typing.MatLike, matchesThickness: int, matchColor: cv2.typing.Scalar = ..., singlePointColor: cv2.typing.Scalar = ..., matchesMask: _typing.Sequence[str] = ..., flags: DrawMatchesFlags = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def drawMatches(img1: UMat, keypoints1: _typing.Sequence[KeyPoint], img2: UMat, keypoints2: _typing.Sequence[KeyPoint], matches1to2: _typing.Sequence[DMatch], outImg: UMat, matchesThickness: int, matchColor: cv2.typing.Scalar = ..., singlePointColor: cv2.typing.Scalar = ..., matchesMask: _typing.Sequence[str] = ..., flags: DrawMatchesFlags = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def drawMatchesKnn(img1: cv2.typing.MatLike, keypoints1: _typing.Sequence[KeyPoint], img2: cv2.typing.MatLike, keypoints2: _typing.Sequence[KeyPoint], matches1to2: _typing.Sequence[_typing.Sequence[DMatch]], outImg: cv2.typing.MatLike, matchColor: cv2.typing.Scalar = ..., singlePointColor: cv2.typing.Scalar = ..., matchesMask: _typing.Sequence[_typing.Sequence[str]] = ..., flags: DrawMatchesFlags = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def drawMatchesKnn(img1: UMat, keypoints1: _typing.Sequence[KeyPoint], img2: UMat, keypoints2: _typing.Sequence[KeyPoint], matches1to2: _typing.Sequence[_typing.Sequence[DMatch]], outImg: UMat, matchColor: cv2.typing.Scalar = ..., singlePointColor: cv2.typing.Scalar = ..., matchesMask: _typing.Sequence[_typing.Sequence[str]] = ..., flags: DrawMatchesFlags = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def edgePreservingFilter(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., flags: int = ..., sigma_s: float = ..., sigma_r: float = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def edgePreservingFilter(src: UMat, dst: UMat | None = ..., flags: int = ..., sigma_s: float = ..., sigma_r: float = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def eigen(src: cv2.typing.MatLike, eigenvalues: cv2.typing.MatLike | None = ..., eigenvectors: cv2.typing.MatLike | None = ...) -> tuple[bool, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def eigen(src: UMat, eigenvalues: UMat | None = ..., eigenvectors: UMat | None = ...) -> tuple[bool, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def eigenNonSymmetric(src: cv2.typing.MatLike, eigenvalues: cv2.typing.MatLike | None = ..., eigenvectors: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def eigenNonSymmetric(src: UMat, eigenvalues: UMat | None = ..., eigenvectors: UMat | None = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def ellipse(img: cv2.typing.MatLike, center: cv2.typing.Point, axes: cv2.typing.Size, angle: float, startAngle: float, endAngle: float, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ..., shift: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def ellipse(img: UMat, center: cv2.typing.Point, axes: cv2.typing.Size, angle: float, startAngle: float, endAngle: float, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ..., shift: int = ...) -> UMat: ...
|
|
@_typing.overload
|
|
def ellipse(img: cv2.typing.MatLike, box: cv2.typing.RotatedRect, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def ellipse(img: UMat, box: cv2.typing.RotatedRect, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ...) -> UMat: ...
|
|
|
|
def ellipse2Poly(center: cv2.typing.Point, axes: cv2.typing.Size, angle: int, arcStart: int, arcEnd: int, delta: int) -> _typing.Sequence[cv2.typing.Point]: ...
|
|
|
|
def empty_array_desc() -> GArrayDesc: ...
|
|
|
|
def empty_gopaque_desc() -> GOpaqueDesc: ...
|
|
|
|
def empty_scalar_desc() -> GScalarDesc: ...
|
|
|
|
@_typing.overload
|
|
def equalizeHist(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def equalizeHist(src: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def erode(src: cv2.typing.MatLike, kernel: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., anchor: cv2.typing.Point = ..., iterations: int = ..., borderType: int = ..., borderValue: cv2.typing.Scalar = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def erode(src: UMat, kernel: UMat, dst: UMat | None = ..., anchor: cv2.typing.Point = ..., iterations: int = ..., borderType: int = ..., borderValue: cv2.typing.Scalar = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def estimateAffine2D(from_: cv2.typing.MatLike, to: cv2.typing.MatLike, inliers: cv2.typing.MatLike | None = ..., method: int = ..., ransacReprojThreshold: float = ..., maxIters: int = ..., confidence: float = ..., refineIters: int = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def estimateAffine2D(from_: UMat, to: UMat, inliers: UMat | None = ..., method: int = ..., ransacReprojThreshold: float = ..., maxIters: int = ..., confidence: float = ..., refineIters: int = ...) -> tuple[cv2.typing.MatLike, UMat]: ...
|
|
@_typing.overload
|
|
def estimateAffine2D(pts1: cv2.typing.MatLike, pts2: cv2.typing.MatLike, params: UsacParams, inliers: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def estimateAffine2D(pts1: UMat, pts2: UMat, params: UsacParams, inliers: UMat | None = ...) -> tuple[cv2.typing.MatLike, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def estimateAffine3D(src: cv2.typing.MatLike, dst: cv2.typing.MatLike, out: cv2.typing.MatLike | None = ..., inliers: cv2.typing.MatLike | None = ..., ransacThreshold: float = ..., confidence: float = ...) -> tuple[int, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def estimateAffine3D(src: UMat, dst: UMat, out: UMat | None = ..., inliers: UMat | None = ..., ransacThreshold: float = ..., confidence: float = ...) -> tuple[int, UMat, UMat]: ...
|
|
@_typing.overload
|
|
def estimateAffine3D(src: cv2.typing.MatLike, dst: cv2.typing.MatLike, force_rotation: bool = ...) -> tuple[cv2.typing.MatLike, float]: ...
|
|
@_typing.overload
|
|
def estimateAffine3D(src: UMat, dst: UMat, force_rotation: bool = ...) -> tuple[cv2.typing.MatLike, float]: ...
|
|
|
|
@_typing.overload
|
|
def estimateAffinePartial2D(from_: cv2.typing.MatLike, to: cv2.typing.MatLike, inliers: cv2.typing.MatLike | None = ..., method: int = ..., ransacReprojThreshold: float = ..., maxIters: int = ..., confidence: float = ..., refineIters: int = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def estimateAffinePartial2D(from_: UMat, to: UMat, inliers: UMat | None = ..., method: int = ..., ransacReprojThreshold: float = ..., maxIters: int = ..., confidence: float = ..., refineIters: int = ...) -> tuple[cv2.typing.MatLike, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def estimateChessboardSharpness(image: cv2.typing.MatLike, patternSize: cv2.typing.Size, corners: cv2.typing.MatLike, rise_distance: float = ..., vertical: bool = ..., sharpness: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.Scalar, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def estimateChessboardSharpness(image: UMat, patternSize: cv2.typing.Size, corners: UMat, rise_distance: float = ..., vertical: bool = ..., sharpness: UMat | None = ...) -> tuple[cv2.typing.Scalar, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def estimateTranslation3D(src: cv2.typing.MatLike, dst: cv2.typing.MatLike, out: cv2.typing.MatLike | None = ..., inliers: cv2.typing.MatLike | None = ..., ransacThreshold: float = ..., confidence: float = ...) -> tuple[int, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def estimateTranslation3D(src: UMat, dst: UMat, out: UMat | None = ..., inliers: UMat | None = ..., ransacThreshold: float = ..., confidence: float = ...) -> tuple[int, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def exp(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def exp(src: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def extractChannel(src: cv2.typing.MatLike, coi: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def extractChannel(src: UMat, coi: int, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
def fastAtan2(y: float, x: float) -> float: ...
|
|
|
|
@_typing.overload
|
|
def fastNlMeansDenoising(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., h: float = ..., templateWindowSize: int = ..., searchWindowSize: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def fastNlMeansDenoising(src: UMat, dst: UMat | None = ..., h: float = ..., templateWindowSize: int = ..., searchWindowSize: int = ...) -> UMat: ...
|
|
@_typing.overload
|
|
def fastNlMeansDenoising(src: cv2.typing.MatLike, h: _typing.Sequence[float], dst: cv2.typing.MatLike | None = ..., templateWindowSize: int = ..., searchWindowSize: int = ..., normType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def fastNlMeansDenoising(src: UMat, h: _typing.Sequence[float], dst: UMat | None = ..., templateWindowSize: int = ..., searchWindowSize: int = ..., normType: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def fastNlMeansDenoisingColored(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., h: float = ..., hColor: float = ..., templateWindowSize: int = ..., searchWindowSize: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def fastNlMeansDenoisingColored(src: UMat, dst: UMat | None = ..., h: float = ..., hColor: float = ..., templateWindowSize: int = ..., searchWindowSize: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def fastNlMeansDenoisingColoredMulti(srcImgs: _typing.Sequence[cv2.typing.MatLike], imgToDenoiseIndex: int, temporalWindowSize: int, dst: cv2.typing.MatLike | None = ..., h: float = ..., hColor: float = ..., templateWindowSize: int = ..., searchWindowSize: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def fastNlMeansDenoisingColoredMulti(srcImgs: _typing.Sequence[UMat], imgToDenoiseIndex: int, temporalWindowSize: int, dst: UMat | None = ..., h: float = ..., hColor: float = ..., templateWindowSize: int = ..., searchWindowSize: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def fastNlMeansDenoisingMulti(srcImgs: _typing.Sequence[cv2.typing.MatLike], imgToDenoiseIndex: int, temporalWindowSize: int, dst: cv2.typing.MatLike | None = ..., h: float = ..., templateWindowSize: int = ..., searchWindowSize: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def fastNlMeansDenoisingMulti(srcImgs: _typing.Sequence[UMat], imgToDenoiseIndex: int, temporalWindowSize: int, dst: UMat | None = ..., h: float = ..., templateWindowSize: int = ..., searchWindowSize: int = ...) -> UMat: ...
|
|
@_typing.overload
|
|
def fastNlMeansDenoisingMulti(srcImgs: _typing.Sequence[cv2.typing.MatLike], imgToDenoiseIndex: int, temporalWindowSize: int, h: _typing.Sequence[float], dst: cv2.typing.MatLike | None = ..., templateWindowSize: int = ..., searchWindowSize: int = ..., normType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def fastNlMeansDenoisingMulti(srcImgs: _typing.Sequence[UMat], imgToDenoiseIndex: int, temporalWindowSize: int, h: _typing.Sequence[float], dst: UMat | None = ..., templateWindowSize: int = ..., searchWindowSize: int = ..., normType: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def fillConvexPoly(img: cv2.typing.MatLike, points: cv2.typing.MatLike, color: cv2.typing.Scalar, lineType: int = ..., shift: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def fillConvexPoly(img: UMat, points: UMat, color: cv2.typing.Scalar, lineType: int = ..., shift: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def fillPoly(img: cv2.typing.MatLike, pts: _typing.Sequence[cv2.typing.MatLike], color: cv2.typing.Scalar, lineType: int = ..., shift: int = ..., offset: cv2.typing.Point = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def fillPoly(img: UMat, pts: _typing.Sequence[UMat], color: cv2.typing.Scalar, lineType: int = ..., shift: int = ..., offset: cv2.typing.Point = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def filter2D(src: cv2.typing.MatLike, ddepth: int, kernel: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., anchor: cv2.typing.Point = ..., delta: float = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def filter2D(src: UMat, ddepth: int, kernel: UMat, dst: UMat | None = ..., anchor: cv2.typing.Point = ..., delta: float = ..., borderType: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def filterHomographyDecompByVisibleRefpoints(rotations: _typing.Sequence[cv2.typing.MatLike], normals: _typing.Sequence[cv2.typing.MatLike], beforePoints: cv2.typing.MatLike, afterPoints: cv2.typing.MatLike, possibleSolutions: cv2.typing.MatLike | None = ..., pointsMask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def filterHomographyDecompByVisibleRefpoints(rotations: _typing.Sequence[UMat], normals: _typing.Sequence[UMat], beforePoints: UMat, afterPoints: UMat, possibleSolutions: UMat | None = ..., pointsMask: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def filterSpeckles(img: cv2.typing.MatLike, newVal: float, maxSpeckleSize: int, maxDiff: float, buf: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def filterSpeckles(img: UMat, newVal: float, maxSpeckleSize: int, maxDiff: float, buf: UMat | None = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def find4QuadCornerSubpix(img: cv2.typing.MatLike, corners: cv2.typing.MatLike, region_size: cv2.typing.Size) -> tuple[bool, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def find4QuadCornerSubpix(img: UMat, corners: UMat, region_size: cv2.typing.Size) -> tuple[bool, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def findChessboardCorners(image: cv2.typing.MatLike, patternSize: cv2.typing.Size, corners: cv2.typing.MatLike | None = ..., flags: int = ...) -> tuple[bool, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findChessboardCorners(image: UMat, patternSize: cv2.typing.Size, corners: UMat | None = ..., flags: int = ...) -> tuple[bool, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def findChessboardCornersSB(image: cv2.typing.MatLike, patternSize: cv2.typing.Size, corners: cv2.typing.MatLike | None = ..., flags: int = ...) -> tuple[bool, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findChessboardCornersSB(image: UMat, patternSize: cv2.typing.Size, corners: UMat | None = ..., flags: int = ...) -> tuple[bool, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def findChessboardCornersSBWithMeta(image: cv2.typing.MatLike, patternSize: cv2.typing.Size, flags: int, corners: cv2.typing.MatLike | None = ..., meta: cv2.typing.MatLike | None = ...) -> tuple[bool, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findChessboardCornersSBWithMeta(image: UMat, patternSize: cv2.typing.Size, flags: int, corners: UMat | None = ..., meta: UMat | None = ...) -> tuple[bool, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def findCirclesGrid(image: cv2.typing.MatLike, patternSize: cv2.typing.Size, flags: int, blobDetector: cv2.typing.FeatureDetector, parameters: CirclesGridFinderParameters, centers: cv2.typing.MatLike | None = ...) -> tuple[bool, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findCirclesGrid(image: UMat, patternSize: cv2.typing.Size, flags: int, blobDetector: cv2.typing.FeatureDetector, parameters: CirclesGridFinderParameters, centers: UMat | None = ...) -> tuple[bool, UMat]: ...
|
|
@_typing.overload
|
|
def findCirclesGrid(image: cv2.typing.MatLike, patternSize: cv2.typing.Size, centers: cv2.typing.MatLike | None = ..., flags: int = ..., blobDetector: cv2.typing.FeatureDetector = ...) -> tuple[bool, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findCirclesGrid(image: UMat, patternSize: cv2.typing.Size, centers: UMat | None = ..., flags: int = ..., blobDetector: cv2.typing.FeatureDetector = ...) -> tuple[bool, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def findContours(image: cv2.typing.MatLike, mode: int, method: int, contours: _typing.Sequence[cv2.typing.MatLike] | None = ..., hierarchy: cv2.typing.MatLike | None = ..., offset: cv2.typing.Point = ...) -> tuple[_typing.Sequence[cv2.typing.MatLike], cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findContours(image: UMat, mode: int, method: int, contours: _typing.Sequence[UMat] | None = ..., hierarchy: UMat | None = ..., offset: cv2.typing.Point = ...) -> tuple[_typing.Sequence[UMat], UMat]: ...
|
|
|
|
@_typing.overload
|
|
def findContoursLinkRuns(image: cv2.typing.MatLike, contours: _typing.Sequence[cv2.typing.MatLike] | None = ..., hierarchy: cv2.typing.MatLike | None = ...) -> tuple[_typing.Sequence[cv2.typing.MatLike], cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findContoursLinkRuns(image: UMat, contours: _typing.Sequence[UMat] | None = ..., hierarchy: UMat | None = ...) -> tuple[_typing.Sequence[UMat], UMat]: ...
|
|
@_typing.overload
|
|
def findContoursLinkRuns(image: cv2.typing.MatLike, contours: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findContoursLinkRuns(image: UMat, contours: _typing.Sequence[UMat] | None = ...) -> _typing.Sequence[UMat]: ...
|
|
|
|
@_typing.overload
|
|
def findEssentialMat(points1: cv2.typing.MatLike, points2: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, method: int = ..., prob: float = ..., threshold: float = ..., maxIters: int = ..., mask: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findEssentialMat(points1: UMat, points2: UMat, cameraMatrix: UMat, method: int = ..., prob: float = ..., threshold: float = ..., maxIters: int = ..., mask: UMat | None = ...) -> tuple[cv2.typing.MatLike, UMat]: ...
|
|
@_typing.overload
|
|
def findEssentialMat(points1: cv2.typing.MatLike, points2: cv2.typing.MatLike, focal: float = ..., pp: cv2.typing.Point2d = ..., method: int = ..., prob: float = ..., threshold: float = ..., maxIters: int = ..., mask: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findEssentialMat(points1: UMat, points2: UMat, focal: float = ..., pp: cv2.typing.Point2d = ..., method: int = ..., prob: float = ..., threshold: float = ..., maxIters: int = ..., mask: UMat | None = ...) -> tuple[cv2.typing.MatLike, UMat]: ...
|
|
@_typing.overload
|
|
def findEssentialMat(points1: cv2.typing.MatLike, points2: cv2.typing.MatLike, cameraMatrix1: cv2.typing.MatLike, distCoeffs1: cv2.typing.MatLike, cameraMatrix2: cv2.typing.MatLike, distCoeffs2: cv2.typing.MatLike, method: int = ..., prob: float = ..., threshold: float = ..., mask: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findEssentialMat(points1: UMat, points2: UMat, cameraMatrix1: UMat, distCoeffs1: UMat, cameraMatrix2: UMat, distCoeffs2: UMat, method: int = ..., prob: float = ..., threshold: float = ..., mask: UMat | None = ...) -> tuple[cv2.typing.MatLike, UMat]: ...
|
|
@_typing.overload
|
|
def findEssentialMat(points1: cv2.typing.MatLike, points2: cv2.typing.MatLike, cameraMatrix1: cv2.typing.MatLike, cameraMatrix2: cv2.typing.MatLike, dist_coeff1: cv2.typing.MatLike, dist_coeff2: cv2.typing.MatLike, params: UsacParams, mask: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findEssentialMat(points1: UMat, points2: UMat, cameraMatrix1: UMat, cameraMatrix2: UMat, dist_coeff1: UMat, dist_coeff2: UMat, params: UsacParams, mask: UMat | None = ...) -> tuple[cv2.typing.MatLike, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def findFundamentalMat(points1: cv2.typing.MatLike, points2: cv2.typing.MatLike, method: int, ransacReprojThreshold: float, confidence: float, maxIters: int, mask: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findFundamentalMat(points1: UMat, points2: UMat, method: int, ransacReprojThreshold: float, confidence: float, maxIters: int, mask: UMat | None = ...) -> tuple[cv2.typing.MatLike, UMat]: ...
|
|
@_typing.overload
|
|
def findFundamentalMat(points1: cv2.typing.MatLike, points2: cv2.typing.MatLike, method: int = ..., ransacReprojThreshold: float = ..., confidence: float = ..., mask: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findFundamentalMat(points1: UMat, points2: UMat, method: int = ..., ransacReprojThreshold: float = ..., confidence: float = ..., mask: UMat | None = ...) -> tuple[cv2.typing.MatLike, UMat]: ...
|
|
@_typing.overload
|
|
def findFundamentalMat(points1: cv2.typing.MatLike, points2: cv2.typing.MatLike, params: UsacParams, mask: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findFundamentalMat(points1: UMat, points2: UMat, params: UsacParams, mask: UMat | None = ...) -> tuple[cv2.typing.MatLike, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def findHomography(srcPoints: cv2.typing.MatLike, dstPoints: cv2.typing.MatLike, method: int = ..., ransacReprojThreshold: float = ..., mask: cv2.typing.MatLike | None = ..., maxIters: int = ..., confidence: float = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findHomography(srcPoints: UMat, dstPoints: UMat, method: int = ..., ransacReprojThreshold: float = ..., mask: UMat | None = ..., maxIters: int = ..., confidence: float = ...) -> tuple[cv2.typing.MatLike, UMat]: ...
|
|
@_typing.overload
|
|
def findHomography(srcPoints: cv2.typing.MatLike, dstPoints: cv2.typing.MatLike, params: UsacParams, mask: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findHomography(srcPoints: UMat, dstPoints: UMat, params: UsacParams, mask: UMat | None = ...) -> tuple[cv2.typing.MatLike, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def findNonZero(src: cv2.typing.MatLike, idx: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def findNonZero(src: UMat, idx: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def findTransformECC(templateImage: cv2.typing.MatLike, inputImage: cv2.typing.MatLike, warpMatrix: cv2.typing.MatLike, motionType: int, criteria: cv2.typing.TermCriteria, inputMask: cv2.typing.MatLike, gaussFiltSize: int) -> tuple[float, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findTransformECC(templateImage: UMat, inputImage: UMat, warpMatrix: UMat, motionType: int, criteria: cv2.typing.TermCriteria, inputMask: UMat, gaussFiltSize: int) -> tuple[float, UMat]: ...
|
|
@_typing.overload
|
|
def findTransformECC(templateImage: cv2.typing.MatLike, inputImage: cv2.typing.MatLike, warpMatrix: cv2.typing.MatLike, motionType: int = ..., criteria: cv2.typing.TermCriteria = ..., inputMask: cv2.typing.MatLike | None = ...) -> tuple[float, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def findTransformECC(templateImage: UMat, inputImage: UMat, warpMatrix: UMat, motionType: int = ..., criteria: cv2.typing.TermCriteria = ..., inputMask: UMat | None = ...) -> tuple[float, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def fitEllipse(points: cv2.typing.MatLike) -> cv2.typing.RotatedRect: ...
|
|
@_typing.overload
|
|
def fitEllipse(points: UMat) -> cv2.typing.RotatedRect: ...
|
|
|
|
@_typing.overload
|
|
def fitEllipseAMS(points: cv2.typing.MatLike) -> cv2.typing.RotatedRect: ...
|
|
@_typing.overload
|
|
def fitEllipseAMS(points: UMat) -> cv2.typing.RotatedRect: ...
|
|
|
|
@_typing.overload
|
|
def fitEllipseDirect(points: cv2.typing.MatLike) -> cv2.typing.RotatedRect: ...
|
|
@_typing.overload
|
|
def fitEllipseDirect(points: UMat) -> cv2.typing.RotatedRect: ...
|
|
|
|
@_typing.overload
|
|
def fitLine(points: cv2.typing.MatLike, distType: int, param: float, reps: float, aeps: float, line: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def fitLine(points: UMat, distType: int, param: float, reps: float, aeps: float, line: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def flip(src: cv2.typing.MatLike, flipCode: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def flip(src: UMat, flipCode: int, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def flipND(src: cv2.typing.MatLike, axis: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def flipND(src: UMat, axis: int, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def floodFill(image: cv2.typing.MatLike, mask: cv2.typing.MatLike, seedPoint: cv2.typing.Point, newVal: cv2.typing.Scalar, loDiff: cv2.typing.Scalar = ..., upDiff: cv2.typing.Scalar = ..., flags: int = ...) -> tuple[int, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.Rect]: ...
|
|
@_typing.overload
|
|
def floodFill(image: UMat, mask: UMat, seedPoint: cv2.typing.Point, newVal: cv2.typing.Scalar, loDiff: cv2.typing.Scalar = ..., upDiff: cv2.typing.Scalar = ..., flags: int = ...) -> tuple[int, UMat, UMat, cv2.typing.Rect]: ...
|
|
|
|
@_typing.overload
|
|
def gemm(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, alpha: float, src3: cv2.typing.MatLike, beta: float, dst: cv2.typing.MatLike | None = ..., flags: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def gemm(src1: UMat, src2: UMat, alpha: float, src3: UMat, beta: float, dst: UMat | None = ..., flags: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def getAffineTransform(src: cv2.typing.MatLike, dst: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def getAffineTransform(src: UMat, dst: UMat) -> cv2.typing.MatLike: ...
|
|
|
|
def getBuildInformation() -> str: ...
|
|
|
|
def getCPUFeaturesLine() -> str: ...
|
|
|
|
def getCPUTickCount() -> int: ...
|
|
|
|
@_typing.overload
|
|
def getDefaultNewCameraMatrix(cameraMatrix: cv2.typing.MatLike, imgsize: cv2.typing.Size = ..., centerPrincipalPoint: bool = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def getDefaultNewCameraMatrix(cameraMatrix: UMat, imgsize: cv2.typing.Size = ..., centerPrincipalPoint: bool = ...) -> cv2.typing.MatLike: ...
|
|
|
|
@_typing.overload
|
|
def getDerivKernels(dx: int, dy: int, ksize: int, kx: cv2.typing.MatLike | None = ..., ky: cv2.typing.MatLike | None = ..., normalize: bool = ..., ktype: int = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def getDerivKernels(dx: int, dy: int, ksize: int, kx: UMat | None = ..., ky: UMat | None = ..., normalize: bool = ..., ktype: int = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
def getFontScaleFromHeight(fontFace: int, pixelHeight: int, thickness: int = ...) -> float: ...
|
|
|
|
def getGaborKernel(ksize: cv2.typing.Size, sigma: float, theta: float, lambd: float, gamma: float, psi: float = ..., ktype: int = ...) -> cv2.typing.MatLike: ...
|
|
|
|
def getGaussianKernel(ksize: int, sigma: float, ktype: int = ...) -> cv2.typing.MatLike: ...
|
|
|
|
def getHardwareFeatureName(feature: int) -> str: ...
|
|
|
|
def getLogLevel() -> int: ...
|
|
|
|
def getNumThreads() -> int: ...
|
|
|
|
def getNumberOfCPUs() -> int: ...
|
|
|
|
def getOptimalDFTSize(vecsize: int) -> int: ...
|
|
|
|
@_typing.overload
|
|
def getOptimalNewCameraMatrix(cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, imageSize: cv2.typing.Size, alpha: float, newImgSize: cv2.typing.Size = ..., centerPrincipalPoint: bool = ...) -> tuple[cv2.typing.MatLike, cv2.typing.Rect]: ...
|
|
@_typing.overload
|
|
def getOptimalNewCameraMatrix(cameraMatrix: UMat, distCoeffs: UMat, imageSize: cv2.typing.Size, alpha: float, newImgSize: cv2.typing.Size = ..., centerPrincipalPoint: bool = ...) -> tuple[cv2.typing.MatLike, cv2.typing.Rect]: ...
|
|
|
|
@_typing.overload
|
|
def getPerspectiveTransform(src: cv2.typing.MatLike, dst: cv2.typing.MatLike, solveMethod: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def getPerspectiveTransform(src: UMat, dst: UMat, solveMethod: int = ...) -> cv2.typing.MatLike: ...
|
|
|
|
@_typing.overload
|
|
def getRectSubPix(image: cv2.typing.MatLike, patchSize: cv2.typing.Size, center: cv2.typing.Point2f, patch: cv2.typing.MatLike | None = ..., patchType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def getRectSubPix(image: UMat, patchSize: cv2.typing.Size, center: cv2.typing.Point2f, patch: UMat | None = ..., patchType: int = ...) -> UMat: ...
|
|
|
|
def getRotationMatrix2D(center: cv2.typing.Point2f, angle: float, scale: float) -> cv2.typing.MatLike: ...
|
|
|
|
def getStructuringElement(shape: int, ksize: cv2.typing.Size, anchor: cv2.typing.Point = ...) -> cv2.typing.MatLike: ...
|
|
|
|
def getTextSize(text: str, fontFace: int, fontScale: float, thickness: int) -> tuple[cv2.typing.Size, int]: ...
|
|
|
|
def getThreadNum() -> int: ...
|
|
|
|
def getTickCount() -> int: ...
|
|
|
|
def getTickFrequency() -> float: ...
|
|
|
|
def getTrackbarPos(trackbarname: str, winname: str) -> int: ...
|
|
|
|
def getValidDisparityROI(roi1: cv2.typing.Rect, roi2: cv2.typing.Rect, minDisparity: int, numberOfDisparities: int, blockSize: int) -> cv2.typing.Rect: ...
|
|
|
|
def getVersionMajor() -> int: ...
|
|
|
|
def getVersionMinor() -> int: ...
|
|
|
|
def getVersionRevision() -> int: ...
|
|
|
|
def getVersionString() -> str: ...
|
|
|
|
def getWindowImageRect(winname: str) -> cv2.typing.Rect: ...
|
|
|
|
def getWindowProperty(winname: str, prop_id: int) -> float: ...
|
|
|
|
@_typing.overload
|
|
def goodFeaturesToTrack(image: cv2.typing.MatLike, maxCorners: int, qualityLevel: float, minDistance: float, corners: cv2.typing.MatLike | None = ..., mask: cv2.typing.MatLike | None = ..., blockSize: int = ..., useHarrisDetector: bool = ..., k: float = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def goodFeaturesToTrack(image: UMat, maxCorners: int, qualityLevel: float, minDistance: float, corners: UMat | None = ..., mask: UMat | None = ..., blockSize: int = ..., useHarrisDetector: bool = ..., k: float = ...) -> UMat: ...
|
|
@_typing.overload
|
|
def goodFeaturesToTrack(image: cv2.typing.MatLike, maxCorners: int, qualityLevel: float, minDistance: float, mask: cv2.typing.MatLike, blockSize: int, gradientSize: int, corners: cv2.typing.MatLike | None = ..., useHarrisDetector: bool = ..., k: float = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def goodFeaturesToTrack(image: UMat, maxCorners: int, qualityLevel: float, minDistance: float, mask: UMat, blockSize: int, gradientSize: int, corners: UMat | None = ..., useHarrisDetector: bool = ..., k: float = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def goodFeaturesToTrackWithQuality(image: cv2.typing.MatLike, maxCorners: int, qualityLevel: float, minDistance: float, mask: cv2.typing.MatLike, corners: cv2.typing.MatLike | None = ..., cornersQuality: cv2.typing.MatLike | None = ..., blockSize: int = ..., gradientSize: int = ..., useHarrisDetector: bool = ..., k: float = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def goodFeaturesToTrackWithQuality(image: UMat, maxCorners: int, qualityLevel: float, minDistance: float, mask: UMat, corners: UMat | None = ..., cornersQuality: UMat | None = ..., blockSize: int = ..., gradientSize: int = ..., useHarrisDetector: bool = ..., k: float = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def grabCut(img: cv2.typing.MatLike, mask: cv2.typing.MatLike, rect: cv2.typing.Rect, bgdModel: cv2.typing.MatLike, fgdModel: cv2.typing.MatLike, iterCount: int, mode: int = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def grabCut(img: UMat, mask: UMat, rect: cv2.typing.Rect, bgdModel: UMat, fgdModel: UMat, iterCount: int, mode: int = ...) -> tuple[UMat, UMat, UMat]: ...
|
|
|
|
def groupRectangles(rectList: _typing.Sequence[cv2.typing.Rect], groupThreshold: int, eps: float = ...) -> tuple[_typing.Sequence[cv2.typing.Rect], _typing.Sequence[int]]: ...
|
|
|
|
@_typing.overload
|
|
def hasNonZero(src: cv2.typing.MatLike) -> bool: ...
|
|
@_typing.overload
|
|
def hasNonZero(src: UMat) -> bool: ...
|
|
|
|
def haveImageReader(filename: str) -> bool: ...
|
|
|
|
def haveImageWriter(filename: str) -> bool: ...
|
|
|
|
def haveOpenVX() -> bool: ...
|
|
|
|
@_typing.overload
|
|
def hconcat(src: _typing.Sequence[cv2.typing.MatLike], dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def hconcat(src: _typing.Sequence[UMat], dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def idct(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., flags: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def idct(src: UMat, dst: UMat | None = ..., flags: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def idft(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., flags: int = ..., nonzeroRows: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def idft(src: UMat, dst: UMat | None = ..., flags: int = ..., nonzeroRows: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def illuminationChange(src: cv2.typing.MatLike, mask: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., alpha: float = ..., beta: float = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def illuminationChange(src: UMat, mask: UMat, dst: UMat | None = ..., alpha: float = ..., beta: float = ...) -> UMat: ...
|
|
|
|
def imcount(filename: str, flags: int = ...) -> int: ...
|
|
|
|
@_typing.overload
|
|
def imdecode(buf: cv2.typing.MatLike, flags: int) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def imdecode(buf: UMat, flags: int) -> cv2.typing.MatLike: ...
|
|
|
|
@_typing.overload
|
|
def imdecodemulti(buf: cv2.typing.MatLike, flags: int, mats: _typing.Sequence[cv2.typing.MatLike] | None = ..., range: cv2.typing.Range = ...) -> tuple[bool, _typing.Sequence[cv2.typing.MatLike]]: ...
|
|
@_typing.overload
|
|
def imdecodemulti(buf: UMat, flags: int, mats: _typing.Sequence[cv2.typing.MatLike] | None = ..., range: cv2.typing.Range = ...) -> tuple[bool, _typing.Sequence[cv2.typing.MatLike]]: ...
|
|
|
|
@_typing.overload
|
|
def imencode(ext: str, img: cv2.typing.MatLike, params: _typing.Sequence[int] = ...) -> tuple[bool, numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]]]: ...
|
|
@_typing.overload
|
|
def imencode(ext: str, img: UMat, params: _typing.Sequence[int] = ...) -> tuple[bool, numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]]]: ...
|
|
|
|
@_typing.overload
|
|
def imread(filename: str, flags: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def imread(filename: str, dst: cv2.typing.MatLike | None = ..., flags: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def imread(filename: str, dst: UMat | None = ..., flags: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def imreadmulti(filename: str, mats: _typing.Sequence[cv2.typing.MatLike] | None = ..., flags: int = ...) -> tuple[bool, _typing.Sequence[cv2.typing.MatLike]]: ...
|
|
@_typing.overload
|
|
def imreadmulti(filename: str, start: int, count: int, mats: _typing.Sequence[cv2.typing.MatLike] | None = ..., flags: int = ...) -> tuple[bool, _typing.Sequence[cv2.typing.MatLike]]: ...
|
|
|
|
@_typing.overload
|
|
def imshow(winname: str, mat: cv2.typing.MatLike) -> None: ...
|
|
@_typing.overload
|
|
def imshow(winname: str, mat: cv2.cuda.GpuMat) -> None: ...
|
|
@_typing.overload
|
|
def imshow(winname: str, mat: UMat) -> None: ...
|
|
|
|
@_typing.overload
|
|
def imwrite(filename: str, img: cv2.typing.MatLike, params: _typing.Sequence[int] = ...) -> bool: ...
|
|
@_typing.overload
|
|
def imwrite(filename: str, img: UMat, params: _typing.Sequence[int] = ...) -> bool: ...
|
|
|
|
@_typing.overload
|
|
def imwritemulti(filename: str, img: _typing.Sequence[cv2.typing.MatLike], params: _typing.Sequence[int] = ...) -> bool: ...
|
|
@_typing.overload
|
|
def imwritemulti(filename: str, img: _typing.Sequence[UMat], params: _typing.Sequence[int] = ...) -> bool: ...
|
|
|
|
@_typing.overload
|
|
def inRange(src: cv2.typing.MatLike, lowerb: cv2.typing.MatLike, upperb: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def inRange(src: UMat, lowerb: UMat, upperb: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def initCameraMatrix2D(objectPoints: _typing.Sequence[cv2.typing.MatLike], imagePoints: _typing.Sequence[cv2.typing.MatLike], imageSize: cv2.typing.Size, aspectRatio: float = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def initCameraMatrix2D(objectPoints: _typing.Sequence[UMat], imagePoints: _typing.Sequence[UMat], imageSize: cv2.typing.Size, aspectRatio: float = ...) -> cv2.typing.MatLike: ...
|
|
|
|
@_typing.overload
|
|
def initInverseRectificationMap(cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, R: cv2.typing.MatLike, newCameraMatrix: cv2.typing.MatLike, size: cv2.typing.Size, m1type: int, map1: cv2.typing.MatLike | None = ..., map2: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def initInverseRectificationMap(cameraMatrix: UMat, distCoeffs: UMat, R: UMat, newCameraMatrix: UMat, size: cv2.typing.Size, m1type: int, map1: UMat | None = ..., map2: UMat | None = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def initUndistortRectifyMap(cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, R: cv2.typing.MatLike, newCameraMatrix: cv2.typing.MatLike, size: cv2.typing.Size, m1type: int, map1: cv2.typing.MatLike | None = ..., map2: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def initUndistortRectifyMap(cameraMatrix: UMat, distCoeffs: UMat, R: UMat, newCameraMatrix: UMat, size: cv2.typing.Size, m1type: int, map1: UMat | None = ..., map2: UMat | None = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def inpaint(src: cv2.typing.MatLike, inpaintMask: cv2.typing.MatLike, inpaintRadius: float, flags: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def inpaint(src: UMat, inpaintMask: UMat, inpaintRadius: float, flags: int, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def insertChannel(src: cv2.typing.MatLike, dst: cv2.typing.MatLike, coi: int) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def insertChannel(src: UMat, dst: UMat, coi: int) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def integral(src: cv2.typing.MatLike, sum: cv2.typing.MatLike | None = ..., sdepth: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def integral(src: UMat, sum: UMat | None = ..., sdepth: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def integral2(src: cv2.typing.MatLike, sum: cv2.typing.MatLike | None = ..., sqsum: cv2.typing.MatLike | None = ..., sdepth: int = ..., sqdepth: int = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def integral2(src: UMat, sum: UMat | None = ..., sqsum: UMat | None = ..., sdepth: int = ..., sqdepth: int = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def integral3(src: cv2.typing.MatLike, sum: cv2.typing.MatLike | None = ..., sqsum: cv2.typing.MatLike | None = ..., tilted: cv2.typing.MatLike | None = ..., sdepth: int = ..., sqdepth: int = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def integral3(src: UMat, sum: UMat | None = ..., sqsum: UMat | None = ..., tilted: UMat | None = ..., sdepth: int = ..., sqdepth: int = ...) -> tuple[UMat, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def intersectConvexConvex(p1: cv2.typing.MatLike, p2: cv2.typing.MatLike, p12: cv2.typing.MatLike | None = ..., handleNested: bool = ...) -> tuple[float, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def intersectConvexConvex(p1: UMat, p2: UMat, p12: UMat | None = ..., handleNested: bool = ...) -> tuple[float, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def invert(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., flags: int = ...) -> tuple[float, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def invert(src: UMat, dst: UMat | None = ..., flags: int = ...) -> tuple[float, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def invertAffineTransform(M: cv2.typing.MatLike, iM: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def invertAffineTransform(M: UMat, iM: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def isContourConvex(contour: cv2.typing.MatLike) -> bool: ...
|
|
@_typing.overload
|
|
def isContourConvex(contour: UMat) -> bool: ...
|
|
|
|
@_typing.overload
|
|
def kmeans(data: cv2.typing.MatLike, K: int, bestLabels: cv2.typing.MatLike, criteria: cv2.typing.TermCriteria, attempts: int, flags: int, centers: cv2.typing.MatLike | None = ...) -> tuple[float, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def kmeans(data: UMat, K: int, bestLabels: UMat, criteria: cv2.typing.TermCriteria, attempts: int, flags: int, centers: UMat | None = ...) -> tuple[float, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def line(img: cv2.typing.MatLike, pt1: cv2.typing.Point, pt2: cv2.typing.Point, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ..., shift: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def line(img: UMat, pt1: cv2.typing.Point, pt2: cv2.typing.Point, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ..., shift: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def linearPolar(src: cv2.typing.MatLike, center: cv2.typing.Point2f, maxRadius: float, flags: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def linearPolar(src: UMat, center: cv2.typing.Point2f, maxRadius: float, flags: int, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def log(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def log(src: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def logPolar(src: cv2.typing.MatLike, center: cv2.typing.Point2f, M: float, flags: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def logPolar(src: UMat, center: cv2.typing.Point2f, M: float, flags: int, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def magnitude(x: cv2.typing.MatLike, y: cv2.typing.MatLike, magnitude: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def magnitude(x: UMat, y: UMat, magnitude: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def matMulDeriv(A: cv2.typing.MatLike, B: cv2.typing.MatLike, dABdA: cv2.typing.MatLike | None = ..., dABdB: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def matMulDeriv(A: UMat, B: UMat, dABdA: UMat | None = ..., dABdB: UMat | None = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def matchShapes(contour1: cv2.typing.MatLike, contour2: cv2.typing.MatLike, method: int, parameter: float) -> float: ...
|
|
@_typing.overload
|
|
def matchShapes(contour1: UMat, contour2: UMat, method: int, parameter: float) -> float: ...
|
|
|
|
@_typing.overload
|
|
def matchTemplate(image: cv2.typing.MatLike, templ: cv2.typing.MatLike, method: int, result: cv2.typing.MatLike | None = ..., mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def matchTemplate(image: UMat, templ: UMat, method: int, result: UMat | None = ..., mask: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def max(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def max(src1: UMat, src2: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def mean(src: cv2.typing.MatLike, mask: cv2.typing.MatLike | None = ...) -> cv2.typing.Scalar: ...
|
|
@_typing.overload
|
|
def mean(src: UMat, mask: UMat | None = ...) -> cv2.typing.Scalar: ...
|
|
|
|
@_typing.overload
|
|
def meanShift(probImage: cv2.typing.MatLike, window: cv2.typing.Rect, criteria: cv2.typing.TermCriteria) -> tuple[int, cv2.typing.Rect]: ...
|
|
@_typing.overload
|
|
def meanShift(probImage: UMat, window: cv2.typing.Rect, criteria: cv2.typing.TermCriteria) -> tuple[int, cv2.typing.Rect]: ...
|
|
|
|
@_typing.overload
|
|
def meanStdDev(src: cv2.typing.MatLike, mean: cv2.typing.MatLike | None = ..., stddev: cv2.typing.MatLike | None = ..., mask: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def meanStdDev(src: UMat, mean: UMat | None = ..., stddev: UMat | None = ..., mask: UMat | None = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def medianBlur(src: cv2.typing.MatLike, ksize: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def medianBlur(src: UMat, ksize: int, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def merge(mv: _typing.Sequence[cv2.typing.MatLike], dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def merge(mv: _typing.Sequence[UMat], dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def min(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def min(src1: UMat, src2: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def minAreaRect(points: cv2.typing.MatLike) -> cv2.typing.RotatedRect: ...
|
|
@_typing.overload
|
|
def minAreaRect(points: UMat) -> cv2.typing.RotatedRect: ...
|
|
|
|
@_typing.overload
|
|
def minEnclosingCircle(points: cv2.typing.MatLike) -> tuple[cv2.typing.Point2f, float]: ...
|
|
@_typing.overload
|
|
def minEnclosingCircle(points: UMat) -> tuple[cv2.typing.Point2f, float]: ...
|
|
|
|
@_typing.overload
|
|
def minEnclosingTriangle(points: cv2.typing.MatLike, triangle: cv2.typing.MatLike | None = ...) -> tuple[float, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def minEnclosingTriangle(points: UMat, triangle: UMat | None = ...) -> tuple[float, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def minMaxLoc(src: cv2.typing.MatLike, mask: cv2.typing.MatLike | None = ...) -> tuple[float, float, cv2.typing.Point, cv2.typing.Point]: ...
|
|
@_typing.overload
|
|
def minMaxLoc(src: UMat, mask: UMat | None = ...) -> tuple[float, float, cv2.typing.Point, cv2.typing.Point]: ...
|
|
|
|
@_typing.overload
|
|
def mixChannels(src: _typing.Sequence[cv2.typing.MatLike], dst: _typing.Sequence[cv2.typing.MatLike], fromTo: _typing.Sequence[int]) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def mixChannels(src: _typing.Sequence[UMat], dst: _typing.Sequence[UMat], fromTo: _typing.Sequence[int]) -> _typing.Sequence[UMat]: ...
|
|
|
|
@_typing.overload
|
|
def moments(array: cv2.typing.MatLike, binaryImage: bool = ...) -> cv2.typing.Moments: ...
|
|
@_typing.overload
|
|
def moments(array: UMat, binaryImage: bool = ...) -> cv2.typing.Moments: ...
|
|
|
|
@_typing.overload
|
|
def morphologyEx(src: cv2.typing.MatLike, op: int, kernel: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., anchor: cv2.typing.Point = ..., iterations: int = ..., borderType: int = ..., borderValue: cv2.typing.Scalar = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def morphologyEx(src: UMat, op: int, kernel: UMat, dst: UMat | None = ..., anchor: cv2.typing.Point = ..., iterations: int = ..., borderType: int = ..., borderValue: cv2.typing.Scalar = ...) -> UMat: ...
|
|
|
|
def moveWindow(winname: str, x: int, y: int) -> None: ...
|
|
|
|
@_typing.overload
|
|
def mulSpectrums(a: cv2.typing.MatLike, b: cv2.typing.MatLike, flags: int, c: cv2.typing.MatLike | None = ..., conjB: bool = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def mulSpectrums(a: UMat, b: UMat, flags: int, c: UMat | None = ..., conjB: bool = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def mulTransposed(src: cv2.typing.MatLike, aTa: bool, dst: cv2.typing.MatLike | None = ..., delta: cv2.typing.MatLike | None = ..., scale: float = ..., dtype: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def mulTransposed(src: UMat, aTa: bool, dst: UMat | None = ..., delta: UMat | None = ..., scale: float = ..., dtype: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def multiply(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., scale: float = ..., dtype: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def multiply(src1: UMat, src2: UMat, dst: UMat | None = ..., scale: float = ..., dtype: int = ...) -> UMat: ...
|
|
|
|
def namedWindow(winname: str, flags: int = ...) -> None: ...
|
|
|
|
@_typing.overload
|
|
def norm(src1: cv2.typing.MatLike, normType: int = ..., mask: cv2.typing.MatLike | None = ...) -> float: ...
|
|
@_typing.overload
|
|
def norm(src1: UMat, normType: int = ..., mask: UMat | None = ...) -> float: ...
|
|
@_typing.overload
|
|
def norm(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, normType: int = ..., mask: cv2.typing.MatLike | None = ...) -> float: ...
|
|
@_typing.overload
|
|
def norm(src1: UMat, src2: UMat, normType: int = ..., mask: UMat | None = ...) -> float: ...
|
|
|
|
@_typing.overload
|
|
def normalize(src: cv2.typing.MatLike, dst: cv2.typing.MatLike, alpha: float = ..., beta: float = ..., norm_type: int = ..., dtype: int = ..., mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def normalize(src: UMat, dst: UMat, alpha: float = ..., beta: float = ..., norm_type: int = ..., dtype: int = ..., mask: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def patchNaNs(a: cv2.typing.MatLike, val: float = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def patchNaNs(a: UMat, val: float = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def pencilSketch(src: cv2.typing.MatLike, dst1: cv2.typing.MatLike | None = ..., dst2: cv2.typing.MatLike | None = ..., sigma_s: float = ..., sigma_r: float = ..., shade_factor: float = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def pencilSketch(src: UMat, dst1: UMat | None = ..., dst2: UMat | None = ..., sigma_s: float = ..., sigma_r: float = ..., shade_factor: float = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def perspectiveTransform(src: cv2.typing.MatLike, m: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def perspectiveTransform(src: UMat, m: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def phase(x: cv2.typing.MatLike, y: cv2.typing.MatLike, angle: cv2.typing.MatLike | None = ..., angleInDegrees: bool = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def phase(x: UMat, y: UMat, angle: UMat | None = ..., angleInDegrees: bool = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def phaseCorrelate(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, window: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.Point2d, float]: ...
|
|
@_typing.overload
|
|
def phaseCorrelate(src1: UMat, src2: UMat, window: UMat | None = ...) -> tuple[cv2.typing.Point2d, float]: ...
|
|
|
|
@_typing.overload
|
|
def pointPolygonTest(contour: cv2.typing.MatLike, pt: cv2.typing.Point2f, measureDist: bool) -> float: ...
|
|
@_typing.overload
|
|
def pointPolygonTest(contour: UMat, pt: cv2.typing.Point2f, measureDist: bool) -> float: ...
|
|
|
|
@_typing.overload
|
|
def polarToCart(magnitude: cv2.typing.MatLike, angle: cv2.typing.MatLike, x: cv2.typing.MatLike | None = ..., y: cv2.typing.MatLike | None = ..., angleInDegrees: bool = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def polarToCart(magnitude: UMat, angle: UMat, x: UMat | None = ..., y: UMat | None = ..., angleInDegrees: bool = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
def pollKey() -> int: ...
|
|
|
|
@_typing.overload
|
|
def polylines(img: cv2.typing.MatLike, pts: _typing.Sequence[cv2.typing.MatLike], isClosed: bool, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ..., shift: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def polylines(img: UMat, pts: _typing.Sequence[UMat], isClosed: bool, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ..., shift: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def pow(src: cv2.typing.MatLike, power: float, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def pow(src: UMat, power: float, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def preCornerDetect(src: cv2.typing.MatLike, ksize: int, dst: cv2.typing.MatLike | None = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def preCornerDetect(src: UMat, ksize: int, dst: UMat | None = ..., borderType: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def projectPoints(objectPoints: cv2.typing.MatLike, rvec: cv2.typing.MatLike, tvec: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, imagePoints: cv2.typing.MatLike | None = ..., jacobian: cv2.typing.MatLike | None = ..., aspectRatio: float = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def projectPoints(objectPoints: UMat, rvec: UMat, tvec: UMat, cameraMatrix: UMat, distCoeffs: UMat, imagePoints: UMat | None = ..., jacobian: UMat | None = ..., aspectRatio: float = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def putText(img: cv2.typing.MatLike, text: str, org: cv2.typing.Point, fontFace: int, fontScale: float, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ..., bottomLeftOrigin: bool = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def putText(img: UMat, text: str, org: cv2.typing.Point, fontFace: int, fontScale: float, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ..., bottomLeftOrigin: bool = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def pyrDown(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., dstsize: cv2.typing.Size = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def pyrDown(src: UMat, dst: UMat | None = ..., dstsize: cv2.typing.Size = ..., borderType: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def pyrMeanShiftFiltering(src: cv2.typing.MatLike, sp: float, sr: float, dst: cv2.typing.MatLike | None = ..., maxLevel: int = ..., termcrit: cv2.typing.TermCriteria = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def pyrMeanShiftFiltering(src: UMat, sp: float, sr: float, dst: UMat | None = ..., maxLevel: int = ..., termcrit: cv2.typing.TermCriteria = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def pyrUp(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., dstsize: cv2.typing.Size = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def pyrUp(src: UMat, dst: UMat | None = ..., dstsize: cv2.typing.Size = ..., borderType: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def randShuffle(dst: cv2.typing.MatLike, iterFactor: float = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def randShuffle(dst: UMat, iterFactor: float = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def randn(dst: cv2.typing.MatLike, mean: cv2.typing.MatLike, stddev: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def randn(dst: UMat, mean: UMat, stddev: UMat) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def randu(dst: cv2.typing.MatLike, low: cv2.typing.MatLike, high: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def randu(dst: UMat, low: UMat, high: UMat) -> UMat: ...
|
|
|
|
def readOpticalFlow(path: str) -> cv2.typing.MatLike: ...
|
|
|
|
@_typing.overload
|
|
def recoverPose(points1: cv2.typing.MatLike, points2: cv2.typing.MatLike, cameraMatrix1: cv2.typing.MatLike, distCoeffs1: cv2.typing.MatLike, cameraMatrix2: cv2.typing.MatLike, distCoeffs2: cv2.typing.MatLike, E: cv2.typing.MatLike | None = ..., R: cv2.typing.MatLike | None = ..., t: cv2.typing.MatLike | None = ..., method: int = ..., prob: float = ..., threshold: float = ..., mask: cv2.typing.MatLike | None = ...) -> tuple[int, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def recoverPose(points1: UMat, points2: UMat, cameraMatrix1: UMat, distCoeffs1: UMat, cameraMatrix2: UMat, distCoeffs2: UMat, E: UMat | None = ..., R: UMat | None = ..., t: UMat | None = ..., method: int = ..., prob: float = ..., threshold: float = ..., mask: UMat | None = ...) -> tuple[int, UMat, UMat, UMat, UMat]: ...
|
|
@_typing.overload
|
|
def recoverPose(E: cv2.typing.MatLike, points1: cv2.typing.MatLike, points2: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, R: cv2.typing.MatLike | None = ..., t: cv2.typing.MatLike | None = ..., mask: cv2.typing.MatLike | None = ...) -> tuple[int, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def recoverPose(E: UMat, points1: UMat, points2: UMat, cameraMatrix: UMat, R: UMat | None = ..., t: UMat | None = ..., mask: UMat | None = ...) -> tuple[int, UMat, UMat, UMat]: ...
|
|
@_typing.overload
|
|
def recoverPose(E: cv2.typing.MatLike, points1: cv2.typing.MatLike, points2: cv2.typing.MatLike, R: cv2.typing.MatLike | None = ..., t: cv2.typing.MatLike | None = ..., focal: float = ..., pp: cv2.typing.Point2d = ..., mask: cv2.typing.MatLike | None = ...) -> tuple[int, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def recoverPose(E: UMat, points1: UMat, points2: UMat, R: UMat | None = ..., t: UMat | None = ..., focal: float = ..., pp: cv2.typing.Point2d = ..., mask: UMat | None = ...) -> tuple[int, UMat, UMat, UMat]: ...
|
|
@_typing.overload
|
|
def recoverPose(E: cv2.typing.MatLike, points1: cv2.typing.MatLike, points2: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, distanceThresh: float, R: cv2.typing.MatLike | None = ..., t: cv2.typing.MatLike | None = ..., mask: cv2.typing.MatLike | None = ..., triangulatedPoints: cv2.typing.MatLike | None = ...) -> tuple[int, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def recoverPose(E: UMat, points1: UMat, points2: UMat, cameraMatrix: UMat, distanceThresh: float, R: UMat | None = ..., t: UMat | None = ..., mask: UMat | None = ..., triangulatedPoints: UMat | None = ...) -> tuple[int, UMat, UMat, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def rectangle(img: cv2.typing.MatLike, pt1: cv2.typing.Point, pt2: cv2.typing.Point, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ..., shift: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def rectangle(img: UMat, pt1: cv2.typing.Point, pt2: cv2.typing.Point, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ..., shift: int = ...) -> UMat: ...
|
|
@_typing.overload
|
|
def rectangle(img: cv2.typing.MatLike, rec: cv2.typing.Rect, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ..., shift: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def rectangle(img: UMat, rec: cv2.typing.Rect, color: cv2.typing.Scalar, thickness: int = ..., lineType: int = ..., shift: int = ...) -> UMat: ...
|
|
|
|
def rectangleIntersectionArea(a: cv2.typing.Rect2d, b: cv2.typing.Rect2d) -> float: ...
|
|
|
|
@_typing.overload
|
|
def rectify3Collinear(cameraMatrix1: cv2.typing.MatLike, distCoeffs1: cv2.typing.MatLike, cameraMatrix2: cv2.typing.MatLike, distCoeffs2: cv2.typing.MatLike, cameraMatrix3: cv2.typing.MatLike, distCoeffs3: cv2.typing.MatLike, imgpt1: _typing.Sequence[cv2.typing.MatLike], imgpt3: _typing.Sequence[cv2.typing.MatLike], imageSize: cv2.typing.Size, R12: cv2.typing.MatLike, T12: cv2.typing.MatLike, R13: cv2.typing.MatLike, T13: cv2.typing.MatLike, alpha: float, newImgSize: cv2.typing.Size, flags: int, R1: cv2.typing.MatLike | None = ..., R2: cv2.typing.MatLike | None = ..., R3: cv2.typing.MatLike | None = ..., P1: cv2.typing.MatLike | None = ..., P2: cv2.typing.MatLike | None = ..., P3: cv2.typing.MatLike | None = ..., Q: cv2.typing.MatLike | None = ...) -> tuple[float, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.Rect, cv2.typing.Rect]: ...
|
|
@_typing.overload
|
|
def rectify3Collinear(cameraMatrix1: UMat, distCoeffs1: UMat, cameraMatrix2: UMat, distCoeffs2: UMat, cameraMatrix3: UMat, distCoeffs3: UMat, imgpt1: _typing.Sequence[UMat], imgpt3: _typing.Sequence[UMat], imageSize: cv2.typing.Size, R12: UMat, T12: UMat, R13: UMat, T13: UMat, alpha: float, newImgSize: cv2.typing.Size, flags: int, R1: UMat | None = ..., R2: UMat | None = ..., R3: UMat | None = ..., P1: UMat | None = ..., P2: UMat | None = ..., P3: UMat | None = ..., Q: UMat | None = ...) -> tuple[float, UMat, UMat, UMat, UMat, UMat, UMat, UMat, cv2.typing.Rect, cv2.typing.Rect]: ...
|
|
|
|
@_typing.overload
|
|
def reduce(src: cv2.typing.MatLike, dim: int, rtype: int, dst: cv2.typing.MatLike | None = ..., dtype: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def reduce(src: UMat, dim: int, rtype: int, dst: UMat | None = ..., dtype: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def reduceArgMax(src: cv2.typing.MatLike, axis: int, dst: cv2.typing.MatLike | None = ..., lastIndex: bool = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def reduceArgMax(src: UMat, axis: int, dst: UMat | None = ..., lastIndex: bool = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def reduceArgMin(src: cv2.typing.MatLike, axis: int, dst: cv2.typing.MatLike | None = ..., lastIndex: bool = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def reduceArgMin(src: UMat, axis: int, dst: UMat | None = ..., lastIndex: bool = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def remap(src: cv2.typing.MatLike, map1: cv2.typing.MatLike, map2: cv2.typing.MatLike, interpolation: int, dst: cv2.typing.MatLike | None = ..., borderMode: int = ..., borderValue: cv2.typing.Scalar = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def remap(src: UMat, map1: UMat, map2: UMat, interpolation: int, dst: UMat | None = ..., borderMode: int = ..., borderValue: cv2.typing.Scalar = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def repeat(src: cv2.typing.MatLike, ny: int, nx: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def repeat(src: UMat, ny: int, nx: int, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def reprojectImageTo3D(disparity: cv2.typing.MatLike, Q: cv2.typing.MatLike, _3dImage: cv2.typing.MatLike | None = ..., handleMissingValues: bool = ..., ddepth: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def reprojectImageTo3D(disparity: UMat, Q: UMat, _3dImage: UMat | None = ..., handleMissingValues: bool = ..., ddepth: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def resize(src: cv2.typing.MatLike, dsize: cv2.typing.Size | None, dst: cv2.typing.MatLike | None = ..., fx: float = ..., fy: float = ..., interpolation: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def resize(src: UMat, dsize: cv2.typing.Size | None, dst: UMat | None = ..., fx: float = ..., fy: float = ..., interpolation: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def resizeWindow(winname: str, width: int, height: int) -> None: ...
|
|
@_typing.overload
|
|
def resizeWindow(winname: str, size: cv2.typing.Size) -> None: ...
|
|
|
|
@_typing.overload
|
|
def rotate(src: cv2.typing.MatLike, rotateCode: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def rotate(src: UMat, rotateCode: int, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def rotatedRectangleIntersection(rect1: cv2.typing.RotatedRect, rect2: cv2.typing.RotatedRect, intersectingRegion: cv2.typing.MatLike | None = ...) -> tuple[int, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def rotatedRectangleIntersection(rect1: cv2.typing.RotatedRect, rect2: cv2.typing.RotatedRect, intersectingRegion: UMat | None = ...) -> tuple[int, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def sampsonDistance(pt1: cv2.typing.MatLike, pt2: cv2.typing.MatLike, F: cv2.typing.MatLike) -> float: ...
|
|
@_typing.overload
|
|
def sampsonDistance(pt1: UMat, pt2: UMat, F: UMat) -> float: ...
|
|
|
|
@_typing.overload
|
|
def scaleAdd(src1: cv2.typing.MatLike, alpha: float, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def scaleAdd(src1: UMat, alpha: float, src2: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def seamlessClone(src: cv2.typing.MatLike, dst: cv2.typing.MatLike, mask: cv2.typing.MatLike, p: cv2.typing.Point, flags: int, blend: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def seamlessClone(src: UMat, dst: UMat, mask: UMat, p: cv2.typing.Point, flags: int, blend: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def selectROI(windowName: str, img: cv2.typing.MatLike, showCrosshair: bool = ..., fromCenter: bool = ..., printNotice: bool = ...) -> cv2.typing.Rect: ...
|
|
@_typing.overload
|
|
def selectROI(windowName: str, img: UMat, showCrosshair: bool = ..., fromCenter: bool = ..., printNotice: bool = ...) -> cv2.typing.Rect: ...
|
|
@_typing.overload
|
|
def selectROI(img: cv2.typing.MatLike, showCrosshair: bool = ..., fromCenter: bool = ..., printNotice: bool = ...) -> cv2.typing.Rect: ...
|
|
@_typing.overload
|
|
def selectROI(img: UMat, showCrosshair: bool = ..., fromCenter: bool = ..., printNotice: bool = ...) -> cv2.typing.Rect: ...
|
|
|
|
@_typing.overload
|
|
def selectROIs(windowName: str, img: cv2.typing.MatLike, showCrosshair: bool = ..., fromCenter: bool = ..., printNotice: bool = ...) -> _typing.Sequence[cv2.typing.Rect]: ...
|
|
@_typing.overload
|
|
def selectROIs(windowName: str, img: UMat, showCrosshair: bool = ..., fromCenter: bool = ..., printNotice: bool = ...) -> _typing.Sequence[cv2.typing.Rect]: ...
|
|
|
|
@_typing.overload
|
|
def sepFilter2D(src: cv2.typing.MatLike, ddepth: int, kernelX: cv2.typing.MatLike, kernelY: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., anchor: cv2.typing.Point = ..., delta: float = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def sepFilter2D(src: UMat, ddepth: int, kernelX: UMat, kernelY: UMat, dst: UMat | None = ..., anchor: cv2.typing.Point = ..., delta: float = ..., borderType: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def setIdentity(mtx: cv2.typing.MatLike, s: cv2.typing.Scalar = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def setIdentity(mtx: UMat, s: cv2.typing.Scalar = ...) -> UMat: ...
|
|
|
|
def setLogLevel(level: int) -> int: ...
|
|
|
|
def setNumThreads(nthreads: int) -> None: ...
|
|
|
|
def setRNGSeed(seed: int) -> None: ...
|
|
|
|
def setTrackbarMax(trackbarname: str, winname: str, maxval: int) -> None: ...
|
|
|
|
def setTrackbarMin(trackbarname: str, winname: str, minval: int) -> None: ...
|
|
|
|
def setTrackbarPos(trackbarname: str, winname: str, pos: int) -> None: ...
|
|
|
|
def setUseOpenVX(flag: bool) -> None: ...
|
|
|
|
def setUseOptimized(onoff: bool) -> None: ...
|
|
|
|
def setWindowProperty(winname: str, prop_id: int, prop_value: float) -> None: ...
|
|
|
|
def setWindowTitle(winname: str, title: str) -> None: ...
|
|
|
|
@_typing.overload
|
|
def solve(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., flags: int = ...) -> tuple[bool, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def solve(src1: UMat, src2: UMat, dst: UMat | None = ..., flags: int = ...) -> tuple[bool, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def solveCubic(coeffs: cv2.typing.MatLike, roots: cv2.typing.MatLike | None = ...) -> tuple[int, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def solveCubic(coeffs: UMat, roots: UMat | None = ...) -> tuple[int, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def solveLP(Func: cv2.typing.MatLike, Constr: cv2.typing.MatLike, constr_eps: float, z: cv2.typing.MatLike | None = ...) -> tuple[int, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def solveLP(Func: UMat, Constr: UMat, constr_eps: float, z: UMat | None = ...) -> tuple[int, UMat]: ...
|
|
@_typing.overload
|
|
def solveLP(Func: cv2.typing.MatLike, Constr: cv2.typing.MatLike, z: cv2.typing.MatLike | None = ...) -> tuple[int, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def solveLP(Func: UMat, Constr: UMat, z: UMat | None = ...) -> tuple[int, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def solveP3P(objectPoints: cv2.typing.MatLike, imagePoints: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, flags: int, rvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., tvecs: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> tuple[int, _typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike]]: ...
|
|
@_typing.overload
|
|
def solveP3P(objectPoints: UMat, imagePoints: UMat, cameraMatrix: UMat, distCoeffs: UMat, flags: int, rvecs: _typing.Sequence[UMat] | None = ..., tvecs: _typing.Sequence[UMat] | None = ...) -> tuple[int, _typing.Sequence[UMat], _typing.Sequence[UMat]]: ...
|
|
|
|
@_typing.overload
|
|
def solvePnP(objectPoints: cv2.typing.MatLike, imagePoints: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, rvec: cv2.typing.MatLike | None = ..., tvec: cv2.typing.MatLike | None = ..., useExtrinsicGuess: bool = ..., flags: int = ...) -> tuple[bool, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def solvePnP(objectPoints: UMat, imagePoints: UMat, cameraMatrix: UMat, distCoeffs: UMat, rvec: UMat | None = ..., tvec: UMat | None = ..., useExtrinsicGuess: bool = ..., flags: int = ...) -> tuple[bool, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def solvePnPGeneric(objectPoints: cv2.typing.MatLike, imagePoints: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, rvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., tvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., useExtrinsicGuess: bool = ..., flags: SolvePnPMethod = ..., rvec: cv2.typing.MatLike | None = ..., tvec: cv2.typing.MatLike | None = ..., reprojectionError: cv2.typing.MatLike | None = ...) -> tuple[int, _typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike], cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def solvePnPGeneric(objectPoints: UMat, imagePoints: UMat, cameraMatrix: UMat, distCoeffs: UMat, rvecs: _typing.Sequence[UMat] | None = ..., tvecs: _typing.Sequence[UMat] | None = ..., useExtrinsicGuess: bool = ..., flags: SolvePnPMethod = ..., rvec: UMat | None = ..., tvec: UMat | None = ..., reprojectionError: UMat | None = ...) -> tuple[int, _typing.Sequence[UMat], _typing.Sequence[UMat], UMat]: ...
|
|
|
|
@_typing.overload
|
|
def solvePnPRansac(objectPoints: cv2.typing.MatLike, imagePoints: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, rvec: cv2.typing.MatLike | None = ..., tvec: cv2.typing.MatLike | None = ..., useExtrinsicGuess: bool = ..., iterationsCount: int = ..., reprojectionError: float = ..., confidence: float = ..., inliers: cv2.typing.MatLike | None = ..., flags: int = ...) -> tuple[bool, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def solvePnPRansac(objectPoints: UMat, imagePoints: UMat, cameraMatrix: UMat, distCoeffs: UMat, rvec: UMat | None = ..., tvec: UMat | None = ..., useExtrinsicGuess: bool = ..., iterationsCount: int = ..., reprojectionError: float = ..., confidence: float = ..., inliers: UMat | None = ..., flags: int = ...) -> tuple[bool, UMat, UMat, UMat]: ...
|
|
@_typing.overload
|
|
def solvePnPRansac(objectPoints: cv2.typing.MatLike, imagePoints: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, rvec: cv2.typing.MatLike | None = ..., tvec: cv2.typing.MatLike | None = ..., inliers: cv2.typing.MatLike | None = ..., params: UsacParams = ...) -> tuple[bool, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def solvePnPRansac(objectPoints: UMat, imagePoints: UMat, cameraMatrix: UMat, distCoeffs: UMat, rvec: UMat | None = ..., tvec: UMat | None = ..., inliers: UMat | None = ..., params: UsacParams = ...) -> tuple[bool, UMat, UMat, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def solvePnPRefineLM(objectPoints: cv2.typing.MatLike, imagePoints: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, rvec: cv2.typing.MatLike, tvec: cv2.typing.MatLike, criteria: cv2.typing.TermCriteria = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def solvePnPRefineLM(objectPoints: UMat, imagePoints: UMat, cameraMatrix: UMat, distCoeffs: UMat, rvec: UMat, tvec: UMat, criteria: cv2.typing.TermCriteria = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def solvePnPRefineVVS(objectPoints: cv2.typing.MatLike, imagePoints: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, rvec: cv2.typing.MatLike, tvec: cv2.typing.MatLike, criteria: cv2.typing.TermCriteria = ..., VVSlambda: float = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def solvePnPRefineVVS(objectPoints: UMat, imagePoints: UMat, cameraMatrix: UMat, distCoeffs: UMat, rvec: UMat, tvec: UMat, criteria: cv2.typing.TermCriteria = ..., VVSlambda: float = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def solvePoly(coeffs: cv2.typing.MatLike, roots: cv2.typing.MatLike | None = ..., maxIters: int = ...) -> tuple[float, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def solvePoly(coeffs: UMat, roots: UMat | None = ..., maxIters: int = ...) -> tuple[float, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def sort(src: cv2.typing.MatLike, flags: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def sort(src: UMat, flags: int, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def sortIdx(src: cv2.typing.MatLike, flags: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def sortIdx(src: UMat, flags: int, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def spatialGradient(src: cv2.typing.MatLike, dx: cv2.typing.MatLike | None = ..., dy: cv2.typing.MatLike | None = ..., ksize: int = ..., borderType: int = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def spatialGradient(src: UMat, dx: UMat | None = ..., dy: UMat | None = ..., ksize: int = ..., borderType: int = ...) -> tuple[UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def split(m: cv2.typing.MatLike, mv: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def split(m: UMat, mv: _typing.Sequence[UMat] | None = ...) -> _typing.Sequence[UMat]: ...
|
|
|
|
@_typing.overload
|
|
def sqrBoxFilter(src: cv2.typing.MatLike, ddepth: int, ksize: cv2.typing.Size, dst: cv2.typing.MatLike | None = ..., anchor: cv2.typing.Point = ..., normalize: bool = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def sqrBoxFilter(src: UMat, ddepth: int, ksize: cv2.typing.Size, dst: UMat | None = ..., anchor: cv2.typing.Point = ..., normalize: bool = ..., borderType: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def sqrt(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def sqrt(src: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def stackBlur(src: cv2.typing.MatLike, ksize: cv2.typing.Size, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def stackBlur(src: UMat, ksize: cv2.typing.Size, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
def startWindowThread() -> int: ...
|
|
|
|
@_typing.overload
|
|
def stereoCalibrate(objectPoints: _typing.Sequence[cv2.typing.MatLike], imagePoints1: _typing.Sequence[cv2.typing.MatLike], imagePoints2: _typing.Sequence[cv2.typing.MatLike], cameraMatrix1: cv2.typing.MatLike, distCoeffs1: cv2.typing.MatLike, cameraMatrix2: cv2.typing.MatLike, distCoeffs2: cv2.typing.MatLike, imageSize: cv2.typing.Size, R: cv2.typing.MatLike | None = ..., T: cv2.typing.MatLike | None = ..., E: cv2.typing.MatLike | None = ..., F: cv2.typing.MatLike | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def stereoCalibrate(objectPoints: _typing.Sequence[UMat], imagePoints1: _typing.Sequence[UMat], imagePoints2: _typing.Sequence[UMat], cameraMatrix1: UMat, distCoeffs1: UMat, cameraMatrix2: UMat, distCoeffs2: UMat, imageSize: cv2.typing.Size, R: UMat | None = ..., T: UMat | None = ..., E: UMat | None = ..., F: UMat | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, UMat, UMat, UMat, UMat, UMat, UMat, UMat, UMat]: ...
|
|
@_typing.overload
|
|
def stereoCalibrate(objectPoints: _typing.Sequence[cv2.typing.MatLike], imagePoints1: _typing.Sequence[cv2.typing.MatLike], imagePoints2: _typing.Sequence[cv2.typing.MatLike], cameraMatrix1: cv2.typing.MatLike, distCoeffs1: cv2.typing.MatLike, cameraMatrix2: cv2.typing.MatLike, distCoeffs2: cv2.typing.MatLike, imageSize: cv2.typing.Size, R: cv2.typing.MatLike, T: cv2.typing.MatLike, E: cv2.typing.MatLike | None = ..., F: cv2.typing.MatLike | None = ..., perViewErrors: cv2.typing.MatLike | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def stereoCalibrate(objectPoints: _typing.Sequence[UMat], imagePoints1: _typing.Sequence[UMat], imagePoints2: _typing.Sequence[UMat], cameraMatrix1: UMat, distCoeffs1: UMat, cameraMatrix2: UMat, distCoeffs2: UMat, imageSize: cv2.typing.Size, R: UMat, T: UMat, E: UMat | None = ..., F: UMat | None = ..., perViewErrors: UMat | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, UMat, UMat, UMat, UMat, UMat, UMat, UMat, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def stereoCalibrateExtended(objectPoints: _typing.Sequence[cv2.typing.MatLike], imagePoints1: _typing.Sequence[cv2.typing.MatLike], imagePoints2: _typing.Sequence[cv2.typing.MatLike], cameraMatrix1: cv2.typing.MatLike, distCoeffs1: cv2.typing.MatLike, cameraMatrix2: cv2.typing.MatLike, distCoeffs2: cv2.typing.MatLike, imageSize: cv2.typing.Size, R: cv2.typing.MatLike, T: cv2.typing.MatLike, E: cv2.typing.MatLike | None = ..., F: cv2.typing.MatLike | None = ..., rvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., tvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., perViewErrors: cv2.typing.MatLike | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, _typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike], cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def stereoCalibrateExtended(objectPoints: _typing.Sequence[UMat], imagePoints1: _typing.Sequence[UMat], imagePoints2: _typing.Sequence[UMat], cameraMatrix1: UMat, distCoeffs1: UMat, cameraMatrix2: UMat, distCoeffs2: UMat, imageSize: cv2.typing.Size, R: UMat, T: UMat, E: UMat | None = ..., F: UMat | None = ..., rvecs: _typing.Sequence[UMat] | None = ..., tvecs: _typing.Sequence[UMat] | None = ..., perViewErrors: UMat | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, UMat, UMat, UMat, UMat, UMat, UMat, UMat, UMat, _typing.Sequence[UMat], _typing.Sequence[UMat], UMat]: ...
|
|
|
|
@_typing.overload
|
|
def stereoRectify(cameraMatrix1: cv2.typing.MatLike, distCoeffs1: cv2.typing.MatLike, cameraMatrix2: cv2.typing.MatLike, distCoeffs2: cv2.typing.MatLike, imageSize: cv2.typing.Size, R: cv2.typing.MatLike, T: cv2.typing.MatLike, R1: cv2.typing.MatLike | None = ..., R2: cv2.typing.MatLike | None = ..., P1: cv2.typing.MatLike | None = ..., P2: cv2.typing.MatLike | None = ..., Q: cv2.typing.MatLike | None = ..., flags: int = ..., alpha: float = ..., newImageSize: cv2.typing.Size = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.Rect, cv2.typing.Rect]: ...
|
|
@_typing.overload
|
|
def stereoRectify(cameraMatrix1: UMat, distCoeffs1: UMat, cameraMatrix2: UMat, distCoeffs2: UMat, imageSize: cv2.typing.Size, R: UMat, T: UMat, R1: UMat | None = ..., R2: UMat | None = ..., P1: UMat | None = ..., P2: UMat | None = ..., Q: UMat | None = ..., flags: int = ..., alpha: float = ..., newImageSize: cv2.typing.Size = ...) -> tuple[UMat, UMat, UMat, UMat, UMat, cv2.typing.Rect, cv2.typing.Rect]: ...
|
|
|
|
@_typing.overload
|
|
def stereoRectifyUncalibrated(points1: cv2.typing.MatLike, points2: cv2.typing.MatLike, F: cv2.typing.MatLike, imgSize: cv2.typing.Size, H1: cv2.typing.MatLike | None = ..., H2: cv2.typing.MatLike | None = ..., threshold: float = ...) -> tuple[bool, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def stereoRectifyUncalibrated(points1: UMat, points2: UMat, F: UMat, imgSize: cv2.typing.Size, H1: UMat | None = ..., H2: UMat | None = ..., threshold: float = ...) -> tuple[bool, UMat, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def stylization(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., sigma_s: float = ..., sigma_r: float = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def stylization(src: UMat, dst: UMat | None = ..., sigma_s: float = ..., sigma_r: float = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def subtract(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., mask: cv2.typing.MatLike | None = ..., dtype: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def subtract(src1: UMat, src2: UMat, dst: UMat | None = ..., mask: UMat | None = ..., dtype: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def sumElems(src: cv2.typing.MatLike) -> cv2.typing.Scalar: ...
|
|
@_typing.overload
|
|
def sumElems(src: UMat) -> cv2.typing.Scalar: ...
|
|
|
|
@_typing.overload
|
|
def textureFlattening(src: cv2.typing.MatLike, mask: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., low_threshold: float = ..., high_threshold: float = ..., kernel_size: int = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def textureFlattening(src: UMat, mask: UMat, dst: UMat | None = ..., low_threshold: float = ..., high_threshold: float = ..., kernel_size: int = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def threshold(src: cv2.typing.MatLike, thresh: float, maxval: float, type: int, dst: cv2.typing.MatLike | None = ...) -> tuple[float, cv2.typing.MatLike]: ...
|
|
@_typing.overload
|
|
def threshold(src: UMat, thresh: float, maxval: float, type: int, dst: UMat | None = ...) -> tuple[float, UMat]: ...
|
|
|
|
@_typing.overload
|
|
def trace(mtx: cv2.typing.MatLike) -> cv2.typing.Scalar: ...
|
|
@_typing.overload
|
|
def trace(mtx: UMat) -> cv2.typing.Scalar: ...
|
|
|
|
@_typing.overload
|
|
def transform(src: cv2.typing.MatLike, m: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def transform(src: UMat, m: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def transpose(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
|
@_typing.overload
|
|
def transpose(src: UMat, dst: UMat | None = ...) -> UMat: ...
|
|
|
|
@_typing.overload
|
|
def transposeND(src: cv2.typing.MatLike, order: _typing.Sequence[int], dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
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def transposeND(src: UMat, order: _typing.Sequence[int], dst: UMat | None = ...) -> UMat: ...
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@_typing.overload
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def triangulatePoints(projMatr1: cv2.typing.MatLike, projMatr2: cv2.typing.MatLike, projPoints1: cv2.typing.MatLike, projPoints2: cv2.typing.MatLike, points4D: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
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def triangulatePoints(projMatr1: UMat, projMatr2: UMat, projPoints1: UMat, projPoints2: UMat, points4D: UMat | None = ...) -> UMat: ...
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@_typing.overload
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def undistort(src: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., newCameraMatrix: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
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def undistort(src: UMat, cameraMatrix: UMat, distCoeffs: UMat, dst: UMat | None = ..., newCameraMatrix: UMat | None = ...) -> UMat: ...
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@_typing.overload
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def undistortImagePoints(src: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., arg1: cv2.typing.TermCriteria = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
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def undistortImagePoints(src: UMat, cameraMatrix: UMat, distCoeffs: UMat, dst: UMat | None = ..., arg1: cv2.typing.TermCriteria = ...) -> UMat: ...
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@_typing.overload
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def undistortPoints(src: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., R: cv2.typing.MatLike | None = ..., P: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
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def undistortPoints(src: UMat, cameraMatrix: UMat, distCoeffs: UMat, dst: UMat | None = ..., R: UMat | None = ..., P: UMat | None = ...) -> UMat: ...
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@_typing.overload
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def undistortPointsIter(src: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, R: cv2.typing.MatLike, P: cv2.typing.MatLike, criteria: cv2.typing.TermCriteria, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
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def undistortPointsIter(src: UMat, cameraMatrix: UMat, distCoeffs: UMat, R: UMat, P: UMat, criteria: cv2.typing.TermCriteria, dst: UMat | None = ...) -> UMat: ...
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def useOpenVX() -> bool: ...
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def useOptimized() -> bool: ...
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@_typing.overload
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def validateDisparity(disparity: cv2.typing.MatLike, cost: cv2.typing.MatLike, minDisparity: int, numberOfDisparities: int, disp12MaxDisp: int = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
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def validateDisparity(disparity: UMat, cost: UMat, minDisparity: int, numberOfDisparities: int, disp12MaxDisp: int = ...) -> UMat: ...
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@_typing.overload
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def vconcat(src: _typing.Sequence[cv2.typing.MatLike], dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
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def vconcat(src: _typing.Sequence[UMat], dst: UMat | None = ...) -> UMat: ...
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def waitKey(delay: int = ...) -> int: ...
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def waitKeyEx(delay: int = ...) -> int: ...
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@_typing.overload
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def warpAffine(src: cv2.typing.MatLike, M: cv2.typing.MatLike, dsize: cv2.typing.Size, dst: cv2.typing.MatLike | None = ..., flags: int = ..., borderMode: int = ..., borderValue: cv2.typing.Scalar = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
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def warpAffine(src: UMat, M: UMat, dsize: cv2.typing.Size, dst: UMat | None = ..., flags: int = ..., borderMode: int = ..., borderValue: cv2.typing.Scalar = ...) -> UMat: ...
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@_typing.overload
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def warpPerspective(src: cv2.typing.MatLike, M: cv2.typing.MatLike, dsize: cv2.typing.Size, dst: cv2.typing.MatLike | None = ..., flags: int = ..., borderMode: int = ..., borderValue: cv2.typing.Scalar = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
|
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def warpPerspective(src: UMat, M: UMat, dsize: cv2.typing.Size, dst: UMat | None = ..., flags: int = ..., borderMode: int = ..., borderValue: cv2.typing.Scalar = ...) -> UMat: ...
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@_typing.overload
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def warpPolar(src: cv2.typing.MatLike, dsize: cv2.typing.Size, center: cv2.typing.Point2f, maxRadius: float, flags: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
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@_typing.overload
|
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def warpPolar(src: UMat, dsize: cv2.typing.Size, center: cv2.typing.Point2f, maxRadius: float, flags: int, dst: UMat | None = ...) -> UMat: ...
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@_typing.overload
|
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def watershed(image: cv2.typing.MatLike, markers: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
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@_typing.overload
|
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def watershed(image: UMat, markers: UMat) -> UMat: ...
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@_typing.overload
|
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def writeOpticalFlow(path: str, flow: cv2.typing.MatLike) -> bool: ...
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@_typing.overload
|
|
def writeOpticalFlow(path: str, flow: UMat) -> bool: ...
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def createTrackbar(trackbarName: str, windowName: str, value: int, count: int, onChange: _typing.Callable[[int], None]) -> None: ...
|
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def createButton(buttonName: str, onChange: _typing.Callable[[tuple[int] | tuple[int, _typing.Any]], None], userData: _typing.Any | None = ..., buttonType: int = ..., initialButtonState: int = ...) -> None: ...
|
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def setMouseCallback(windowName: str, onMouse: _typing.Callable[[int, int, int, int, _typing.Any | None], None], param: _typing.Any | None = ...) -> None: ...
|
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def CV_8UC(channels: int) -> int: ...
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def CV_8SC(channels: int) -> int: ...
|
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def CV_16UC(channels: int) -> int: ...
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def CV_16SC(channels: int) -> int: ...
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def CV_32SC(channels: int) -> int: ...
|
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def CV_32FC(channels: int) -> int: ...
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def CV_64FC(channels: int) -> int: ...
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def CV_16FC(channels: int) -> int: ...
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def CV_MAKETYPE(depth: int, channels: int) -> int: ...
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def dnn_registerLayer(layerTypeName: str, layerClass: _typing.Type[cv2.dnn.LayerProtocol]) -> None: ...
|
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def dnn_unregisterLayer(layerTypeName: str) -> None: ...
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def redirectError(onError: _typing.Callable[[int, str, str, str, int], None] | None) -> None: ...
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