__all__: list[str] = []

import cv2.aruco
import cv2.cuda
import cv2.detail
import cv2.dnn
import cv2.gapi
import cv2.gapi.ot
import cv2.gapi.streaming
import cv2.typing
import numpy
import typing as _typing


from cv2 import Error as Error
from cv2 import alphamat as alphamat
from cv2 import aruco as aruco
from cv2 import barcode as barcode
from cv2 import bgsegm as bgsegm
from cv2 import bioinspired as bioinspired
from cv2 import ccm as ccm
from cv2 import colored_kinfu as colored_kinfu
from cv2 import cuda as cuda
from cv2 import datasets as datasets
from cv2 import detail as detail
from cv2 import dnn as dnn
from cv2 import dnn_superres as dnn_superres
from cv2 import dpm as dpm
from cv2 import dynafu as dynafu
from cv2 import face as face
from cv2 import fisheye as fisheye
from cv2 import flann as flann
from cv2 import freetype as freetype
from cv2 import ft as ft
from cv2 import gapi as gapi
from cv2 import hfs as hfs
from cv2 import img_hash as img_hash
from cv2 import intensity_transform as intensity_transform
from cv2 import ipp as ipp
from cv2 import kinfu as kinfu
from cv2 import large_kinfu as large_kinfu
from cv2 import legacy as legacy
from cv2 import line_descriptor as line_descriptor
from cv2 import linemod as linemod
from cv2 import mcc as mcc
from cv2 import ml as ml
from cv2 import motempl as motempl
from cv2 import multicalib as multicalib
from cv2 import ocl as ocl
from cv2 import ogl as ogl
from cv2 import omnidir as omnidir
from cv2 import optflow as optflow
from cv2 import parallel as parallel
from cv2 import phase_unwrapping as phase_unwrapping
from cv2 import plot as plot
from cv2 import ppf_match_3d as ppf_match_3d
from cv2 import quality as quality
from cv2 import rapid as rapid
from cv2 import reg as reg
from cv2 import rgbd as rgbd
from cv2 import saliency as saliency
from cv2 import samples as samples
from cv2 import segmentation as segmentation
from cv2 import signal as signal
from cv2 import stereo as stereo
from cv2 import structured_light as structured_light
from cv2 import text as text
from cv2 import typing as typing
from cv2 import utils as utils
from cv2 import videoio_registry as videoio_registry
from cv2 import videostab as videostab
from cv2 import wechat_qrcode as wechat_qrcode
from cv2 import xfeatures2d as xfeatures2d
from cv2 import ximgproc as ximgproc
from cv2 import xphoto as xphoto
from cv2.mat_wrapper import Mat as Mat


# Enumerations
SORT_EVERY_ROW: int
SORT_EVERY_COLUMN: int
SORT_ASCENDING: int
SORT_DESCENDING: int
SortFlags = int
"""One of [SORT_EVERY_ROW, SORT_EVERY_COLUMN, SORT_ASCENDING, SORT_DESCENDING]"""

COVAR_SCRAMBLED: int
COVAR_NORMAL: int
COVAR_USE_AVG: int
COVAR_SCALE: int
COVAR_ROWS: int
COVAR_COLS: int
CovarFlags = int
"""One of [COVAR_SCRAMBLED, COVAR_NORMAL, COVAR_USE_AVG, COVAR_SCALE, COVAR_ROWS, COVAR_COLS]"""

REDUCE_SUM: int
REDUCE_AVG: int
REDUCE_MAX: int
REDUCE_MIN: int
REDUCE_SUM2: int
ReduceTypes = int
"""One of [REDUCE_SUM, REDUCE_AVG, REDUCE_MAX, REDUCE_MIN, REDUCE_SUM2]"""

ROTATE_90_CLOCKWISE: int
ROTATE_180: int
ROTATE_90_COUNTERCLOCKWISE: int
RotateFlags = int
"""One of [ROTATE_90_CLOCKWISE, ROTATE_180, ROTATE_90_COUNTERCLOCKWISE]"""

KMEANS_RANDOM_CENTERS: int
KMEANS_PP_CENTERS: int
KMEANS_USE_INITIAL_LABELS: int
KmeansFlags = int
"""One of [KMEANS_RANDOM_CENTERS, KMEANS_PP_CENTERS, KMEANS_USE_INITIAL_LABELS]"""

Param_INT: int
PARAM_INT: int
Param_BOOLEAN: int
PARAM_BOOLEAN: int
Param_REAL: int
PARAM_REAL: int
Param_STRING: int
PARAM_STRING: int
Param_MAT: int
PARAM_MAT: int
Param_MAT_VECTOR: int
PARAM_MAT_VECTOR: int
Param_ALGORITHM: int
PARAM_ALGORITHM: int
Param_FLOAT: int
PARAM_FLOAT: int
Param_UNSIGNED_INT: int
PARAM_UNSIGNED_INT: int
Param_UINT64: int
PARAM_UINT64: int
Param_UCHAR: int
PARAM_UCHAR: int
Param_SCALAR: int
PARAM_SCALAR: int
Param = int
"""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]"""

DECOMP_LU: int
DECOMP_SVD: int
DECOMP_EIG: int
DECOMP_CHOLESKY: int
DECOMP_QR: int
DECOMP_NORMAL: int
DecompTypes = int
"""One of [DECOMP_LU, DECOMP_SVD, DECOMP_EIG, DECOMP_CHOLESKY, DECOMP_QR, DECOMP_NORMAL]"""

NORM_INF: int
NORM_L1: int
NORM_L2: int
NORM_L2SQR: int
NORM_HAMMING: int
NORM_HAMMING2: int
NORM_TYPE_MASK: int
NORM_RELATIVE: int
NORM_MINMAX: int
NormTypes = int
"""One of [NORM_INF, NORM_L1, NORM_L2, NORM_L2SQR, NORM_HAMMING, NORM_HAMMING2, NORM_TYPE_MASK, NORM_RELATIVE, NORM_MINMAX]"""

CMP_EQ: int
CMP_GT: int
CMP_GE: int
CMP_LT: int
CMP_LE: int
CMP_NE: int
CmpTypes = int
"""One of [CMP_EQ, CMP_GT, CMP_GE, CMP_LT, CMP_LE, CMP_NE]"""

GEMM_1_T: int
GEMM_2_T: int
GEMM_3_T: int
GemmFlags = int
"""One of [GEMM_1_T, GEMM_2_T, GEMM_3_T]"""

DFT_INVERSE: int
DFT_SCALE: int
DFT_ROWS: int
DFT_COMPLEX_OUTPUT: int
DFT_REAL_OUTPUT: int
DFT_COMPLEX_INPUT: int
DCT_INVERSE: int
DCT_ROWS: int
DftFlags = int
"""One of [DFT_INVERSE, DFT_SCALE, DFT_ROWS, DFT_COMPLEX_OUTPUT, DFT_REAL_OUTPUT, DFT_COMPLEX_INPUT, DCT_INVERSE, DCT_ROWS]"""

BORDER_CONSTANT: int
BORDER_REPLICATE: int
BORDER_REFLECT: int
BORDER_WRAP: int
BORDER_REFLECT_101: int
BORDER_TRANSPARENT: int
BORDER_REFLECT101: int
BORDER_DEFAULT: int
BORDER_ISOLATED: int
BorderTypes = int
"""One of [BORDER_CONSTANT, BORDER_REPLICATE, BORDER_REFLECT, BORDER_WRAP, BORDER_REFLECT_101, BORDER_TRANSPARENT, BORDER_REFLECT101, BORDER_DEFAULT, BORDER_ISOLATED]"""

ACCESS_READ: int
ACCESS_WRITE: int
ACCESS_RW: int
ACCESS_MASK: int
ACCESS_FAST: int
AccessFlag = int
"""One of [ACCESS_READ, ACCESS_WRITE, ACCESS_RW, ACCESS_MASK, ACCESS_FAST]"""

USAGE_DEFAULT: int
USAGE_ALLOCATE_HOST_MEMORY: int
USAGE_ALLOCATE_DEVICE_MEMORY: int
USAGE_ALLOCATE_SHARED_MEMORY: int
__UMAT_USAGE_FLAGS_32BIT: int
UMatUsageFlags = int
"""One of [USAGE_DEFAULT, USAGE_ALLOCATE_HOST_MEMORY, USAGE_ALLOCATE_DEVICE_MEMORY, USAGE_ALLOCATE_SHARED_MEMORY, __UMAT_USAGE_FLAGS_32BIT]"""

SOLVELP_LOST: int
SOLVELP_UNBOUNDED: int
SOLVELP_UNFEASIBLE: int
SOLVELP_SINGLE: int
SOLVELP_MULTI: int
SolveLPResult = int
"""One of [SOLVELP_LOST, SOLVELP_UNBOUNDED, SOLVELP_UNFEASIBLE, SOLVELP_SINGLE, SOLVELP_MULTI]"""

QUAT_ASSUME_NOT_UNIT: int
QUAT_ASSUME_UNIT: int
QuatAssumeType = int
"""One of [QUAT_ASSUME_NOT_UNIT, QUAT_ASSUME_UNIT]"""

ALGO_HINT_DEFAULT: int
ALGO_HINT_ACCURATE: int
ALGO_HINT_APPROX: int
AlgorithmHint = int
"""One of [ALGO_HINT_DEFAULT, ALGO_HINT_ACCURATE, ALGO_HINT_APPROX]"""

FILTER_SCHARR: int
SpecialFilter = int
"""One of [FILTER_SCHARR]"""

MORPH_ERODE: int
MORPH_DILATE: int
MORPH_OPEN: int
MORPH_CLOSE: int
MORPH_GRADIENT: int
MORPH_TOPHAT: int
MORPH_BLACKHAT: int
MORPH_HITMISS: int
MorphTypes = int
"""One of [MORPH_ERODE, MORPH_DILATE, MORPH_OPEN, MORPH_CLOSE, MORPH_GRADIENT, MORPH_TOPHAT, MORPH_BLACKHAT, MORPH_HITMISS]"""

MORPH_RECT: int
MORPH_CROSS: int
MORPH_ELLIPSE: int
MORPH_DIAMOND: int
MorphShapes = int
"""One of [MORPH_RECT, MORPH_CROSS, MORPH_ELLIPSE, MORPH_DIAMOND]"""

INTER_NEAREST: int
INTER_LINEAR: int
INTER_CUBIC: int
INTER_AREA: int
INTER_LANCZOS4: int
INTER_LINEAR_EXACT: int
INTER_NEAREST_EXACT: int
INTER_MAX: int
WARP_FILL_OUTLIERS: int
WARP_INVERSE_MAP: int
WARP_RELATIVE_MAP: int
InterpolationFlags = int
"""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]"""

WARP_POLAR_LINEAR: int
WARP_POLAR_LOG: int
WarpPolarMode = int
"""One of [WARP_POLAR_LINEAR, WARP_POLAR_LOG]"""

INTER_BITS: int
INTER_BITS2: int
INTER_TAB_SIZE: int
INTER_TAB_SIZE2: int
InterpolationMasks = int
"""One of [INTER_BITS, INTER_BITS2, INTER_TAB_SIZE, INTER_TAB_SIZE2]"""

DIST_USER: int
DIST_L1: int
DIST_L2: int
DIST_C: int
DIST_L12: int
DIST_FAIR: int
DIST_WELSCH: int
DIST_HUBER: int
DistanceTypes = int
"""One of [DIST_USER, DIST_L1, DIST_L2, DIST_C, DIST_L12, DIST_FAIR, DIST_WELSCH, DIST_HUBER]"""

DIST_MASK_3: int
DIST_MASK_5: int
DIST_MASK_PRECISE: int
DistanceTransformMasks = int
"""One of [DIST_MASK_3, DIST_MASK_5, DIST_MASK_PRECISE]"""

THRESH_BINARY: int
THRESH_BINARY_INV: int
THRESH_TRUNC: int
THRESH_TOZERO: int
THRESH_TOZERO_INV: int
THRESH_MASK: int
THRESH_OTSU: int
THRESH_TRIANGLE: int
THRESH_DRYRUN: int
ThresholdTypes = int
"""One of [THRESH_BINARY, THRESH_BINARY_INV, THRESH_TRUNC, THRESH_TOZERO, THRESH_TOZERO_INV, THRESH_MASK, THRESH_OTSU, THRESH_TRIANGLE, THRESH_DRYRUN]"""

ADAPTIVE_THRESH_MEAN_C: int
ADAPTIVE_THRESH_GAUSSIAN_C: int
AdaptiveThresholdTypes = int
"""One of [ADAPTIVE_THRESH_MEAN_C, ADAPTIVE_THRESH_GAUSSIAN_C]"""

GC_BGD: int
GC_FGD: int
GC_PR_BGD: int
GC_PR_FGD: int
GrabCutClasses = int
"""One of [GC_BGD, GC_FGD, GC_PR_BGD, GC_PR_FGD]"""

GC_INIT_WITH_RECT: int
GC_INIT_WITH_MASK: int
GC_EVAL: int
GC_EVAL_FREEZE_MODEL: int
GrabCutModes = int
"""One of [GC_INIT_WITH_RECT, GC_INIT_WITH_MASK, GC_EVAL, GC_EVAL_FREEZE_MODEL]"""

DIST_LABEL_CCOMP: int
DIST_LABEL_PIXEL: int
DistanceTransformLabelTypes = int
"""One of [DIST_LABEL_CCOMP, DIST_LABEL_PIXEL]"""

FLOODFILL_FIXED_RANGE: int
FLOODFILL_MASK_ONLY: int
FloodFillFlags = int
"""One of [FLOODFILL_FIXED_RANGE, FLOODFILL_MASK_ONLY]"""

CC_STAT_LEFT: int
CC_STAT_TOP: int
CC_STAT_WIDTH: int
CC_STAT_HEIGHT: int
CC_STAT_AREA: int
CC_STAT_MAX: int
ConnectedComponentsTypes = int
"""One of [CC_STAT_LEFT, CC_STAT_TOP, CC_STAT_WIDTH, CC_STAT_HEIGHT, CC_STAT_AREA, CC_STAT_MAX]"""

CCL_DEFAULT: int
CCL_WU: int
CCL_GRANA: int
CCL_BOLELLI: int
CCL_SAUF: int
CCL_BBDT: int
CCL_SPAGHETTI: int
ConnectedComponentsAlgorithmsTypes = int
"""One of [CCL_DEFAULT, CCL_WU, CCL_GRANA, CCL_BOLELLI, CCL_SAUF, CCL_BBDT, CCL_SPAGHETTI]"""

RETR_EXTERNAL: int
RETR_LIST: int
RETR_CCOMP: int
RETR_TREE: int
RETR_FLOODFILL: int
RetrievalModes = int
"""One of [RETR_EXTERNAL, RETR_LIST, RETR_CCOMP, RETR_TREE, RETR_FLOODFILL]"""

CHAIN_APPROX_NONE: int
CHAIN_APPROX_SIMPLE: int
CHAIN_APPROX_TC89_L1: int
CHAIN_APPROX_TC89_KCOS: int
ContourApproximationModes = int
"""One of [CHAIN_APPROX_NONE, CHAIN_APPROX_SIMPLE, CHAIN_APPROX_TC89_L1, CHAIN_APPROX_TC89_KCOS]"""

CONTOURS_MATCH_I1: int
CONTOURS_MATCH_I2: int
CONTOURS_MATCH_I3: int
ShapeMatchModes = int
"""One of [CONTOURS_MATCH_I1, CONTOURS_MATCH_I2, CONTOURS_MATCH_I3]"""

HOUGH_STANDARD: int
HOUGH_PROBABILISTIC: int
HOUGH_MULTI_SCALE: int
HOUGH_GRADIENT: int
HOUGH_GRADIENT_ALT: int
HoughModes = int
"""One of [HOUGH_STANDARD, HOUGH_PROBABILISTIC, HOUGH_MULTI_SCALE, HOUGH_GRADIENT, HOUGH_GRADIENT_ALT]"""

LSD_REFINE_NONE: int
LSD_REFINE_STD: int
LSD_REFINE_ADV: int
LineSegmentDetectorModes = int
"""One of [LSD_REFINE_NONE, LSD_REFINE_STD, LSD_REFINE_ADV]"""

HISTCMP_CORREL: int
HISTCMP_CHISQR: int
HISTCMP_INTERSECT: int
HISTCMP_BHATTACHARYYA: int
HISTCMP_HELLINGER: int
HISTCMP_CHISQR_ALT: int
HISTCMP_KL_DIV: int
HistCompMethods = int
"""One of [HISTCMP_CORREL, HISTCMP_CHISQR, HISTCMP_INTERSECT, HISTCMP_BHATTACHARYYA, HISTCMP_HELLINGER, HISTCMP_CHISQR_ALT, HISTCMP_KL_DIV]"""

COLOR_BGR2BGRA: int
COLOR_RGB2RGBA: int
COLOR_BGRA2BGR: int
COLOR_RGBA2RGB: int
COLOR_BGR2RGBA: int
COLOR_RGB2BGRA: int
COLOR_RGBA2BGR: int
COLOR_BGRA2RGB: int
COLOR_BGR2RGB: int
COLOR_RGB2BGR: int
COLOR_BGRA2RGBA: int
COLOR_RGBA2BGRA: int
COLOR_BGR2GRAY: int
COLOR_RGB2GRAY: int
COLOR_GRAY2BGR: int
COLOR_GRAY2RGB: int
COLOR_GRAY2BGRA: int
COLOR_GRAY2RGBA: int
COLOR_BGRA2GRAY: int
COLOR_RGBA2GRAY: int
COLOR_BGR2BGR565: int
COLOR_RGB2BGR565: int
COLOR_BGR5652BGR: int
COLOR_BGR5652RGB: int
COLOR_BGRA2BGR565: int
COLOR_RGBA2BGR565: int
COLOR_BGR5652BGRA: int
COLOR_BGR5652RGBA: int
COLOR_GRAY2BGR565: int
COLOR_BGR5652GRAY: int
COLOR_BGR2BGR555: int
COLOR_RGB2BGR555: int
COLOR_BGR5552BGR: int
COLOR_BGR5552RGB: int
COLOR_BGRA2BGR555: int
COLOR_RGBA2BGR555: int
COLOR_BGR5552BGRA: int
COLOR_BGR5552RGBA: int
COLOR_GRAY2BGR555: int
COLOR_BGR5552GRAY: int
COLOR_BGR2XYZ: int
COLOR_RGB2XYZ: int
COLOR_XYZ2BGR: int
COLOR_XYZ2RGB: int
COLOR_BGR2YCrCb: int
COLOR_BGR2YCR_CB: int
COLOR_RGB2YCrCb: int
COLOR_RGB2YCR_CB: int
COLOR_YCrCb2BGR: int
COLOR_YCR_CB2BGR: int
COLOR_YCrCb2RGB: int
COLOR_YCR_CB2RGB: int
COLOR_BGR2HSV: int
COLOR_RGB2HSV: int
COLOR_BGR2Lab: int
COLOR_BGR2LAB: int
COLOR_RGB2Lab: int
COLOR_RGB2LAB: int
COLOR_BGR2Luv: int
COLOR_BGR2LUV: int
COLOR_RGB2Luv: int
COLOR_RGB2LUV: int
COLOR_BGR2HLS: int
COLOR_RGB2HLS: int
COLOR_HSV2BGR: int
COLOR_HSV2RGB: int
COLOR_Lab2BGR: int
COLOR_LAB2BGR: int
COLOR_Lab2RGB: int
COLOR_LAB2RGB: int
COLOR_Luv2BGR: int
COLOR_LUV2BGR: int
COLOR_Luv2RGB: int
COLOR_LUV2RGB: int
COLOR_HLS2BGR: int
COLOR_HLS2RGB: int
COLOR_BGR2HSV_FULL: int
COLOR_RGB2HSV_FULL: int
COLOR_BGR2HLS_FULL: int
COLOR_RGB2HLS_FULL: int
COLOR_HSV2BGR_FULL: int
COLOR_HSV2RGB_FULL: int
COLOR_HLS2BGR_FULL: int
COLOR_HLS2RGB_FULL: int
COLOR_LBGR2Lab: int
COLOR_LBGR2LAB: int
COLOR_LRGB2Lab: int
COLOR_LRGB2LAB: int
COLOR_LBGR2Luv: int
COLOR_LBGR2LUV: int
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
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_ANDROID_DEVICE_TORCH: 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

NORMAL_CLONE: int
MIXED_CLONE: int
MONOCHROME_TRANSFER: int
NORMAL_CLONE_WIDE: int
MIXED_CLONE_WIDE: int
MONOCHROME_TRANSFER_WIDE: int
SeamlessCloneFlags = int
"""One of [NORMAL_CLONE, MIXED_CLONE, MONOCHROME_TRANSFER, NORMAL_CLONE_WIDE, MIXED_CLONE_WIDE, MONOCHROME_TRANSFER_WIDE]"""

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_BGR: 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
IMREAD_COLOR_RGB: int
ImreadModes = int
"""One of [IMREAD_UNCHANGED, IMREAD_GRAYSCALE, IMREAD_COLOR_BGR, 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, IMREAD_COLOR_RGB]"""

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_PNG_FILTER: 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
IMWRITE_JPEGXL_QUALITY: int
IMWRITE_JPEGXL_EFFORT: int
IMWRITE_JPEGXL_DISTANCE: int
IMWRITE_JPEGXL_DECODING_SPEED: int
IMWRITE_GIF_LOOP: int
IMWRITE_GIF_SPEED: int
IMWRITE_GIF_QUALITY: int
IMWRITE_GIF_DITHER: int
IMWRITE_GIF_TRANSPARENCY: int
IMWRITE_GIF_COLORTABLE: 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_PNG_FILTER, 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_JPEGXL_QUALITY, IMWRITE_JPEGXL_EFFORT, IMWRITE_JPEGXL_DISTANCE, IMWRITE_JPEGXL_DECODING_SPEED, IMWRITE_GIF_LOOP, IMWRITE_GIF_SPEED, IMWRITE_GIF_QUALITY, IMWRITE_GIF_DITHER, IMWRITE_GIF_TRANSPARENCY, IMWRITE_GIF_COLORTABLE]"""

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_PNG_FILTER_NONE: int
IMWRITE_PNG_FILTER_SUB: int
IMWRITE_PNG_FILTER_UP: int
IMWRITE_PNG_FILTER_AVG: int
IMWRITE_PNG_FILTER_PAETH: int
IMWRITE_PNG_FAST_FILTERS: int
IMWRITE_PNG_ALL_FILTERS: int
ImwritePNGFilterFlags = int
"""One of [IMWRITE_PNG_FILTER_NONE, IMWRITE_PNG_FILTER_SUB, IMWRITE_PNG_FILTER_UP, IMWRITE_PNG_FILTER_AVG, IMWRITE_PNG_FILTER_PAETH, IMWRITE_PNG_FAST_FILTERS, IMWRITE_PNG_ALL_FILTERS]"""

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]"""

IMWRITE_GIF_FAST_NO_DITHER: int
IMWRITE_GIF_FAST_FLOYD_DITHER: int
IMWRITE_GIF_COLORTABLE_SIZE_8: int
IMWRITE_GIF_COLORTABLE_SIZE_16: int
IMWRITE_GIF_COLORTABLE_SIZE_32: int
IMWRITE_GIF_COLORTABLE_SIZE_64: int
IMWRITE_GIF_COLORTABLE_SIZE_128: int
IMWRITE_GIF_COLORTABLE_SIZE_256: int
ImwriteGIFCompressionFlags = int
"""One of [IMWRITE_GIF_FAST_NO_DITHER, IMWRITE_GIF_FAST_FLOYD_DITHER, IMWRITE_GIF_COLORTABLE_SIZE_8, IMWRITE_GIF_COLORTABLE_SIZE_16, IMWRITE_GIF_COLORTABLE_SIZE_32, IMWRITE_GIF_COLORTABLE_SIZE_64, IMWRITE_GIF_COLORTABLE_SIZE_128, IMWRITE_GIF_COLORTABLE_SIZE_256]"""

IMAGE_METADATA_UNKNOWN: int
IMAGE_METADATA_EXIF: int
IMAGE_METADATA_XMP: int
IMAGE_METADATA_ICCP: int
IMAGE_METADATA_MAX: int
ImageMetadataType = int
"""One of [IMAGE_METADATA_UNKNOWN, IMAGE_METADATA_EXIF, IMAGE_METADATA_XMP, IMAGE_METADATA_ICCP, IMAGE_METADATA_MAX]"""

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
CAP_PROP_PTS: int
CAP_PROP_DTS_DELAY: 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, CAP_PROP_PTS, CAP_PROP_DTS_DELAY]"""

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
VIDEOWRITER_PROP_PTS: int
VIDEOWRITER_PROP_DTS_DELAY: 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, VIDEOWRITER_PROP_PTS, VIDEOWRITER_PROP_DTS_DELAY]"""

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_SHIFT_JIS: int
QRCODE_ENCODER_ECI_SHIFT_JIS: int
QRCodeEncoder_ECI_UTF8: int
QRCODE_ENCODER_ECI_UTF8: int
QRCodeEncoder_ECIEncodings = int
"""One of [QRCodeEncoder_ECI_SHIFT_JIS, QRCODE_ENCODER_ECI_SHIFT_JIS, 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]"""

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

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]"""

TrackerKCF_GRAY: int
TRACKER_KCF_GRAY: int
TrackerKCF_CN: int
TRACKER_KCF_CN: int
TrackerKCF_CUSTOM: int
TRACKER_KCF_CUSTOM: int
TrackerKCF_MODE = int
"""One of [TrackerKCF_GRAY, TRACKER_KCF_GRAY, TrackerKCF_CN, TRACKER_KCF_CN, TrackerKCF_CUSTOM, TRACKER_KCF_CUSTOM]"""

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: 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 getLastTimeTicks(self) -> int: ...

    def getLastTimeMicro(self) -> float: ...

    def getLastTimeMilli(self) -> float: ...

    def getLastTimeSec(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(Algorithm):
    # 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 Animation:
    loop_count: int
    bgcolor: cv2.typing.Scalar
    durations: _typing.Sequence[int]
    frames: _typing.Sequence[cv2.typing.MatLike]
    still_image: cv2.typing.MatLike

    # Functions
    def __init__(self, loopCount: int = ..., bgColor: cv2.typing.Scalar = ...) -> None: ...


class IStreamReader:
    # Functions
    def read(self, buffer: str, size: int) -> int: ...

    def seek(self, offset: int, origin: int) -> 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 __init__(self, source: IStreamReader, 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: ...
    @_typing.overload
    def open(self, source: IStreamReader, 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]: ...

    def getEncoding(self, codeIdx: int = ...) -> QRCodeEncoder_ECIEncodings: ...


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]]: ...

    @_typing.overload
    def detectAndDecodeBytes(self, img: cv2.typing.MatLike, points: cv2.typing.MatLike | None = ..., straight_code: cv2.typing.MatLike | None = ...) -> tuple[bytes, cv2.typing.MatLike, cv2.typing.MatLike]: ...
    @_typing.overload
    def detectAndDecodeBytes(self, img: UMat, points: UMat | None = ..., straight_code: UMat | None = ...) -> tuple[bytes, UMat, UMat]: ...

    @_typing.overload
    def decodeBytes(self, img: cv2.typing.MatLike, points: cv2.typing.MatLike, straight_code: cv2.typing.MatLike | None = ...) -> tuple[bytes, cv2.typing.MatLike]: ...
    @_typing.overload
    def decodeBytes(self, img: UMat, points: UMat, straight_code: UMat | None = ...) -> tuple[bytes, UMat]: ...

    @_typing.overload
    def decodeBytesMulti(self, img: cv2.typing.MatLike, points: cv2.typing.MatLike, straight_code: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> tuple[bool, _typing.Sequence[bytes], _typing.Sequence[cv2.typing.MatLike]]: ...
    @_typing.overload
    def decodeBytesMulti(self, img: UMat, points: UMat, straight_code: _typing.Sequence[UMat] | None = ...) -> tuple[bool, _typing.Sequence[bytes], _typing.Sequence[UMat]]: ...

    @_typing.overload
    def detectAndDecodeBytesMulti(self, img: cv2.typing.MatLike, points: cv2.typing.MatLike | None = ..., straight_code: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> tuple[bool, _typing.Sequence[bytes], cv2.typing.MatLike, _typing.Sequence[cv2.typing.MatLike]]: ...
    @_typing.overload
    def detectAndDecodeBytesMulti(self, img: UMat, points: UMat | None = ..., straight_code: _typing.Sequence[UMat] | None = ...) -> tuple[bool, _typing.Sequence[bytes], 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
    @_typing.overload
    def create(cls, model: str, config: str, backend_id: int = ..., target_id: int = ...) -> FaceRecognizerSF: ...
    @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]], backend_id: int = ..., target_id: int = ...) -> FaceRecognizerSF: ...


class HistogramCostExtractor(Algorithm):
    # Functions
    @_typing.overload
    def buildCostMatrix(self, descriptors1: cv2.typing.MatLike, descriptors2: cv2.typing.MatLike, costMatrix: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
    @_typing.overload
    def buildCostMatrix(self, descriptors1: UMat, descriptors2: UMat, costMatrix: UMat | None = ...) -> UMat: ...

    def setNDummies(self, nDummies: int) -> None: ...

    def getNDummies(self) -> int: ...

    def setDefaultCost(self, defaultCost: float) -> None: ...

    def getDefaultCost(self) -> float: ...


class NormHistogramCostExtractor(HistogramCostExtractor):
    # Functions
    def setNormFlag(self, flag: int) -> None: ...

    def getNormFlag(self) -> int: ...


class EMDHistogramCostExtractor(HistogramCostExtractor):
    # Functions
    def setNormFlag(self, flag: int) -> None: ...

    def getNormFlag(self) -> int: ...


class ChiHistogramCostExtractor(HistogramCostExtractor):
    ...

class EMDL1HistogramCostExtractor(HistogramCostExtractor):
    ...

class ShapeDistanceExtractor(Algorithm):
    # Functions
    @_typing.overload
    def computeDistance(self, contour1: cv2.typing.MatLike, contour2: cv2.typing.MatLike) -> float: ...
    @_typing.overload
    def computeDistance(self, contour1: UMat, contour2: UMat) -> float: ...


class ShapeContextDistanceExtractor(ShapeDistanceExtractor):
    # Functions
    def setAngularBins(self, nAngularBins: int) -> None: ...

    def getAngularBins(self) -> int: ...

    def setRadialBins(self, nRadialBins: int) -> None: ...

    def getRadialBins(self) -> int: ...

    def setInnerRadius(self, innerRadius: float) -> None: ...

    def getInnerRadius(self) -> float: ...

    def setOuterRadius(self, outerRadius: float) -> None: ...

    def getOuterRadius(self) -> float: ...

    def setRotationInvariant(self, rotationInvariant: bool) -> None: ...

    def getRotationInvariant(self) -> bool: ...

    def setShapeContextWeight(self, shapeContextWeight: float) -> None: ...

    def getShapeContextWeight(self) -> float: ...

    def setImageAppearanceWeight(self, imageAppearanceWeight: float) -> None: ...

    def getImageAppearanceWeight(self) -> float: ...

    def setBendingEnergyWeight(self, bendingEnergyWeight: float) -> None: ...

    def getBendingEnergyWeight(self) -> float: ...

    @_typing.overload
    def setImages(self, image1: cv2.typing.MatLike, image2: cv2.typing.MatLike) -> None: ...
    @_typing.overload
    def setImages(self, image1: UMat, image2: UMat) -> None: ...

    @_typing.overload
    def getImages(self, image1: cv2.typing.MatLike | None = ..., image2: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
    @_typing.overload
    def getImages(self, image1: UMat | None = ..., image2: UMat | None = ...) -> tuple[UMat, UMat]: ...

    def setIterations(self, iterations: int) -> None: ...

    def getIterations(self) -> int: ...

    def setCostExtractor(self, comparer: HistogramCostExtractor) -> None: ...

    def getCostExtractor(self) -> HistogramCostExtractor: ...

    def setStdDev(self, sigma: float) -> None: ...

    def getStdDev(self) -> float: ...

    def setTransformAlgorithm(self, transformer: ShapeTransformer) -> None: ...

    def getTransformAlgorithm(self) -> ShapeTransformer: ...


class HausdorffDistanceExtractor(ShapeDistanceExtractor):
    # Functions
    def setDistanceFlag(self, distanceFlag: int) -> None: ...

    def getDistanceFlag(self) -> int: ...

    def setRankProportion(self, rankProportion: float) -> None: ...

    def getRankProportion(self) -> float: ...


class ShapeTransformer(Algorithm):
    # Functions
    @_typing.overload
    def estimateTransformation(self, transformingShape: cv2.typing.MatLike, targetShape: cv2.typing.MatLike, matches: _typing.Sequence[DMatch]) -> None: ...
    @_typing.overload
    def estimateTransformation(self, transformingShape: UMat, targetShape: UMat, matches: _typing.Sequence[DMatch]) -> None: ...

    @_typing.overload
    def applyTransformation(self, input: cv2.typing.MatLike, output: cv2.typing.MatLike | None = ...) -> tuple[float, cv2.typing.MatLike]: ...
    @_typing.overload
    def applyTransformation(self, input: UMat, output: UMat | None = ...) -> tuple[float, UMat]: ...

    @_typing.overload
    def warpImage(self, transformingImage: cv2.typing.MatLike, output: cv2.typing.MatLike | None = ..., flags: int = ..., borderMode: int = ..., borderValue: cv2.typing.Scalar = ...) -> cv2.typing.MatLike: ...
    @_typing.overload
    def warpImage(self, transformingImage: UMat, output: UMat | None = ..., flags: int = ..., borderMode: int = ..., borderValue: cv2.typing.Scalar = ...) -> UMat: ...


class ThinPlateSplineShapeTransformer(ShapeTransformer):
    # Functions
    def setRegularizationParameter(self, beta: float) -> None: ...

    def getRegularizationParameter(self) -> float: ...


class AffineTransformer(ShapeTransformer):
    # Functions
    def setFullAffine(self, fullAffine: bool) -> None: ...

    def getFullAffine(self) -> bool: ...


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
    @_typing.overload
    def create(cls, parameters: TrackerGOTURN.Params = ...) -> TrackerGOTURN: ...
    @classmethod
    @_typing.overload
    def create(cls, model: cv2.dnn.Net) -> 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
    @_typing.overload
    def create(cls, parameters: TrackerDaSiamRPN.Params = ...) -> TrackerDaSiamRPN: ...
    @classmethod
    @_typing.overload
    def create(cls, siam_rpn: cv2.dnn.Net, kernel_cls1: cv2.dnn.Net, kernel_r1: cv2.dnn.Net) -> 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
    @_typing.overload
    def create(cls, parameters: TrackerNano.Params = ...) -> TrackerNano: ...
    @classmethod
    @_typing.overload
    def create(cls, backbone: cv2.dnn.Net, neckhead: cv2.dnn.Net) -> 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
        tracking_score_threshold: float

        # Functions
        def __init__(self) -> None: ...



    # Functions
    @classmethod
    @_typing.overload
    def create(cls, parameters: TrackerVit.Params = ...) -> TrackerVit: ...
    @classmethod
    @_typing.overload
    def create(cls, model: cv2.dnn.Net, meanvalue: cv2.typing.Scalar = ..., stdvalue: cv2.typing.Scalar = ..., tracking_score_threshold: float = ...) -> 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 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 component(self) -> _typing.Sequence[int]: ...

    def cameras(self) -> _typing.Sequence[cv2.detail.CameraParams]: ...

    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 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 TrackerCSRT(Tracker):
    # Classes
    class Params:
        use_hog: bool
        use_color_names: bool
        use_gray: bool
        use_rgb: bool
        use_channel_weights: bool
        use_segmentation: bool
        window_function: str
        kaiser_alpha: float
        cheb_attenuation: float
        template_size: float
        gsl_sigma: float
        hog_orientations: float
        hog_clip: float
        padding: float
        filter_lr: float
        weights_lr: float
        num_hog_channels_used: int
        admm_iterations: int
        histogram_bins: int
        histogram_lr: float
        background_ratio: int
        number_of_scales: int
        scale_sigma_factor: float
        scale_model_max_area: float
        scale_lr: float
        scale_step: float
        psr_threshold: float

        # Functions
        def __init__(self) -> None: ...



    # Functions
    @classmethod
    def create(cls, parameters: TrackerCSRT.Params = ...) -> TrackerCSRT: ...

    @_typing.overload
    def setInitialMask(self, mask: cv2.typing.MatLike) -> None: ...
    @_typing.overload
    def setInitialMask(self, mask: UMat) -> None: ...


class TrackerKCF(Tracker):
    # Classes
    class Params:
        detect_thresh: float
        sigma: float
        lambda_: float
        interp_factor: float
        output_sigma_factor: float
        pca_learning_rate: float
        resize: bool
        split_coeff: bool
        wrap_kernel: bool
        compress_feature: bool
        max_patch_size: int
        compressed_size: int
        desc_pca: int
        desc_npca: int

        # Functions
        def __init__(self) -> None: ...



    # Functions
    @classmethod
    def create(cls, parameters: TrackerKCF.Params = ...) -> TrackerKCF: ...


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 = ..., hint: AlgorithmHint = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def GaussianBlur(src: UMat, ksize: cv2.typing.Size, sigmaX: float, dst: UMat | None = ..., sigmaY: float = ..., borderType: int = ..., hint: AlgorithmHint = ...) -> 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 HoughCirclesWithAccumulator(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 HoughCirclesWithAccumulator(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 = ..., use_edgeval: bool = ...) -> 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 = ..., use_edgeval: bool = ...) -> 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 = ..., use_edgeval: bool = ...) -> 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 = ..., use_edgeval: bool = ...) -> 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]: ...
@_typing.overload
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]: ...

@_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]: ...
@_typing.overload
def Rodrigues(src: UMat, dst: UMat | None = ..., jacobian: UMat | None = ...) -> tuple[UMat, UMat]: ...

@_typing.overload
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: ...
@_typing.overload
def SVBackSubst(w: UMat, u: UMat, vt: UMat, rhs: UMat, dst: UMat | None = ...) -> UMat: ...

@_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]: ...
@_typing.overload
def SVDecomp(src: UMat, w: UMat | None = ..., u: UMat | None = ..., vt: UMat | None = ..., flags: int = ...) -> tuple[UMat, UMat, UMat]: ...

@_typing.overload
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: ...
@_typing.overload
def Scharr(src: UMat, ddepth: int, dx: int, dy: int, dst: UMat | None = ..., scale: float = ..., delta: float = ..., borderType: int = ...) -> UMat: ...

@_typing.overload
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: ...
@_typing.overload
def Sobel(src: UMat, ddepth: int, dx: int, dy: int, dst: UMat | None = ..., ksize: int = ..., scale: float = ..., delta: float = ..., borderType: int = ...) -> UMat: ...

@_typing.overload
def absdiff(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def absdiff(src1: UMat, src2: UMat, dst: UMat | None = ...) -> UMat: ...

@_typing.overload
def accumulate(src: cv2.typing.MatLike, dst: cv2.typing.MatLike, mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def accumulate(src: UMat, dst: UMat, mask: UMat | None = ...) -> UMat: ...

@_typing.overload
def accumulateProduct(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, dst: cv2.typing.MatLike, mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def accumulateProduct(src1: UMat, src2: UMat, dst: UMat, mask: UMat | None = ...) -> UMat: ...

@_typing.overload
def accumulateSquare(src: cv2.typing.MatLike, dst: cv2.typing.MatLike, mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def accumulateSquare(src: UMat, dst: UMat, mask: UMat | None = ...) -> UMat: ...

@_typing.overload
def accumulateWeighted(src: cv2.typing.MatLike, dst: cv2.typing.MatLike, alpha: float, mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def accumulateWeighted(src: UMat, dst: UMat, alpha: float, mask: UMat | None = ...) -> UMat: ...

@_typing.overload
def adaptiveThreshold(src: cv2.typing.MatLike, maxValue: float, adaptiveMethod: int, thresholdType: int, blockSize: int, C: float, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def adaptiveThreshold(src: UMat, maxValue: float, adaptiveMethod: int, thresholdType: int, blockSize: int, C: float, dst: UMat | None = ...) -> UMat: ...

@_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: ...
@_typing.overload
def add(src1: UMat, src2: UMat, dst: UMat | None = ..., mask: UMat | None = ..., dtype: int = ...) -> UMat: ...

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: ...

@_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: ...
@_typing.overload
def addWeighted(src1: UMat, alpha: float, src2: UMat, beta: float, gamma: float, dst: UMat | None = ..., dtype: int = ...) -> UMat: ...

@_typing.overload
def applyColorMap(src: cv2.typing.MatLike, colormap: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def applyColorMap(src: UMat, colormap: int, dst: UMat | None = ...) -> UMat: ...
@_typing.overload
def applyColorMap(src: cv2.typing.MatLike, userColor: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def applyColorMap(src: UMat, userColor: UMat, dst: UMat | None = ...) -> UMat: ...

@_typing.overload
def approxPolyDP(curve: cv2.typing.MatLike, epsilon: float, closed: bool, approxCurve: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def approxPolyDP(curve: UMat, epsilon: float, closed: bool, approxCurve: UMat | None = ...) -> UMat: ...

@_typing.overload
def approxPolyN(curve: cv2.typing.MatLike, nsides: int, approxCurve: cv2.typing.MatLike | None = ..., epsilon_percentage: float = ..., ensure_convex: bool = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def approxPolyN(curve: UMat, nsides: int, approxCurve: UMat | None = ..., epsilon_percentage: float = ..., ensure_convex: bool = ...) -> UMat: ...

@_typing.overload
def arcLength(curve: cv2.typing.MatLike, closed: bool) -> float: ...
@_typing.overload
def arcLength(curve: UMat, closed: bool) -> float: ...

@_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: ...
@_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: ...

@_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]: ...
@_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]: ...

@_typing.overload
def bilateralFilter(src: cv2.typing.MatLike, d: int, sigmaColor: float, sigmaSpace: float, dst: cv2.typing.MatLike | None = ..., borderType: int = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def bilateralFilter(src: UMat, d: int, sigmaColor: float, sigmaSpace: float, dst: UMat | None = ..., borderType: int = ...) -> UMat: ...

@_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: ...
@_typing.overload
def bitwise_and(src1: UMat, src2: UMat, dst: UMat | None = ..., mask: UMat | None = ...) -> UMat: ...

@_typing.overload
def bitwise_not(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def bitwise_not(src: UMat, dst: UMat | None = ..., mask: UMat | None = ...) -> UMat: ...

@_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: ...
@_typing.overload
def bitwise_or(src1: UMat, src2: UMat, dst: UMat | None = ..., mask: UMat | None = ...) -> UMat: ...

@_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: ...
@_typing.overload
def bitwise_xor(src1: UMat, src2: UMat, dst: UMat | None = ..., mask: UMat | None = ...) -> UMat: ...

@_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: ...

@_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: ...

def borderInterpolate(p: int, len: int, borderType: int) -> int: ...

@_typing.overload
def boundingRect(array: cv2.typing.MatLike) -> cv2.typing.Rect: ...
@_typing.overload
def boundingRect(array: UMat) -> cv2.typing.Rect: ...

@_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: ...

@_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]: ...

@_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]: ...
@_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]: ...

@_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]: ...
@_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]: ...

@_typing.overload
def calibrationMatrixValues(cameraMatrix: cv2.typing.MatLike, imageSize: cv2.typing.Size, apertureWidth: float, apertureHeight: float) -> tuple[float, float, float, cv2.typing.Point2d, float]: ...
@_typing.overload
def calibrationMatrixValues(cameraMatrix: UMat, imageSize: cv2.typing.Size, apertureWidth: float, apertureHeight: float) -> tuple[float, float, float, cv2.typing.Point2d, float]: ...

@_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]: ...
@_typing.overload
def cartToPolar(x: UMat, y: UMat, magnitude: UMat | None = ..., angle: UMat | None = ..., angleInDegrees: bool = ...) -> tuple[UMat, UMat]: ...

@_typing.overload
def checkChessboard(img: cv2.typing.MatLike, size: cv2.typing.Size) -> bool: ...
@_typing.overload
def checkChessboard(img: UMat, size: cv2.typing.Size) -> bool: ...

def checkHardwareSupport(feature: int) -> bool: ...

@_typing.overload
def checkRange(a: cv2.typing.MatLike, quiet: bool = ..., minVal: float = ..., maxVal: float = ...) -> tuple[bool, cv2.typing.Point]: ...
@_typing.overload
def checkRange(a: UMat, quiet: bool = ..., minVal: float = ..., maxVal: float = ...) -> tuple[bool, cv2.typing.Point]: ...

@_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]: ...

@_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: ...

@_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: ...

@_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: ...

@_typing.overload
def completeSymm(m: cv2.typing.MatLike, lowerToUpper: bool = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def completeSymm(m: UMat, lowerToUpper: bool = ...) -> UMat: ...

@_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]: ...
@_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: ...
@_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: ...

@_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 createAffineTransformer(fullAffine: bool) -> AffineTransformer: ...

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 createChiHistogramCostExtractor(nDummies: int = ..., defaultCost: float = ...) -> HistogramCostExtractor: ...

def createEMDHistogramCostExtractor(flag: int = ..., nDummies: int = ..., defaultCost: float = ...) -> HistogramCostExtractor: ...

def createEMDL1HistogramCostExtractor(nDummies: int = ..., defaultCost: float = ...) -> HistogramCostExtractor: ...

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 createHausdorffDistanceExtractor(distanceFlag: int = ..., rankProp: float = ...) -> HausdorffDistanceExtractor: ...

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 createNormHistogramCostExtractor(flag: int = ..., nDummies: int = ..., defaultCost: float = ...) -> HistogramCostExtractor: ...

def createShapeContextDistanceExtractor(nAngularBins: int = ..., nRadialBins: int = ..., innerRadius: float = ..., outerRadius: float = ..., iterations: int = ..., comparer: HistogramCostExtractor = ..., transformer: ShapeTransformer = ...) -> ShapeContextDistanceExtractor: ...

def createThinPlateSplineShapeTransformer(regularizationParameter: float = ...) -> ThinPlateSplineShapeTransformer: ...

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 = ..., hint: AlgorithmHint = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def cvtColor(src: UMat, code: int, dst: UMat | None = ..., dstCn: int = ..., hint: AlgorithmHint = ...) -> UMat: ...

@_typing.overload
def cvtColorTwoPlane(src1: cv2.typing.MatLike, src2: cv2.typing.MatLike, code: int, dst: cv2.typing.MatLike | None = ..., hint: AlgorithmHint = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def cvtColorTwoPlane(src1: UMat, src2: UMat, code: int, dst: UMat | None = ..., hint: AlgorithmHint = ...) -> 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]: ...
@_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: ...

@_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: ...

@_typing.overload
def determinant(mtx: cv2.typing.MatLike) -> float: ...
@_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: ...

@_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: ...
@_typing.overload
def dilate(src: UMat, kernel: UMat, dst: UMat | None = ..., anchor: cv2.typing.Point = ..., iterations: int = ..., borderType: int = ..., borderValue: cv2.typing.Scalar = ...) -> UMat: ...

def displayOverlay(winname: str, text: str, delayms: int = ...) -> None: ...

def displayStatusBar(winname: str, text: str, delayms: int = ...) -> None: ...

@_typing.overload
def distanceTransform(src: cv2.typing.MatLike, distanceType: int, maskSize: int, dst: cv2.typing.MatLike | None = ..., dstType: int = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def distanceTransform(src: UMat, distanceType: int, maskSize: int, dst: UMat | None = ..., dstType: int = ...) -> UMat: ...

@_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]: ...

@_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 | None, 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 | None, 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 getClosestEllipsePoints(ellipse_params: cv2.typing.RotatedRect, points: cv2.typing.MatLike, closest_pts: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def getClosestEllipsePoints(ellipse_params: cv2.typing.RotatedRect, points: UMat, closest_pts: UMat | None = ...) -> UMat: ...

def getDefaultAlgorithmHint() -> AlgorithmHint: ...

@_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 | None: ...
@_typing.overload
def imdecode(buf: UMat, flags: int) -> cv2.typing.MatLike | None: ...

@_typing.overload
def imdecodeWithMetadata(buf: cv2.typing.MatLike, metadata: _typing.Sequence[cv2.typing.MatLike] | None = ..., flags: int = ...) -> tuple[cv2.typing.MatLike, _typing.Sequence[int], _typing.Sequence[cv2.typing.MatLike]]: ...
@_typing.overload
def imdecodeWithMetadata(buf: UMat, metadata: _typing.Sequence[UMat] | None = ..., flags: int = ...) -> tuple[cv2.typing.MatLike, _typing.Sequence[int], _typing.Sequence[UMat]]: ...

@_typing.overload
def imdecodeanimation(buf: cv2.typing.MatLike, start: int = ..., count: int = ...) -> tuple[bool, Animation]: ...
@_typing.overload
def imdecodeanimation(buf: UMat, start: int = ..., count: int = ...) -> tuple[bool, Animation]: ...

@_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 imencodeWithMetadata(ext: str, img: cv2.typing.MatLike, metadataTypes: _typing.Sequence[int], metadata: _typing.Sequence[cv2.typing.MatLike], params: _typing.Sequence[int] = ...) -> tuple[bool, numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]]]: ...
@_typing.overload
def imencodeWithMetadata(ext: str, img: UMat, metadataTypes: _typing.Sequence[int], metadata: _typing.Sequence[UMat], params: _typing.Sequence[int] = ...) -> tuple[bool, numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]]]: ...

def imencodeanimation(ext: str, animation: Animation, params: _typing.Sequence[int] = ...) -> tuple[bool, numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]]]: ...

@_typing.overload
def imencodemulti(ext: str, imgs: _typing.Sequence[cv2.typing.MatLike], params: _typing.Sequence[int] = ...) -> tuple[bool, numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]]]: ...
@_typing.overload
def imencodemulti(ext: str, imgs: _typing.Sequence[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 | None: ...
@_typing.overload
def imread(filename: str, dst: cv2.typing.MatLike | None = ..., flags: int = ...) -> cv2.typing.MatLike | None: ...
@_typing.overload
def imread(filename: str, dst: UMat | None = ..., flags: int = ...) -> UMat | None: ...

@_typing.overload
def imreadWithMetadata(filename: str, metadata: _typing.Sequence[cv2.typing.MatLike] | None = ..., flags: int = ...) -> tuple[cv2.typing.MatLike, _typing.Sequence[int], _typing.Sequence[cv2.typing.MatLike]]: ...
@_typing.overload
def imreadWithMetadata(filename: str, metadata: _typing.Sequence[UMat] | None = ..., flags: int = ...) -> tuple[cv2.typing.MatLike, _typing.Sequence[int], _typing.Sequence[UMat]]: ...

def imreadanimation(filename: str, start: int = ..., count: int = ...) -> tuple[bool, Animation]: ...

@_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 imwriteWithMetadata(filename: str, img: cv2.typing.MatLike, metadataTypes: _typing.Sequence[int], metadata: _typing.Sequence[cv2.typing.MatLike], params: _typing.Sequence[int] = ...) -> bool: ...
@_typing.overload
def imwriteWithMetadata(filename: str, img: UMat, metadataTypes: _typing.Sequence[int], metadata: _typing.Sequence[UMat], params: _typing.Sequence[int] = ...) -> bool: ...

def imwriteanimation(filename: str, animation: Animation, 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 thresholdWithMask(src: cv2.typing.MatLike, dst: cv2.typing.MatLike, mask: cv2.typing.MatLike, thresh: float, maxval: float, type: int) -> tuple[float, cv2.typing.MatLike]: ...
@_typing.overload
def thresholdWithMask(src: UMat, dst: UMat, mask: UMat, thresh: float, maxval: float, type: int) -> 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: ...
@_typing.overload
def transposeND(src: UMat, order: _typing.Sequence[int], dst: UMat | None = ...) -> UMat: ...

@_typing.overload
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: ...
@_typing.overload
def triangulatePoints(projMatr1: UMat, projMatr2: UMat, projPoints1: UMat, projPoints2: UMat, points4D: UMat | None = ...) -> UMat: ...

@_typing.overload
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: ...
@_typing.overload
def undistort(src: UMat, cameraMatrix: UMat, distCoeffs: UMat, dst: UMat | None = ..., newCameraMatrix: UMat | None = ...) -> UMat: ...

@_typing.overload
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: ...
@_typing.overload
def undistortImagePoints(src: UMat, cameraMatrix: UMat, distCoeffs: UMat, dst: UMat | None = ..., arg1: cv2.typing.TermCriteria = ...) -> UMat: ...

@_typing.overload
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: ...
@_typing.overload
def undistortPoints(src: UMat, cameraMatrix: UMat, distCoeffs: UMat, dst: UMat | None = ..., R: UMat | None = ..., P: UMat | None = ...) -> UMat: ...

@_typing.overload
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: ...
@_typing.overload
def undistortPointsIter(src: UMat, cameraMatrix: UMat, distCoeffs: UMat, R: UMat, P: UMat, criteria: cv2.typing.TermCriteria, dst: UMat | None = ...) -> UMat: ...

def useOpenVX() -> bool: ...

def useOptimized() -> bool: ...

@_typing.overload
def validateDisparity(disparity: cv2.typing.MatLike, cost: cv2.typing.MatLike, minDisparity: int, numberOfDisparities: int, disp12MaxDisp: int = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def validateDisparity(disparity: UMat, cost: UMat, minDisparity: int, numberOfDisparities: int, disp12MaxDisp: int = ...) -> UMat: ...

@_typing.overload
def vconcat(src: _typing.Sequence[cv2.typing.MatLike], dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def vconcat(src: _typing.Sequence[UMat], dst: UMat | None = ...) -> UMat: ...

def waitKey(delay: int = ...) -> int: ...

def waitKeyEx(delay: int = ...) -> int: ...

@_typing.overload
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: ...
@_typing.overload
def warpAffine(src: UMat, M: UMat, dsize: cv2.typing.Size, dst: UMat | None = ..., flags: int = ..., borderMode: int = ..., borderValue: cv2.typing.Scalar = ...) -> UMat: ...

@_typing.overload
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: ...
@_typing.overload
def warpPerspective(src: UMat, M: UMat, dsize: cv2.typing.Size, dst: UMat | None = ..., flags: int = ..., borderMode: int = ..., borderValue: cv2.typing.Scalar = ...) -> UMat: ...

@_typing.overload
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: ...
@_typing.overload
def warpPolar(src: UMat, dsize: cv2.typing.Size, center: cv2.typing.Point2f, maxRadius: float, flags: int, dst: UMat | None = ...) -> UMat: ...

@_typing.overload
def watershed(image: cv2.typing.MatLike, markers: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
@_typing.overload
def watershed(image: UMat, markers: UMat) -> UMat: ...

@_typing.overload
def writeOpticalFlow(path: str, flow: cv2.typing.MatLike) -> bool: ...
@_typing.overload
def writeOpticalFlow(path: str, flow: UMat) -> bool: ...

def createTrackbar(trackbarName: str, windowName: str, value: int, count: int, onChange: _typing.Callable[[int], None]) -> None: ...

def createButton(buttonName: str, onChange: _typing.Callable[[tuple[int] | tuple[int, _typing.Any]], None], userData: _typing.Any | None = ..., buttonType: int = ..., initialButtonState: int = ...) -> None: ...

def setMouseCallback(windowName: str, onMouse: _typing.Callable[[int, int, int, int, _typing.Any | None], None], param: _typing.Any | None = ...) -> None: ...

def CV_8UC(channels: int) -> int: ...

def CV_8SC(channels: int) -> int: ...

def CV_16UC(channels: int) -> int: ...

def CV_16SC(channels: int) -> int: ...

def CV_32SC(channels: int) -> int: ...

def CV_32FC(channels: int) -> int: ...

def CV_64FC(channels: int) -> int: ...

def CV_16FC(channels: int) -> int: ...

def CV_MAKETYPE(depth: int, channels: int) -> int: ...

def dnn_registerLayer(layerTypeName: str, layerClass: _typing.Type[cv2.dnn.LayerProtocol]) -> None: ...

def dnn_unregisterLayer(layerTypeName: str) -> None: ...

def redirectError(onError: _typing.Callable[[int, str, str, str, int], None] | None) -> None: ...


