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Aluode/PerceptionLabPortable

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rootpython_embedLibsite-packagescv2fisheye__init__.pyi
__init__.pyi89 linesDownload Raw Back to fisheye
1__all__: list[str] = []
2
3import cv2
4import cv2.typing
5import typing as _typing
6
7
8# Enumerations
9CALIB_USE_INTRINSIC_GUESS: int
10CALIB_RECOMPUTE_EXTRINSIC: int
11CALIB_CHECK_COND: int
12CALIB_FIX_SKEW: int
13CALIB_FIX_K1: int
14CALIB_FIX_K2: int
15CALIB_FIX_K3: int
16CALIB_FIX_K4: int
17CALIB_FIX_INTRINSIC: int
18CALIB_FIX_PRINCIPAL_POINT: int
19CALIB_ZERO_DISPARITY: int
20CALIB_FIX_FOCAL_LENGTH: int
21
22
23
24# Functions
25@_typing.overload
26def calibrate(objectPoints: _typing.Sequence[cv2.typing.MatLike], imagePoints: _typing.Sequence[cv2.typing.MatLike], image_size: cv2.typing.Size, K: cv2.typing.MatLike, D: 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]]: ...
27@_typing.overload
28def calibrate(objectPoints: _typing.Sequence[cv2.UMat], imagePoints: _typing.Sequence[cv2.UMat], image_size: cv2.typing.Size, K: cv2.UMat, D: cv2.UMat, rvecs: _typing.Sequence[cv2.UMat] | None = ..., tvecs: _typing.Sequence[cv2.UMat] | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, cv2.UMat, cv2.UMat, _typing.Sequence[cv2.UMat], _typing.Sequence[cv2.UMat]]: ...
29
30@_typing.overload
31def distortPoints(undistorted: cv2.typing.MatLike, K: cv2.typing.MatLike, D: cv2.typing.MatLike, distorted: cv2.typing.MatLike | None = ..., alpha: float = ...) -> cv2.typing.MatLike: ...
32@_typing.overload
33def distortPoints(undistorted: cv2.UMat, K: cv2.UMat, D: cv2.UMat, distorted: cv2.UMat | None = ..., alpha: float = ...) -> cv2.UMat: ...
34@_typing.overload
35def distortPoints(undistorted: cv2.typing.MatLike, Kundistorted: cv2.typing.MatLike, K: cv2.typing.MatLike, D: cv2.typing.MatLike, distorted: cv2.typing.MatLike | None = ..., alpha: float = ...) -> cv2.typing.MatLike: ...
36@_typing.overload
37def distortPoints(undistorted: cv2.UMat, Kundistorted: cv2.UMat, K: cv2.UMat, D: cv2.UMat, distorted: cv2.UMat | None = ..., alpha: float = ...) -> cv2.UMat: ...
38
39@_typing.overload
40def estimateNewCameraMatrixForUndistortRectify(K: cv2.typing.MatLike, D: cv2.typing.MatLike, image_size: cv2.typing.Size, R: cv2.typing.MatLike, P: cv2.typing.MatLike | None = ..., balance: float = ..., new_size: cv2.typing.Size = ..., fov_scale: float = ...) -> cv2.typing.MatLike: ...
41@_typing.overload
42def estimateNewCameraMatrixForUndistortRectify(K: cv2.UMat, D: cv2.UMat, image_size: cv2.typing.Size, R: cv2.UMat, P: cv2.UMat | None = ..., balance: float = ..., new_size: cv2.typing.Size = ..., fov_scale: float = ...) -> cv2.UMat: ...
43
44@_typing.overload
45def initUndistortRectifyMap(K: cv2.typing.MatLike, D: cv2.typing.MatLike, R: cv2.typing.MatLike, P: 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]: ...
46@_typing.overload
47def initUndistortRectifyMap(K: cv2.UMat, D: cv2.UMat, R: cv2.UMat, P: cv2.UMat, size: cv2.typing.Size, m1type: int, map1: cv2.UMat | None = ..., map2: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat]: ...
48
49@_typing.overload
50def projectPoints(objectPoints: cv2.typing.MatLike, rvec: cv2.typing.MatLike, tvec: cv2.typing.MatLike, K: cv2.typing.MatLike, D: cv2.typing.MatLike, imagePoints: cv2.typing.MatLike | None = ..., alpha: float = ..., jacobian: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
51@_typing.overload
52def projectPoints(objectPoints: cv2.UMat, rvec: cv2.UMat, tvec: cv2.UMat, K: cv2.UMat, D: cv2.UMat, imagePoints: cv2.UMat | None = ..., alpha: float = ..., jacobian: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat]: ...
53
54@_typing.overload
55def 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 = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[bool, cv2.typing.MatLike, cv2.typing.MatLike]: ...
56@_typing.overload
57def solvePnP(objectPoints: cv2.UMat, imagePoints: cv2.UMat, cameraMatrix: cv2.UMat, distCoeffs: cv2.UMat, rvec: cv2.UMat | None = ..., tvec: cv2.UMat | None = ..., useExtrinsicGuess: bool = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[bool, cv2.UMat, cv2.UMat]: ...
58
59@_typing.overload
60def 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 = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[bool, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
61@_typing.overload
62def solvePnPRansac(objectPoints: cv2.UMat, imagePoints: cv2.UMat, cameraMatrix: cv2.UMat, distCoeffs: cv2.UMat, rvec: cv2.UMat | None = ..., tvec: cv2.UMat | None = ..., useExtrinsicGuess: bool = ..., iterationsCount: int = ..., reprojectionError: float = ..., confidence: float = ..., inliers: cv2.UMat | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[bool, cv2.UMat, cv2.UMat, cv2.UMat]: ...
63
64@_typing.overload
65def stereoCalibrate(objectPoints: _typing.Sequence[cv2.typing.MatLike], imagePoints1: _typing.Sequence[cv2.typing.MatLike], imagePoints2: _typing.Sequence[cv2.typing.MatLike], K1: cv2.typing.MatLike, D1: cv2.typing.MatLike, K2: cv2.typing.MatLike, D2: cv2.typing.MatLike, imageSize: cv2.typing.Size, R: cv2.typing.MatLike | None = ..., T: cv2.typing.MatLike | None = ..., 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, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, _typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike]]: ...
66@_typing.overload
67def stereoCalibrate(objectPoints: _typing.Sequence[cv2.UMat], imagePoints1: _typing.Sequence[cv2.UMat], imagePoints2: _typing.Sequence[cv2.UMat], K1: cv2.UMat, D1: cv2.UMat, K2: cv2.UMat, D2: cv2.UMat, imageSize: cv2.typing.Size, R: cv2.UMat | None = ..., T: cv2.UMat | None = ..., rvecs: _typing.Sequence[cv2.UMat] | None = ..., tvecs: _typing.Sequence[cv2.UMat] | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat, _typing.Sequence[cv2.UMat], _typing.Sequence[cv2.UMat]]: ...
68@_typing.overload
69def stereoCalibrate(objectPoints: _typing.Sequence[cv2.typing.MatLike], imagePoints1: _typing.Sequence[cv2.typing.MatLike], imagePoints2: _typing.Sequence[cv2.typing.MatLike], K1: cv2.typing.MatLike, D1: cv2.typing.MatLike, K2: cv2.typing.MatLike, D2: cv2.typing.MatLike, imageSize: cv2.typing.Size, R: cv2.typing.MatLike | None = ..., T: 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]: ...
70@_typing.overload
71def stereoCalibrate(objectPoints: _typing.Sequence[cv2.UMat], imagePoints1: _typing.Sequence[cv2.UMat], imagePoints2: _typing.Sequence[cv2.UMat], K1: cv2.UMat, D1: cv2.UMat, K2: cv2.UMat, D2: cv2.UMat, imageSize: cv2.typing.Size, R: cv2.UMat | None = ..., T: cv2.UMat | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat]: ...
72
73@_typing.overload
74def stereoRectify(K1: cv2.typing.MatLike, D1: cv2.typing.MatLike, K2: cv2.typing.MatLike, D2: cv2.typing.MatLike, imageSize: cv2.typing.Size, R: cv2.typing.MatLike, tvec: cv2.typing.MatLike, flags: int, 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 = ..., newImageSize: cv2.typing.Size = ..., balance: float = ..., fov_scale: float = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
75@_typing.overload
76def stereoRectify(K1: cv2.UMat, D1: cv2.UMat, K2: cv2.UMat, D2: cv2.UMat, imageSize: cv2.typing.Size, R: cv2.UMat, tvec: cv2.UMat, flags: int, R1: cv2.UMat | None = ..., R2: cv2.UMat | None = ..., P1: cv2.UMat | None = ..., P2: cv2.UMat | None = ..., Q: cv2.UMat | None = ..., newImageSize: cv2.typing.Size = ..., balance: float = ..., fov_scale: float = ...) -> tuple[cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat]: ...
77
78@_typing.overload
79def undistortImage(distorted: cv2.typing.MatLike, K: cv2.typing.MatLike, D: cv2.typing.MatLike, undistorted: cv2.typing.MatLike | None = ..., Knew: cv2.typing.MatLike | None = ..., new_size: cv2.typing.Size = ...) -> cv2.typing.MatLike: ...
80@_typing.overload
81def undistortImage(distorted: cv2.UMat, K: cv2.UMat, D: cv2.UMat, undistorted: cv2.UMat | None = ..., Knew: cv2.UMat | None = ..., new_size: cv2.typing.Size = ...) -> cv2.UMat: ...
82
83@_typing.overload
84def undistortPoints(distorted: cv2.typing.MatLike, K: cv2.typing.MatLike, D: cv2.typing.MatLike, undistorted: cv2.typing.MatLike | None = ..., R: cv2.typing.MatLike | None = ..., P: cv2.typing.MatLike | None = ..., criteria: cv2.typing.TermCriteria = ...) -> cv2.typing.MatLike: ...
85@_typing.overload
86def undistortPoints(distorted: cv2.UMat, K: cv2.UMat, D: cv2.UMat, undistorted: cv2.UMat | None = ..., R: cv2.UMat | None = ..., P: cv2.UMat | None = ..., criteria: cv2.typing.TermCriteria = ...) -> cv2.UMat: ...
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