calib3d
library
Functions
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calibrateCamera(Contours3f objectPoints, Contours2f imagePoints, (int, int) imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, {Mat? rvecs, Mat? tvecs, int flags = 0, (int, int, double) criteria = (TERM_COUNT + TERM_EPS, 30, 1e-4)})
→ (double, Mat, Mat, Mat, Mat)
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calibrateCameraAsync(Contours3f objectPoints, Contours2f imagePoints, (int, int) imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, {Mat? rvecs, Mat? tvecs, int flags = 0, (int, int, double) criteria = (TERM_COUNT + TERM_EPS, 30, 1e-4)})
→ Future<(double, Mat, Mat, Mat, Mat)>
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drawChessboardCorners(InputOutputArray image, (int, int) patternSize, InputArray corners, bool patternWasFound)
→ Mat
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drawChessboardCornersAsync(InputOutputArray image, (int, int) patternSize, InputArray corners, bool patternWasFound)
→ Future<Mat>
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estimateAffine2D(VecPoint2f from, VecPoint2f to, {int method = RANSAC, double ransacReprojThreshold = 3, int maxIters = 2000, double confidence = 0.99, int refineIters = 10, OutputArray? inliers})
→ (Mat, Mat)
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estimateAffine2DAsync(VecPoint2f from, VecPoint2f to, {int method = RANSAC, double ransacReprojThreshold = 3, int maxIters = 2000, double confidence = 0.99, int refineIters = 10})
→ Future<(Mat, Mat)>
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estimateAffinePartial2D(VecPoint2f from, VecPoint2f to, {int method = RANSAC, double ransacReprojThreshold = 3, int maxIters = 2000, double confidence = 0.99, int refineIters = 10, OutputArray? inliers})
→ (Mat, Mat)
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estimateAffinePartial2DAsync(VecPoint2f from, VecPoint2f to, {int method = RANSAC, double ransacReprojThreshold = 3, int maxIters = 2000, double confidence = 0.99, int refineIters = 10})
→ Future<(Mat, Mat)>
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findChessboardCorners(InputArray image, (int, int) patternSize, {OutputArray? corners, int flags = CALIB_CB_ADAPTIVE_THRESH + CALIB_CB_NORMALIZE_IMAGE})
→ (bool, Mat)
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findChessboardCornersAsync(InputArray image, (int, int) patternSize, {int flags = CALIB_CB_ADAPTIVE_THRESH + CALIB_CB_NORMALIZE_IMAGE})
→ Future<(bool, Mat)>
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getOptimalNewCameraMatrix(InputArray cameraMatrix, InputArray distCoeffs, (int, int) imageSize, double alpha, {(int, int) newImgSize = (0, 0), bool centerPrincipalPoint = false})
→ (Mat, Rect)
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GetOptimalNewCameraMatrixWithParams computes and returns the optimal new camera matrix based on the free scaling parameter.
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getOptimalNewCameraMatrixAsync(InputArray cameraMatrix, InputArray distCoeffs, (int, int) imageSize, double alpha, {(int, int) newImgSize = (0, 0), bool centerPrincipalPoint = false})
→ Future<(Mat, Rect)>
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GetOptimalNewCameraMatrixWithParams computes and returns the optimal new camera matrix based on the free scaling parameter.
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initUndistortRectifyMap(InputArray cameraMatrix, InputArray distCoeffs, InputArray R, InputArray newCameraMatrix, (int, int) size, int m1type, {OutputArray? map1, OutputArray? map2})
→ (Mat, Mat)
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InitUndistortRectifyMap computes the joint undistortion and rectification transformation and represents the result in the form of maps for remap
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initUndistortRectifyMapAsync(InputArray cameraMatrix, InputArray distCoeffs, InputArray R, InputArray newCameraMatrix, (int, int) size, int m1type)
→ Future<(Mat, Mat)>
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InitUndistortRectifyMap computes the joint undistortion and rectification transformation and represents the result in the form of maps for remap
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undistort(InputArray src, InputArray cameraMatrix, InputArray distCoeffs, {OutputArray? dst, InputArray? newCameraMatrix})
→ Mat
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undistortAsync(InputArray src, InputArray cameraMatrix, InputArray distCoeffs, {InputArray? newCameraMatrix})
→ Future<Mat>
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undistortPoints(InputArray src, InputArray cameraMatrix, InputArray distCoeffs, {OutputArray? dst, InputArray? R, InputArray? P, (int, int, double) criteria = (TERM_COUNT + TERM_EPS, 30, 1e-4)})
→ Mat
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undistortPointsAsync(InputArray src, InputArray cameraMatrix, InputArray distCoeffs, {InputArray? R, InputArray? P, (int, int, double) criteria = (TERM_COUNT + TERM_EPS, 30, 1e-4)})
→ Future<Mat>
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