Uses of Class org.opencv.core.Mat (AistCV 4.5.3 API)

Packages that use Mat
Package	Description
org.opencv.aruco
org.opencv.barcode
org.opencv.bgsegm
org.opencv.bioinspired
org.opencv.calib3d
org.opencv.core
org.opencv.dnn
org.opencv.face
org.opencv.features2d
org.opencv.highgui
org.opencv.img_hash
org.opencv.imgcodecs
org.opencv.imgproc
org.opencv.ml
org.opencv.objdetect
org.opencv.phase_unwrapping
org.opencv.photo
org.opencv.plot
org.opencv.structured_light
org.opencv.text
org.opencv.tracking
org.opencv.utils
org.opencv.video
org.opencv.videoio
org.opencv.wechat_qrcode
org.opencv.xfeatures2d
org.opencv.ximgproc
org.opencv.xphoto

Uses of Mat in org.opencv.aruco

Methods in org.opencv.aruco that return Mat
Modifier and Type	Method	Description
`Mat`	Dictionary.`get_bytesList()`
`static Mat`	Dictionary.`getBitsFromByteList(Mat byteList, int markerSize)`	Transform list of bytes to matrix of bits
`static Mat`	Dictionary.`getByteListFromBits(Mat bits)`	Transform matrix of bits to list of bytes in the 4 rotations

Methods in org.opencv.aruco with parameters of type Mat
Modifier and Type	Method	Description
`static double`	Aruco.`calibrateCameraAruco(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs)`	It's the same function as #calibrateCameraAruco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraAruco(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs)`	It's the same function as #calibrateCameraAruco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraAruco(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs)`	It's the same function as #calibrateCameraAruco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraAruco(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags)`	It's the same function as #calibrateCameraAruco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraAruco(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags, TermCriteria criteria)`	It's the same function as #calibrateCameraAruco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraArucoExtended(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors)`	Calibrate a camera using aruco markers
`static double`	Aruco.`calibrateCameraArucoExtended(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags)`	Calibrate a camera using aruco markers
`static double`	Aruco.`calibrateCameraArucoExtended(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags, TermCriteria criteria)`	Calibrate a camera using aruco markers
`static double`	Aruco.`calibrateCameraCharuco(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs)`	It's the same function as #calibrateCameraCharuco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraCharuco(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs)`	It's the same function as #calibrateCameraCharuco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraCharuco(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs)`	It's the same function as #calibrateCameraCharuco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraCharuco(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags)`	It's the same function as #calibrateCameraCharuco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraCharuco(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags, TermCriteria criteria)`	It's the same function as #calibrateCameraCharuco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraCharucoExtended(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors)`	Calibrate a camera using Charuco corners
`static double`	Aruco.`calibrateCameraCharucoExtended(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags)`	Calibrate a camera using Charuco corners
`static double`	Aruco.`calibrateCameraCharucoExtended(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags, TermCriteria criteria)`	Calibrate a camera using Charuco corners
`static Board`	Board.`create(List<Mat> objPoints, Dictionary dictionary, Mat ids)`	Provide way to create Board by passing necessary data.
`static void`	Aruco.`detectCharucoDiamond(Mat image, List<Mat> markerCorners, Mat markerIds, float squareMarkerLengthRate, List<Mat> diamondCorners, Mat diamondIds)`	Detect ChArUco Diamond markers
`static void`	Aruco.`detectCharucoDiamond(Mat image, List<Mat> markerCorners, Mat markerIds, float squareMarkerLengthRate, List<Mat> diamondCorners, Mat diamondIds, Mat cameraMatrix)`	Detect ChArUco Diamond markers
`static void`	Aruco.`detectCharucoDiamond(Mat image, List<Mat> markerCorners, Mat markerIds, float squareMarkerLengthRate, List<Mat> diamondCorners, Mat diamondIds, Mat cameraMatrix, Mat distCoeffs)`	Detect ChArUco Diamond markers
`static void`	Aruco.`detectMarkers(Mat image, Dictionary dictionary, List<Mat> corners, Mat ids)`	Basic marker detection
`static void`	Aruco.`detectMarkers(Mat image, Dictionary dictionary, List<Mat> corners, Mat ids, DetectorParameters parameters)`	Basic marker detection
`static void`	Aruco.`detectMarkers(Mat image, Dictionary dictionary, List<Mat> corners, Mat ids, DetectorParameters parameters, List<Mat> rejectedImgPoints)`	Basic marker detection
`static void`	Aruco.`detectMarkers(Mat image, Dictionary dictionary, List<Mat> corners, Mat ids, DetectorParameters parameters, List<Mat> rejectedImgPoints, Mat cameraMatrix)`	Basic marker detection
`static void`	Aruco.`detectMarkers(Mat image, Dictionary dictionary, List<Mat> corners, Mat ids, DetectorParameters parameters, List<Mat> rejectedImgPoints, Mat cameraMatrix, Mat distCoeff)`	Basic marker detection
`void`	CharucoBoard.`draw(Size outSize, Mat img)`	Draw a ChArUco board
`void`	CharucoBoard.`draw(Size outSize, Mat img, int marginSize)`	Draw a ChArUco board
`void`	CharucoBoard.`draw(Size outSize, Mat img, int marginSize, int borderBits)`	Draw a ChArUco board
`void`	GridBoard.`draw(Size outSize, Mat img)`	Draw a GridBoard
`void`	GridBoard.`draw(Size outSize, Mat img, int marginSize)`	Draw a GridBoard
`void`	GridBoard.`draw(Size outSize, Mat img, int marginSize, int borderBits)`	Draw a GridBoard
`static void`	Aruco.`drawAxis(Mat image, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, float length)`	Deprecated. use cv::drawFrameAxes
`static void`	Aruco.`drawDetectedCornersCharuco(Mat image, Mat charucoCorners)`	Draws a set of Charuco corners
`static void`	Aruco.`drawDetectedCornersCharuco(Mat image, Mat charucoCorners, Mat charucoIds)`	Draws a set of Charuco corners
`static void`	Aruco.`drawDetectedCornersCharuco(Mat image, Mat charucoCorners, Mat charucoIds, Scalar cornerColor)`	Draws a set of Charuco corners
`static void`	Aruco.`drawDetectedDiamonds(Mat image, List<Mat> diamondCorners)`	Draw a set of detected ChArUco Diamond markers
`static void`	Aruco.`drawDetectedDiamonds(Mat image, List<Mat> diamondCorners, Mat diamondIds)`	Draw a set of detected ChArUco Diamond markers
`static void`	Aruco.`drawDetectedDiamonds(Mat image, List<Mat> diamondCorners, Mat diamondIds, Scalar borderColor)`	Draw a set of detected ChArUco Diamond markers
`static void`	Aruco.`drawDetectedMarkers(Mat image, List<Mat> corners)`	Draw detected markers in image
`static void`	Aruco.`drawDetectedMarkers(Mat image, List<Mat> corners, Mat ids)`	Draw detected markers in image
`static void`	Aruco.`drawDetectedMarkers(Mat image, List<Mat> corners, Mat ids, Scalar borderColor)`	Draw detected markers in image
`static void`	Aruco.`drawMarker(Dictionary dictionary, int id, int sidePixels, Mat img)`	Draw a canonical marker image
`static void`	Aruco.`drawMarker(Dictionary dictionary, int id, int sidePixels, Mat img, int borderBits)`	Draw a canonical marker image
`void`	Dictionary.`drawMarker(int id, int sidePixels, Mat _img)`	Draw a canonical marker image
`void`	Dictionary.`drawMarker(int id, int sidePixels, Mat _img, int borderBits)`	Draw a canonical marker image
`static void`	Aruco.`drawPlanarBoard(Board board, Size outSize, Mat img)`	Draw a planar board SEE: _drawPlanarBoardImpl
`static void`	Aruco.`drawPlanarBoard(Board board, Size outSize, Mat img, int marginSize)`	Draw a planar board SEE: _drawPlanarBoardImpl
`static void`	Aruco.`drawPlanarBoard(Board board, Size outSize, Mat img, int marginSize, int borderBits)`	Draw a planar board SEE: _drawPlanarBoardImpl
`static int`	Aruco.`estimatePoseBoard(List<Mat> corners, Mat ids, Board board, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec)`	Pose estimation for a board of markers
`static int`	Aruco.`estimatePoseBoard(List<Mat> corners, Mat ids, Board board, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, boolean useExtrinsicGuess)`	Pose estimation for a board of markers
`static boolean`	Aruco.`estimatePoseCharucoBoard(Mat charucoCorners, Mat charucoIds, CharucoBoard board, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec)`	Pose estimation for a ChArUco board given some of their corners
`static boolean`	Aruco.`estimatePoseCharucoBoard(Mat charucoCorners, Mat charucoIds, CharucoBoard board, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, boolean useExtrinsicGuess)`	Pose estimation for a ChArUco board given some of their corners
`static void`	Aruco.`estimatePoseSingleMarkers(List<Mat> corners, float markerLength, Mat cameraMatrix, Mat distCoeffs, Mat rvecs, Mat tvecs)`	Pose estimation for single markers
`static void`	Aruco.`estimatePoseSingleMarkers(List<Mat> corners, float markerLength, Mat cameraMatrix, Mat distCoeffs, Mat rvecs, Mat tvecs, Mat _objPoints)`	Pose estimation for single markers
`static Mat`	Dictionary.`getBitsFromByteList(Mat byteList, int markerSize)`	Transform list of bytes to matrix of bits
`static void`	Aruco.`getBoardObjectAndImagePoints(Board board, List<Mat> detectedCorners, Mat detectedIds, Mat objPoints, Mat imgPoints)`	Given a board configuration and a set of detected markers, returns the corresponding image points and object points to call solvePnP
`static Mat`	Dictionary.`getByteListFromBits(Mat bits)`	Transform matrix of bits to list of bytes in the 4 rotations
`static int`	Aruco.`interpolateCornersCharuco(List<Mat> markerCorners, Mat markerIds, Mat image, CharucoBoard board, Mat charucoCorners, Mat charucoIds)`	Interpolate position of ChArUco board corners
`static int`	Aruco.`interpolateCornersCharuco(List<Mat> markerCorners, Mat markerIds, Mat image, CharucoBoard board, Mat charucoCorners, Mat charucoIds, Mat cameraMatrix)`	Interpolate position of ChArUco board corners
`static int`	Aruco.`interpolateCornersCharuco(List<Mat> markerCorners, Mat markerIds, Mat image, CharucoBoard board, Mat charucoCorners, Mat charucoIds, Mat cameraMatrix, Mat distCoeffs)`	Interpolate position of ChArUco board corners
`static int`	Aruco.`interpolateCornersCharuco(List<Mat> markerCorners, Mat markerIds, Mat image, CharucoBoard board, Mat charucoCorners, Mat charucoIds, Mat cameraMatrix, Mat distCoeffs, int minMarkers)`	Interpolate position of ChArUco board corners
`static void`	Aruco.`refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners)`	Refind not detected markers based on the already detected and the board layout
`static void`	Aruco.`refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix)`	Refind not detected markers based on the already detected and the board layout
`static void`	Aruco.`refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs)`	Refind not detected markers based on the already detected and the board layout
`static void`	Aruco.`refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, float minRepDistance)`	Refind not detected markers based on the already detected and the board layout
`static void`	Aruco.`refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, float minRepDistance, float errorCorrectionRate)`	Refind not detected markers based on the already detected and the board layout
`static void`	Aruco.`refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, float minRepDistance, float errorCorrectionRate, boolean checkAllOrders)`	Refind not detected markers based on the already detected and the board layout
`static void`	Aruco.`refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, float minRepDistance, float errorCorrectionRate, boolean checkAllOrders, Mat recoveredIdxs)`	Refind not detected markers based on the already detected and the board layout
`static void`	Aruco.`refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, float minRepDistance, float errorCorrectionRate, boolean checkAllOrders, Mat recoveredIdxs, DetectorParameters parameters)`	Refind not detected markers based on the already detected and the board layout
`void`	Dictionary.`set_bytesList(Mat bytesList)`
`void`	Board.`setIds(Mat ids)`	Set ids vector
`static boolean`	Aruco.`testCharucoCornersCollinear(CharucoBoard _board, Mat _charucoIds)`	test whether the ChArUco markers are collinear

Method parameters in org.opencv.aruco with type arguments of type Mat
Modifier and Type	Method	Description
`static double`	Aruco.`calibrateCameraAruco(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs)`	It's the same function as #calibrateCameraAruco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraAruco(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs)`	It's the same function as #calibrateCameraAruco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraAruco(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs)`	It's the same function as #calibrateCameraAruco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraAruco(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags)`	It's the same function as #calibrateCameraAruco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraAruco(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags, TermCriteria criteria)`	It's the same function as #calibrateCameraAruco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraArucoExtended(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors)`	Calibrate a camera using aruco markers
`static double`	Aruco.`calibrateCameraArucoExtended(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags)`	Calibrate a camera using aruco markers
`static double`	Aruco.`calibrateCameraArucoExtended(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags, TermCriteria criteria)`	Calibrate a camera using aruco markers
`static double`	Aruco.`calibrateCameraCharuco(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs)`	It's the same function as #calibrateCameraCharuco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraCharuco(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs)`	It's the same function as #calibrateCameraCharuco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraCharuco(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs)`	It's the same function as #calibrateCameraCharuco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraCharuco(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags)`	It's the same function as #calibrateCameraCharuco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraCharuco(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags, TermCriteria criteria)`	It's the same function as #calibrateCameraCharuco but without calibration error estimation.
`static double`	Aruco.`calibrateCameraCharucoExtended(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors)`	Calibrate a camera using Charuco corners
`static double`	Aruco.`calibrateCameraCharucoExtended(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags)`	Calibrate a camera using Charuco corners
`static double`	Aruco.`calibrateCameraCharucoExtended(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags, TermCriteria criteria)`	Calibrate a camera using Charuco corners
`static Board`	Board.`create(List<Mat> objPoints, Dictionary dictionary, Mat ids)`	Provide way to create Board by passing necessary data.
`static void`	Aruco.`detectCharucoDiamond(Mat image, List<Mat> markerCorners, Mat markerIds, float squareMarkerLengthRate, List<Mat> diamondCorners, Mat diamondIds)`	Detect ChArUco Diamond markers
`static void`	Aruco.`detectCharucoDiamond(Mat image, List<Mat> markerCorners, Mat markerIds, float squareMarkerLengthRate, List<Mat> diamondCorners, Mat diamondIds, Mat cameraMatrix)`	Detect ChArUco Diamond markers
`static void`	Aruco.`detectCharucoDiamond(Mat image, List<Mat> markerCorners, Mat markerIds, float squareMarkerLengthRate, List<Mat> diamondCorners, Mat diamondIds, Mat cameraMatrix, Mat distCoeffs)`	Detect ChArUco Diamond markers
`static void`	Aruco.`detectMarkers(Mat image, Dictionary dictionary, List<Mat> corners, Mat ids)`	Basic marker detection
`static void`	Aruco.`detectMarkers(Mat image, Dictionary dictionary, List<Mat> corners, Mat ids, DetectorParameters parameters)`	Basic marker detection
`static void`	Aruco.`detectMarkers(Mat image, Dictionary dictionary, List<Mat> corners, Mat ids, DetectorParameters parameters, List<Mat> rejectedImgPoints)`	Basic marker detection
`static void`	Aruco.`detectMarkers(Mat image, Dictionary dictionary, List<Mat> corners, Mat ids, DetectorParameters parameters, List<Mat> rejectedImgPoints, Mat cameraMatrix)`	Basic marker detection
`static void`	Aruco.`detectMarkers(Mat image, Dictionary dictionary, List<Mat> corners, Mat ids, DetectorParameters parameters, List<Mat> rejectedImgPoints, Mat cameraMatrix, Mat distCoeff)`	Basic marker detection
`static void`	Aruco.`drawDetectedDiamonds(Mat image, List<Mat> diamondCorners)`	Draw a set of detected ChArUco Diamond markers
`static void`	Aruco.`drawDetectedDiamonds(Mat image, List<Mat> diamondCorners, Mat diamondIds)`	Draw a set of detected ChArUco Diamond markers
`static void`	Aruco.`drawDetectedDiamonds(Mat image, List<Mat> diamondCorners, Mat diamondIds, Scalar borderColor)`	Draw a set of detected ChArUco Diamond markers
`static void`	Aruco.`drawDetectedMarkers(Mat image, List<Mat> corners)`	Draw detected markers in image
`static void`	Aruco.`drawDetectedMarkers(Mat image, List<Mat> corners, Mat ids)`	Draw detected markers in image
`static void`	Aruco.`drawDetectedMarkers(Mat image, List<Mat> corners, Mat ids, Scalar borderColor)`	Draw detected markers in image
`static int`	Aruco.`estimatePoseBoard(List<Mat> corners, Mat ids, Board board, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec)`	Pose estimation for a board of markers
`static int`	Aruco.`estimatePoseBoard(List<Mat> corners, Mat ids, Board board, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, boolean useExtrinsicGuess)`	Pose estimation for a board of markers
`static void`	Aruco.`estimatePoseSingleMarkers(List<Mat> corners, float markerLength, Mat cameraMatrix, Mat distCoeffs, Mat rvecs, Mat tvecs)`	Pose estimation for single markers
`static void`	Aruco.`estimatePoseSingleMarkers(List<Mat> corners, float markerLength, Mat cameraMatrix, Mat distCoeffs, Mat rvecs, Mat tvecs, Mat _objPoints)`	Pose estimation for single markers
`static void`	Aruco.`getBoardObjectAndImagePoints(Board board, List<Mat> detectedCorners, Mat detectedIds, Mat objPoints, Mat imgPoints)`	Given a board configuration and a set of detected markers, returns the corresponding image points and object points to call solvePnP
`static int`	Aruco.`interpolateCornersCharuco(List<Mat> markerCorners, Mat markerIds, Mat image, CharucoBoard board, Mat charucoCorners, Mat charucoIds)`	Interpolate position of ChArUco board corners
`static int`	Aruco.`interpolateCornersCharuco(List<Mat> markerCorners, Mat markerIds, Mat image, CharucoBoard board, Mat charucoCorners, Mat charucoIds, Mat cameraMatrix)`	Interpolate position of ChArUco board corners
`static int`	Aruco.`interpolateCornersCharuco(List<Mat> markerCorners, Mat markerIds, Mat image, CharucoBoard board, Mat charucoCorners, Mat charucoIds, Mat cameraMatrix, Mat distCoeffs)`	Interpolate position of ChArUco board corners
`static int`	Aruco.`interpolateCornersCharuco(List<Mat> markerCorners, Mat markerIds, Mat image, CharucoBoard board, Mat charucoCorners, Mat charucoIds, Mat cameraMatrix, Mat distCoeffs, int minMarkers)`	Interpolate position of ChArUco board corners
`static void`	Aruco.`refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners)`	Refind not detected markers based on the already detected and the board layout
`static void`	Aruco.`refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix)`	Refind not detected markers based on the already detected and the board layout
`static void`	Aruco.`refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs)`	Refind not detected markers based on the already detected and the board layout
`static void`	Aruco.`refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, float minRepDistance)`	Refind not detected markers based on the already detected and the board layout
`static void`	Aruco.`refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, float minRepDistance, float errorCorrectionRate)`	Refind not detected markers based on the already detected and the board layout
`static void`	Aruco.`refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, float minRepDistance, float errorCorrectionRate, boolean checkAllOrders)`	Refind not detected markers based on the already detected and the board layout
`static void`	Aruco.`refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, float minRepDistance, float errorCorrectionRate, boolean checkAllOrders, Mat recoveredIdxs)`	Refind not detected markers based on the already detected and the board layout
`static void`	Aruco.`refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, float minRepDistance, float errorCorrectionRate, boolean checkAllOrders, Mat recoveredIdxs, DetectorParameters parameters)`	Refind not detected markers based on the already detected and the board layout

Uses of Mat in org.opencv.barcode

Methods in org.opencv.barcode with parameters of type Mat
Modifier and Type	Method	Description
`boolean`	BarcodeDetector.`decode(Mat img, Mat points, List<String> decoded_info, List<Integer> decoded_type)`	Decodes barcode in image once it's found by the detect() method.
`boolean`	BarcodeDetector.`detect(Mat img, Mat points)`	Detects Barcode in image and returns the rectangle(s) containing the code.
`boolean`	BarcodeDetector.`detectAndDecode(Mat img, List<String> decoded_info, List<Integer> decoded_type)`	Both detects and decodes barcode
`boolean`	BarcodeDetector.`detectAndDecode(Mat img, List<String> decoded_info, List<Integer> decoded_type, Mat points)`	Both detects and decodes barcode

Uses of Mat in org.opencv.bgsegm

Methods in org.opencv.bgsegm with parameters of type Mat
Modifier and Type	Method	Description
`void`	BackgroundSubtractorCNT.`apply(Mat image, Mat fgmask)`
`void`	BackgroundSubtractorCNT.`apply(Mat image, Mat fgmask, double learningRate)`
`void`	BackgroundSubtractorGSOC.`apply(Mat image, Mat fgmask)`
`void`	BackgroundSubtractorGSOC.`apply(Mat image, Mat fgmask, double learningRate)`
`void`	BackgroundSubtractorLSBP.`apply(Mat image, Mat fgmask)`
`void`	BackgroundSubtractorLSBP.`apply(Mat image, Mat fgmask, double learningRate)`
`static SyntheticSequenceGenerator`	Bgsegm.`createSyntheticSequenceGenerator(Mat background, Mat object)`	Creates an instance of SyntheticSequenceGenerator.
`static SyntheticSequenceGenerator`	Bgsegm.`createSyntheticSequenceGenerator(Mat background, Mat object, double amplitude)`	Creates an instance of SyntheticSequenceGenerator.
`static SyntheticSequenceGenerator`	Bgsegm.`createSyntheticSequenceGenerator(Mat background, Mat object, double amplitude, double wavelength)`	Creates an instance of SyntheticSequenceGenerator.
`static SyntheticSequenceGenerator`	Bgsegm.`createSyntheticSequenceGenerator(Mat background, Mat object, double amplitude, double wavelength, double wavespeed)`	Creates an instance of SyntheticSequenceGenerator.
`static SyntheticSequenceGenerator`	Bgsegm.`createSyntheticSequenceGenerator(Mat background, Mat object, double amplitude, double wavelength, double wavespeed, double objspeed)`	Creates an instance of SyntheticSequenceGenerator.
`void`	BackgroundSubtractorCNT.`getBackgroundImage(Mat backgroundImage)`
`void`	BackgroundSubtractorGSOC.`getBackgroundImage(Mat backgroundImage)`
`void`	BackgroundSubtractorLSBP.`getBackgroundImage(Mat backgroundImage)`
`void`	SyntheticSequenceGenerator.`getNextFrame(Mat frame, Mat gtMask)`	Obtain the next frame in the sequence.

Constructors in org.opencv.bgsegm with parameters of type Mat
Constructor	Description
`SyntheticSequenceGenerator(Mat background, Mat object, double amplitude, double wavelength, double wavespeed, double objspeed)`	Creates an instance of SyntheticSequenceGenerator.

Uses of Mat in org.opencv.bioinspired

Methods in org.opencv.bioinspired that return Mat
Modifier and Type	Method	Description
`Mat`	Retina.`getMagnoRAW()`
`Mat`	Retina.`getParvoRAW()`

Methods in org.opencv.bioinspired with parameters of type Mat
Modifier and Type	Method	Description
`void`	Retina.`applyFastToneMapping(Mat inputImage, Mat outputToneMappedImage)`	Method which processes an image in the aim to correct its luminance correct backlight problems, enhance details in shadows.
`void`	RetinaFastToneMapping.`applyFastToneMapping(Mat inputImage, Mat outputToneMappedImage)`	applies a luminance correction (initially High Dynamic Range (HDR) tone mapping) using only the 2 local adaptation stages of the retina parvocellular channel : photoreceptors level and ganlion cells level.
`void`	Retina.`getMagno(Mat retinaOutput_magno)`	Accessor of the motion channel of the retina (models peripheral vision).
`void`	Retina.`getMagnoRAW(Mat retinaOutput_magno)`	Accessor of the motion channel of the retina (models peripheral vision).
`void`	Retina.`getParvo(Mat retinaOutput_parvo)`	Accessor of the details channel of the retina (models foveal vision).
`void`	Retina.`getParvoRAW(Mat retinaOutput_parvo)`	Accessor of the details channel of the retina (models foveal vision).
`void`	TransientAreasSegmentationModule.`getSegmentationPicture(Mat transientAreas)`	access function return the last segmentation result: a boolean picture which is resampled between 0 and 255 for a display purpose
`void`	Retina.`run(Mat inputImage)`	Method which allows retina to be applied on an input image, after run, encapsulated retina module is ready to deliver its outputs using dedicated acccessors, see getParvo and getMagno methods
`void`	TransientAreasSegmentationModule.`run(Mat inputToSegment)`	main processing method, get result using methods getSegmentationPicture()
`void`	TransientAreasSegmentationModule.`run(Mat inputToSegment, int channelIndex)`	main processing method, get result using methods getSegmentationPicture()

Uses of Mat in org.opencv.calib3d

Methods in org.opencv.calib3d that return Mat
Modifier and Type	Method	Description
`static Mat`	Calib3d.`estimateAffine2D(Mat from, Mat to)`	Computes an optimal affine transformation between two 2D point sets.
`static Mat`	Calib3d.`estimateAffine2D(Mat from, Mat to, Mat inliers)`	Computes an optimal affine transformation between two 2D point sets.
`static Mat`	Calib3d.`estimateAffine2D(Mat from, Mat to, Mat inliers, int method)`	Computes an optimal affine transformation between two 2D point sets.
`static Mat`	Calib3d.`estimateAffine2D(Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold)`	Computes an optimal affine transformation between two 2D point sets.
`static Mat`	Calib3d.`estimateAffine2D(Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters)`	Computes an optimal affine transformation between two 2D point sets.
`static Mat`	Calib3d.`estimateAffine2D(Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters, double confidence)`	Computes an optimal affine transformation between two 2D point sets.
`static Mat`	Calib3d.`estimateAffine2D(Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters, double confidence, long refineIters)`	Computes an optimal affine transformation between two 2D point sets.
`static Mat`	Calib3d.`estimateAffine2D(Mat pts1, Mat pts2, Mat inliers, UsacParams params)`
`static Mat`	Calib3d.`estimateAffine3D(Mat src, Mat dst)`	Computes an optimal affine transformation between two 3D point sets.
`static Mat`	Calib3d.`estimateAffine3D(Mat src, Mat dst, double[] scale)`	Computes an optimal affine transformation between two 3D point sets.
`static Mat`	Calib3d.`estimateAffine3D(Mat src, Mat dst, double[] scale, boolean force_rotation)`	Computes an optimal affine transformation between two 3D point sets.
`static Mat`	Calib3d.`estimateAffinePartial2D(Mat from, Mat to)`	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.
`static Mat`	Calib3d.`estimateAffinePartial2D(Mat from, Mat to, Mat inliers)`	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.
`static Mat`	Calib3d.`estimateAffinePartial2D(Mat from, Mat to, Mat inliers, int method)`	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.
`static Mat`	Calib3d.`estimateAffinePartial2D(Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold)`	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.
`static Mat`	Calib3d.`estimateAffinePartial2D(Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters)`	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.
`static Mat`	Calib3d.`estimateAffinePartial2D(Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters, double confidence)`	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.
`static Mat`	Calib3d.`estimateAffinePartial2D(Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters, double confidence, long refineIters)`	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, double focal)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, double focal, Point pp)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, double focal, Point pp, int method)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, double focal, Point pp, int method, double prob)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, double focal, Point pp, int method, double prob, double threshold)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, double focal, Point pp, int method, double prob, double threshold, int maxIters)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, double focal, Point pp, int method, double prob, double threshold, int maxIters, Mat mask)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix)`	Calculates an essential matrix from the corresponding points in two images.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix, int method)`	Calculates an essential matrix from the corresponding points in two images.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix, int method, double prob)`	Calculates an essential matrix from the corresponding points in two images.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix, int method, double prob, double threshold)`	Calculates an essential matrix from the corresponding points in two images.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix, int method, double prob, double threshold, int maxIters)`	Calculates an essential matrix from the corresponding points in two images.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix, int method, double prob, double threshold, int maxIters, Mat mask)`	Calculates an essential matrix from the corresponding points in two images.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2)`	Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, int method)`	Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, int method, double prob)`	Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, int method, double prob, double threshold)`	Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, int method, double prob, double threshold, Mat mask)`	Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix1, Mat cameraMatrix2, Mat dist_coeff1, Mat dist_coeff2, Mat mask, UsacParams params)`
`static Mat`	Calib3d.`findFundamentalMat(MatOfPoint2f points1, MatOfPoint2f points2)`
`static Mat`	Calib3d.`findFundamentalMat(MatOfPoint2f points1, MatOfPoint2f points2, int method)`
`static Mat`	Calib3d.`findFundamentalMat(MatOfPoint2f points1, MatOfPoint2f points2, int method, double ransacReprojThreshold)`
`static Mat`	Calib3d.`findFundamentalMat(MatOfPoint2f points1, MatOfPoint2f points2, int method, double ransacReprojThreshold, double confidence)`
`static Mat`	Calib3d.`findFundamentalMat(MatOfPoint2f points1, MatOfPoint2f points2, int method, double ransacReprojThreshold, double confidence, int maxIters)`	Calculates a fundamental matrix from the corresponding points in two images.
`static Mat`	Calib3d.`findFundamentalMat(MatOfPoint2f points1, MatOfPoint2f points2, int method, double ransacReprojThreshold, double confidence, int maxIters, Mat mask)`	Calculates a fundamental matrix from the corresponding points in two images.
`static Mat`	Calib3d.`findFundamentalMat(MatOfPoint2f points1, MatOfPoint2f points2, int method, double ransacReprojThreshold, double confidence, Mat mask)`
`static Mat`	Calib3d.`findFundamentalMat(MatOfPoint2f points1, MatOfPoint2f points2, Mat mask, UsacParams params)`
`static Mat`	Calib3d.`findHomography(MatOfPoint2f srcPoints, MatOfPoint2f dstPoints)`	Finds a perspective transformation between two planes.
`static Mat`	Calib3d.`findHomography(MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, int method)`	Finds a perspective transformation between two planes.
`static Mat`	Calib3d.`findHomography(MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, int method, double ransacReprojThreshold)`	Finds a perspective transformation between two planes.
`static Mat`	Calib3d.`findHomography(MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, int method, double ransacReprojThreshold, Mat mask)`	Finds a perspective transformation between two planes.
`static Mat`	Calib3d.`findHomography(MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, int method, double ransacReprojThreshold, Mat mask, int maxIters)`	Finds a perspective transformation between two planes.
`static Mat`	Calib3d.`findHomography(MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, int method, double ransacReprojThreshold, Mat mask, int maxIters, double confidence)`	Finds a perspective transformation between two planes.
`static Mat`	Calib3d.`findHomography(MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, Mat mask, UsacParams params)`
`static Mat`	Calib3d.`getDefaultNewCameraMatrix(Mat cameraMatrix)`	Returns the default new camera matrix.
`static Mat`	Calib3d.`getDefaultNewCameraMatrix(Mat cameraMatrix, Size imgsize)`	Returns the default new camera matrix.
`static Mat`	Calib3d.`getDefaultNewCameraMatrix(Mat cameraMatrix, Size imgsize, boolean centerPrincipalPoint)`	Returns the default new camera matrix.
`static Mat`	Calib3d.`getOptimalNewCameraMatrix(Mat cameraMatrix, Mat distCoeffs, Size imageSize, double alpha)`	Returns the new camera intrinsic matrix based on the free scaling parameter.
`static Mat`	Calib3d.`getOptimalNewCameraMatrix(Mat cameraMatrix, Mat distCoeffs, Size imageSize, double alpha, Size newImgSize)`	Returns the new camera intrinsic matrix based on the free scaling parameter.
`static Mat`	Calib3d.`getOptimalNewCameraMatrix(Mat cameraMatrix, Mat distCoeffs, Size imageSize, double alpha, Size newImgSize, Rect validPixROI)`	Returns the new camera intrinsic matrix based on the free scaling parameter.
`static Mat`	Calib3d.`getOptimalNewCameraMatrix(Mat cameraMatrix, Mat distCoeffs, Size imageSize, double alpha, Size newImgSize, Rect validPixROI, boolean centerPrincipalPoint)`	Returns the new camera intrinsic matrix based on the free scaling parameter.
`static Mat`	Calib3d.`initCameraMatrix2D(List<MatOfPoint3f> objectPoints, List<MatOfPoint2f> imagePoints, Size imageSize)`	Finds an initial camera intrinsic matrix from 3D-2D point correspondences.
`static Mat`	Calib3d.`initCameraMatrix2D(List<MatOfPoint3f> objectPoints, List<MatOfPoint2f> imagePoints, Size imageSize, double aspectRatio)`	Finds an initial camera intrinsic matrix from 3D-2D point correspondences.

Methods in org.opencv.calib3d with parameters of type Mat
Modifier and Type	Method	Description
`static double`	Calib3d.`calibrateCamera(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs)`
`static double`	Calib3d.`calibrateCamera(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags)`
`static double`	Calib3d.`calibrateCamera(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags, TermCriteria criteria)`
`static double`	Calib3d.`calibrateCameraExtended(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors)`	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.
`static double`	Calib3d.`calibrateCameraExtended(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags)`	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.
`static double`	Calib3d.`calibrateCameraExtended(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags, TermCriteria criteria)`	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.
`static double`	Calib3d.`calibrateCameraRO(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat newObjPoints)`
`static double`	Calib3d.`calibrateCameraRO(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat newObjPoints, int flags)`
`static double`	Calib3d.`calibrateCameraRO(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat newObjPoints, int flags, TermCriteria criteria)`
`static double`	Calib3d.`calibrateCameraROExtended(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat newObjPoints, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat stdDeviationsObjPoints, Mat perViewErrors)`	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.
`static double`	Calib3d.`calibrateCameraROExtended(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat newObjPoints, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat stdDeviationsObjPoints, Mat perViewErrors, int flags)`	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.
`static double`	Calib3d.`calibrateCameraROExtended(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat newObjPoints, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat stdDeviationsObjPoints, Mat perViewErrors, int flags, TermCriteria criteria)`	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.
`static void`	Calib3d.`calibrateHandEye(List<Mat> R_gripper2base, List<Mat> t_gripper2base, List<Mat> R_target2cam, List<Mat> t_target2cam, Mat R_cam2gripper, Mat t_cam2gripper)`	Computes Hand-Eye calibration: \(_{}^{g}\textrm{T}_c\)
`static void`	Calib3d.`calibrateHandEye(List<Mat> R_gripper2base, List<Mat> t_gripper2base, List<Mat> R_target2cam, List<Mat> t_target2cam, Mat R_cam2gripper, Mat t_cam2gripper, int method)`	Computes Hand-Eye calibration: \(_{}^{g}\textrm{T}_c\)
`static void`	Calib3d.`calibrateRobotWorldHandEye(List<Mat> R_world2cam, List<Mat> t_world2cam, List<Mat> R_base2gripper, List<Mat> t_base2gripper, Mat R_base2world, Mat t_base2world, Mat R_gripper2cam, Mat t_gripper2cam)`	Computes Robot-World/Hand-Eye calibration: \(_{}^{w}\textrm{T}_b\) and \(_{}^{c}\textrm{T}_g\)
`static void`	Calib3d.`calibrateRobotWorldHandEye(List<Mat> R_world2cam, List<Mat> t_world2cam, List<Mat> R_base2gripper, List<Mat> t_base2gripper, Mat R_base2world, Mat t_base2world, Mat R_gripper2cam, Mat t_gripper2cam, int method)`	Computes Robot-World/Hand-Eye calibration: \(_{}^{w}\textrm{T}_b\) and \(_{}^{c}\textrm{T}_g\)
`static void`	Calib3d.`calibrationMatrixValues(Mat cameraMatrix, Size imageSize, double apertureWidth, double apertureHeight, double[] fovx, double[] fovy, double[] focalLength, Point principalPoint, double[] aspectRatio)`	Computes useful camera characteristics from the camera intrinsic matrix.
`static boolean`	Calib3d.`checkChessboard(Mat img, Size size)`
`static void`	Calib3d.`composeRT(Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3)`	Combines two rotation-and-shift transformations.
`static void`	Calib3d.`composeRT(Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3, Mat dr3dr1)`	Combines two rotation-and-shift transformations.
`static void`	Calib3d.`composeRT(Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3, Mat dr3dr1, Mat dr3dt1)`	Combines two rotation-and-shift transformations.
`static void`	Calib3d.`composeRT(Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3, Mat dr3dr1, Mat dr3dt1, Mat dr3dr2)`	Combines two rotation-and-shift transformations.
`static void`	Calib3d.`composeRT(Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3, Mat dr3dr1, Mat dr3dt1, Mat dr3dr2, Mat dr3dt2)`	Combines two rotation-and-shift transformations.
`static void`	Calib3d.`composeRT(Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3, Mat dr3dr1, Mat dr3dt1, Mat dr3dr2, Mat dr3dt2, Mat dt3dr1)`	Combines two rotation-and-shift transformations.
`static void`	Calib3d.`composeRT(Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3, Mat dr3dr1, Mat dr3dt1, Mat dr3dr2, Mat dr3dt2, Mat dt3dr1, Mat dt3dt1)`	Combines two rotation-and-shift transformations.
`static void`	Calib3d.`composeRT(Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3, Mat dr3dr1, Mat dr3dt1, Mat dr3dr2, Mat dr3dt2, Mat dt3dr1, Mat dt3dt1, Mat dt3dr2)`	Combines two rotation-and-shift transformations.
`static void`	Calib3d.`composeRT(Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3, Mat dr3dr1, Mat dr3dt1, Mat dr3dr2, Mat dr3dt2, Mat dt3dr1, Mat dt3dt1, Mat dt3dr2, Mat dt3dt2)`	Combines two rotation-and-shift transformations.
`void`	StereoMatcher.`compute(Mat left, Mat right, Mat disparity)`	Computes disparity map for the specified stereo pair
`static void`	Calib3d.`computeCorrespondEpilines(Mat points, int whichImage, Mat F, Mat lines)`	For points in an image of a stereo pair, computes the corresponding epilines in the other image.
`static void`	Calib3d.`convertPointsFromHomogeneous(Mat src, Mat dst)`	Converts points from homogeneous to Euclidean space.
`static void`	Calib3d.`convertPointsToHomogeneous(Mat src, Mat dst)`	Converts points from Euclidean to homogeneous space.
`static void`	Calib3d.`correctMatches(Mat F, Mat points1, Mat points2, Mat newPoints1, Mat newPoints2)`	Refines coordinates of corresponding points.
`static void`	Calib3d.`decomposeEssentialMat(Mat E, Mat R1, Mat R2, Mat t)`	Decompose an essential matrix to possible rotations and translation.
`static int`	Calib3d.`decomposeHomographyMat(Mat H, Mat K, List<Mat> rotations, List<Mat> translations, List<Mat> normals)`	Decompose a homography matrix to rotation(s), translation(s) and plane normal(s).
`static void`	Calib3d.`decomposeProjectionMatrix(Mat projMatrix, Mat cameraMatrix, Mat rotMatrix, Mat transVect)`	Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.
`static void`	Calib3d.`decomposeProjectionMatrix(Mat projMatrix, Mat cameraMatrix, Mat rotMatrix, Mat transVect, Mat rotMatrixX)`	Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.
`static void`	Calib3d.`decomposeProjectionMatrix(Mat projMatrix, Mat cameraMatrix, Mat rotMatrix, Mat transVect, Mat rotMatrixX, Mat rotMatrixY)`	Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.
`static void`	Calib3d.`decomposeProjectionMatrix(Mat projMatrix, Mat cameraMatrix, Mat rotMatrix, Mat transVect, Mat rotMatrixX, Mat rotMatrixY, Mat rotMatrixZ)`	Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.
`static void`	Calib3d.`decomposeProjectionMatrix(Mat projMatrix, Mat cameraMatrix, Mat rotMatrix, Mat transVect, Mat rotMatrixX, Mat rotMatrixY, Mat rotMatrixZ, Mat eulerAngles)`	Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.
`static void`	Calib3d.`drawChessboardCorners(Mat image, Size patternSize, MatOfPoint2f corners, boolean patternWasFound)`	Renders the detected chessboard corners.
`static void`	Calib3d.`drawFrameAxes(Mat image, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, float length)`	Draw axes of the world/object coordinate system from pose estimation.
`static void`	Calib3d.`drawFrameAxes(Mat image, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, float length, int thickness)`	Draw axes of the world/object coordinate system from pose estimation.
`static Mat`	Calib3d.`estimateAffine2D(Mat from, Mat to)`	Computes an optimal affine transformation between two 2D point sets.
`static Mat`	Calib3d.`estimateAffine2D(Mat from, Mat to, Mat inliers)`	Computes an optimal affine transformation between two 2D point sets.
`static Mat`	Calib3d.`estimateAffine2D(Mat from, Mat to, Mat inliers, int method)`	Computes an optimal affine transformation between two 2D point sets.
`static Mat`	Calib3d.`estimateAffine2D(Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold)`	Computes an optimal affine transformation between two 2D point sets.
`static Mat`	Calib3d.`estimateAffine2D(Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters)`	Computes an optimal affine transformation between two 2D point sets.
`static Mat`	Calib3d.`estimateAffine2D(Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters, double confidence)`	Computes an optimal affine transformation between two 2D point sets.
`static Mat`	Calib3d.`estimateAffine2D(Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters, double confidence, long refineIters)`	Computes an optimal affine transformation between two 2D point sets.
`static Mat`	Calib3d.`estimateAffine2D(Mat pts1, Mat pts2, Mat inliers, UsacParams params)`
`static Mat`	Calib3d.`estimateAffine3D(Mat src, Mat dst)`	Computes an optimal affine transformation between two 3D point sets.
`static Mat`	Calib3d.`estimateAffine3D(Mat src, Mat dst, double[] scale)`	Computes an optimal affine transformation between two 3D point sets.
`static Mat`	Calib3d.`estimateAffine3D(Mat src, Mat dst, double[] scale, boolean force_rotation)`	Computes an optimal affine transformation between two 3D point sets.
`static int`	Calib3d.`estimateAffine3D(Mat src, Mat dst, Mat out, Mat inliers)`	Computes an optimal affine transformation between two 3D point sets.
`static int`	Calib3d.`estimateAffine3D(Mat src, Mat dst, Mat out, Mat inliers, double ransacThreshold)`	Computes an optimal affine transformation between two 3D point sets.
`static int`	Calib3d.`estimateAffine3D(Mat src, Mat dst, Mat out, Mat inliers, double ransacThreshold, double confidence)`	Computes an optimal affine transformation between two 3D point sets.
`static Mat`	Calib3d.`estimateAffinePartial2D(Mat from, Mat to)`	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.
`static Mat`	Calib3d.`estimateAffinePartial2D(Mat from, Mat to, Mat inliers)`	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.
`static Mat`	Calib3d.`estimateAffinePartial2D(Mat from, Mat to, Mat inliers, int method)`	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.
`static Mat`	Calib3d.`estimateAffinePartial2D(Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold)`	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.
`static Mat`	Calib3d.`estimateAffinePartial2D(Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters)`	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.
`static Mat`	Calib3d.`estimateAffinePartial2D(Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters, double confidence)`	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.
`static Mat`	Calib3d.`estimateAffinePartial2D(Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters, double confidence, long refineIters)`	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.
`static Scalar`	Calib3d.`estimateChessboardSharpness(Mat image, Size patternSize, Mat corners)`	Estimates the sharpness of a detected chessboard.
`static Scalar`	Calib3d.`estimateChessboardSharpness(Mat image, Size patternSize, Mat corners, float rise_distance)`	Estimates the sharpness of a detected chessboard.
`static Scalar`	Calib3d.`estimateChessboardSharpness(Mat image, Size patternSize, Mat corners, float rise_distance, boolean vertical)`	Estimates the sharpness of a detected chessboard.
`static Scalar`	Calib3d.`estimateChessboardSharpness(Mat image, Size patternSize, Mat corners, float rise_distance, boolean vertical, Mat sharpness)`	Estimates the sharpness of a detected chessboard.
`static int`	Calib3d.`estimateTranslation3D(Mat src, Mat dst, Mat out, Mat inliers)`	Computes an optimal translation between two 3D point sets.
`static int`	Calib3d.`estimateTranslation3D(Mat src, Mat dst, Mat out, Mat inliers, double ransacThreshold)`	Computes an optimal translation between two 3D point sets.
`static int`	Calib3d.`estimateTranslation3D(Mat src, Mat dst, Mat out, Mat inliers, double ransacThreshold, double confidence)`	Computes an optimal translation between two 3D point sets.
`static void`	Calib3d.`filterHomographyDecompByVisibleRefpoints(List<Mat> rotations, List<Mat> normals, Mat beforePoints, Mat afterPoints, Mat possibleSolutions)`	Filters homography decompositions based on additional information.
`static void`	Calib3d.`filterHomographyDecompByVisibleRefpoints(List<Mat> rotations, List<Mat> normals, Mat beforePoints, Mat afterPoints, Mat possibleSolutions, Mat pointsMask)`	Filters homography decompositions based on additional information.
`static void`	Calib3d.`filterSpeckles(Mat img, double newVal, int maxSpeckleSize, double maxDiff)`	Filters off small noise blobs (speckles) in the disparity map
`static void`	Calib3d.`filterSpeckles(Mat img, double newVal, int maxSpeckleSize, double maxDiff, Mat buf)`	Filters off small noise blobs (speckles) in the disparity map
`static boolean`	Calib3d.`find4QuadCornerSubpix(Mat img, Mat corners, Size region_size)`
`static boolean`	Calib3d.`findChessboardCorners(Mat image, Size patternSize, MatOfPoint2f corners)`	Finds the positions of internal corners of the chessboard.
`static boolean`	Calib3d.`findChessboardCorners(Mat image, Size patternSize, MatOfPoint2f corners, int flags)`	Finds the positions of internal corners of the chessboard.
`static boolean`	Calib3d.`findChessboardCornersSB(Mat image, Size patternSize, Mat corners)`
`static boolean`	Calib3d.`findChessboardCornersSB(Mat image, Size patternSize, Mat corners, int flags)`
`static boolean`	Calib3d.`findChessboardCornersSBWithMeta(Mat image, Size patternSize, Mat corners, int flags, Mat meta)`	Finds the positions of internal corners of the chessboard using a sector based approach.
`static boolean`	Calib3d.`findCirclesGrid(Mat image, Size patternSize, Mat centers)`
`static boolean`	Calib3d.`findCirclesGrid(Mat image, Size patternSize, Mat centers, int flags)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, double focal)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, double focal, Point pp)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, double focal, Point pp, int method)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, double focal, Point pp, int method, double prob)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, double focal, Point pp, int method, double prob, double threshold)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, double focal, Point pp, int method, double prob, double threshold, int maxIters)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, double focal, Point pp, int method, double prob, double threshold, int maxIters, Mat mask)`
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix)`	Calculates an essential matrix from the corresponding points in two images.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix, int method)`	Calculates an essential matrix from the corresponding points in two images.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix, int method, double prob)`	Calculates an essential matrix from the corresponding points in two images.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix, int method, double prob, double threshold)`	Calculates an essential matrix from the corresponding points in two images.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix, int method, double prob, double threshold, int maxIters)`	Calculates an essential matrix from the corresponding points in two images.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix, int method, double prob, double threshold, int maxIters, Mat mask)`	Calculates an essential matrix from the corresponding points in two images.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2)`	Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, int method)`	Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, int method, double prob)`	Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, int method, double prob, double threshold)`	Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, int method, double prob, double threshold, Mat mask)`	Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.
`static Mat`	Calib3d.`findEssentialMat(Mat points1, Mat points2, Mat cameraMatrix1, Mat cameraMatrix2, Mat dist_coeff1, Mat dist_coeff2, Mat mask, UsacParams params)`
`static Mat`	Calib3d.`findFundamentalMat(MatOfPoint2f points1, MatOfPoint2f points2, int method, double ransacReprojThreshold, double confidence, int maxIters, Mat mask)`	Calculates a fundamental matrix from the corresponding points in two images.
`static Mat`	Calib3d.`findFundamentalMat(MatOfPoint2f points1, MatOfPoint2f points2, int method, double ransacReprojThreshold, double confidence, Mat mask)`
`static Mat`	Calib3d.`findFundamentalMat(MatOfPoint2f points1, MatOfPoint2f points2, Mat mask, UsacParams params)`
`static Mat`	Calib3d.`findHomography(MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, int method, double ransacReprojThreshold, Mat mask)`	Finds a perspective transformation between two planes.
`static Mat`	Calib3d.`findHomography(MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, int method, double ransacReprojThreshold, Mat mask, int maxIters)`	Finds a perspective transformation between two planes.
`static Mat`	Calib3d.`findHomography(MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, int method, double ransacReprojThreshold, Mat mask, int maxIters, double confidence)`	Finds a perspective transformation between two planes.
`static Mat`	Calib3d.`findHomography(MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, Mat mask, UsacParams params)`
`static double`	Calib3d.`fisheye_calibrate(List<Mat> objectPoints, List<Mat> imagePoints, Size image_size, Mat K, Mat D, List<Mat> rvecs, List<Mat> tvecs)`	Performs camera calibaration
`static double`	Calib3d.`fisheye_calibrate(List<Mat> objectPoints, List<Mat> imagePoints, Size image_size, Mat K, Mat D, List<Mat> rvecs, List<Mat> tvecs, int flags)`	Performs camera calibaration
`static double`	Calib3d.`fisheye_calibrate(List<Mat> objectPoints, List<Mat> imagePoints, Size image_size, Mat K, Mat D, List<Mat> rvecs, List<Mat> tvecs, int flags, TermCriteria criteria)`	Performs camera calibaration
`static void`	Calib3d.`fisheye_distortPoints(Mat undistorted, Mat distorted, Mat K, Mat D)`	Distorts 2D points using fisheye model.
`static void`	Calib3d.`fisheye_distortPoints(Mat undistorted, Mat distorted, Mat K, Mat D, double alpha)`	Distorts 2D points using fisheye model.
`static void`	Calib3d.`fisheye_estimateNewCameraMatrixForUndistortRectify(Mat K, Mat D, Size image_size, Mat R, Mat P)`	Estimates new camera intrinsic matrix for undistortion or rectification.
`static void`	Calib3d.`fisheye_estimateNewCameraMatrixForUndistortRectify(Mat K, Mat D, Size image_size, Mat R, Mat P, double balance)`	Estimates new camera intrinsic matrix for undistortion or rectification.
`static void`	Calib3d.`fisheye_estimateNewCameraMatrixForUndistortRectify(Mat K, Mat D, Size image_size, Mat R, Mat P, double balance, Size new_size)`	Estimates new camera intrinsic matrix for undistortion or rectification.
`static void`	Calib3d.`fisheye_estimateNewCameraMatrixForUndistortRectify(Mat K, Mat D, Size image_size, Mat R, Mat P, double balance, Size new_size, double fov_scale)`	Estimates new camera intrinsic matrix for undistortion or rectification.
`static void`	Calib3d.`fisheye_initUndistortRectifyMap(Mat K, Mat D, Mat R, Mat P, Size size, int m1type, Mat map1, Mat map2)`	Computes undistortion and rectification maps for image transform by #remap.
`static void`	Calib3d.`fisheye_projectPoints(Mat objectPoints, Mat imagePoints, Mat rvec, Mat tvec, Mat K, Mat D)`
`static void`	Calib3d.`fisheye_projectPoints(Mat objectPoints, Mat imagePoints, Mat rvec, Mat tvec, Mat K, Mat D, double alpha)`
`static void`	Calib3d.`fisheye_projectPoints(Mat objectPoints, Mat imagePoints, Mat rvec, Mat tvec, Mat K, Mat D, double alpha, Mat jacobian)`
`static double`	Calib3d.`fisheye_stereoCalibrate(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat T)`	Performs stereo calibration
`static double`	Calib3d.`fisheye_stereoCalibrate(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat T, int flags)`	Performs stereo calibration
`static double`	Calib3d.`fisheye_stereoCalibrate(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat T, int flags, TermCriteria criteria)`	Performs stereo calibration
`static void`	Calib3d.`fisheye_stereoRectify(Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat tvec, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags)`	Stereo rectification for fisheye camera model
`static void`	Calib3d.`fisheye_stereoRectify(Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat tvec, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, Size newImageSize)`	Stereo rectification for fisheye camera model
`static void`	Calib3d.`fisheye_stereoRectify(Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat tvec, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, Size newImageSize, double balance)`	Stereo rectification for fisheye camera model
`static void`	Calib3d.`fisheye_stereoRectify(Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat tvec, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, Size newImageSize, double balance, double fov_scale)`	Stereo rectification for fisheye camera model
`static void`	Calib3d.`fisheye_undistortImage(Mat distorted, Mat undistorted, Mat K, Mat D)`	Transforms an image to compensate for fisheye lens distortion.
`static void`	Calib3d.`fisheye_undistortImage(Mat distorted, Mat undistorted, Mat K, Mat D, Mat Knew)`	Transforms an image to compensate for fisheye lens distortion.
`static void`	Calib3d.`fisheye_undistortImage(Mat distorted, Mat undistorted, Mat K, Mat D, Mat Knew, Size new_size)`	Transforms an image to compensate for fisheye lens distortion.
`static void`	Calib3d.`fisheye_undistortPoints(Mat distorted, Mat undistorted, Mat K, Mat D)`	Undistorts 2D points using fisheye model
`static void`	Calib3d.`fisheye_undistortPoints(Mat distorted, Mat undistorted, Mat K, Mat D, Mat R)`	Undistorts 2D points using fisheye model
`static void`	Calib3d.`fisheye_undistortPoints(Mat distorted, Mat undistorted, Mat K, Mat D, Mat R, Mat P)`	Undistorts 2D points using fisheye model
`static Mat`	Calib3d.`getDefaultNewCameraMatrix(Mat cameraMatrix)`	Returns the default new camera matrix.
`static Mat`	Calib3d.`getDefaultNewCameraMatrix(Mat cameraMatrix, Size imgsize)`	Returns the default new camera matrix.
`static Mat`	Calib3d.`getDefaultNewCameraMatrix(Mat cameraMatrix, Size imgsize, boolean centerPrincipalPoint)`	Returns the default new camera matrix.
`static Mat`	Calib3d.`getOptimalNewCameraMatrix(Mat cameraMatrix, Mat distCoeffs, Size imageSize, double alpha)`	Returns the new camera intrinsic matrix based on the free scaling parameter.
`static Mat`	Calib3d.`getOptimalNewCameraMatrix(Mat cameraMatrix, Mat distCoeffs, Size imageSize, double alpha, Size newImgSize)`	Returns the new camera intrinsic matrix based on the free scaling parameter.
`static Mat`	Calib3d.`getOptimalNewCameraMatrix(Mat cameraMatrix, Mat distCoeffs, Size imageSize, double alpha, Size newImgSize, Rect validPixROI)`	Returns the new camera intrinsic matrix based on the free scaling parameter.
`static Mat`	Calib3d.`getOptimalNewCameraMatrix(Mat cameraMatrix, Mat distCoeffs, Size imageSize, double alpha, Size newImgSize, Rect validPixROI, boolean centerPrincipalPoint)`	Returns the new camera intrinsic matrix based on the free scaling parameter.
`static void`	Calib3d.`initInverseRectificationMap(Mat cameraMatrix, Mat distCoeffs, Mat R, Mat newCameraMatrix, Size size, int m1type, Mat map1, Mat map2)`	Computes the projection and inverse-rectification transformation map.
`static void`	Calib3d.`initUndistortRectifyMap(Mat cameraMatrix, Mat distCoeffs, Mat R, Mat newCameraMatrix, Size size, int m1type, Mat map1, Mat map2)`	Computes the undistortion and rectification transformation map.
`static void`	Calib3d.`matMulDeriv(Mat A, Mat B, Mat dABdA, Mat dABdB)`	Computes partial derivatives of the matrix product for each multiplied matrix.
`static void`	Calib3d.`projectPoints(MatOfPoint3f objectPoints, Mat rvec, Mat tvec, Mat cameraMatrix, MatOfDouble distCoeffs, MatOfPoint2f imagePoints)`	Projects 3D points to an image plane.
`static void`	Calib3d.`projectPoints(MatOfPoint3f objectPoints, Mat rvec, Mat tvec, Mat cameraMatrix, MatOfDouble distCoeffs, MatOfPoint2f imagePoints, Mat jacobian)`	Projects 3D points to an image plane.
`static void`	Calib3d.`projectPoints(MatOfPoint3f objectPoints, Mat rvec, Mat tvec, Mat cameraMatrix, MatOfDouble distCoeffs, MatOfPoint2f imagePoints, Mat jacobian, double aspectRatio)`	Projects 3D points to an image plane.
`static int`	Calib3d.`recoverPose(Mat E, Mat points1, Mat points2, Mat R, Mat t)`
`static int`	Calib3d.`recoverPose(Mat E, Mat points1, Mat points2, Mat R, Mat t, double focal)`
`static int`	Calib3d.`recoverPose(Mat E, Mat points1, Mat points2, Mat R, Mat t, double focal, Point pp)`
`static int`	Calib3d.`recoverPose(Mat E, Mat points1, Mat points2, Mat R, Mat t, double focal, Point pp, Mat mask)`
`static int`	Calib3d.`recoverPose(Mat E, Mat points1, Mat points2, Mat cameraMatrix, Mat R, Mat t)`	Recovers the relative camera rotation and the translation from an estimated essential matrix and the corresponding points in two images, using cheirality check.
`static int`	Calib3d.`recoverPose(Mat E, Mat points1, Mat points2, Mat cameraMatrix, Mat R, Mat t, double distanceThresh)`
`static int`	Calib3d.`recoverPose(Mat E, Mat points1, Mat points2, Mat cameraMatrix, Mat R, Mat t, double distanceThresh, Mat mask)`
`static int`	Calib3d.`recoverPose(Mat E, Mat points1, Mat points2, Mat cameraMatrix, Mat R, Mat t, double distanceThresh, Mat mask, Mat triangulatedPoints)`
`static int`	Calib3d.`recoverPose(Mat E, Mat points1, Mat points2, Mat cameraMatrix, Mat R, Mat t, Mat mask)`	Recovers the relative camera rotation and the translation from an estimated essential matrix and the corresponding points in two images, using cheirality check.
`static float`	Calib3d.`rectify3Collinear(Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Mat cameraMatrix3, Mat distCoeffs3, List<Mat> imgpt1, List<Mat> imgpt3, Size imageSize, Mat R12, Mat T12, Mat R13, Mat T13, Mat R1, Mat R2, Mat R3, Mat P1, Mat P2, Mat P3, Mat Q, double alpha, Size newImgSize, Rect roi1, Rect roi2, int flags)`
`static void`	Calib3d.`reprojectImageTo3D(Mat disparity, Mat _3dImage, Mat Q)`	Reprojects a disparity image to 3D space.
`static void`	Calib3d.`reprojectImageTo3D(Mat disparity, Mat _3dImage, Mat Q, boolean handleMissingValues)`	Reprojects a disparity image to 3D space.
`static void`	Calib3d.`reprojectImageTo3D(Mat disparity, Mat _3dImage, Mat Q, boolean handleMissingValues, int ddepth)`	Reprojects a disparity image to 3D space.
`static void`	Calib3d.`Rodrigues(Mat src, Mat dst)`	Converts a rotation matrix to a rotation vector or vice versa.
`static void`	Calib3d.`Rodrigues(Mat src, Mat dst, Mat jacobian)`	Converts a rotation matrix to a rotation vector or vice versa.
`static double[]`	Calib3d.`RQDecomp3x3(Mat src, Mat mtxR, Mat mtxQ)`	Computes an RQ decomposition of 3x3 matrices.
`static double[]`	Calib3d.`RQDecomp3x3(Mat src, Mat mtxR, Mat mtxQ, Mat Qx)`	Computes an RQ decomposition of 3x3 matrices.
`static double[]`	Calib3d.`RQDecomp3x3(Mat src, Mat mtxR, Mat mtxQ, Mat Qx, Mat Qy)`	Computes an RQ decomposition of 3x3 matrices.
`static double[]`	Calib3d.`RQDecomp3x3(Mat src, Mat mtxR, Mat mtxQ, Mat Qx, Mat Qy, Mat Qz)`	Computes an RQ decomposition of 3x3 matrices.
`static double`	Calib3d.`sampsonDistance(Mat pt1, Mat pt2, Mat F)`	Calculates the Sampson Distance between two points.
`static int`	Calib3d.`solveP3P(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags)`	Finds an object pose from 3 3D-2D point correspondences.
`static boolean`	Calib3d.`solvePnP(MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec)`	Finds an object pose from 3D-2D point correspondences.
`static boolean`	Calib3d.`solvePnP(MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, boolean useExtrinsicGuess)`	Finds an object pose from 3D-2D point correspondences.
`static boolean`	Calib3d.`solvePnP(MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, boolean useExtrinsicGuess, int flags)`	Finds an object pose from 3D-2D point correspondences.
`static int`	Calib3d.`solvePnPGeneric(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs)`	Finds an object pose from 3D-2D point correspondences.
`static int`	Calib3d.`solvePnPGeneric(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, boolean useExtrinsicGuess)`	Finds an object pose from 3D-2D point correspondences.
`static int`	Calib3d.`solvePnPGeneric(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, boolean useExtrinsicGuess, int flags)`	Finds an object pose from 3D-2D point correspondences.
`static int`	Calib3d.`solvePnPGeneric(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, boolean useExtrinsicGuess, int flags, Mat rvec)`	Finds an object pose from 3D-2D point correspondences.
`static int`	Calib3d.`solvePnPGeneric(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, boolean useExtrinsicGuess, int flags, Mat rvec, Mat tvec)`	Finds an object pose from 3D-2D point correspondences.
`static int`	Calib3d.`solvePnPGeneric(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, boolean useExtrinsicGuess, int flags, Mat rvec, Mat tvec, Mat reprojectionError)`	Finds an object pose from 3D-2D point correspondences.
`static boolean`	Calib3d.`solvePnPRansac(MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec)`	Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.
`static boolean`	Calib3d.`solvePnPRansac(MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, boolean useExtrinsicGuess)`	Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.
`static boolean`	Calib3d.`solvePnPRansac(MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, boolean useExtrinsicGuess, int iterationsCount)`	Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.
`static boolean`	Calib3d.`solvePnPRansac(MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, boolean useExtrinsicGuess, int iterationsCount, float reprojectionError)`	Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.
`static boolean`	Calib3d.`solvePnPRansac(MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, boolean useExtrinsicGuess, int iterationsCount, float reprojectionError, double confidence)`	Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.
`static boolean`	Calib3d.`solvePnPRansac(MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, boolean useExtrinsicGuess, int iterationsCount, float reprojectionError, double confidence, Mat inliers)`	Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.
`static boolean`	Calib3d.`solvePnPRansac(MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, boolean useExtrinsicGuess, int iterationsCount, float reprojectionError, double confidence, Mat inliers, int flags)`	Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.
`static boolean`	Calib3d.`solvePnPRansac(MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, Mat inliers)`
`static boolean`	Calib3d.`solvePnPRansac(MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, Mat inliers, UsacParams params)`
`static void`	Calib3d.`solvePnPRefineLM(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec)`	Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.
`static void`	Calib3d.`solvePnPRefineLM(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, TermCriteria criteria)`	Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.
`static void`	Calib3d.`solvePnPRefineVVS(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec)`	Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.
`static void`	Calib3d.`solvePnPRefineVVS(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, TermCriteria criteria)`	Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.
`static void`	Calib3d.`solvePnPRefineVVS(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, TermCriteria criteria, double VVSlambda)`	Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.
`static double`	Calib3d.`stereoCalibrate(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F)`
`static double`	Calib3d.`stereoCalibrate(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, int flags)`
`static double`	Calib3d.`stereoCalibrate(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, int flags, TermCriteria criteria)`
`static double`	Calib3d.`stereoCalibrateExtended(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, Mat perViewErrors)`	Calibrates a stereo camera set up.
`static double`	Calib3d.`stereoCalibrateExtended(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, Mat perViewErrors, int flags)`	Calibrates a stereo camera set up.
`static double`	Calib3d.`stereoCalibrateExtended(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, Mat perViewErrors, int flags, TermCriteria criteria)`	Calibrates a stereo camera set up.
`static void`	Calib3d.`stereoRectify(Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q)`	Computes rectification transforms for each head of a calibrated stereo camera.
`static void`	Calib3d.`stereoRectify(Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags)`	Computes rectification transforms for each head of a calibrated stereo camera.
`static void`	Calib3d.`stereoRectify(Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, double alpha)`	Computes rectification transforms for each head of a calibrated stereo camera.
`static void`	Calib3d.`stereoRectify(Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, double alpha, Size newImageSize)`	Computes rectification transforms for each head of a calibrated stereo camera.
`static void`	Calib3d.`stereoRectify(Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, double alpha, Size newImageSize, Rect validPixROI1)`	Computes rectification transforms for each head of a calibrated stereo camera.
`static void`	Calib3d.`stereoRectify(Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, double alpha, Size newImageSize, Rect validPixROI1, Rect validPixROI2)`	Computes rectification transforms for each head of a calibrated stereo camera.
`static boolean`	Calib3d.`stereoRectifyUncalibrated(Mat points1, Mat points2, Mat F, Size imgSize, Mat H1, Mat H2)`	Computes a rectification transform for an uncalibrated stereo camera.
`static boolean`	Calib3d.`stereoRectifyUncalibrated(Mat points1, Mat points2, Mat F, Size imgSize, Mat H1, Mat H2, double threshold)`	Computes a rectification transform for an uncalibrated stereo camera.
`static void`	Calib3d.`triangulatePoints(Mat projMatr1, Mat projMatr2, Mat projPoints1, Mat projPoints2, Mat points4D)`	This function reconstructs 3-dimensional points (in homogeneous coordinates) by using their observations with a stereo camera.
`static void`	Calib3d.`undistort(Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs)`	Transforms an image to compensate for lens distortion.
`static void`	Calib3d.`undistort(Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs, Mat newCameraMatrix)`	Transforms an image to compensate for lens distortion.
`static void`	Calib3d.`undistortPoints(MatOfPoint2f src, MatOfPoint2f dst, Mat cameraMatrix, Mat distCoeffs)`	Computes the ideal point coordinates from the observed point coordinates.
`static void`	Calib3d.`undistortPoints(MatOfPoint2f src, MatOfPoint2f dst, Mat cameraMatrix, Mat distCoeffs, Mat R)`	Computes the ideal point coordinates from the observed point coordinates.
`static void`	Calib3d.`undistortPoints(MatOfPoint2f src, MatOfPoint2f dst, Mat cameraMatrix, Mat distCoeffs, Mat R, Mat P)`	Computes the ideal point coordinates from the observed point coordinates.
`static void`	Calib3d.`undistortPointsIter(Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs, Mat R, Mat P, TermCriteria criteria)`	Note: Default version of #undistortPoints does 5 iterations to compute undistorted points.
`static void`	Calib3d.`validateDisparity(Mat disparity, Mat cost, int minDisparity, int numberOfDisparities)`
`static void`	Calib3d.`validateDisparity(Mat disparity, Mat cost, int minDisparity, int numberOfDisparities, int disp12MaxDisp)`

Method parameters in org.opencv.calib3d with type arguments of type Mat
Modifier and Type	Method	Description
`static double`	Calib3d.`calibrateCamera(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs)`
`static double`	Calib3d.`calibrateCamera(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags)`
`static double`	Calib3d.`calibrateCamera(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags, TermCriteria criteria)`
`static double`	Calib3d.`calibrateCameraExtended(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors)`	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.
`static double`	Calib3d.`calibrateCameraExtended(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags)`	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.
`static double`	Calib3d.`calibrateCameraExtended(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags, TermCriteria criteria)`	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.
`static double`	Calib3d.`calibrateCameraRO(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat newObjPoints)`
`static double`	Calib3d.`calibrateCameraRO(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat newObjPoints, int flags)`
`static double`	Calib3d.`calibrateCameraRO(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat newObjPoints, int flags, TermCriteria criteria)`
`static double`	Calib3d.`calibrateCameraROExtended(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat newObjPoints, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat stdDeviationsObjPoints, Mat perViewErrors)`	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.
`static double`	Calib3d.`calibrateCameraROExtended(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat newObjPoints, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat stdDeviationsObjPoints, Mat perViewErrors, int flags)`	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.
`static double`	Calib3d.`calibrateCameraROExtended(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat newObjPoints, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat stdDeviationsObjPoints, Mat perViewErrors, int flags, TermCriteria criteria)`	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.
`static void`	Calib3d.`calibrateHandEye(List<Mat> R_gripper2base, List<Mat> t_gripper2base, List<Mat> R_target2cam, List<Mat> t_target2cam, Mat R_cam2gripper, Mat t_cam2gripper)`	Computes Hand-Eye calibration: \(_{}^{g}\textrm{T}_c\)
`static void`	Calib3d.`calibrateHandEye(List<Mat> R_gripper2base, List<Mat> t_gripper2base, List<Mat> R_target2cam, List<Mat> t_target2cam, Mat R_cam2gripper, Mat t_cam2gripper, int method)`	Computes Hand-Eye calibration: \(_{}^{g}\textrm{T}_c\)
`static void`	Calib3d.`calibrateRobotWorldHandEye(List<Mat> R_world2cam, List<Mat> t_world2cam, List<Mat> R_base2gripper, List<Mat> t_base2gripper, Mat R_base2world, Mat t_base2world, Mat R_gripper2cam, Mat t_gripper2cam)`	Computes Robot-World/Hand-Eye calibration: \(_{}^{w}\textrm{T}_b\) and \(_{}^{c}\textrm{T}_g\)
`static void`	Calib3d.`calibrateRobotWorldHandEye(List<Mat> R_world2cam, List<Mat> t_world2cam, List<Mat> R_base2gripper, List<Mat> t_base2gripper, Mat R_base2world, Mat t_base2world, Mat R_gripper2cam, Mat t_gripper2cam, int method)`	Computes Robot-World/Hand-Eye calibration: \(_{}^{w}\textrm{T}_b\) and \(_{}^{c}\textrm{T}_g\)
`static int`	Calib3d.`decomposeHomographyMat(Mat H, Mat K, List<Mat> rotations, List<Mat> translations, List<Mat> normals)`	Decompose a homography matrix to rotation(s), translation(s) and plane normal(s).
`static void`	Calib3d.`filterHomographyDecompByVisibleRefpoints(List<Mat> rotations, List<Mat> normals, Mat beforePoints, Mat afterPoints, Mat possibleSolutions)`	Filters homography decompositions based on additional information.
`static void`	Calib3d.`filterHomographyDecompByVisibleRefpoints(List<Mat> rotations, List<Mat> normals, Mat beforePoints, Mat afterPoints, Mat possibleSolutions, Mat pointsMask)`	Filters homography decompositions based on additional information.
`static double`	Calib3d.`fisheye_calibrate(List<Mat> objectPoints, List<Mat> imagePoints, Size image_size, Mat K, Mat D, List<Mat> rvecs, List<Mat> tvecs)`	Performs camera calibaration
`static double`	Calib3d.`fisheye_calibrate(List<Mat> objectPoints, List<Mat> imagePoints, Size image_size, Mat K, Mat D, List<Mat> rvecs, List<Mat> tvecs, int flags)`	Performs camera calibaration
`static double`	Calib3d.`fisheye_calibrate(List<Mat> objectPoints, List<Mat> imagePoints, Size image_size, Mat K, Mat D, List<Mat> rvecs, List<Mat> tvecs, int flags, TermCriteria criteria)`	Performs camera calibaration
`static double`	Calib3d.`fisheye_stereoCalibrate(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat T)`	Performs stereo calibration
`static double`	Calib3d.`fisheye_stereoCalibrate(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat T, int flags)`	Performs stereo calibration
`static double`	Calib3d.`fisheye_stereoCalibrate(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat T, int flags, TermCriteria criteria)`	Performs stereo calibration
`static float`	Calib3d.`rectify3Collinear(Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Mat cameraMatrix3, Mat distCoeffs3, List<Mat> imgpt1, List<Mat> imgpt3, Size imageSize, Mat R12, Mat T12, Mat R13, Mat T13, Mat R1, Mat R2, Mat R3, Mat P1, Mat P2, Mat P3, Mat Q, double alpha, Size newImgSize, Rect roi1, Rect roi2, int flags)`
`static int`	Calib3d.`solveP3P(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags)`	Finds an object pose from 3 3D-2D point correspondences.
`static int`	Calib3d.`solvePnPGeneric(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs)`	Finds an object pose from 3D-2D point correspondences.
`static int`	Calib3d.`solvePnPGeneric(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, boolean useExtrinsicGuess)`	Finds an object pose from 3D-2D point correspondences.
`static int`	Calib3d.`solvePnPGeneric(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, boolean useExtrinsicGuess, int flags)`	Finds an object pose from 3D-2D point correspondences.
`static int`	Calib3d.`solvePnPGeneric(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, boolean useExtrinsicGuess, int flags, Mat rvec)`	Finds an object pose from 3D-2D point correspondences.
`static int`	Calib3d.`solvePnPGeneric(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, boolean useExtrinsicGuess, int flags, Mat rvec, Mat tvec)`	Finds an object pose from 3D-2D point correspondences.
`static int`	Calib3d.`solvePnPGeneric(Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, boolean useExtrinsicGuess, int flags, Mat rvec, Mat tvec, Mat reprojectionError)`	Finds an object pose from 3D-2D point correspondences.
`static double`	Calib3d.`stereoCalibrate(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F)`
`static double`	Calib3d.`stereoCalibrate(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, int flags)`
`static double`	Calib3d.`stereoCalibrate(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, int flags, TermCriteria criteria)`
`static double`	Calib3d.`stereoCalibrateExtended(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, Mat perViewErrors)`	Calibrates a stereo camera set up.
`static double`	Calib3d.`stereoCalibrateExtended(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, Mat perViewErrors, int flags)`	Calibrates a stereo camera set up.
`static double`	Calib3d.`stereoCalibrateExtended(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, Mat perViewErrors, int flags, TermCriteria criteria)`	Calibrates a stereo camera set up.

Uses of Mat in org.opencv.core

Subclasses of Mat in org.opencv.core
Modifier and Type	Class	Description
`class`	`MatOfByte`
`class`	`MatOfDMatch`
`class`	`MatOfDouble`
`class`	`MatOfFloat`
`class`	`MatOfFloat4`
`class`	`MatOfFloat6`
`class`	`MatOfInt`
`class`	`MatOfInt4`
`class`	`MatOfKeyPoint`
`class`	`MatOfPoint`
`class`	`MatOfPoint2f`
`class`	`MatOfPoint3`
`class`	`MatOfPoint3f`
`class`	`MatOfRect`
`class`	`MatOfRect2d`
`class`	`MatOfRotatedRect`

Methods in org.opencv.core that return Mat
Modifier and Type	Method	Description
`Mat`	Mat.`adjustROI(int dtop, int dbottom, int dleft, int dright)`
`Mat`	Mat.`clone()`
`Mat`	Mat.`col(int x)`
`Mat`	Mat.`colRange(int startcol, int endcol)`
`Mat`	Mat.`colRange(Range r)`
`Mat`	Mat.`cross(Mat m)`
`Mat`	Mat.`diag()`
`Mat`	Mat.`diag(int d)`
`static Mat`	Mat.`diag(Mat d)`
`static Mat`	Mat.`eye(int rows, int cols, int type)`
`static Mat`	Mat.`eye(Size size, int type)`
`Mat`	Mat.`inv()`
`Mat`	Mat.`inv(int method)`
`Mat`	Mat.`mul(Mat m)`
`Mat`	Mat.`mul(Mat m, double scale)`
`static Mat`	Mat.`ones(int[] sizes, int type)`
`static Mat`	Mat.`ones(int rows, int cols, int type)`
`static Mat`	Mat.`ones(Size size, int type)`
`Mat`	Mat.`reshape(int cn)`
`Mat`	Mat.`reshape(int cn, int rows)`
`Mat`	Mat.`reshape(int cn, int[] newshape)`
`Mat`	Mat.`row(int y)`
`Mat`	Mat.`rowRange(int startrow, int endrow)`
`Mat`	Mat.`rowRange(Range r)`
`Mat`	Mat.`setTo(Mat value)`
`Mat`	Mat.`setTo(Mat value, Mat mask)`
`Mat`	Mat.`setTo(Scalar s)`
`Mat`	Mat.`setTo(Scalar value, Mat mask)`
`Mat`	Mat.`submat(int rowStart, int rowEnd, int colStart, int colEnd)`
`Mat`	Mat.`submat(Range[] ranges)`
`Mat`	Mat.`submat(Range rowRange, Range colRange)`
`Mat`	Mat.`submat(Rect roi)`
`Mat`	Mat.`t()`
`static Mat`	Mat.`zeros(int[] sizes, int type)`
`static Mat`	Mat.`zeros(int rows, int cols, int type)`
`static Mat`	Mat.`zeros(Size size, int type)`

Methods in org.opencv.core with parameters of type Mat
Modifier and Type	Method	Description
`static void`	Core.`absdiff(Mat src1, Mat src2, Mat dst)`	Calculates the per-element absolute difference between two arrays or between an array and a scalar.
`static void`	Core.`absdiff(Mat src1, Scalar src2, Mat dst)`
`static void`	Core.`add(Mat src1, Mat src2, Mat dst)`	Calculates the per-element sum of two arrays or an array and a scalar.
`static void`	Core.`add(Mat src1, Mat src2, Mat dst, Mat mask)`	Calculates the per-element sum of two arrays or an array and a scalar.
`static void`	Core.`add(Mat src1, Mat src2, Mat dst, Mat mask, int dtype)`	Calculates the per-element sum of two arrays or an array and a scalar.
`static void`	Core.`add(Mat src1, Scalar src2, Mat dst)`
`static void`	Core.`add(Mat src1, Scalar src2, Mat dst, Mat mask)`
`static void`	Core.`add(Mat src1, Scalar src2, Mat dst, Mat mask, int dtype)`
`static void`	Core.`addWeighted(Mat src1, double alpha, Mat src2, double beta, double gamma, Mat dst)`	Calculates the weighted sum of two arrays.
`static void`	Core.`addWeighted(Mat src1, double alpha, Mat src2, double beta, double gamma, Mat dst, int dtype)`	Calculates the weighted sum of two arrays.
`void`	Mat.`assignTo(Mat m)`
`void`	Mat.`assignTo(Mat m, int type)`
`static void`	Core.`batchDistance(Mat src1, Mat src2, Mat dist, int dtype, Mat nidx)`	naive nearest neighbor finder see http://en.wikipedia.org/wiki/Nearest_neighbor_search TODO: document
`static void`	Core.`batchDistance(Mat src1, Mat src2, Mat dist, int dtype, Mat nidx, int normType)`	naive nearest neighbor finder see http://en.wikipedia.org/wiki/Nearest_neighbor_search TODO: document
`static void`	Core.`batchDistance(Mat src1, Mat src2, Mat dist, int dtype, Mat nidx, int normType, int K)`	naive nearest neighbor finder see http://en.wikipedia.org/wiki/Nearest_neighbor_search TODO: document
`static void`	Core.`batchDistance(Mat src1, Mat src2, Mat dist, int dtype, Mat nidx, int normType, int K, Mat mask)`	naive nearest neighbor finder see http://en.wikipedia.org/wiki/Nearest_neighbor_search TODO: document
`static void`	Core.`batchDistance(Mat src1, Mat src2, Mat dist, int dtype, Mat nidx, int normType, int K, Mat mask, int update)`	naive nearest neighbor finder see http://en.wikipedia.org/wiki/Nearest_neighbor_search TODO: document
`static void`	Core.`batchDistance(Mat src1, Mat src2, Mat dist, int dtype, Mat nidx, int normType, int K, Mat mask, int update, boolean crosscheck)`	naive nearest neighbor finder see http://en.wikipedia.org/wiki/Nearest_neighbor_search TODO: document
`static void`	Core.`bitwise_and(Mat src1, Mat src2, Mat dst)`	computes bitwise conjunction of the two arrays (dst = src1 & src2) Calculates the per-element bit-wise conjunction of two arrays or an array and a scalar.
`static void`	Core.`bitwise_and(Mat src1, Mat src2, Mat dst, Mat mask)`	computes bitwise conjunction of the two arrays (dst = src1 & src2) Calculates the per-element bit-wise conjunction of two arrays or an array and a scalar.
`static void`	Core.`bitwise_not(Mat src, Mat dst)`	Inverts every bit of an array.
`static void`	Core.`bitwise_not(Mat src, Mat dst, Mat mask)`	Inverts every bit of an array.
`static void`	Core.`bitwise_or(Mat src1, Mat src2, Mat dst)`	Calculates the per-element bit-wise disjunction of two arrays or an array and a scalar.
`static void`	Core.`bitwise_or(Mat src1, Mat src2, Mat dst, Mat mask)`	Calculates the per-element bit-wise disjunction of two arrays or an array and a scalar.
`static void`	Core.`bitwise_xor(Mat src1, Mat src2, Mat dst)`	Calculates the per-element bit-wise "exclusive or" operation on two arrays or an array and a scalar.
`static void`	Core.`bitwise_xor(Mat src1, Mat src2, Mat dst, Mat mask)`	Calculates the per-element bit-wise "exclusive or" operation on two arrays or an array and a scalar.
`static void`	Core.`calcCovarMatrix(Mat samples, Mat covar, Mat mean, int flags)`	Note: use #COVAR_ROWS or #COVAR_COLS flag
`static void`	Core.`calcCovarMatrix(Mat samples, Mat covar, Mat mean, int flags, int ctype)`	Note: use #COVAR_ROWS or #COVAR_COLS flag
`static void`	Core.`cartToPolar(Mat x, Mat y, Mat magnitude, Mat angle)`	Calculates the magnitude and angle of 2D vectors.
`static void`	Core.`cartToPolar(Mat x, Mat y, Mat magnitude, Mat angle, boolean angleInDegrees)`	Calculates the magnitude and angle of 2D vectors.
`static boolean`	Core.`checkRange(Mat a)`	Checks every element of an input array for invalid values.
`static boolean`	Core.`checkRange(Mat a, boolean quiet)`	Checks every element of an input array for invalid values.
`static boolean`	Core.`checkRange(Mat a, boolean quiet, double minVal)`	Checks every element of an input array for invalid values.
`static boolean`	Core.`checkRange(Mat a, boolean quiet, double minVal, double maxVal)`	Checks every element of an input array for invalid values.
`static void`	Core.`compare(Mat src1, Mat src2, Mat dst, int cmpop)`	Performs the per-element comparison of two arrays or an array and scalar value.
`static void`	Core.`compare(Mat src1, Scalar src2, Mat dst, int cmpop)`
`static void`	Core.`completeSymm(Mat m)`	Copies the lower or the upper half of a square matrix to its another half.
`static void`	Core.`completeSymm(Mat m, boolean lowerToUpper)`	Copies the lower or the upper half of a square matrix to its another half.
`static void`	Core.`convertFp16(Mat src, Mat dst)`	Converts an array to half precision floating number.
`static void`	Core.`convertScaleAbs(Mat src, Mat dst)`	Scales, calculates absolute values, and converts the result to 8-bit.
`static void`	Core.`convertScaleAbs(Mat src, Mat dst, double alpha)`	Scales, calculates absolute values, and converts the result to 8-bit.
`static void`	Core.`convertScaleAbs(Mat src, Mat dst, double alpha, double beta)`	Scales, calculates absolute values, and converts the result to 8-bit.
`void`	Mat.`convertTo(Mat m, int rtype)`
`void`	Mat.`convertTo(Mat m, int rtype, double alpha)`
`void`	Mat.`convertTo(Mat m, int rtype, double alpha, double beta)`
`static void`	Core.`copyMakeBorder(Mat src, Mat dst, int top, int bottom, int left, int right, int borderType)`	Forms a border around an image.
`static void`	Core.`copyMakeBorder(Mat src, Mat dst, int top, int bottom, int left, int right, int borderType, Scalar value)`	Forms a border around an image.
`void`	Mat.`copySize(Mat m)`
`static void`	Core.`copyTo(Mat src, Mat dst, Mat mask)`	This is an overloaded member function, provided for convenience (python) Copies the matrix to another one.
`void`	Mat.`copyTo(Mat m)`
`void`	Mat.`copyTo(Mat m, Mat mask)`
`static int`	Core.`countNonZero(Mat src)`	Counts non-zero array elements.
`Mat`	Mat.`cross(Mat m)`
`static void`	Core.`dct(Mat src, Mat dst)`	Performs a forward or inverse discrete Cosine transform of 1D or 2D array.
`static void`	Core.`dct(Mat src, Mat dst, int flags)`	Performs a forward or inverse discrete Cosine transform of 1D or 2D array.
`static double`	Core.`determinant(Mat mtx)`	Returns the determinant of a square floating-point matrix.
`static void`	Core.`dft(Mat src, Mat dst)`	Performs a forward or inverse Discrete Fourier transform of a 1D or 2D floating-point array.
`static void`	Core.`dft(Mat src, Mat dst, int flags)`	Performs a forward or inverse Discrete Fourier transform of a 1D or 2D floating-point array.
`static void`	Core.`dft(Mat src, Mat dst, int flags, int nonzeroRows)`	Performs a forward or inverse Discrete Fourier transform of a 1D or 2D floating-point array.
`static Mat`	Mat.`diag(Mat d)`
`static void`	Core.`divide(double scale, Mat src2, Mat dst)`
`static void`	Core.`divide(double scale, Mat src2, Mat dst, int dtype)`
`static void`	Core.`divide(Mat src1, Mat src2, Mat dst)`	Performs per-element division of two arrays or a scalar by an array.
`static void`	Core.`divide(Mat src1, Mat src2, Mat dst, double scale)`	Performs per-element division of two arrays or a scalar by an array.
`static void`	Core.`divide(Mat src1, Mat src2, Mat dst, double scale, int dtype)`	Performs per-element division of two arrays or a scalar by an array.
`static void`	Core.`divide(Mat src1, Scalar src2, Mat dst)`
`static void`	Core.`divide(Mat src1, Scalar src2, Mat dst, double scale)`
`static void`	Core.`divide(Mat src1, Scalar src2, Mat dst, double scale, int dtype)`
`double`	Mat.`dot(Mat m)`
`static boolean`	Core.`eigen(Mat src, Mat eigenvalues)`	Calculates eigenvalues and eigenvectors of a symmetric matrix.
`static boolean`	Core.`eigen(Mat src, Mat eigenvalues, Mat eigenvectors)`	Calculates eigenvalues and eigenvectors of a symmetric matrix.
`static void`	Core.`eigenNonSymmetric(Mat src, Mat eigenvalues, Mat eigenvectors)`	Calculates eigenvalues and eigenvectors of a non-symmetric matrix (real eigenvalues only).
`static void`	Core.`exp(Mat src, Mat dst)`	Calculates the exponent of every array element.
`static void`	Core.`extractChannel(Mat src, Mat dst, int coi)`	Extracts a single channel from src (coi is 0-based index)
`static void`	Core.`findNonZero(Mat src, Mat idx)`	Returns the list of locations of non-zero pixels Given a binary matrix (likely returned from an operation such as threshold(), compare(), >, ==, etc, return all of the non-zero indices as a cv::Mat or std::vector<cv::Point> (x,y) For example: `cv::Mat binaryImage; // input, binary image cv::Mat locations; // output, locations of non-zero pixels cv::findNonZero(binaryImage, locations); // access pixel coordinates Point pnt = locations.at<Point>(i);` or `cv::Mat binaryImage; // input, binary image vector<Point> locations; // output, locations of non-zero pixels cv::findNonZero(binaryImage, locations); // access pixel coordinates Point pnt = locations[i];`
`static void`	Core.`flip(Mat src, Mat dst, int flipCode)`	Flips a 2D array around vertical, horizontal, or both axes.
`static void`	Core.`gemm(Mat src1, Mat src2, double alpha, Mat src3, double beta, Mat dst)`	Performs generalized matrix multiplication.
`static void`	Core.`gemm(Mat src1, Mat src2, double alpha, Mat src3, double beta, Mat dst, int flags)`	Performs generalized matrix multiplication.
`static void`	Core.`hconcat(List<Mat> src, Mat dst)`	`std::vector<cv::Mat> matrices = { cv::Mat(4, 1, CV_8UC1, cv::Scalar(1)), cv::Mat(4, 1, CV_8UC1, cv::Scalar(2)), cv::Mat(4, 1, CV_8UC1, cv::Scalar(3)),}; cv::Mat out; cv::hconcat( matrices, out ); //out: //[1, 2, 3; // 1, 2, 3; // 1, 2, 3; // 1, 2, 3]`
`static void`	Core.`idct(Mat src, Mat dst)`	Calculates the inverse Discrete Cosine Transform of a 1D or 2D array.
`static void`	Core.`idct(Mat src, Mat dst, int flags)`	Calculates the inverse Discrete Cosine Transform of a 1D or 2D array.
`static void`	Core.`idft(Mat src, Mat dst)`	Calculates the inverse Discrete Fourier Transform of a 1D or 2D array.
`static void`	Core.`idft(Mat src, Mat dst, int flags)`	Calculates the inverse Discrete Fourier Transform of a 1D or 2D array.
`static void`	Core.`idft(Mat src, Mat dst, int flags, int nonzeroRows)`	Calculates the inverse Discrete Fourier Transform of a 1D or 2D array.
`static void`	Core.`inRange(Mat src, Scalar lowerb, Scalar upperb, Mat dst)`	Checks if array elements lie between the elements of two other arrays.
`static void`	Core.`insertChannel(Mat src, Mat dst, int coi)`	Inserts a single channel to dst (coi is 0-based index)
`static double`	Core.`invert(Mat src, Mat dst)`	Finds the inverse or pseudo-inverse of a matrix.
`static double`	Core.`invert(Mat src, Mat dst, int flags)`	Finds the inverse or pseudo-inverse of a matrix.
`static double`	Core.`kmeans(Mat data, int K, Mat bestLabels, TermCriteria criteria, int attempts, int flags)`	Finds centers of clusters and groups input samples around the clusters.
`static double`	Core.`kmeans(Mat data, int K, Mat bestLabels, TermCriteria criteria, int attempts, int flags, Mat centers)`	Finds centers of clusters and groups input samples around the clusters.
`static void`	Core.`log(Mat src, Mat dst)`	Calculates the natural logarithm of every array element.
`static void`	Core.`LUT(Mat src, Mat lut, Mat dst)`	Performs a look-up table transform of an array.
`static void`	Core.`magnitude(Mat x, Mat y, Mat magnitude)`	Calculates the magnitude of 2D vectors.
`static double`	Core.`Mahalanobis(Mat v1, Mat v2, Mat icovar)`	Calculates the Mahalanobis distance between two vectors.
`static void`	Core.`max(Mat src1, Mat src2, Mat dst)`	Calculates per-element maximum of two arrays or an array and a scalar.
`static void`	Core.`max(Mat src1, Scalar src2, Mat dst)`
`static Scalar`	Core.`mean(Mat src)`	Calculates an average (mean) of array elements.
`static Scalar`	Core.`mean(Mat src, Mat mask)`	Calculates an average (mean) of array elements.
`static void`	Core.`meanStdDev(Mat src, MatOfDouble mean, MatOfDouble stddev)`	Calculates a mean and standard deviation of array elements.
`static void`	Core.`meanStdDev(Mat src, MatOfDouble mean, MatOfDouble stddev, Mat mask)`	Calculates a mean and standard deviation of array elements.
`static void`	Core.`merge(List<Mat> mv, Mat dst)`
`static void`	Core.`min(Mat src1, Mat src2, Mat dst)`	Calculates per-element minimum of two arrays or an array and a scalar.
`static void`	Core.`min(Mat src1, Scalar src2, Mat dst)`
`static Core.MinMaxLocResult`	Core.`minMaxLoc(Mat src)`
`static Core.MinMaxLocResult`	Core.`minMaxLoc(Mat src, Mat mask)`
`Mat`	Mat.`mul(Mat m)`
`Mat`	Mat.`mul(Mat m, double scale)`
`static void`	Core.`mulSpectrums(Mat a, Mat b, Mat c, int flags)`	Performs the per-element multiplication of two Fourier spectrums.
`static void`	Core.`mulSpectrums(Mat a, Mat b, Mat c, int flags, boolean conjB)`	Performs the per-element multiplication of two Fourier spectrums.
`static void`	Core.`multiply(Mat src1, Mat src2, Mat dst)`	Calculates the per-element scaled product of two arrays.
`static void`	Core.`multiply(Mat src1, Mat src2, Mat dst, double scale)`	Calculates the per-element scaled product of two arrays.
`static void`	Core.`multiply(Mat src1, Mat src2, Mat dst, double scale, int dtype)`	Calculates the per-element scaled product of two arrays.
`static void`	Core.`multiply(Mat src1, Scalar src2, Mat dst)`
`static void`	Core.`multiply(Mat src1, Scalar src2, Mat dst, double scale)`
`static void`	Core.`multiply(Mat src1, Scalar src2, Mat dst, double scale, int dtype)`
`static void`	Core.`mulTransposed(Mat src, Mat dst, boolean aTa)`	Calculates the product of a matrix and its transposition.
`static void`	Core.`mulTransposed(Mat src, Mat dst, boolean aTa, Mat delta)`	Calculates the product of a matrix and its transposition.
`static void`	Core.`mulTransposed(Mat src, Mat dst, boolean aTa, Mat delta, double scale)`	Calculates the product of a matrix and its transposition.
`static void`	Core.`mulTransposed(Mat src, Mat dst, boolean aTa, Mat delta, double scale, int dtype)`	Calculates the product of a matrix and its transposition.
`static double`	Core.`norm(Mat src1)`	Calculates the absolute norm of an array.
`static double`	Core.`norm(Mat src1, int normType)`	Calculates the absolute norm of an array.
`static double`	Core.`norm(Mat src1, int normType, Mat mask)`	Calculates the absolute norm of an array.
`static double`	Core.`norm(Mat src1, Mat src2)`	Calculates an absolute difference norm or a relative difference norm.
`static double`	Core.`norm(Mat src1, Mat src2, int normType)`	Calculates an absolute difference norm or a relative difference norm.
`static double`	Core.`norm(Mat src1, Mat src2, int normType, Mat mask)`	Calculates an absolute difference norm or a relative difference norm.
`static void`	Core.`normalize(Mat src, Mat dst)`	Normalizes the norm or value range of an array.
`static void`	Core.`normalize(Mat src, Mat dst, double alpha)`	Normalizes the norm or value range of an array.
`static void`	Core.`normalize(Mat src, Mat dst, double alpha, double beta)`	Normalizes the norm or value range of an array.
`static void`	Core.`normalize(Mat src, Mat dst, double alpha, double beta, int norm_type)`	Normalizes the norm or value range of an array.
`static void`	Core.`normalize(Mat src, Mat dst, double alpha, double beta, int norm_type, int dtype)`	Normalizes the norm or value range of an array.
`static void`	Core.`normalize(Mat src, Mat dst, double alpha, double beta, int norm_type, int dtype, Mat mask)`	Normalizes the norm or value range of an array.
`static void`	Core.`patchNaNs(Mat a)`	converts NaNs to the given number
`static void`	Core.`patchNaNs(Mat a, double val)`	converts NaNs to the given number
`static void`	Core.`PCABackProject(Mat data, Mat mean, Mat eigenvectors, Mat result)`	wrap PCA::backProject
`static void`	Core.`PCACompute(Mat data, Mat mean, Mat eigenvectors)`	wrap PCA::operator()
`static void`	Core.`PCACompute(Mat data, Mat mean, Mat eigenvectors, double retainedVariance)`	wrap PCA::operator()
`static void`	Core.`PCACompute(Mat data, Mat mean, Mat eigenvectors, int maxComponents)`	wrap PCA::operator()
`static void`	Core.`PCACompute2(Mat data, Mat mean, Mat eigenvectors, Mat eigenvalues)`	wrap PCA::operator() and add eigenvalues output parameter
`static void`	Core.`PCACompute2(Mat data, Mat mean, Mat eigenvectors, Mat eigenvalues, double retainedVariance)`	wrap PCA::operator() and add eigenvalues output parameter
`static void`	Core.`PCACompute2(Mat data, Mat mean, Mat eigenvectors, Mat eigenvalues, int maxComponents)`	wrap PCA::operator() and add eigenvalues output parameter
`static void`	Core.`PCAProject(Mat data, Mat mean, Mat eigenvectors, Mat result)`	wrap PCA::project
`static void`	Core.`perspectiveTransform(Mat src, Mat dst, Mat m)`	Performs the perspective matrix transformation of vectors.
`static void`	Core.`phase(Mat x, Mat y, Mat angle)`	Calculates the rotation angle of 2D vectors.
`static void`	Core.`phase(Mat x, Mat y, Mat angle, boolean angleInDegrees)`	Calculates the rotation angle of 2D vectors.
`static void`	Core.`polarToCart(Mat magnitude, Mat angle, Mat x, Mat y)`	Calculates x and y coordinates of 2D vectors from their magnitude and angle.
`static void`	Core.`polarToCart(Mat magnitude, Mat angle, Mat x, Mat y, boolean angleInDegrees)`	Calculates x and y coordinates of 2D vectors from their magnitude and angle.
`static void`	Core.`pow(Mat src, double power, Mat dst)`	Raises every array element to a power.
`static double`	Core.`PSNR(Mat src1, Mat src2)`	Computes the Peak Signal-to-Noise Ratio (PSNR) image quality metric.
`static double`	Core.`PSNR(Mat src1, Mat src2, double R)`	Computes the Peak Signal-to-Noise Ratio (PSNR) image quality metric.
`void`	Mat.`push_back(Mat m)`
`static void`	Core.`randn(Mat dst, double mean, double stddev)`	Fills the array with normally distributed random numbers.
`static void`	Core.`randShuffle(Mat dst)`	Shuffles the array elements randomly.
`static void`	Core.`randShuffle(Mat dst, double iterFactor)`	Shuffles the array elements randomly.
`static void`	Core.`randu(Mat dst, double low, double high)`	Generates a single uniformly-distributed random number or an array of random numbers.
`static void`	Core.`reduce(Mat src, Mat dst, int dim, int rtype)`	Reduces a matrix to a vector.
`static void`	Core.`reduce(Mat src, Mat dst, int dim, int rtype, int dtype)`	Reduces a matrix to a vector.
`static void`	Core.`repeat(Mat src, int ny, int nx, Mat dst)`	Fills the output array with repeated copies of the input array.
`static void`	Core.`rotate(Mat src, Mat dst, int rotateCode)`	Rotates a 2D array in multiples of 90 degrees.
`static void`	Core.`scaleAdd(Mat src1, double alpha, Mat src2, Mat dst)`	Calculates the sum of a scaled array and another array.
`static void`	Core.`setIdentity(Mat mtx)`	Initializes a scaled identity matrix.
`static void`	Core.`setIdentity(Mat mtx, Scalar s)`	Initializes a scaled identity matrix.
`Mat`	Mat.`setTo(Mat value)`
`Mat`	Mat.`setTo(Mat value, Mat mask)`
`Mat`	Mat.`setTo(Scalar value, Mat mask)`
`static boolean`	Core.`solve(Mat src1, Mat src2, Mat dst)`	Solves one or more linear systems or least-squares problems.
`static boolean`	Core.`solve(Mat src1, Mat src2, Mat dst, int flags)`	Solves one or more linear systems or least-squares problems.
`static int`	Core.`solveCubic(Mat coeffs, Mat roots)`	Finds the real roots of a cubic equation.
`static double`	Core.`solvePoly(Mat coeffs, Mat roots)`	Finds the real or complex roots of a polynomial equation.
`static double`	Core.`solvePoly(Mat coeffs, Mat roots, int maxIters)`	Finds the real or complex roots of a polynomial equation.
`static void`	Core.`sort(Mat src, Mat dst, int flags)`	Sorts each row or each column of a matrix.
`static void`	Core.`sortIdx(Mat src, Mat dst, int flags)`	Sorts each row or each column of a matrix.
`static void`	Core.`split(Mat m, List<Mat> mv)`
`static void`	Core.`sqrt(Mat src, Mat dst)`	Calculates a square root of array elements.
`static void`	Core.`subtract(Mat src1, Mat src2, Mat dst)`	Calculates the per-element difference between two arrays or array and a scalar.
`static void`	Core.`subtract(Mat src1, Mat src2, Mat dst, Mat mask)`	Calculates the per-element difference between two arrays or array and a scalar.
`static void`	Core.`subtract(Mat src1, Mat src2, Mat dst, Mat mask, int dtype)`	Calculates the per-element difference between two arrays or array and a scalar.
`static void`	Core.`subtract(Mat src1, Scalar src2, Mat dst)`
`static void`	Core.`subtract(Mat src1, Scalar src2, Mat dst, Mat mask)`
`static void`	Core.`subtract(Mat src1, Scalar src2, Mat dst, Mat mask, int dtype)`
`static Scalar`	Core.`sumElems(Mat src)`	Calculates the sum of array elements.
`static void`	Core.`SVBackSubst(Mat w, Mat u, Mat vt, Mat rhs, Mat dst)`	wrap SVD::backSubst
`static void`	Core.`SVDecomp(Mat src, Mat w, Mat u, Mat vt)`	wrap SVD::compute
`static void`	Core.`SVDecomp(Mat src, Mat w, Mat u, Mat vt, int flags)`	wrap SVD::compute
`static Scalar`	Core.`trace(Mat mtx)`	Returns the trace of a matrix.
`static void`	Core.`transform(Mat src, Mat dst, Mat m)`	Performs the matrix transformation of every array element.
`static void`	Core.`transpose(Mat src, Mat dst)`	Transposes a matrix.
`static void`	Core.`vconcat(List<Mat> src, Mat dst)`	`std::vector<cv::Mat> matrices = { cv::Mat(1, 4, CV_8UC1, cv::Scalar(1)), cv::Mat(1, 4, CV_8UC1, cv::Scalar(2)), cv::Mat(1, 4, CV_8UC1, cv::Scalar(3)),}; cv::Mat out; cv::vconcat( matrices, out ); //out: //[1, 1, 1, 1; // 2, 2, 2, 2; // 3, 3, 3, 3]`

Method parameters in org.opencv.core with type arguments of type Mat
Modifier and Type	Method	Description
`static void`	Core.`hconcat(List<Mat> src, Mat dst)`	`std::vector<cv::Mat> matrices = { cv::Mat(4, 1, CV_8UC1, cv::Scalar(1)), cv::Mat(4, 1, CV_8UC1, cv::Scalar(2)), cv::Mat(4, 1, CV_8UC1, cv::Scalar(3)),}; cv::Mat out; cv::hconcat( matrices, out ); //out: //[1, 2, 3; // 1, 2, 3; // 1, 2, 3; // 1, 2, 3]`
`static void`	Core.`merge(List<Mat> mv, Mat dst)`
`static void`	Core.`mixChannels(List<Mat> src, List<Mat> dst, MatOfInt fromTo)`
`static void`	Core.`split(Mat m, List<Mat> mv)`
`static void`	Core.`vconcat(List<Mat> src, Mat dst)`	`std::vector<cv::Mat> matrices = { cv::Mat(1, 4, CV_8UC1, cv::Scalar(1)), cv::Mat(1, 4, CV_8UC1, cv::Scalar(2)), cv::Mat(1, 4, CV_8UC1, cv::Scalar(3)),}; cv::Mat out; cv::vconcat( matrices, out ); //out: //[1, 1, 1, 1; // 2, 2, 2, 2; // 3, 3, 3, 3]`

Constructors in org.opencv.core with parameters of type Mat
Constructor	Description
`Mat(Mat m, Range rowRange)`
`Mat(Mat m, Range[] ranges)`
`Mat(Mat m, Range rowRange, Range colRange)`
`Mat(Mat m, Rect roi)`
`MatOfByte(Mat m)`
`MatOfDMatch(Mat m)`
`MatOfDouble(Mat m)`
`MatOfFloat(Mat m)`
`MatOfFloat4(Mat m)`
`MatOfFloat6(Mat m)`
`MatOfInt(Mat m)`
`MatOfInt4(Mat m)`
`MatOfKeyPoint(Mat m)`
`MatOfPoint(Mat m)`
`MatOfPoint2f(Mat m)`
`MatOfPoint3(Mat m)`
`MatOfPoint3f(Mat m)`
`MatOfRect(Mat m)`
`MatOfRect2d(Mat m)`
`MatOfRotatedRect(Mat m)`

Uses of Mat in org.opencv.dnn

Methods in org.opencv.dnn that return Mat
Modifier and Type	Method	Description
`static Mat`	Dnn.`blobFromImage(Mat image)`	Creates 4-dimensional blob from image.
`static Mat`	Dnn.`blobFromImage(Mat image, double scalefactor)`	Creates 4-dimensional blob from image.
`static Mat`	Dnn.`blobFromImage(Mat image, double scalefactor, Size size)`	Creates 4-dimensional blob from image.
`static Mat`	Dnn.`blobFromImage(Mat image, double scalefactor, Size size, Scalar mean)`	Creates 4-dimensional blob from image.
`static Mat`	Dnn.`blobFromImage(Mat image, double scalefactor, Size size, Scalar mean, boolean swapRB)`	Creates 4-dimensional blob from image.
`static Mat`	Dnn.`blobFromImage(Mat image, double scalefactor, Size size, Scalar mean, boolean swapRB, boolean crop)`	Creates 4-dimensional blob from image.
`static Mat`	Dnn.`blobFromImage(Mat image, double scalefactor, Size size, Scalar mean, boolean swapRB, boolean crop, int ddepth)`	Creates 4-dimensional blob from image.
`static Mat`	Dnn.`blobFromImages(List<Mat> images)`	Creates 4-dimensional blob from series of images.
`static Mat`	Dnn.`blobFromImages(List<Mat> images, double scalefactor)`	Creates 4-dimensional blob from series of images.
`static Mat`	Dnn.`blobFromImages(List<Mat> images, double scalefactor, Size size)`	Creates 4-dimensional blob from series of images.
`static Mat`	Dnn.`blobFromImages(List<Mat> images, double scalefactor, Size size, Scalar mean)`	Creates 4-dimensional blob from series of images.
`static Mat`	Dnn.`blobFromImages(List<Mat> images, double scalefactor, Size size, Scalar mean, boolean swapRB)`	Creates 4-dimensional blob from series of images.
`static Mat`	Dnn.`blobFromImages(List<Mat> images, double scalefactor, Size size, Scalar mean, boolean swapRB, boolean crop)`	Creates 4-dimensional blob from series of images.
`static Mat`	Dnn.`blobFromImages(List<Mat> images, double scalefactor, Size size, Scalar mean, boolean swapRB, boolean crop, int ddepth)`	Creates 4-dimensional blob from series of images.
`Mat`	Net.`forward()`	Runs forward pass to compute output of layer with name `outputName`.
`Mat`	Net.`forward(String outputName)`	Runs forward pass to compute output of layer with name `outputName`.
`Mat`	Net.`getParam(DictValue layer)`	Returns parameter blob of the layer.
`Mat`	Net.`getParam(DictValue layer, int numParam)`	Returns parameter blob of the layer.
`static Mat`	Dnn.`readTensorFromONNX(String path)`	Creates blob from .pb file.
`static Mat`	Dnn.`readTorchBlob(String filename)`	Loads blob which was serialized as torch.Tensor object of Torch7 framework.
`static Mat`	Dnn.`readTorchBlob(String filename, boolean isBinary)`	Loads blob which was serialized as torch.Tensor object of Torch7 framework.

Methods in org.opencv.dnn that return types with arguments of type Mat
Modifier and Type	Method	Description
`List<Mat>`	Layer.`get_blobs()`

Methods in org.opencv.dnn with parameters of type Mat
Modifier and Type	Method	Description
`static Mat`	Dnn.`blobFromImage(Mat image)`	Creates 4-dimensional blob from image.
`static Mat`	Dnn.`blobFromImage(Mat image, double scalefactor)`	Creates 4-dimensional blob from image.
`static Mat`	Dnn.`blobFromImage(Mat image, double scalefactor, Size size)`	Creates 4-dimensional blob from image.
`static Mat`	Dnn.`blobFromImage(Mat image, double scalefactor, Size size, Scalar mean)`	Creates 4-dimensional blob from image.
`static Mat`	Dnn.`blobFromImage(Mat image, double scalefactor, Size size, Scalar mean, boolean swapRB)`	Creates 4-dimensional blob from image.
`static Mat`	Dnn.`blobFromImage(Mat image, double scalefactor, Size size, Scalar mean, boolean swapRB, boolean crop)`	Creates 4-dimensional blob from image.
`static Mat`	Dnn.`blobFromImage(Mat image, double scalefactor, Size size, Scalar mean, boolean swapRB, boolean crop, int ddepth)`	Creates 4-dimensional blob from image.
`void`	ClassificationModel.`classify(Mat frame, int[] classId, float[] conf)`
`void`	DetectionModel.`detect(Mat frame, MatOfInt classIds, MatOfFloat confidences, MatOfRect boxes)`	Given the `input` frame, create input blob, run net and return result detections.
`void`	DetectionModel.`detect(Mat frame, MatOfInt classIds, MatOfFloat confidences, MatOfRect boxes, float confThreshold)`	Given the `input` frame, create input blob, run net and return result detections.
`void`	DetectionModel.`detect(Mat frame, MatOfInt classIds, MatOfFloat confidences, MatOfRect boxes, float confThreshold, float nmsThreshold)`	Given the `input` frame, create input blob, run net and return result detections.
`void`	TextDetectionModel.`detect(Mat frame, List<MatOfPoint> detections)`
`void`	TextDetectionModel.`detect(Mat frame, List<MatOfPoint> detections, MatOfFloat confidences)`	Performs detection Given the input `frame`, prepare network input, run network inference, post-process network output and return result detections.
`void`	TextDetectionModel.`detectTextRectangles(Mat frame, MatOfRotatedRect detections)`
`void`	TextDetectionModel.`detectTextRectangles(Mat frame, MatOfRotatedRect detections, MatOfFloat confidences)`	Performs detection Given the input `frame`, prepare network input, run network inference, post-process network output and return result detections.
`MatOfPoint2f`	KeypointsModel.`estimate(Mat frame)`	Given the `input` frame, create input blob, run net
`MatOfPoint2f`	KeypointsModel.`estimate(Mat frame, float thresh)`	Given the `input` frame, create input blob, run net
`static void`	Dnn.`imagesFromBlob(Mat blob_, List<Mat> images_)`	Parse a 4D blob and output the images it contains as 2D arrays through a simpler data structure (std::vector<cv::Mat>).
`void`	Model.`predict(Mat frame, List<Mat> outs)`	Given the `input` frame, create input blob, run net and return the output `blobs`.
`String`	TextRecognitionModel.`recognize(Mat frame)`	Given the `input` frame, create input blob, run net and return recognition result
`void`	TextRecognitionModel.`recognize(Mat frame, List<Mat> roiRects, List<String> results)`	Given the `input` frame, create input blob, run net and return recognition result
`void`	SegmentationModel.`segment(Mat frame, Mat mask)`	Given the `input` frame, create input blob, run net
`void`	Net.`setInput(Mat blob)`	Sets the new input value for the network
`void`	Net.`setInput(Mat blob, String name)`	Sets the new input value for the network
`void`	Net.`setInput(Mat blob, String name, double scalefactor)`	Sets the new input value for the network
`void`	Net.`setInput(Mat blob, String name, double scalefactor, Scalar mean)`	Sets the new input value for the network
`void`	Net.`setParam(DictValue layer, int numParam, Mat blob)`	Sets the new value for the learned param of the layer.

Method parameters in org.opencv.dnn with type arguments of type Mat
Modifier and Type	Method	Description
`static Mat`	Dnn.`blobFromImages(List<Mat> images)`	Creates 4-dimensional blob from series of images.
`static Mat`	Dnn.`blobFromImages(List<Mat> images, double scalefactor)`	Creates 4-dimensional blob from series of images.
`static Mat`	Dnn.`blobFromImages(List<Mat> images, double scalefactor, Size size)`	Creates 4-dimensional blob from series of images.
`static Mat`	Dnn.`blobFromImages(List<Mat> images, double scalefactor, Size size, Scalar mean)`	Creates 4-dimensional blob from series of images.
`static Mat`	Dnn.`blobFromImages(List<Mat> images, double scalefactor, Size size, Scalar mean, boolean swapRB)`	Creates 4-dimensional blob from series of images.
`static Mat`	Dnn.`blobFromImages(List<Mat> images, double scalefactor, Size size, Scalar mean, boolean swapRB, boolean crop)`	Creates 4-dimensional blob from series of images.
`static Mat`	Dnn.`blobFromImages(List<Mat> images, double scalefactor, Size size, Scalar mean, boolean swapRB, boolean crop, int ddepth)`	Creates 4-dimensional blob from series of images.
`void`	Layer.`finalize(List<Mat> inputs, List<Mat> outputs)`	Computes and sets internal parameters according to inputs, outputs and blobs.
`void`	Net.`forward(List<Mat> outputBlobs)`	Runs forward pass to compute output of layer with name `outputName`.
`void`	Net.`forward(List<Mat> outputBlobs, String outputName)`	Runs forward pass to compute output of layer with name `outputName`.
`void`	Net.`forward(List<Mat> outputBlobs, List<String> outBlobNames)`	Runs forward pass to compute outputs of layers listed in `outBlobNames`.
`static void`	Dnn.`imagesFromBlob(Mat blob_, List<Mat> images_)`	Parse a 4D blob and output the images it contains as 2D arrays through a simpler data structure (std::vector<cv::Mat>).
`void`	Model.`predict(Mat frame, List<Mat> outs)`	Given the `input` frame, create input blob, run net and return the output `blobs`.
`void`	TextRecognitionModel.`recognize(Mat frame, List<Mat> roiRects, List<String> results)`	Given the `input` frame, create input blob, run net and return recognition result
`void`	Layer.`run(List<Mat> inputs, List<Mat> outputs, List<Mat> internals)`	Deprecated. This method will be removed in the future release.
`void`	Layer.`set_blobs(List<Mat> blobs)`

Uses of Mat in org.opencv.face

Methods in org.opencv.face that return Mat
Modifier and Type	Method	Description
`Mat`	BasicFaceRecognizer.`getEigenValues()`
`Mat`	BasicFaceRecognizer.`getEigenVectors()`
`Mat`	BasicFaceRecognizer.`getLabels()`
`Mat`	LBPHFaceRecognizer.`getLabels()`
`Mat`	BasicFaceRecognizer.`getMean()`

Methods in org.opencv.face that return types with arguments of type Mat
Modifier and Type	Method	Description
`List<Mat>`	LBPHFaceRecognizer.`getHistograms()`
`List<Mat>`	BasicFaceRecognizer.`getProjections()`

Methods in org.opencv.face with parameters of type Mat
Modifier and Type	Method	Description
`void`	BIF.`compute(Mat image, Mat features)`	Computes features sby input image.
`static void`	Face.`drawFacemarks(Mat image, Mat points)`	Utility to draw the detected facial landmark points
`static void`	Face.`drawFacemarks(Mat image, Mat points, Scalar color)`	Utility to draw the detected facial landmark points
`boolean`	Facemark.`fit(Mat image, MatOfRect faces, List<MatOfPoint2f> landmarks)`	Detect facial landmarks from an image.
`static boolean`	Face.`getFacesHAAR(Mat image, Mat faces, String face_cascade_name)`	Default face detector This function is mainly utilized by the implementation of a Facemark Algorithm.
`static boolean`	Face.`loadFacePoints(String filename, Mat points)`	A utility to load facial landmark information from a given file.
`static boolean`	Face.`loadFacePoints(String filename, Mat points, float offset)`	A utility to load facial landmark information from a given file.
`static boolean`	Face.`loadTrainingData(String imageList, String groundTruth, List<String> images, Mat facePoints)`	A utility to load facial landmark information from the dataset.
`static boolean`	Face.`loadTrainingData(String imageList, String groundTruth, List<String> images, Mat facePoints, float offset)`	A utility to load facial landmark information from the dataset.
`static boolean`	Face.`loadTrainingData(String filename, List<String> images, Mat facePoints)`	A utility to load facial landmark dataset from a single file.
`static boolean`	Face.`loadTrainingData(String filename, List<String> images, Mat facePoints, char delim)`	A utility to load facial landmark dataset from a single file.
`static boolean`	Face.`loadTrainingData(String filename, List<String> images, Mat facePoints, char delim, float offset)`	A utility to load facial landmark dataset from a single file.
`void`	FaceRecognizer.`predict(Mat src, int[] label, double[] confidence)`	Predicts a label and associated confidence (e.g.
`void`	FaceRecognizer.`predict_collect(Mat src, PredictCollector collector)`	if implemented - send all result of prediction to collector that can be used for somehow custom result handling
`int`	FaceRecognizer.`predict_label(Mat src)`
`boolean`	MACE.`same(Mat query)`	correlate query img and threshold to min class value
`void`	FaceRecognizer.`train(List<Mat> src, Mat labels)`	Trains a FaceRecognizer with given data and associated labels.
`void`	FaceRecognizer.`update(List<Mat> src, Mat labels)`	Updates a FaceRecognizer with given data and associated labels.

Method parameters in org.opencv.face with type arguments of type Mat
Modifier and Type	Method	Description
`void`	FaceRecognizer.`train(List<Mat> src, Mat labels)`	Trains a FaceRecognizer with given data and associated labels.
`void`	MACE.`train(List<Mat> images)`	train it on positive features compute the mace filter: `h = D(-1) * X * (X(+) * D(-1) * X)(-1) * C` also calculate a minimal threshold for this class, the smallest self-similarity from the train images
`void`	FaceRecognizer.`update(List<Mat> src, Mat labels)`	Updates a FaceRecognizer with given data and associated labels.

Uses of Mat in org.opencv.features2d

Methods in org.opencv.features2d that return Mat
Modifier and Type	Method	Description
`Mat`	BOWKMeansTrainer.`cluster()`
`Mat`	BOWKMeansTrainer.`cluster(Mat descriptors)`
`Mat`	BOWTrainer.`cluster()`
`Mat`	BOWTrainer.`cluster(Mat descriptors)`	Clusters train descriptors.
`Mat`	BOWImgDescriptorExtractor.`getVocabulary()`	Returns the set vocabulary.

Methods in org.opencv.features2d that return types with arguments of type Mat
Modifier and Type	Method	Description
`List<Mat>`	BOWTrainer.`getDescriptors()`	Returns a training set of descriptors.
`List<Mat>`	DescriptorMatcher.`getTrainDescriptors()`	Returns a constant link to the train descriptor collection trainDescCollection .

Methods in org.opencv.features2d with parameters of type Mat
Modifier and Type	Method	Description
`void`	BOWTrainer.`add(Mat descriptors)`	Adds descriptors to a training set.
`Mat`	BOWKMeansTrainer.`cluster(Mat descriptors)`
`Mat`	BOWTrainer.`cluster(Mat descriptors)`	Clusters train descriptors.
`void`	BOWImgDescriptorExtractor.`compute(Mat image, MatOfKeyPoint keypoints, Mat imgDescriptor)`
`void`	Feature2D.`compute(Mat image, MatOfKeyPoint keypoints, Mat descriptors)`	Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).
`void`	Feature2D.`detect(Mat image, MatOfKeyPoint keypoints)`	Detects keypoints in an image (first variant) or image set (second variant).
`void`	Feature2D.`detect(Mat image, MatOfKeyPoint keypoints, Mat mask)`	Detects keypoints in an image (first variant) or image set (second variant).
`void`	Feature2D.`detectAndCompute(Mat image, Mat mask, MatOfKeyPoint keypoints, Mat descriptors)`	Detects keypoints and computes the descriptors
`void`	Feature2D.`detectAndCompute(Mat image, Mat mask, MatOfKeyPoint keypoints, Mat descriptors, boolean useProvidedKeypoints)`	Detects keypoints and computes the descriptors
`void`	MSER.`detectRegions(Mat image, List<MatOfPoint> msers, MatOfRect bboxes)`	Detect %MSER regions
`static void`	Features2d.`drawKeypoints(Mat image, MatOfKeyPoint keypoints, Mat outImage)`	Draws keypoints.
`static void`	Features2d.`drawKeypoints(Mat image, MatOfKeyPoint keypoints, Mat outImage, Scalar color)`	Draws keypoints.
`static void`	Features2d.`drawKeypoints(Mat image, MatOfKeyPoint keypoints, Mat outImage, Scalar color, int flags)`	Draws keypoints.
`static void`	Features2d.`drawMatches(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, Mat outImg)`	Draws the found matches of keypoints from two images.
`static void`	Features2d.`drawMatches(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, Mat outImg, int matchesThickness)`
`static void`	Features2d.`drawMatches(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, Mat outImg, int matchesThickness, Scalar matchColor)`
`static void`	Features2d.`drawMatches(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, Mat outImg, int matchesThickness, Scalar matchColor, Scalar singlePointColor)`
`static void`	Features2d.`drawMatches(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, Mat outImg, int matchesThickness, Scalar matchColor, Scalar singlePointColor, MatOfByte matchesMask)`
`static void`	Features2d.`drawMatches(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, Mat outImg, int matchesThickness, Scalar matchColor, Scalar singlePointColor, MatOfByte matchesMask, int flags)`
`static void`	Features2d.`drawMatches(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, Mat outImg, Scalar matchColor)`	Draws the found matches of keypoints from two images.
`static void`	Features2d.`drawMatches(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, Mat outImg, Scalar matchColor, Scalar singlePointColor)`	Draws the found matches of keypoints from two images.
`static void`	Features2d.`drawMatches(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, Mat outImg, Scalar matchColor, Scalar singlePointColor, MatOfByte matchesMask)`	Draws the found matches of keypoints from two images.
`static void`	Features2d.`drawMatches(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, Mat outImg, Scalar matchColor, Scalar singlePointColor, MatOfByte matchesMask, int flags)`	Draws the found matches of keypoints from two images.
`static void`	Features2d.`drawMatchesKnn(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, List<MatOfDMatch> matches1to2, Mat outImg)`
`static void`	Features2d.`drawMatchesKnn(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, List<MatOfDMatch> matches1to2, Mat outImg, Scalar matchColor)`
`static void`	Features2d.`drawMatchesKnn(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, List<MatOfDMatch> matches1to2, Mat outImg, Scalar matchColor, Scalar singlePointColor)`
`static void`	Features2d.`drawMatchesKnn(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, List<MatOfDMatch> matches1to2, Mat outImg, Scalar matchColor, Scalar singlePointColor, List<MatOfByte> matchesMask)`
`static void`	Features2d.`drawMatchesKnn(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, List<MatOfDMatch> matches1to2, Mat outImg, Scalar matchColor, Scalar singlePointColor, List<MatOfByte> matchesMask, int flags)`
`void`	DescriptorMatcher.`knnMatch(Mat queryDescriptors, List<MatOfDMatch> matches, int k)`
`void`	DescriptorMatcher.`knnMatch(Mat queryDescriptors, List<MatOfDMatch> matches, int k, List<Mat> masks)`
`void`	DescriptorMatcher.`knnMatch(Mat queryDescriptors, List<MatOfDMatch> matches, int k, List<Mat> masks, boolean compactResult)`
`void`	DescriptorMatcher.`knnMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, int k)`	Finds the k best matches for each descriptor from a query set.
`void`	DescriptorMatcher.`knnMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, int k, Mat mask)`	Finds the k best matches for each descriptor from a query set.
`void`	DescriptorMatcher.`knnMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, int k, Mat mask, boolean compactResult)`	Finds the k best matches for each descriptor from a query set.
`void`	DescriptorMatcher.`match(Mat queryDescriptors, MatOfDMatch matches)`
`void`	DescriptorMatcher.`match(Mat queryDescriptors, MatOfDMatch matches, List<Mat> masks)`
`void`	DescriptorMatcher.`match(Mat queryDescriptors, Mat trainDescriptors, MatOfDMatch matches)`	Finds the best match for each descriptor from a query set.
`void`	DescriptorMatcher.`match(Mat queryDescriptors, Mat trainDescriptors, MatOfDMatch matches, Mat mask)`	Finds the best match for each descriptor from a query set.
`void`	DescriptorMatcher.`radiusMatch(Mat queryDescriptors, List<MatOfDMatch> matches, float maxDistance)`
`void`	DescriptorMatcher.`radiusMatch(Mat queryDescriptors, List<MatOfDMatch> matches, float maxDistance, List<Mat> masks)`
`void`	DescriptorMatcher.`radiusMatch(Mat queryDescriptors, List<MatOfDMatch> matches, float maxDistance, List<Mat> masks, boolean compactResult)`
`void`	DescriptorMatcher.`radiusMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, float maxDistance)`	For each query descriptor, finds the training descriptors not farther than the specified distance.
`void`	DescriptorMatcher.`radiusMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, float maxDistance, Mat mask)`	For each query descriptor, finds the training descriptors not farther than the specified distance.
`void`	DescriptorMatcher.`radiusMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, float maxDistance, Mat mask, boolean compactResult)`	For each query descriptor, finds the training descriptors not farther than the specified distance.
`void`	BOWImgDescriptorExtractor.`setVocabulary(Mat vocabulary)`	Sets a visual vocabulary.

Method parameters in org.opencv.features2d with type arguments of type Mat
Modifier and Type	Method	Description
`void`	DescriptorMatcher.`add(List<Mat> descriptors)`	Adds descriptors to train a CPU(trainDescCollectionis) or GPU(utrainDescCollectionis) descriptor collection.
`void`	Feature2D.`compute(List<Mat> images, List<MatOfKeyPoint> keypoints, List<Mat> descriptors)`
`void`	Feature2D.`detect(List<Mat> images, List<MatOfKeyPoint> keypoints)`
`void`	Feature2D.`detect(List<Mat> images, List<MatOfKeyPoint> keypoints, List<Mat> masks)`
`void`	DescriptorMatcher.`match(Mat queryDescriptors, MatOfDMatch matches, List<Mat> masks)`

Uses of Mat in org.opencv.highgui

Fields in org.opencv.highgui declared as Mat
Modifier and Type	Field	Description
`Mat`	ImageWindow.`img`

Methods in org.opencv.highgui with parameters of type Mat
Modifier and Type	Method	Description
`static void`	HighGui.`imshow(String winname, Mat img)`
`void`	ImageWindow.`setMat(Mat img)`
`static Image`	HighGui.`toBufferedImage(Mat m)`

Constructors in org.opencv.highgui with parameters of type Mat
Constructor	Description
`ImageWindow(String name, Mat img)`

Uses of Mat in org.opencv.img_hash

Methods in org.opencv.img_hash with parameters of type Mat
Modifier and Type	Method	Description
`static void`	Img_hash.`averageHash(Mat inputArr, Mat outputArr)`	Calculates img_hash::AverageHash in one call
`static void`	Img_hash.`blockMeanHash(Mat inputArr, Mat outputArr)`	Computes block mean hash of the input image
`static void`	Img_hash.`blockMeanHash(Mat inputArr, Mat outputArr, int mode)`	Computes block mean hash of the input image
`static void`	Img_hash.`colorMomentHash(Mat inputArr, Mat outputArr)`	Computes color moment hash of the input, the algorithm is come from the paper "Perceptual Hashing for Color Images Using Invariant Moments"
`double`	ImgHashBase.`compare(Mat hashOne, Mat hashTwo)`	Compare the hash value between inOne and inTwo
`void`	ImgHashBase.`compute(Mat inputArr, Mat outputArr)`	Computes hash of the input image
`static void`	Img_hash.`marrHildrethHash(Mat inputArr, Mat outputArr)`	Computes average hash value of the input image
`static void`	Img_hash.`marrHildrethHash(Mat inputArr, Mat outputArr, float alpha)`	Computes average hash value of the input image
`static void`	Img_hash.`marrHildrethHash(Mat inputArr, Mat outputArr, float alpha, float scale)`	Computes average hash value of the input image
`static void`	Img_hash.`pHash(Mat inputArr, Mat outputArr)`	Computes pHash value of the input image
`static void`	Img_hash.`radialVarianceHash(Mat inputArr, Mat outputArr)`	Computes radial variance hash of the input image
`static void`	Img_hash.`radialVarianceHash(Mat inputArr, Mat outputArr, double sigma)`	Computes radial variance hash of the input image
`static void`	Img_hash.`radialVarianceHash(Mat inputArr, Mat outputArr, double sigma, int numOfAngleLine)`	Computes radial variance hash of the input image

Uses of Mat in org.opencv.imgcodecs

Methods in org.opencv.imgcodecs that return Mat
Modifier and Type	Method	Description
`static Mat`	Imgcodecs.`imdecode(Mat buf, int flags)`	Reads an image from a buffer in memory.
`static Mat`	Imgcodecs.`imread(String filename)`	Loads an image from a file.
`static Mat`	Imgcodecs.`imread(String filename, int flags)`	Loads an image from a file.

Methods in org.opencv.imgcodecs with parameters of type Mat
Modifier and Type	Method	Description
`static Mat`	Imgcodecs.`imdecode(Mat buf, int flags)`	Reads an image from a buffer in memory.
`static boolean`	Imgcodecs.`imencode(String ext, Mat img, MatOfByte buf)`	Encodes an image into a memory buffer.
`static boolean`	Imgcodecs.`imencode(String ext, Mat img, MatOfByte buf, MatOfInt params)`	Encodes an image into a memory buffer.
`static boolean`	Imgcodecs.`imwrite(String filename, Mat img)`	Saves an image to a specified file.
`static boolean`	Imgcodecs.`imwrite(String filename, Mat img, MatOfInt params)`	Saves an image to a specified file.

Method parameters in org.opencv.imgcodecs with type arguments of type Mat
Modifier and Type	Method	Description
`static boolean`	Imgcodecs.`imreadmulti(String filename, List<Mat> mats)`	Loads a multi-page image from a file.
`static boolean`	Imgcodecs.`imreadmulti(String filename, List<Mat> mats, int flags)`	Loads a multi-page image from a file.
`static boolean`	Imgcodecs.`imreadmulti(String filename, List<Mat> mats, int start, int count)`	Loads a of images of a multi-page image from a file.
`static boolean`	Imgcodecs.`imreadmulti(String filename, List<Mat> mats, int start, int count, int flags)`	Loads a of images of a multi-page image from a file.
`static boolean`	Imgcodecs.`imwritemulti(String filename, List<Mat> img)`
`static boolean`	Imgcodecs.`imwritemulti(String filename, List<Mat> img, MatOfInt params)`

Uses of Mat in org.opencv.imgproc

Methods in org.opencv.imgproc that return Mat
Modifier and Type	Method	Description
`static Mat`	Imgproc.`getAffineTransform(MatOfPoint2f src, MatOfPoint2f dst)`
`static Mat`	Imgproc.`getGaborKernel(Size ksize, double sigma, double theta, double lambd, double gamma)`	Returns Gabor filter coefficients.
`static Mat`	Imgproc.`getGaborKernel(Size ksize, double sigma, double theta, double lambd, double gamma, double psi)`	Returns Gabor filter coefficients.
`static Mat`	Imgproc.`getGaborKernel(Size ksize, double sigma, double theta, double lambd, double gamma, double psi, int ktype)`	Returns Gabor filter coefficients.
`static Mat`	Imgproc.`getGaussianKernel(int ksize, double sigma)`	Returns Gaussian filter coefficients.
`static Mat`	Imgproc.`getGaussianKernel(int ksize, double sigma, int ktype)`	Returns Gaussian filter coefficients.
`static Mat`	Imgproc.`getPerspectiveTransform(Mat src, Mat dst)`	Calculates a perspective transform from four pairs of the corresponding points.
`static Mat`	Imgproc.`getPerspectiveTransform(Mat src, Mat dst, int solveMethod)`	Calculates a perspective transform from four pairs of the corresponding points.
`static Mat`	Imgproc.`getRotationMatrix2D(Point center, double angle, double scale)`	Calculates an affine matrix of 2D rotation.
`static Mat`	Imgproc.`getStructuringElement(int shape, Size ksize)`	Returns a structuring element of the specified size and shape for morphological operations.
`static Mat`	Imgproc.`getStructuringElement(int shape, Size ksize, Point anchor)`	Returns a structuring element of the specified size and shape for morphological operations.

Methods in org.opencv.imgproc with parameters of type Mat
Modifier and Type	Method	Description
`static void`	Imgproc.`accumulate(Mat src, Mat dst)`	Adds an image to the accumulator image.
`static void`	Imgproc.`accumulate(Mat src, Mat dst, Mat mask)`	Adds an image to the accumulator image.
`static void`	Imgproc.`accumulateProduct(Mat src1, Mat src2, Mat dst)`	Adds the per-element product of two input images to the accumulator image.
`static void`	Imgproc.`accumulateProduct(Mat src1, Mat src2, Mat dst, Mat mask)`	Adds the per-element product of two input images to the accumulator image.
`static void`	Imgproc.`accumulateSquare(Mat src, Mat dst)`	Adds the square of a source image to the accumulator image.
`static void`	Imgproc.`accumulateSquare(Mat src, Mat dst, Mat mask)`	Adds the square of a source image to the accumulator image.
`static void`	Imgproc.`accumulateWeighted(Mat src, Mat dst, double alpha)`	Updates a running average.
`static void`	Imgproc.`accumulateWeighted(Mat src, Mat dst, double alpha, Mat mask)`	Updates a running average.
`static void`	Imgproc.`adaptiveThreshold(Mat src, Mat dst, double maxValue, int adaptiveMethod, int thresholdType, int blockSize, double C)`	Applies an adaptive threshold to an array.
`void`	CLAHE.`apply(Mat src, Mat dst)`	Equalizes the histogram of a grayscale image using Contrast Limited Adaptive Histogram Equalization.
`static void`	Imgproc.`applyColorMap(Mat src, Mat dst, int colormap)`	Applies a GNU Octave/MATLAB equivalent colormap on a given image.
`static void`	Imgproc.`applyColorMap(Mat src, Mat dst, Mat userColor)`	Applies a user colormap on a given image.
`IntelligentScissorsMB`	IntelligentScissorsMB.`applyImage(Mat image)`	Specify input image and extract image features
`IntelligentScissorsMB`	IntelligentScissorsMB.`applyImageFeatures(Mat non_edge, Mat gradient_direction, Mat gradient_magnitude)`	Specify custom features of imput image Customized advanced variant of applyImage() call.
`IntelligentScissorsMB`	IntelligentScissorsMB.`applyImageFeatures(Mat non_edge, Mat gradient_direction, Mat gradient_magnitude, Mat image)`	Specify custom features of imput image Customized advanced variant of applyImage() call.
`static void`	Imgproc.`arrowedLine(Mat img, Point pt1, Point pt2, Scalar color)`	Draws a arrow segment pointing from the first point to the second one.
`static void`	Imgproc.`arrowedLine(Mat img, Point pt1, Point pt2, Scalar color, int thickness)`	Draws a arrow segment pointing from the first point to the second one.
`static void`	Imgproc.`arrowedLine(Mat img, Point pt1, Point pt2, Scalar color, int thickness, int line_type)`	Draws a arrow segment pointing from the first point to the second one.
`static void`	Imgproc.`arrowedLine(Mat img, Point pt1, Point pt2, Scalar color, int thickness, int line_type, int shift)`	Draws a arrow segment pointing from the first point to the second one.
`static void`	Imgproc.`arrowedLine(Mat img, Point pt1, Point pt2, Scalar color, int thickness, int line_type, int shift, double tipLength)`	Draws a arrow segment pointing from the first point to the second one.
`static void`	Imgproc.`bilateralFilter(Mat src, Mat dst, int d, double sigmaColor, double sigmaSpace)`	Applies the bilateral filter to an image.
`static void`	Imgproc.`bilateralFilter(Mat src, Mat dst, int d, double sigmaColor, double sigmaSpace, int borderType)`	Applies the bilateral filter to an image.
`static void`	Imgproc.`blendLinear(Mat src1, Mat src2, Mat weights1, Mat weights2, Mat dst)`
`static void`	Imgproc.`blur(Mat src, Mat dst, Size ksize)`	Blurs an image using the normalized box filter.
`static void`	Imgproc.`blur(Mat src, Mat dst, Size ksize, Point anchor)`	Blurs an image using the normalized box filter.
`static void`	Imgproc.`blur(Mat src, Mat dst, Size ksize, Point anchor, int borderType)`	Blurs an image using the normalized box filter.
`static Rect`	Imgproc.`boundingRect(Mat array)`	Calculates the up-right bounding rectangle of a point set or non-zero pixels of gray-scale image.
`static void`	Imgproc.`boxFilter(Mat src, Mat dst, int ddepth, Size ksize)`	Blurs an image using the box filter.
`static void`	Imgproc.`boxFilter(Mat src, Mat dst, int ddepth, Size ksize, Point anchor)`	Blurs an image using the box filter.
`static void`	Imgproc.`boxFilter(Mat src, Mat dst, int ddepth, Size ksize, Point anchor, boolean normalize)`	Blurs an image using the box filter.
`static void`	Imgproc.`boxFilter(Mat src, Mat dst, int ddepth, Size ksize, Point anchor, boolean normalize, int borderType)`	Blurs an image using the box filter.
`static void`	Imgproc.`boxPoints(RotatedRect box, Mat points)`	Finds the four vertices of a rotated rect.
`static void`	Imgproc.`calcBackProject(List<Mat> images, MatOfInt channels, Mat hist, Mat dst, MatOfFloat ranges, double scale)`
`static void`	Imgproc.`calcHist(List<Mat> images, MatOfInt channels, Mat mask, Mat hist, MatOfInt histSize, MatOfFloat ranges)`
`static void`	Imgproc.`calcHist(List<Mat> images, MatOfInt channels, Mat mask, Mat hist, MatOfInt histSize, MatOfFloat ranges, boolean accumulate)`
`static void`	Imgproc.`Canny(Mat image, Mat edges, double threshold1, double threshold2)`	Finds edges in an image using the Canny algorithm CITE: Canny86 .
`static void`	Imgproc.`Canny(Mat image, Mat edges, double threshold1, double threshold2, int apertureSize)`	Finds edges in an image using the Canny algorithm CITE: Canny86 .
`static void`	Imgproc.`Canny(Mat image, Mat edges, double threshold1, double threshold2, int apertureSize, boolean L2gradient)`	Finds edges in an image using the Canny algorithm CITE: Canny86 .
`static void`	Imgproc.`Canny(Mat dx, Mat dy, Mat edges, double threshold1, double threshold2)`	\overload Finds edges in an image using the Canny algorithm with custom image gradient.
`static void`	Imgproc.`Canny(Mat dx, Mat dy, Mat edges, double threshold1, double threshold2, boolean L2gradient)`	\overload Finds edges in an image using the Canny algorithm with custom image gradient.
`static void`	Imgproc.`circle(Mat img, Point center, int radius, Scalar color)`	Draws a circle.
`static void`	Imgproc.`circle(Mat img, Point center, int radius, Scalar color, int thickness)`	Draws a circle.
`static void`	Imgproc.`circle(Mat img, Point center, int radius, Scalar color, int thickness, int lineType)`	Draws a circle.
`static void`	Imgproc.`circle(Mat img, Point center, int radius, Scalar color, int thickness, int lineType, int shift)`	Draws a circle.
`static double`	Imgproc.`compareHist(Mat H1, Mat H2, int method)`	Compares two histograms.
`int`	LineSegmentDetector.`compareSegments(Size size, Mat lines1, Mat lines2)`	Draws two groups of lines in blue and red, counting the non overlapping (mismatching) pixels.
`int`	LineSegmentDetector.`compareSegments(Size size, Mat lines1, Mat lines2, Mat image)`	Draws two groups of lines in blue and red, counting the non overlapping (mismatching) pixels.
`static int`	Imgproc.`connectedComponents(Mat image, Mat labels)`
`static int`	Imgproc.`connectedComponents(Mat image, Mat labels, int connectivity)`
`static int`	Imgproc.`connectedComponents(Mat image, Mat labels, int connectivity, int ltype)`
`static int`	Imgproc.`connectedComponentsWithAlgorithm(Mat image, Mat labels, int connectivity, int ltype, int ccltype)`	computes the connected components labeled image of boolean image image with 4 or 8 way connectivity - returns N, the total number of labels [0, N-1] where 0 represents the background label.
`static int`	Imgproc.`connectedComponentsWithStats(Mat image, Mat labels, Mat stats, Mat centroids)`
`static int`	Imgproc.`connectedComponentsWithStats(Mat image, Mat labels, Mat stats, Mat centroids, int connectivity)`
`static int`	Imgproc.`connectedComponentsWithStats(Mat image, Mat labels, Mat stats, Mat centroids, int connectivity, int ltype)`
`static int`	Imgproc.`connectedComponentsWithStatsWithAlgorithm(Mat image, Mat labels, Mat stats, Mat centroids, int connectivity, int ltype, int ccltype)`	computes the connected components labeled image of boolean image and also produces a statistics output for each label image with 4 or 8 way connectivity - returns N, the total number of labels [0, N-1] where 0 represents the background label.
`static double`	Imgproc.`contourArea(Mat contour)`	Calculates a contour area.
`static double`	Imgproc.`contourArea(Mat contour, boolean oriented)`	Calculates a contour area.
`static void`	Imgproc.`convertMaps(Mat map1, Mat map2, Mat dstmap1, Mat dstmap2, int dstmap1type)`	Converts image transformation maps from one representation to another.
`static void`	Imgproc.`convertMaps(Mat map1, Mat map2, Mat dstmap1, Mat dstmap2, int dstmap1type, boolean nninterpolation)`	Converts image transformation maps from one representation to another.
`static void`	Imgproc.`cornerEigenValsAndVecs(Mat src, Mat dst, int blockSize, int ksize)`	Calculates eigenvalues and eigenvectors of image blocks for corner detection.
`static void`	Imgproc.`cornerEigenValsAndVecs(Mat src, Mat dst, int blockSize, int ksize, int borderType)`	Calculates eigenvalues and eigenvectors of image blocks for corner detection.
`static void`	Imgproc.`cornerHarris(Mat src, Mat dst, int blockSize, int ksize, double k)`	Harris corner detector.
`static void`	Imgproc.`cornerHarris(Mat src, Mat dst, int blockSize, int ksize, double k, int borderType)`	Harris corner detector.
`static void`	Imgproc.`cornerMinEigenVal(Mat src, Mat dst, int blockSize)`	Calculates the minimal eigenvalue of gradient matrices for corner detection.
`static void`	Imgproc.`cornerMinEigenVal(Mat src, Mat dst, int blockSize, int ksize)`	Calculates the minimal eigenvalue of gradient matrices for corner detection.
`static void`	Imgproc.`cornerMinEigenVal(Mat src, Mat dst, int blockSize, int ksize, int borderType)`	Calculates the minimal eigenvalue of gradient matrices for corner detection.
`static void`	Imgproc.`cornerSubPix(Mat image, Mat corners, Size winSize, Size zeroZone, TermCriteria criteria)`	Refines the corner locations.
`static void`	Imgproc.`createHanningWindow(Mat dst, Size winSize, int type)`	This function computes a Hanning window coefficients in two dimensions.
`static void`	Imgproc.`cvtColor(Mat src, Mat dst, int code)`	Converts an image from one color space to another.
`static void`	Imgproc.`cvtColor(Mat src, Mat dst, int code, int dstCn)`	Converts an image from one color space to another.
`static void`	Imgproc.`cvtColorTwoPlane(Mat src1, Mat src2, Mat dst, int code)`	Converts an image from one color space to another where the source image is stored in two planes.
`static void`	Imgproc.`demosaicing(Mat src, Mat dst, int code)`	main function for all demosaicing processes
`static void`	Imgproc.`demosaicing(Mat src, Mat dst, int code, int dstCn)`	main function for all demosaicing processes
`void`	GeneralizedHough.`detect(Mat image, Mat positions)`
`void`	GeneralizedHough.`detect(Mat image, Mat positions, Mat votes)`
`void`	GeneralizedHough.`detect(Mat edges, Mat dx, Mat dy, Mat positions)`
`void`	GeneralizedHough.`detect(Mat edges, Mat dx, Mat dy, Mat positions, Mat votes)`
`void`	LineSegmentDetector.`detect(Mat image, Mat lines)`	Finds lines in the input image.
`void`	LineSegmentDetector.`detect(Mat image, Mat lines, Mat width)`	Finds lines in the input image.
`void`	LineSegmentDetector.`detect(Mat image, Mat lines, Mat width, Mat prec)`	Finds lines in the input image.
`void`	LineSegmentDetector.`detect(Mat image, Mat lines, Mat width, Mat prec, Mat nfa)`	Finds lines in the input image.
`static void`	Imgproc.`dilate(Mat src, Mat dst, Mat kernel)`	Dilates an image by using a specific structuring element.
`static void`	Imgproc.`dilate(Mat src, Mat dst, Mat kernel, Point anchor)`	Dilates an image by using a specific structuring element.
`static void`	Imgproc.`dilate(Mat src, Mat dst, Mat kernel, Point anchor, int iterations)`	Dilates an image by using a specific structuring element.
`static void`	Imgproc.`dilate(Mat src, Mat dst, Mat kernel, Point anchor, int iterations, int borderType)`	Dilates an image by using a specific structuring element.
`static void`	Imgproc.`dilate(Mat src, Mat dst, Mat kernel, Point anchor, int iterations, int borderType, Scalar borderValue)`	Dilates an image by using a specific structuring element.
`static void`	Imgproc.`distanceTransform(Mat src, Mat dst, int distanceType, int maskSize)`
`static void`	Imgproc.`distanceTransform(Mat src, Mat dst, int distanceType, int maskSize, int dstType)`
`static void`	Imgproc.`distanceTransformWithLabels(Mat src, Mat dst, Mat labels, int distanceType, int maskSize)`	Calculates the distance to the closest zero pixel for each pixel of the source image.
`static void`	Imgproc.`distanceTransformWithLabels(Mat src, Mat dst, Mat labels, int distanceType, int maskSize, int labelType)`	Calculates the distance to the closest zero pixel for each pixel of the source image.
`static void`	Imgproc.`divSpectrums(Mat a, Mat b, Mat c, int flags)`	Performs the per-element division of the first Fourier spectrum by the second Fourier spectrum.
`static void`	Imgproc.`divSpectrums(Mat a, Mat b, Mat c, int flags, boolean conjB)`	Performs the per-element division of the first Fourier spectrum by the second Fourier spectrum.
`static void`	Imgproc.`drawContours(Mat image, List<MatOfPoint> contours, int contourIdx, Scalar color)`	Draws contours outlines or filled contours.
`static void`	Imgproc.`drawContours(Mat image, List<MatOfPoint> contours, int contourIdx, Scalar color, int thickness)`	Draws contours outlines or filled contours.
`static void`	Imgproc.`drawContours(Mat image, List<MatOfPoint> contours, int contourIdx, Scalar color, int thickness, int lineType)`	Draws contours outlines or filled contours.
`static void`	Imgproc.`drawContours(Mat image, List<MatOfPoint> contours, int contourIdx, Scalar color, int thickness, int lineType, Mat hierarchy)`	Draws contours outlines or filled contours.
`static void`	Imgproc.`drawContours(Mat image, List<MatOfPoint> contours, int contourIdx, Scalar color, int thickness, int lineType, Mat hierarchy, int maxLevel)`	Draws contours outlines or filled contours.
`static void`	Imgproc.`drawContours(Mat image, List<MatOfPoint> contours, int contourIdx, Scalar color, int thickness, int lineType, Mat hierarchy, int maxLevel, Point offset)`	Draws contours outlines or filled contours.
`static void`	Imgproc.`drawMarker(Mat img, Point position, Scalar color)`	Draws a marker on a predefined position in an image.
`static void`	Imgproc.`drawMarker(Mat img, Point position, Scalar color, int markerType)`	Draws a marker on a predefined position in an image.
`static void`	Imgproc.`drawMarker(Mat img, Point position, Scalar color, int markerType, int markerSize)`	Draws a marker on a predefined position in an image.
`static void`	Imgproc.`drawMarker(Mat img, Point position, Scalar color, int markerType, int markerSize, int thickness)`	Draws a marker on a predefined position in an image.
`static void`	Imgproc.`drawMarker(Mat img, Point position, Scalar color, int markerType, int markerSize, int thickness, int line_type)`	Draws a marker on a predefined position in an image.
`void`	LineSegmentDetector.`drawSegments(Mat image, Mat lines)`	Draws the line segments on a given image.
`static void`	Imgproc.`ellipse(Mat img, Point center, Size axes, double angle, double startAngle, double endAngle, Scalar color)`	Draws a simple or thick elliptic arc or fills an ellipse sector.
`static void`	Imgproc.`ellipse(Mat img, Point center, Size axes, double angle, double startAngle, double endAngle, Scalar color, int thickness)`	Draws a simple or thick elliptic arc or fills an ellipse sector.
`static void`	Imgproc.`ellipse(Mat img, Point center, Size axes, double angle, double startAngle, double endAngle, Scalar color, int thickness, int lineType)`	Draws a simple or thick elliptic arc or fills an ellipse sector.
`static void`	Imgproc.`ellipse(Mat img, Point center, Size axes, double angle, double startAngle, double endAngle, Scalar color, int thickness, int lineType, int shift)`	Draws a simple or thick elliptic arc or fills an ellipse sector.
`static void`	Imgproc.`ellipse(Mat img, RotatedRect box, Scalar color)`
`static void`	Imgproc.`ellipse(Mat img, RotatedRect box, Scalar color, int thickness)`
`static void`	Imgproc.`ellipse(Mat img, RotatedRect box, Scalar color, int thickness, int lineType)`
`static float`	Imgproc.`EMD(Mat signature1, Mat signature2, int distType)`	Computes the "minimal work" distance between two weighted point configurations.
`static float`	Imgproc.`EMD(Mat signature1, Mat signature2, int distType, Mat cost)`	Computes the "minimal work" distance between two weighted point configurations.
`static float`	Imgproc.`EMD(Mat signature1, Mat signature2, int distType, Mat cost, Mat flow)`	Computes the "minimal work" distance between two weighted point configurations.
`static void`	Imgproc.`equalizeHist(Mat src, Mat dst)`	Equalizes the histogram of a grayscale image.
`static void`	Imgproc.`erode(Mat src, Mat dst, Mat kernel)`	Erodes an image by using a specific structuring element.
`static void`	Imgproc.`erode(Mat src, Mat dst, Mat kernel, Point anchor)`	Erodes an image by using a specific structuring element.
`static void`	Imgproc.`erode(Mat src, Mat dst, Mat kernel, Point anchor, int iterations)`	Erodes an image by using a specific structuring element.
`static void`	Imgproc.`erode(Mat src, Mat dst, Mat kernel, Point anchor, int iterations, int borderType)`	Erodes an image by using a specific structuring element.
`static void`	Imgproc.`erode(Mat src, Mat dst, Mat kernel, Point anchor, int iterations, int borderType, Scalar borderValue)`	Erodes an image by using a specific structuring element.
`static void`	Imgproc.`fillConvexPoly(Mat img, MatOfPoint points, Scalar color)`	Fills a convex polygon.
`static void`	Imgproc.`fillConvexPoly(Mat img, MatOfPoint points, Scalar color, int lineType)`	Fills a convex polygon.
`static void`	Imgproc.`fillConvexPoly(Mat img, MatOfPoint points, Scalar color, int lineType, int shift)`	Fills a convex polygon.
`static void`	Imgproc.`fillPoly(Mat img, List<MatOfPoint> pts, Scalar color)`	Fills the area bounded by one or more polygons.
`static void`	Imgproc.`fillPoly(Mat img, List<MatOfPoint> pts, Scalar color, int lineType)`	Fills the area bounded by one or more polygons.
`static void`	Imgproc.`fillPoly(Mat img, List<MatOfPoint> pts, Scalar color, int lineType, int shift)`	Fills the area bounded by one or more polygons.
`static void`	Imgproc.`fillPoly(Mat img, List<MatOfPoint> pts, Scalar color, int lineType, int shift, Point offset)`	Fills the area bounded by one or more polygons.
`static void`	Imgproc.`filter2D(Mat src, Mat dst, int ddepth, Mat kernel)`	Convolves an image with the kernel.
`static void`	Imgproc.`filter2D(Mat src, Mat dst, int ddepth, Mat kernel, Point anchor)`	Convolves an image with the kernel.
`static void`	Imgproc.`filter2D(Mat src, Mat dst, int ddepth, Mat kernel, Point anchor, double delta)`	Convolves an image with the kernel.
`static void`	Imgproc.`filter2D(Mat src, Mat dst, int ddepth, Mat kernel, Point anchor, double delta, int borderType)`	Convolves an image with the kernel.
`static void`	Imgproc.`findContours(Mat image, List<MatOfPoint> contours, Mat hierarchy, int mode, int method)`	Finds contours in a binary image.
`static void`	Imgproc.`findContours(Mat image, List<MatOfPoint> contours, Mat hierarchy, int mode, int method, Point offset)`	Finds contours in a binary image.
`static RotatedRect`	Imgproc.`fitEllipseAMS(Mat points)`	Fits an ellipse around a set of 2D points.
`static RotatedRect`	Imgproc.`fitEllipseDirect(Mat points)`	Fits an ellipse around a set of 2D points.
`static void`	Imgproc.`fitLine(Mat points, Mat line, int distType, double param, double reps, double aeps)`	Fits a line to a 2D or 3D point set.
`static int`	Imgproc.`floodFill(Mat image, Mat mask, Point seedPoint, Scalar newVal)`	Fills a connected component with the given color.
`static int`	Imgproc.`floodFill(Mat image, Mat mask, Point seedPoint, Scalar newVal, Rect rect)`	Fills a connected component with the given color.
`static int`	Imgproc.`floodFill(Mat image, Mat mask, Point seedPoint, Scalar newVal, Rect rect, Scalar loDiff)`	Fills a connected component with the given color.
`static int`	Imgproc.`floodFill(Mat image, Mat mask, Point seedPoint, Scalar newVal, Rect rect, Scalar loDiff, Scalar upDiff)`	Fills a connected component with the given color.
`static int`	Imgproc.`floodFill(Mat image, Mat mask, Point seedPoint, Scalar newVal, Rect rect, Scalar loDiff, Scalar upDiff, int flags)`	Fills a connected component with the given color.
`static void`	Imgproc.`GaussianBlur(Mat src, Mat dst, Size ksize, double sigmaX)`	Blurs an image using a Gaussian filter.
`static void`	Imgproc.`GaussianBlur(Mat src, Mat dst, Size ksize, double sigmaX, double sigmaY)`	Blurs an image using a Gaussian filter.
`static void`	Imgproc.`GaussianBlur(Mat src, Mat dst, Size ksize, double sigmaX, double sigmaY, int borderType)`	Blurs an image using a Gaussian filter.
`void`	IntelligentScissorsMB.`getContour(Point targetPt, Mat contour)`	Extracts optimal contour for the given target point on the image Note: buildMap() must be called before this call
`void`	IntelligentScissorsMB.`getContour(Point targetPt, Mat contour, boolean backward)`	Extracts optimal contour for the given target point on the image Note: buildMap() must be called before this call
`static void`	Imgproc.`getDerivKernels(Mat kx, Mat ky, int dx, int dy, int ksize)`	Returns filter coefficients for computing spatial image derivatives.
`static void`	Imgproc.`getDerivKernels(Mat kx, Mat ky, int dx, int dy, int ksize, boolean normalize)`	Returns filter coefficients for computing spatial image derivatives.
`static void`	Imgproc.`getDerivKernels(Mat kx, Mat ky, int dx, int dy, int ksize, boolean normalize, int ktype)`	Returns filter coefficients for computing spatial image derivatives.
`static Mat`	Imgproc.`getPerspectiveTransform(Mat src, Mat dst)`	Calculates a perspective transform from four pairs of the corresponding points.
`static Mat`	Imgproc.`getPerspectiveTransform(Mat src, Mat dst, int solveMethod)`	Calculates a perspective transform from four pairs of the corresponding points.
`static void`	Imgproc.`getRectSubPix(Mat image, Size patchSize, Point center, Mat patch)`	Retrieves a pixel rectangle from an image with sub-pixel accuracy.
`static void`	Imgproc.`getRectSubPix(Mat image, Size patchSize, Point center, Mat patch, int patchType)`	Retrieves a pixel rectangle from an image with sub-pixel accuracy.
`static void`	Imgproc.`goodFeaturesToTrack(Mat image, MatOfPoint corners, int maxCorners, double qualityLevel, double minDistance)`	Determines strong corners on an image.
`static void`	Imgproc.`goodFeaturesToTrack(Mat image, MatOfPoint corners, int maxCorners, double qualityLevel, double minDistance, Mat mask)`	Determines strong corners on an image.
`static void`	Imgproc.`goodFeaturesToTrack(Mat image, MatOfPoint corners, int maxCorners, double qualityLevel, double minDistance, Mat mask, int blockSize)`	Determines strong corners on an image.
`static void`	Imgproc.`goodFeaturesToTrack(Mat image, MatOfPoint corners, int maxCorners, double qualityLevel, double minDistance, Mat mask, int blockSize, boolean useHarrisDetector)`	Determines strong corners on an image.
`static void`	Imgproc.`goodFeaturesToTrack(Mat image, MatOfPoint corners, int maxCorners, double qualityLevel, double minDistance, Mat mask, int blockSize, boolean useHarrisDetector, double k)`	Determines strong corners on an image.
`static void`	Imgproc.`goodFeaturesToTrack(Mat image, MatOfPoint corners, int maxCorners, double qualityLevel, double minDistance, Mat mask, int blockSize, int gradientSize)`
`static void`	Imgproc.`goodFeaturesToTrack(Mat image, MatOfPoint corners, int maxCorners, double qualityLevel, double minDistance, Mat mask, int blockSize, int gradientSize, boolean useHarrisDetector)`
`static void`	Imgproc.`goodFeaturesToTrack(Mat image, MatOfPoint corners, int maxCorners, double qualityLevel, double minDistance, Mat mask, int blockSize, int gradientSize, boolean useHarrisDetector, double k)`
`static void`	Imgproc.`goodFeaturesToTrackWithQuality(Mat image, Mat corners, int maxCorners, double qualityLevel, double minDistance, Mat mask, Mat cornersQuality)`	Same as above, but returns also quality measure of the detected corners.
`static void`	Imgproc.`goodFeaturesToTrackWithQuality(Mat image, Mat corners, int maxCorners, double qualityLevel, double minDistance, Mat mask, Mat cornersQuality, int blockSize)`	Same as above, but returns also quality measure of the detected corners.
`static void`	Imgproc.`goodFeaturesToTrackWithQuality(Mat image, Mat corners, int maxCorners, double qualityLevel, double minDistance, Mat mask, Mat cornersQuality, int blockSize, int gradientSize)`	Same as above, but returns also quality measure of the detected corners.
`static void`	Imgproc.`goodFeaturesToTrackWithQuality(Mat image, Mat corners, int maxCorners, double qualityLevel, double minDistance, Mat mask, Mat cornersQuality, int blockSize, int gradientSize, boolean useHarrisDetector)`	Same as above, but returns also quality measure of the detected corners.
`static void`	Imgproc.`goodFeaturesToTrackWithQuality(Mat image, Mat corners, int maxCorners, double qualityLevel, double minDistance, Mat mask, Mat cornersQuality, int blockSize, int gradientSize, boolean useHarrisDetector, double k)`	Same as above, but returns also quality measure of the detected corners.
`static void`	Imgproc.`grabCut(Mat img, Mat mask, Rect rect, Mat bgdModel, Mat fgdModel, int iterCount)`	Runs the GrabCut algorithm.
`static void`	Imgproc.`grabCut(Mat img, Mat mask, Rect rect, Mat bgdModel, Mat fgdModel, int iterCount, int mode)`	Runs the GrabCut algorithm.
`static void`	Imgproc.`HoughCircles(Mat image, Mat circles, int method, double dp, double minDist)`	Finds circles in a grayscale image using the Hough transform.
`static void`	Imgproc.`HoughCircles(Mat image, Mat circles, int method, double dp, double minDist, double param1)`	Finds circles in a grayscale image using the Hough transform.
`static void`	Imgproc.`HoughCircles(Mat image, Mat circles, int method, double dp, double minDist, double param1, double param2)`	Finds circles in a grayscale image using the Hough transform.
`static void`	Imgproc.`HoughCircles(Mat image, Mat circles, int method, double dp, double minDist, double param1, double param2, int minRadius)`	Finds circles in a grayscale image using the Hough transform.
`static void`	Imgproc.`HoughCircles(Mat image, Mat circles, int method, double dp, double minDist, double param1, double param2, int minRadius, int maxRadius)`	Finds circles in a grayscale image using the Hough transform.
`static void`	Imgproc.`HoughLines(Mat image, Mat lines, double rho, double theta, int threshold)`	Finds lines in a binary image using the standard Hough transform.
`static void`	Imgproc.`HoughLines(Mat image, Mat lines, double rho, double theta, int threshold, double srn)`	Finds lines in a binary image using the standard Hough transform.
`static void`	Imgproc.`HoughLines(Mat image, Mat lines, double rho, double theta, int threshold, double srn, double stn)`	Finds lines in a binary image using the standard Hough transform.
`static void`	Imgproc.`HoughLines(Mat image, Mat lines, double rho, double theta, int threshold, double srn, double stn, double min_theta)`	Finds lines in a binary image using the standard Hough transform.
`static void`	Imgproc.`HoughLines(Mat image, Mat lines, double rho, double theta, int threshold, double srn, double stn, double min_theta, double max_theta)`	Finds lines in a binary image using the standard Hough transform.
`static void`	Imgproc.`HoughLinesP(Mat image, Mat lines, double rho, double theta, int threshold)`	Finds line segments in a binary image using the probabilistic Hough transform.
`static void`	Imgproc.`HoughLinesP(Mat image, Mat lines, double rho, double theta, int threshold, double minLineLength)`	Finds line segments in a binary image using the probabilistic Hough transform.
`static void`	Imgproc.`HoughLinesP(Mat image, Mat lines, double rho, double theta, int threshold, double minLineLength, double maxLineGap)`	Finds line segments in a binary image using the probabilistic Hough transform.
`static void`	Imgproc.`HoughLinesPointSet(Mat point, Mat lines, int lines_max, int threshold, double min_rho, double max_rho, double rho_step, double min_theta, double max_theta, double theta_step)`	Finds lines in a set of points using the standard Hough transform.
`static void`	Imgproc.`HoughLinesWithAccumulator(Mat image, Mat lines, double rho, double theta, int threshold)`	Finds lines in a binary image using the standard Hough transform and get accumulator.
`static void`	Imgproc.`HoughLinesWithAccumulator(Mat image, Mat lines, double rho, double theta, int threshold, double srn)`	Finds lines in a binary image using the standard Hough transform and get accumulator.
`static void`	Imgproc.`HoughLinesWithAccumulator(Mat image, Mat lines, double rho, double theta, int threshold, double srn, double stn)`	Finds lines in a binary image using the standard Hough transform and get accumulator.
`static void`	Imgproc.`HoughLinesWithAccumulator(Mat image, Mat lines, double rho, double theta, int threshold, double srn, double stn, double min_theta)`	Finds lines in a binary image using the standard Hough transform and get accumulator.
`static void`	Imgproc.`HoughLinesWithAccumulator(Mat image, Mat lines, double rho, double theta, int threshold, double srn, double stn, double min_theta, double max_theta)`	Finds lines in a binary image using the standard Hough transform and get accumulator.
`static void`	Imgproc.`HuMoments(Moments m, Mat hu)`
`static void`	Imgproc.`integral(Mat src, Mat sum)`
`static void`	Imgproc.`integral(Mat src, Mat sum, int sdepth)`
`static void`	Imgproc.`integral2(Mat src, Mat sum, Mat sqsum)`
`static void`	Imgproc.`integral2(Mat src, Mat sum, Mat sqsum, int sdepth)`
`static void`	Imgproc.`integral2(Mat src, Mat sum, Mat sqsum, int sdepth, int sqdepth)`
`static void`	Imgproc.`integral3(Mat src, Mat sum, Mat sqsum, Mat tilted)`	Calculates the integral of an image.
`static void`	Imgproc.`integral3(Mat src, Mat sum, Mat sqsum, Mat tilted, int sdepth)`	Calculates the integral of an image.
`static void`	Imgproc.`integral3(Mat src, Mat sum, Mat sqsum, Mat tilted, int sdepth, int sqdepth)`	Calculates the integral of an image.
`static float`	Imgproc.`intersectConvexConvex(Mat p1, Mat p2, Mat p12)`	Finds intersection of two convex polygons
`static float`	Imgproc.`intersectConvexConvex(Mat p1, Mat p2, Mat p12, boolean handleNested)`	Finds intersection of two convex polygons
`static void`	Imgproc.`invertAffineTransform(Mat M, Mat iM)`	Inverts an affine transformation.
`static void`	Imgproc.`Laplacian(Mat src, Mat dst, int ddepth)`	Calculates the Laplacian of an image.
`static void`	Imgproc.`Laplacian(Mat src, Mat dst, int ddepth, int ksize)`	Calculates the Laplacian of an image.
`static void`	Imgproc.`Laplacian(Mat src, Mat dst, int ddepth, int ksize, double scale)`	Calculates the Laplacian of an image.
`static void`	Imgproc.`Laplacian(Mat src, Mat dst, int ddepth, int ksize, double scale, double delta)`	Calculates the Laplacian of an image.
`static void`	Imgproc.`Laplacian(Mat src, Mat dst, int ddepth, int ksize, double scale, double delta, int borderType)`	Calculates the Laplacian of an image.
`static void`	Imgproc.`line(Mat img, Point pt1, Point pt2, Scalar color)`	Draws a line segment connecting two points.
`static void`	Imgproc.`line(Mat img, Point pt1, Point pt2, Scalar color, int thickness)`	Draws a line segment connecting two points.
`static void`	Imgproc.`line(Mat img, Point pt1, Point pt2, Scalar color, int thickness, int lineType)`	Draws a line segment connecting two points.
`static void`	Imgproc.`line(Mat img, Point pt1, Point pt2, Scalar color, int thickness, int lineType, int shift)`	Draws a line segment connecting two points.
`static void`	Imgproc.`linearPolar(Mat src, Mat dst, Point center, double maxRadius, int flags)`	Deprecated. This function produces same result as cv::warpPolar(src, dst, src.size(), center, maxRadius, flags) Transform the source image using the following transformation (See REF: polar_remaps_reference_image "Polar remaps reference image c)"): \(\begin{array}{l} dst( \rho , \phi ) = src(x,y) \\ dst.size() \leftarrow src.size() \end{array}\) where \(\begin{array}{l} I = (dx,dy) = (x - center.x,y - center.y) \\ \rho = Kmag \cdot \texttt{magnitude} (I) ,\\ \phi = angle \cdot \texttt{angle} (I) \end{array}\) and \(\begin{array}{l} Kx = src.cols / maxRadius \\ Ky = src.rows / 2\Pi \end{array}\)
`static void`	Imgproc.`logPolar(Mat src, Mat dst, Point center, double M, int flags)`	Deprecated. This function produces same result as cv::warpPolar(src, dst, src.size(), center, maxRadius, flags+WARP_POLAR_LOG); Transform the source image using the following transformation (See REF: polar_remaps_reference_image "Polar remaps reference image d)"): \(\begin{array}{l} dst( \rho , \phi ) = src(x,y) \\ dst.size() \leftarrow src.size() \end{array}\) where \(\begin{array}{l} I = (dx,dy) = (x - center.x,y - center.y) \\ \rho = M \cdot log_e(\texttt{magnitude} (I)) ,\\ \phi = Kangle \cdot \texttt{angle} (I) \\ \end{array}\) and \(\begin{array}{l} M = src.cols / log_e(maxRadius) \\ Kangle = src.rows / 2\Pi \\ \end{array}\) The function emulates the human "foveal" vision and can be used for fast scale and rotation-invariant template matching, for object tracking and so forth.
`static double`	Imgproc.`matchShapes(Mat contour1, Mat contour2, int method, double parameter)`	Compares two shapes.
`static void`	Imgproc.`matchTemplate(Mat image, Mat templ, Mat result, int method)`	Compares a template against overlapped image regions.
`static void`	Imgproc.`matchTemplate(Mat image, Mat templ, Mat result, int method, Mat mask)`	Compares a template against overlapped image regions.
`static void`	Imgproc.`medianBlur(Mat src, Mat dst, int ksize)`	Blurs an image using the median filter.
`static double`	Imgproc.`minEnclosingTriangle(Mat points, Mat triangle)`	Finds a triangle of minimum area enclosing a 2D point set and returns its area.
`static Moments`	Imgproc.`moments(Mat array)`	Calculates all of the moments up to the third order of a polygon or rasterized shape.
`static Moments`	Imgproc.`moments(Mat array, boolean binaryImage)`	Calculates all of the moments up to the third order of a polygon or rasterized shape.
`static void`	Imgproc.`morphologyEx(Mat src, Mat dst, int op, Mat kernel)`	Performs advanced morphological transformations.
`static void`	Imgproc.`morphologyEx(Mat src, Mat dst, int op, Mat kernel, Point anchor)`	Performs advanced morphological transformations.
`static void`	Imgproc.`morphologyEx(Mat src, Mat dst, int op, Mat kernel, Point anchor, int iterations)`	Performs advanced morphological transformations.
`static void`	Imgproc.`morphologyEx(Mat src, Mat dst, int op, Mat kernel, Point anchor, int iterations, int borderType)`	Performs advanced morphological transformations.
`static void`	Imgproc.`morphologyEx(Mat src, Mat dst, int op, Mat kernel, Point anchor, int iterations, int borderType, Scalar borderValue)`	Performs advanced morphological transformations.
`static Point`	Imgproc.`phaseCorrelate(Mat src1, Mat src2)`	The function is used to detect translational shifts that occur between two images.
`static Point`	Imgproc.`phaseCorrelate(Mat src1, Mat src2, Mat window)`	The function is used to detect translational shifts that occur between two images.
`static Point`	Imgproc.`phaseCorrelate(Mat src1, Mat src2, Mat window, double[] response)`	The function is used to detect translational shifts that occur between two images.
`static void`	Imgproc.`polylines(Mat img, List<MatOfPoint> pts, boolean isClosed, Scalar color)`	Draws several polygonal curves.
`static void`	Imgproc.`polylines(Mat img, List<MatOfPoint> pts, boolean isClosed, Scalar color, int thickness)`	Draws several polygonal curves.
`static void`	Imgproc.`polylines(Mat img, List<MatOfPoint> pts, boolean isClosed, Scalar color, int thickness, int lineType)`	Draws several polygonal curves.
`static void`	Imgproc.`polylines(Mat img, List<MatOfPoint> pts, boolean isClosed, Scalar color, int thickness, int lineType, int shift)`	Draws several polygonal curves.
`static void`	Imgproc.`preCornerDetect(Mat src, Mat dst, int ksize)`	Calculates a feature map for corner detection.
`static void`	Imgproc.`preCornerDetect(Mat src, Mat dst, int ksize, int borderType)`	Calculates a feature map for corner detection.
`static void`	Imgproc.`putText(Mat img, String text, Point org, int fontFace, double fontScale, Scalar color)`	Draws a text string.
`static void`	Imgproc.`putText(Mat img, String text, Point org, int fontFace, double fontScale, Scalar color, int thickness)`	Draws a text string.
`static void`	Imgproc.`putText(Mat img, String text, Point org, int fontFace, double fontScale, Scalar color, int thickness, int lineType)`	Draws a text string.
`static void`	Imgproc.`putText(Mat img, String text, Point org, int fontFace, double fontScale, Scalar color, int thickness, int lineType, boolean bottomLeftOrigin)`	Draws a text string.
`static void`	Imgproc.`pyrDown(Mat src, Mat dst)`	Blurs an image and downsamples it.
`static void`	Imgproc.`pyrDown(Mat src, Mat dst, Size dstsize)`	Blurs an image and downsamples it.
`static void`	Imgproc.`pyrDown(Mat src, Mat dst, Size dstsize, int borderType)`	Blurs an image and downsamples it.
`static void`	Imgproc.`pyrMeanShiftFiltering(Mat src, Mat dst, double sp, double sr)`	Performs initial step of meanshift segmentation of an image.
`static void`	Imgproc.`pyrMeanShiftFiltering(Mat src, Mat dst, double sp, double sr, int maxLevel)`	Performs initial step of meanshift segmentation of an image.
`static void`	Imgproc.`pyrMeanShiftFiltering(Mat src, Mat dst, double sp, double sr, int maxLevel, TermCriteria termcrit)`	Performs initial step of meanshift segmentation of an image.
`static void`	Imgproc.`pyrUp(Mat src, Mat dst)`	Upsamples an image and then blurs it.
`static void`	Imgproc.`pyrUp(Mat src, Mat dst, Size dstsize)`	Upsamples an image and then blurs it.
`static void`	Imgproc.`pyrUp(Mat src, Mat dst, Size dstsize, int borderType)`	Upsamples an image and then blurs it.
`static void`	Imgproc.`rectangle(Mat img, Point pt1, Point pt2, Scalar color)`	Draws a simple, thick, or filled up-right rectangle.
`static void`	Imgproc.`rectangle(Mat img, Point pt1, Point pt2, Scalar color, int thickness)`	Draws a simple, thick, or filled up-right rectangle.
`static void`	Imgproc.`rectangle(Mat img, Point pt1, Point pt2, Scalar color, int thickness, int lineType)`	Draws a simple, thick, or filled up-right rectangle.
`static void`	Imgproc.`rectangle(Mat img, Point pt1, Point pt2, Scalar color, int thickness, int lineType, int shift)`	Draws a simple, thick, or filled up-right rectangle.
`static void`	Imgproc.`rectangle(Mat img, Rect rec, Scalar color)`	use `rec` parameter as alternative specification of the drawn rectangle: `r.tl() and r.br()-Point(1,1)` are opposite corners
`static void`	Imgproc.`rectangle(Mat img, Rect rec, Scalar color, int thickness)`	use `rec` parameter as alternative specification of the drawn rectangle: `r.tl() and r.br()-Point(1,1)` are opposite corners
`static void`	Imgproc.`rectangle(Mat img, Rect rec, Scalar color, int thickness, int lineType)`	use `rec` parameter as alternative specification of the drawn rectangle: `r.tl() and r.br()-Point(1,1)` are opposite corners
`static void`	Imgproc.`rectangle(Mat img, Rect rec, Scalar color, int thickness, int lineType, int shift)`	use `rec` parameter as alternative specification of the drawn rectangle: `r.tl() and r.br()-Point(1,1)` are opposite corners
`static void`	Imgproc.`remap(Mat src, Mat dst, Mat map1, Mat map2, int interpolation)`	Applies a generic geometrical transformation to an image.
`static void`	Imgproc.`remap(Mat src, Mat dst, Mat map1, Mat map2, int interpolation, int borderMode)`	Applies a generic geometrical transformation to an image.
`static void`	Imgproc.`remap(Mat src, Mat dst, Mat map1, Mat map2, int interpolation, int borderMode, Scalar borderValue)`	Applies a generic geometrical transformation to an image.
`static void`	Imgproc.`resize(Mat src, Mat dst, Size dsize)`	Resizes an image.
`static void`	Imgproc.`resize(Mat src, Mat dst, Size dsize, double fx)`	Resizes an image.
`static void`	Imgproc.`resize(Mat src, Mat dst, Size dsize, double fx, double fy)`	Resizes an image.
`static void`	Imgproc.`resize(Mat src, Mat dst, Size dsize, double fx, double fy, int interpolation)`	Resizes an image.
`static int`	Imgproc.`rotatedRectangleIntersection(RotatedRect rect1, RotatedRect rect2, Mat intersectingRegion)`	Finds out if there is any intersection between two rotated rectangles.
`static void`	Imgproc.`Scharr(Mat src, Mat dst, int ddepth, int dx, int dy)`	Calculates the first x- or y- image derivative using Scharr operator.
`static void`	Imgproc.`Scharr(Mat src, Mat dst, int ddepth, int dx, int dy, double scale)`	Calculates the first x- or y- image derivative using Scharr operator.
`static void`	Imgproc.`Scharr(Mat src, Mat dst, int ddepth, int dx, int dy, double scale, double delta)`	Calculates the first x- or y- image derivative using Scharr operator.
`static void`	Imgproc.`Scharr(Mat src, Mat dst, int ddepth, int dx, int dy, double scale, double delta, int borderType)`	Calculates the first x- or y- image derivative using Scharr operator.
`static void`	Imgproc.`sepFilter2D(Mat src, Mat dst, int ddepth, Mat kernelX, Mat kernelY)`	Applies a separable linear filter to an image.
`static void`	Imgproc.`sepFilter2D(Mat src, Mat dst, int ddepth, Mat kernelX, Mat kernelY, Point anchor)`	Applies a separable linear filter to an image.
`static void`	Imgproc.`sepFilter2D(Mat src, Mat dst, int ddepth, Mat kernelX, Mat kernelY, Point anchor, double delta)`	Applies a separable linear filter to an image.
`static void`	Imgproc.`sepFilter2D(Mat src, Mat dst, int ddepth, Mat kernelX, Mat kernelY, Point anchor, double delta, int borderType)`	Applies a separable linear filter to an image.
`void`	GeneralizedHough.`setTemplate(Mat templ)`
`void`	GeneralizedHough.`setTemplate(Mat edges, Mat dx, Mat dy)`
`void`	GeneralizedHough.`setTemplate(Mat edges, Mat dx, Mat dy, Point templCenter)`
`void`	GeneralizedHough.`setTemplate(Mat templ, Point templCenter)`
`static void`	Imgproc.`Sobel(Mat src, Mat dst, int ddepth, int dx, int dy)`	Calculates the first, second, third, or mixed image derivatives using an extended Sobel operator.
`static void`	Imgproc.`Sobel(Mat src, Mat dst, int ddepth, int dx, int dy, int ksize)`	Calculates the first, second, third, or mixed image derivatives using an extended Sobel operator.
`static void`	Imgproc.`Sobel(Mat src, Mat dst, int ddepth, int dx, int dy, int ksize, double scale)`	Calculates the first, second, third, or mixed image derivatives using an extended Sobel operator.
`static void`	Imgproc.`Sobel(Mat src, Mat dst, int ddepth, int dx, int dy, int ksize, double scale, double delta)`	Calculates the first, second, third, or mixed image derivatives using an extended Sobel operator.
`static void`	Imgproc.`Sobel(Mat src, Mat dst, int ddepth, int dx, int dy, int ksize, double scale, double delta, int borderType)`	Calculates the first, second, third, or mixed image derivatives using an extended Sobel operator.
`static void`	Imgproc.`spatialGradient(Mat src, Mat dx, Mat dy)`	Calculates the first order image derivative in both x and y using a Sobel operator Equivalent to calling: `Sobel( src, dx, CV_16SC1, 1, 0, 3 ); Sobel( src, dy, CV_16SC1, 0, 1, 3 );`
`static void`	Imgproc.`spatialGradient(Mat src, Mat dx, Mat dy, int ksize)`	Calculates the first order image derivative in both x and y using a Sobel operator Equivalent to calling: `Sobel( src, dx, CV_16SC1, 1, 0, 3 ); Sobel( src, dy, CV_16SC1, 0, 1, 3 );`
`static void`	Imgproc.`spatialGradient(Mat src, Mat dx, Mat dy, int ksize, int borderType)`	Calculates the first order image derivative in both x and y using a Sobel operator Equivalent to calling: `Sobel( src, dx, CV_16SC1, 1, 0, 3 ); Sobel( src, dy, CV_16SC1, 0, 1, 3 );`
`static void`	Imgproc.`sqrBoxFilter(Mat src, Mat dst, int ddepth, Size ksize)`	Calculates the normalized sum of squares of the pixel values overlapping the filter.
`static void`	Imgproc.`sqrBoxFilter(Mat src, Mat dst, int ddepth, Size ksize, Point anchor)`	Calculates the normalized sum of squares of the pixel values overlapping the filter.
`static void`	Imgproc.`sqrBoxFilter(Mat src, Mat dst, int ddepth, Size ksize, Point anchor, boolean normalize)`	Calculates the normalized sum of squares of the pixel values overlapping the filter.
`static void`	Imgproc.`sqrBoxFilter(Mat src, Mat dst, int ddepth, Size ksize, Point anchor, boolean normalize, int borderType)`	Calculates the normalized sum of squares of the pixel values overlapping the filter.
`static double`	Imgproc.`threshold(Mat src, Mat dst, double thresh, double maxval, int type)`	Applies a fixed-level threshold to each array element.
`static void`	Imgproc.`warpAffine(Mat src, Mat dst, Mat M, Size dsize)`	Applies an affine transformation to an image.
`static void`	Imgproc.`warpAffine(Mat src, Mat dst, Mat M, Size dsize, int flags)`	Applies an affine transformation to an image.
`static void`	Imgproc.`warpAffine(Mat src, Mat dst, Mat M, Size dsize, int flags, int borderMode)`	Applies an affine transformation to an image.
`static void`	Imgproc.`warpAffine(Mat src, Mat dst, Mat M, Size dsize, int flags, int borderMode, Scalar borderValue)`	Applies an affine transformation to an image.
`static void`	Imgproc.`warpPerspective(Mat src, Mat dst, Mat M, Size dsize)`	Applies a perspective transformation to an image.
`static void`	Imgproc.`warpPerspective(Mat src, Mat dst, Mat M, Size dsize, int flags)`	Applies a perspective transformation to an image.
`static void`	Imgproc.`warpPerspective(Mat src, Mat dst, Mat M, Size dsize, int flags, int borderMode)`	Applies a perspective transformation to an image.
`static void`	Imgproc.`warpPerspective(Mat src, Mat dst, Mat M, Size dsize, int flags, int borderMode, Scalar borderValue)`	Applies a perspective transformation to an image.
`static void`	Imgproc.`warpPolar(Mat src, Mat dst, Size dsize, Point center, double maxRadius, int flags)`	Remaps an image to polar or semilog-polar coordinates space polar_remaps_reference_image ![Polar remaps reference](pics/polar_remap_doc.png) Transform the source image using the following transformation: \( dst(\rho , \phi ) = src(x,y) \) where \( \begin{array}{l} \vec{I} = (x - center.x, \;y - center.y) \\ \phi = Kangle \cdot \texttt{angle} (\vec{I}) \\ \rho = \left\{\begin{matrix} Klin \cdot \texttt{magnitude} (\vec{I}) & default \\ Klog \cdot log_e(\texttt{magnitude} (\vec{I})) & if \; semilog \\ \end{matrix}\right.
`static void`	Imgproc.`watershed(Mat image, Mat markers)`	Performs a marker-based image segmentation using the watershed algorithm.

Method parameters in org.opencv.imgproc with type arguments of type Mat
Modifier and Type	Method	Description
`static void`	Imgproc.`calcBackProject(List<Mat> images, MatOfInt channels, Mat hist, Mat dst, MatOfFloat ranges, double scale)`
`static void`	Imgproc.`calcHist(List<Mat> images, MatOfInt channels, Mat mask, Mat hist, MatOfInt histSize, MatOfFloat ranges)`
`static void`	Imgproc.`calcHist(List<Mat> images, MatOfInt channels, Mat mask, Mat hist, MatOfInt histSize, MatOfFloat ranges, boolean accumulate)`

Uses of Mat in org.opencv.ml

Methods in org.opencv.ml that return Mat
Modifier and Type	Method	Description
`Mat`	LogisticRegression.`get_learnt_thetas()`	This function returns the trained parameters arranged across rows.
`Mat`	TrainData.`getCatMap()`
`Mat`	TrainData.`getCatOfs()`
`Mat`	TrainData.`getClassLabels()`	Returns the vector of class labels The function returns vector of unique labels occurred in the responses.
`Mat`	SVM.`getClassWeights()`	SEE: setClassWeights
`Mat`	TrainData.`getDefaultSubstValues()`
`Mat`	ANN_MLP.`getLayerSizes()`	Integer vector specifying the number of neurons in each layer including the input and output layers.
`Mat`	EM.`getMeans()`	Returns the cluster centers (means of the Gaussian mixture) Returns matrix with the number of rows equal to the number of mixtures and number of columns equal to the space dimensionality.
`Mat`	TrainData.`getMissing()`
`Mat`	TrainData.`getNormCatResponses()`
`Mat`	DTrees.`getPriors()`	SEE: setPriors
`Mat`	TrainData.`getResponses()`
`Mat`	TrainData.`getSamples()`
`Mat`	TrainData.`getSampleWeights()`
`static Mat`	TrainData.`getSubMatrix(Mat matrix, Mat idx, int layout)`	Extract from matrix rows/cols specified by passed indexes.
`static Mat`	TrainData.`getSubVector(Mat vec, Mat idx)`	Extract from 1D vector elements specified by passed indexes.
`Mat`	SVM.`getSupportVectors()`	Retrieves all the support vectors The method returns all the support vectors as a floating-point matrix, where support vectors are stored as matrix rows.
`Mat`	TrainData.`getTestNormCatResponses()`
`Mat`	TrainData.`getTestResponses()`
`Mat`	TrainData.`getTestSampleIdx()`
`Mat`	TrainData.`getTestSamples()`	Returns matrix of test samples
`Mat`	TrainData.`getTestSampleWeights()`
`Mat`	TrainData.`getTrainNormCatResponses()`	Returns the vector of normalized categorical responses The function returns vector of responses.
`Mat`	TrainData.`getTrainResponses()`	Returns the vector of responses The function returns ordered or the original categorical responses.
`Mat`	TrainData.`getTrainSampleIdx()`
`Mat`	TrainData.`getTrainSamples()`	Returns matrix of train samples transposed.
`Mat`	TrainData.`getTrainSamples(int layout)`	Returns matrix of train samples
`Mat`	TrainData.`getTrainSamples(int layout, boolean compressSamples)`	Returns matrix of train samples
`Mat`	TrainData.`getTrainSamples(int layout, boolean compressSamples, boolean compressVars)`	Returns matrix of train samples
`Mat`	TrainData.`getTrainSampleWeights()`
`Mat`	SVM.`getUncompressedSupportVectors()`	Retrieves all the uncompressed support vectors of a linear %SVM The method returns all the uncompressed support vectors of a linear %SVM that the compressed support vector, used for prediction, was derived from.
`Mat`	TrainData.`getVarIdx()`
`Mat`	RTrees.`getVarImportance()`	Returns the variable importance array.
`Mat`	TrainData.`getVarSymbolFlags()`
`Mat`	TrainData.`getVarType()`
`Mat`	ANN_MLP.`getWeights(int layerIdx)`
`Mat`	EM.`getWeights()`	Returns weights of the mixtures Returns vector with the number of elements equal to the number of mixtures.
`Mat`	SVMSGD.`getWeights()`

Methods in org.opencv.ml with parameters of type Mat
Modifier and Type	Method	Description
`float`	StatModel.`calcError(TrainData data, boolean test, Mat resp)`	Computes error on the training or test dataset
`static TrainData`	TrainData.`create(Mat samples, int layout, Mat responses)`	Creates training data from in-memory arrays.
`static TrainData`	TrainData.`create(Mat samples, int layout, Mat responses, Mat varIdx)`	Creates training data from in-memory arrays.
`static TrainData`	TrainData.`create(Mat samples, int layout, Mat responses, Mat varIdx, Mat sampleIdx)`	Creates training data from in-memory arrays.
`static TrainData`	TrainData.`create(Mat samples, int layout, Mat responses, Mat varIdx, Mat sampleIdx, Mat sampleWeights)`	Creates training data from in-memory arrays.
`static TrainData`	TrainData.`create(Mat samples, int layout, Mat responses, Mat varIdx, Mat sampleIdx, Mat sampleWeights, Mat varType)`	Creates training data from in-memory arrays.
`float`	KNearest.`findNearest(Mat samples, int k, Mat results)`	Finds the neighbors and predicts responses for input vectors.
`float`	KNearest.`findNearest(Mat samples, int k, Mat results, Mat neighborResponses)`	Finds the neighbors and predicts responses for input vectors.
`float`	KNearest.`findNearest(Mat samples, int k, Mat results, Mat neighborResponses, Mat dist)`	Finds the neighbors and predicts responses for input vectors.
`double`	SVM.`getDecisionFunction(int i, Mat alpha, Mat svidx)`	Retrieves the decision function
`void`	TrainData.`getSample(Mat varIdx, int sidx, float buf)`
`static Mat`	TrainData.`getSubMatrix(Mat matrix, Mat idx, int layout)`	Extract from matrix rows/cols specified by passed indexes.
`static Mat`	TrainData.`getSubVector(Mat vec, Mat idx)`	Extract from 1D vector elements specified by passed indexes.
`void`	TrainData.`getValues(int vi, Mat sidx, float values)`
`void`	RTrees.`getVotes(Mat samples, Mat results, int flags)`	Returns the result of each individual tree in the forest.
`float`	EM.`predict(Mat samples)`	Returns posterior probabilities for the provided samples
`float`	EM.`predict(Mat samples, Mat results)`	Returns posterior probabilities for the provided samples
`float`	EM.`predict(Mat samples, Mat results, int flags)`	Returns posterior probabilities for the provided samples
`float`	LogisticRegression.`predict(Mat samples)`	Predicts responses for input samples and returns a float type.
`float`	LogisticRegression.`predict(Mat samples, Mat results)`	Predicts responses for input samples and returns a float type.
`float`	LogisticRegression.`predict(Mat samples, Mat results, int flags)`	Predicts responses for input samples and returns a float type.
`float`	StatModel.`predict(Mat samples)`	Predicts response(s) for the provided sample(s)
`float`	StatModel.`predict(Mat samples, Mat results)`	Predicts response(s) for the provided sample(s)
`float`	StatModel.`predict(Mat samples, Mat results, int flags)`	Predicts response(s) for the provided sample(s)
`double[]`	EM.`predict2(Mat sample, Mat probs)`	Returns a likelihood logarithm value and an index of the most probable mixture component for the given sample.
`float`	NormalBayesClassifier.`predictProb(Mat inputs, Mat outputs, Mat outputProbs)`	Predicts the response for sample(s).
`float`	NormalBayesClassifier.`predictProb(Mat inputs, Mat outputs, Mat outputProbs, int flags)`	Predicts the response for sample(s).
`void`	SVM.`setClassWeights(Mat val)`	getClassWeights SEE: getClassWeights
`void`	ANN_MLP.`setLayerSizes(Mat _layer_sizes)`	Integer vector specifying the number of neurons in each layer including the input and output layers.
`void`	DTrees.`setPriors(Mat val)`	getPriors SEE: getPriors
`boolean`	StatModel.`train(Mat samples, int layout, Mat responses)`	Trains the statistical model
`boolean`	SVM.`trainAuto(Mat samples, int layout, Mat responses)`	Trains an %SVM with optimal parameters
`boolean`	SVM.`trainAuto(Mat samples, int layout, Mat responses, int kFold)`	Trains an %SVM with optimal parameters
`boolean`	SVM.`trainAuto(Mat samples, int layout, Mat responses, int kFold, ParamGrid Cgrid)`	Trains an %SVM with optimal parameters
`boolean`	SVM.`trainAuto(Mat samples, int layout, Mat responses, int kFold, ParamGrid Cgrid, ParamGrid gammaGrid)`	Trains an %SVM with optimal parameters
`boolean`	SVM.`trainAuto(Mat samples, int layout, Mat responses, int kFold, ParamGrid Cgrid, ParamGrid gammaGrid, ParamGrid pGrid)`	Trains an %SVM with optimal parameters
`boolean`	SVM.`trainAuto(Mat samples, int layout, Mat responses, int kFold, ParamGrid Cgrid, ParamGrid gammaGrid, ParamGrid pGrid, ParamGrid nuGrid)`	Trains an %SVM with optimal parameters
`boolean`	SVM.`trainAuto(Mat samples, int layout, Mat responses, int kFold, ParamGrid Cgrid, ParamGrid gammaGrid, ParamGrid pGrid, ParamGrid nuGrid, ParamGrid coeffGrid)`	Trains an %SVM with optimal parameters
`boolean`	SVM.`trainAuto(Mat samples, int layout, Mat responses, int kFold, ParamGrid Cgrid, ParamGrid gammaGrid, ParamGrid pGrid, ParamGrid nuGrid, ParamGrid coeffGrid, ParamGrid degreeGrid)`	Trains an %SVM with optimal parameters
`boolean`	SVM.`trainAuto(Mat samples, int layout, Mat responses, int kFold, ParamGrid Cgrid, ParamGrid gammaGrid, ParamGrid pGrid, ParamGrid nuGrid, ParamGrid coeffGrid, ParamGrid degreeGrid, boolean balanced)`	Trains an %SVM with optimal parameters
`boolean`	EM.`trainE(Mat samples, Mat means0)`	Estimate the Gaussian mixture parameters from a samples set.
`boolean`	EM.`trainE(Mat samples, Mat means0, Mat covs0)`	Estimate the Gaussian mixture parameters from a samples set.
`boolean`	EM.`trainE(Mat samples, Mat means0, Mat covs0, Mat weights0)`	Estimate the Gaussian mixture parameters from a samples set.
`boolean`	EM.`trainE(Mat samples, Mat means0, Mat covs0, Mat weights0, Mat logLikelihoods)`	Estimate the Gaussian mixture parameters from a samples set.
`boolean`	EM.`trainE(Mat samples, Mat means0, Mat covs0, Mat weights0, Mat logLikelihoods, Mat labels)`	Estimate the Gaussian mixture parameters from a samples set.
`boolean`	EM.`trainE(Mat samples, Mat means0, Mat covs0, Mat weights0, Mat logLikelihoods, Mat labels, Mat probs)`	Estimate the Gaussian mixture parameters from a samples set.
`boolean`	EM.`trainEM(Mat samples)`	Estimate the Gaussian mixture parameters from a samples set.
`boolean`	EM.`trainEM(Mat samples, Mat logLikelihoods)`	Estimate the Gaussian mixture parameters from a samples set.
`boolean`	EM.`trainEM(Mat samples, Mat logLikelihoods, Mat labels)`	Estimate the Gaussian mixture parameters from a samples set.
`boolean`	EM.`trainEM(Mat samples, Mat logLikelihoods, Mat labels, Mat probs)`	Estimate the Gaussian mixture parameters from a samples set.
`boolean`	EM.`trainM(Mat samples, Mat probs0)`	Estimate the Gaussian mixture parameters from a samples set.
`boolean`	EM.`trainM(Mat samples, Mat probs0, Mat logLikelihoods)`	Estimate the Gaussian mixture parameters from a samples set.
`boolean`	EM.`trainM(Mat samples, Mat probs0, Mat logLikelihoods, Mat labels)`	Estimate the Gaussian mixture parameters from a samples set.
`boolean`	EM.`trainM(Mat samples, Mat probs0, Mat logLikelihoods, Mat labels, Mat probs)`	Estimate the Gaussian mixture parameters from a samples set.

Method parameters in org.opencv.ml with type arguments of type Mat
Modifier and Type	Method	Description
`void`	EM.`getCovs(List<Mat> covs)`	Returns covariation matrices Returns vector of covariation matrices.

Uses of Mat in org.opencv.objdetect

Methods in org.opencv.objdetect with parameters of type Mat
Modifier and Type	Method	Description
`void`	HOGDescriptor.`compute(Mat img, MatOfFloat descriptors)`	Computes HOG descriptors of given image.
`void`	HOGDescriptor.`compute(Mat img, MatOfFloat descriptors, Size winStride)`	Computes HOG descriptors of given image.
`void`	HOGDescriptor.`compute(Mat img, MatOfFloat descriptors, Size winStride, Size padding)`	Computes HOG descriptors of given image.
`void`	HOGDescriptor.`compute(Mat img, MatOfFloat descriptors, Size winStride, Size padding, MatOfPoint locations)`	Computes HOG descriptors of given image.
`void`	HOGDescriptor.`computeGradient(Mat img, Mat grad, Mat angleOfs)`	Computes gradients and quantized gradient orientations.
`void`	HOGDescriptor.`computeGradient(Mat img, Mat grad, Mat angleOfs, Size paddingTL)`	Computes gradients and quantized gradient orientations.
`void`	HOGDescriptor.`computeGradient(Mat img, Mat grad, Mat angleOfs, Size paddingTL, Size paddingBR)`	Computes gradients and quantized gradient orientations.
`String`	QRCodeDetector.`decode(Mat img, Mat points)`	Decodes QR code in image once it's found by the detect() method.
`String`	QRCodeDetector.`decode(Mat img, Mat points, Mat straight_qrcode)`	Decodes QR code in image once it's found by the detect() method.
`String`	QRCodeDetector.`decodeCurved(Mat img, Mat points)`	Decodes QR code on a curved surface in image once it's found by the detect() method.
`String`	QRCodeDetector.`decodeCurved(Mat img, Mat points, Mat straight_qrcode)`	Decodes QR code on a curved surface in image once it's found by the detect() method.
`boolean`	QRCodeDetector.`decodeMulti(Mat img, Mat points, List<String> decoded_info)`	Decodes QR codes in image once it's found by the detect() method.
`boolean`	QRCodeDetector.`decodeMulti(Mat img, Mat points, List<String> decoded_info, List<Mat> straight_qrcode)`	Decodes QR codes in image once it's found by the detect() method.
`void`	HOGDescriptor.`detect(Mat img, MatOfPoint foundLocations, MatOfDouble weights)`	Performs object detection without a multi-scale window.
`void`	HOGDescriptor.`detect(Mat img, MatOfPoint foundLocations, MatOfDouble weights, double hitThreshold)`	Performs object detection without a multi-scale window.
`void`	HOGDescriptor.`detect(Mat img, MatOfPoint foundLocations, MatOfDouble weights, double hitThreshold, Size winStride)`	Performs object detection without a multi-scale window.
`void`	HOGDescriptor.`detect(Mat img, MatOfPoint foundLocations, MatOfDouble weights, double hitThreshold, Size winStride, Size padding)`	Performs object detection without a multi-scale window.
`void`	HOGDescriptor.`detect(Mat img, MatOfPoint foundLocations, MatOfDouble weights, double hitThreshold, Size winStride, Size padding, MatOfPoint searchLocations)`	Performs object detection without a multi-scale window.
`boolean`	QRCodeDetector.`detect(Mat img, Mat points)`	Detects QR code in image and returns the quadrangle containing the code.
`String`	QRCodeDetector.`detectAndDecode(Mat img)`	Both detects and decodes QR code
`String`	QRCodeDetector.`detectAndDecode(Mat img, Mat points)`	Both detects and decodes QR code
`String`	QRCodeDetector.`detectAndDecode(Mat img, Mat points, Mat straight_qrcode)`	Both detects and decodes QR code
`String`	QRCodeDetector.`detectAndDecodeCurved(Mat img)`	Both detects and decodes QR code on a curved surface
`String`	QRCodeDetector.`detectAndDecodeCurved(Mat img, Mat points)`	Both detects and decodes QR code on a curved surface
`String`	QRCodeDetector.`detectAndDecodeCurved(Mat img, Mat points, Mat straight_qrcode)`	Both detects and decodes QR code on a curved surface
`boolean`	QRCodeDetector.`detectAndDecodeMulti(Mat img, List<String> decoded_info)`	Both detects and decodes QR codes
`boolean`	QRCodeDetector.`detectAndDecodeMulti(Mat img, List<String> decoded_info, Mat points)`	Both detects and decodes QR codes
`boolean`	QRCodeDetector.`detectAndDecodeMulti(Mat img, List<String> decoded_info, Mat points, List<Mat> straight_qrcode)`	Both detects and decodes QR codes
`boolean`	QRCodeDetector.`detectMulti(Mat img, Mat points)`	Detects QR codes in image and returns the vector of the quadrangles containing the codes.
`void`	CascadeClassifier.`detectMultiScale(Mat image, MatOfRect objects)`	Detects objects of different sizes in the input image.
`void`	CascadeClassifier.`detectMultiScale(Mat image, MatOfRect objects, double scaleFactor)`	Detects objects of different sizes in the input image.
`void`	CascadeClassifier.`detectMultiScale(Mat image, MatOfRect objects, double scaleFactor, int minNeighbors)`	Detects objects of different sizes in the input image.
`void`	CascadeClassifier.`detectMultiScale(Mat image, MatOfRect objects, double scaleFactor, int minNeighbors, int flags)`	Detects objects of different sizes in the input image.
`void`	CascadeClassifier.`detectMultiScale(Mat image, MatOfRect objects, double scaleFactor, int minNeighbors, int flags, Size minSize)`	Detects objects of different sizes in the input image.
`void`	CascadeClassifier.`detectMultiScale(Mat image, MatOfRect objects, double scaleFactor, int minNeighbors, int flags, Size minSize, Size maxSize)`	Detects objects of different sizes in the input image.
`void`	HOGDescriptor.`detectMultiScale(Mat img, MatOfRect foundLocations, MatOfDouble foundWeights)`	Detects objects of different sizes in the input image.
`void`	HOGDescriptor.`detectMultiScale(Mat img, MatOfRect foundLocations, MatOfDouble foundWeights, double hitThreshold)`	Detects objects of different sizes in the input image.
`void`	HOGDescriptor.`detectMultiScale(Mat img, MatOfRect foundLocations, MatOfDouble foundWeights, double hitThreshold, Size winStride)`	Detects objects of different sizes in the input image.
`void`	HOGDescriptor.`detectMultiScale(Mat img, MatOfRect foundLocations, MatOfDouble foundWeights, double hitThreshold, Size winStride, Size padding)`	Detects objects of different sizes in the input image.
`void`	HOGDescriptor.`detectMultiScale(Mat img, MatOfRect foundLocations, MatOfDouble foundWeights, double hitThreshold, Size winStride, Size padding, double scale)`	Detects objects of different sizes in the input image.
`void`	HOGDescriptor.`detectMultiScale(Mat img, MatOfRect foundLocations, MatOfDouble foundWeights, double hitThreshold, Size winStride, Size padding, double scale, double finalThreshold)`	Detects objects of different sizes in the input image.
`void`	HOGDescriptor.`detectMultiScale(Mat img, MatOfRect foundLocations, MatOfDouble foundWeights, double hitThreshold, Size winStride, Size padding, double scale, double finalThreshold, boolean useMeanshiftGrouping)`	Detects objects of different sizes in the input image.
`void`	CascadeClassifier.`detectMultiScale2(Mat image, MatOfRect objects, MatOfInt numDetections)`
`void`	CascadeClassifier.`detectMultiScale2(Mat image, MatOfRect objects, MatOfInt numDetections, double scaleFactor)`
`void`	CascadeClassifier.`detectMultiScale2(Mat image, MatOfRect objects, MatOfInt numDetections, double scaleFactor, int minNeighbors)`
`void`	CascadeClassifier.`detectMultiScale2(Mat image, MatOfRect objects, MatOfInt numDetections, double scaleFactor, int minNeighbors, int flags)`
`void`	CascadeClassifier.`detectMultiScale2(Mat image, MatOfRect objects, MatOfInt numDetections, double scaleFactor, int minNeighbors, int flags, Size minSize)`
`void`	CascadeClassifier.`detectMultiScale2(Mat image, MatOfRect objects, MatOfInt numDetections, double scaleFactor, int minNeighbors, int flags, Size minSize, Size maxSize)`
`void`	CascadeClassifier.`detectMultiScale3(Mat image, MatOfRect objects, MatOfInt rejectLevels, MatOfDouble levelWeights)`	This function allows you to retrieve the final stage decision certainty of classification.
`void`	CascadeClassifier.`detectMultiScale3(Mat image, MatOfRect objects, MatOfInt rejectLevels, MatOfDouble levelWeights, double scaleFactor)`	This function allows you to retrieve the final stage decision certainty of classification.
`void`	CascadeClassifier.`detectMultiScale3(Mat image, MatOfRect objects, MatOfInt rejectLevels, MatOfDouble levelWeights, double scaleFactor, int minNeighbors)`	This function allows you to retrieve the final stage decision certainty of classification.
`void`	CascadeClassifier.`detectMultiScale3(Mat image, MatOfRect objects, MatOfInt rejectLevels, MatOfDouble levelWeights, double scaleFactor, int minNeighbors, int flags)`	This function allows you to retrieve the final stage decision certainty of classification.
`void`	CascadeClassifier.`detectMultiScale3(Mat image, MatOfRect objects, MatOfInt rejectLevels, MatOfDouble levelWeights, double scaleFactor, int minNeighbors, int flags, Size minSize)`	This function allows you to retrieve the final stage decision certainty of classification.
`void`	CascadeClassifier.`detectMultiScale3(Mat image, MatOfRect objects, MatOfInt rejectLevels, MatOfDouble levelWeights, double scaleFactor, int minNeighbors, int flags, Size minSize, Size maxSize)`	This function allows you to retrieve the final stage decision certainty of classification.
`void`	CascadeClassifier.`detectMultiScale3(Mat image, MatOfRect objects, MatOfInt rejectLevels, MatOfDouble levelWeights, double scaleFactor, int minNeighbors, int flags, Size minSize, Size maxSize, boolean outputRejectLevels)`	This function allows you to retrieve the final stage decision certainty of classification.
`void`	HOGDescriptor.`setSVMDetector(Mat svmdetector)`	Sets coefficients for the linear SVM classifier.

Uses of Mat in org.opencv.phase_unwrapping

Methods in org.opencv.phase_unwrapping with parameters of type Mat
Modifier and Type	Method	Description
`void`	HistogramPhaseUnwrapping.`getInverseReliabilityMap(Mat reliabilityMap)`	Get the reliability map computed from the wrapped phase map.
`void`	PhaseUnwrapping.`unwrapPhaseMap(Mat wrappedPhaseMap, Mat unwrappedPhaseMap)`	Unwraps a 2D phase map.
`void`	PhaseUnwrapping.`unwrapPhaseMap(Mat wrappedPhaseMap, Mat unwrappedPhaseMap, Mat shadowMask)`	Unwraps a 2D phase map.

Uses of Mat in org.opencv.photo

Methods in org.opencv.photo that return Mat
Modifier and Type	Method	Description
`Mat`	CalibrateRobertson.`getRadiance()`

Methods in org.opencv.photo with parameters of type Mat
Modifier and Type	Method	Description
`Point`	AlignMTB.`calculateShift(Mat img0, Mat img1)`	Calculates shift between two images, i.
`static void`	Photo.`colorChange(Mat src, Mat mask, Mat dst)`	Given an original color image, two differently colored versions of this image can be mixed seamlessly.
`static void`	Photo.`colorChange(Mat src, Mat mask, Mat dst, float red_mul)`	Given an original color image, two differently colored versions of this image can be mixed seamlessly.
`static void`	Photo.`colorChange(Mat src, Mat mask, Mat dst, float red_mul, float green_mul)`	Given an original color image, two differently colored versions of this image can be mixed seamlessly.
`static void`	Photo.`colorChange(Mat src, Mat mask, Mat dst, float red_mul, float green_mul, float blue_mul)`	Given an original color image, two differently colored versions of this image can be mixed seamlessly.
`void`	AlignMTB.`computeBitmaps(Mat img, Mat tb, Mat eb)`	Computes median threshold and exclude bitmaps of given image.
`static void`	Photo.`decolor(Mat src, Mat grayscale, Mat color_boost)`	Transforms a color image to a grayscale image.
`static void`	Photo.`denoise_TVL1(List<Mat> observations, Mat result)`	Primal-dual algorithm is an algorithm for solving special types of variational problems (that is, finding a function to minimize some functional).
`static void`	Photo.`denoise_TVL1(List<Mat> observations, Mat result, double lambda)`	Primal-dual algorithm is an algorithm for solving special types of variational problems (that is, finding a function to minimize some functional).
`static void`	Photo.`denoise_TVL1(List<Mat> observations, Mat result, double lambda, int niters)`	Primal-dual algorithm is an algorithm for solving special types of variational problems (that is, finding a function to minimize some functional).
`static void`	Photo.`detailEnhance(Mat src, Mat dst)`	This filter enhances the details of a particular image.
`static void`	Photo.`detailEnhance(Mat src, Mat dst, float sigma_s)`	This filter enhances the details of a particular image.
`static void`	Photo.`detailEnhance(Mat src, Mat dst, float sigma_s, float sigma_r)`	This filter enhances the details of a particular image.
`static void`	Photo.`edgePreservingFilter(Mat src, Mat dst)`	Filtering is the fundamental operation in image and video processing.
`static void`	Photo.`edgePreservingFilter(Mat src, Mat dst, int flags)`	Filtering is the fundamental operation in image and video processing.
`static void`	Photo.`edgePreservingFilter(Mat src, Mat dst, int flags, float sigma_s)`	Filtering is the fundamental operation in image and video processing.
`static void`	Photo.`edgePreservingFilter(Mat src, Mat dst, int flags, float sigma_s, float sigma_r)`	Filtering is the fundamental operation in image and video processing.
`static void`	Photo.`fastNlMeansDenoising(Mat src, Mat dst)`	Perform image denoising using Non-local Means Denoising algorithm <http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/> with several computational optimizations.
`static void`	Photo.`fastNlMeansDenoising(Mat src, Mat dst, float h)`	Perform image denoising using Non-local Means Denoising algorithm <http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/> with several computational optimizations.
`static void`	Photo.`fastNlMeansDenoising(Mat src, Mat dst, float h, int templateWindowSize)`	Perform image denoising using Non-local Means Denoising algorithm <http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/> with several computational optimizations.
`static void`	Photo.`fastNlMeansDenoising(Mat src, Mat dst, float h, int templateWindowSize, int searchWindowSize)`	Perform image denoising using Non-local Means Denoising algorithm <http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/> with several computational optimizations.
`static void`	Photo.`fastNlMeansDenoising(Mat src, Mat dst, MatOfFloat h)`	Perform image denoising using Non-local Means Denoising algorithm <http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/> with several computational optimizations.
`static void`	Photo.`fastNlMeansDenoising(Mat src, Mat dst, MatOfFloat h, int templateWindowSize)`	Perform image denoising using Non-local Means Denoising algorithm <http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/> with several computational optimizations.
`static void`	Photo.`fastNlMeansDenoising(Mat src, Mat dst, MatOfFloat h, int templateWindowSize, int searchWindowSize)`	Perform image denoising using Non-local Means Denoising algorithm <http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/> with several computational optimizations.
`static void`	Photo.`fastNlMeansDenoising(Mat src, Mat dst, MatOfFloat h, int templateWindowSize, int searchWindowSize, int normType)`	Perform image denoising using Non-local Means Denoising algorithm <http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/> with several computational optimizations.
`static void`	Photo.`fastNlMeansDenoisingColored(Mat src, Mat dst)`	Modification of fastNlMeansDenoising function for colored images
`static void`	Photo.`fastNlMeansDenoisingColored(Mat src, Mat dst, float h)`	Modification of fastNlMeansDenoising function for colored images
`static void`	Photo.`fastNlMeansDenoisingColored(Mat src, Mat dst, float h, float hColor)`	Modification of fastNlMeansDenoising function for colored images
`static void`	Photo.`fastNlMeansDenoisingColored(Mat src, Mat dst, float h, float hColor, int templateWindowSize)`	Modification of fastNlMeansDenoising function for colored images
`static void`	Photo.`fastNlMeansDenoisingColored(Mat src, Mat dst, float h, float hColor, int templateWindowSize, int searchWindowSize)`	Modification of fastNlMeansDenoising function for colored images
`static void`	Photo.`fastNlMeansDenoisingColoredMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize)`	Modification of fastNlMeansDenoisingMulti function for colored images sequences
`static void`	Photo.`fastNlMeansDenoisingColoredMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h)`	Modification of fastNlMeansDenoisingMulti function for colored images sequences
`static void`	Photo.`fastNlMeansDenoisingColoredMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h, float hColor)`	Modification of fastNlMeansDenoisingMulti function for colored images sequences
`static void`	Photo.`fastNlMeansDenoisingColoredMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h, float hColor, int templateWindowSize)`	Modification of fastNlMeansDenoisingMulti function for colored images sequences
`static void`	Photo.`fastNlMeansDenoisingColoredMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h, float hColor, int templateWindowSize, int searchWindowSize)`	Modification of fastNlMeansDenoisingMulti function for colored images sequences
`static void`	Photo.`fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize)`	Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time.
`static void`	Photo.`fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h)`	Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time.
`static void`	Photo.`fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h, int templateWindowSize)`	Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time.
`static void`	Photo.`fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h, int templateWindowSize, int searchWindowSize)`	Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time.
`static void`	Photo.`fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, MatOfFloat h)`	Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time.
`static void`	Photo.`fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, MatOfFloat h, int templateWindowSize)`	Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time.
`static void`	Photo.`fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, MatOfFloat h, int templateWindowSize, int searchWindowSize)`	Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time.
`static void`	Photo.`fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, MatOfFloat h, int templateWindowSize, int searchWindowSize, int normType)`	Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time.
`static void`	Photo.`illuminationChange(Mat src, Mat mask, Mat dst)`	Applying an appropriate non-linear transformation to the gradient field inside the selection and then integrating back with a Poisson solver, modifies locally the apparent illumination of an image.
`static void`	Photo.`illuminationChange(Mat src, Mat mask, Mat dst, float alpha)`	Applying an appropriate non-linear transformation to the gradient field inside the selection and then integrating back with a Poisson solver, modifies locally the apparent illumination of an image.
`static void`	Photo.`illuminationChange(Mat src, Mat mask, Mat dst, float alpha, float beta)`	Applying an appropriate non-linear transformation to the gradient field inside the selection and then integrating back with a Poisson solver, modifies locally the apparent illumination of an image.
`static void`	Photo.`inpaint(Mat src, Mat inpaintMask, Mat dst, double inpaintRadius, int flags)`	Restores the selected region in an image using the region neighborhood.
`static void`	Photo.`pencilSketch(Mat src, Mat dst1, Mat dst2)`	Pencil-like non-photorealistic line drawing
`static void`	Photo.`pencilSketch(Mat src, Mat dst1, Mat dst2, float sigma_s)`	Pencil-like non-photorealistic line drawing
`static void`	Photo.`pencilSketch(Mat src, Mat dst1, Mat dst2, float sigma_s, float sigma_r)`	Pencil-like non-photorealistic line drawing
`static void`	Photo.`pencilSketch(Mat src, Mat dst1, Mat dst2, float sigma_s, float sigma_r, float shade_factor)`	Pencil-like non-photorealistic line drawing
`void`	AlignExposures.`process(List<Mat> src, List<Mat> dst, Mat times, Mat response)`	Aligns images
`void`	AlignMTB.`process(List<Mat> src, List<Mat> dst, Mat times, Mat response)`
`void`	CalibrateCRF.`process(List<Mat> src, Mat dst, Mat times)`	Recovers inverse camera response.
`void`	MergeDebevec.`process(List<Mat> src, Mat dst, Mat times)`
`void`	MergeDebevec.`process(List<Mat> src, Mat dst, Mat times, Mat response)`
`void`	MergeExposures.`process(List<Mat> src, Mat dst, Mat times, Mat response)`	Merges images.
`void`	MergeMertens.`process(List<Mat> src, Mat dst)`	Short version of process, that doesn't take extra arguments.
`void`	MergeMertens.`process(List<Mat> src, Mat dst, Mat times, Mat response)`
`void`	MergeRobertson.`process(List<Mat> src, Mat dst, Mat times)`
`void`	MergeRobertson.`process(List<Mat> src, Mat dst, Mat times, Mat response)`
`void`	Tonemap.`process(Mat src, Mat dst)`	Tonemaps image
`static void`	Photo.`seamlessClone(Mat src, Mat dst, Mat mask, Point p, Mat blend, int flags)`	Image editing tasks concern either global changes (color/intensity corrections, filters, deformations) or local changes concerned to a selection.
`void`	AlignMTB.`shiftMat(Mat src, Mat dst, Point shift)`	Helper function, that shift Mat filling new regions with zeros.
`static void`	Photo.`stylization(Mat src, Mat dst)`	Stylization aims to produce digital imagery with a wide variety of effects not focused on photorealism.
`static void`	Photo.`stylization(Mat src, Mat dst, float sigma_s)`	Stylization aims to produce digital imagery with a wide variety of effects not focused on photorealism.
`static void`	Photo.`stylization(Mat src, Mat dst, float sigma_s, float sigma_r)`	Stylization aims to produce digital imagery with a wide variety of effects not focused on photorealism.
`static void`	Photo.`textureFlattening(Mat src, Mat mask, Mat dst)`	By retaining only the gradients at edge locations, before integrating with the Poisson solver, one washes out the texture of the selected region, giving its contents a flat aspect.
`static void`	Photo.`textureFlattening(Mat src, Mat mask, Mat dst, float low_threshold)`	By retaining only the gradients at edge locations, before integrating with the Poisson solver, one washes out the texture of the selected region, giving its contents a flat aspect.
`static void`	Photo.`textureFlattening(Mat src, Mat mask, Mat dst, float low_threshold, float high_threshold)`	By retaining only the gradients at edge locations, before integrating with the Poisson solver, one washes out the texture of the selected region, giving its contents a flat aspect.
`static void`	Photo.`textureFlattening(Mat src, Mat mask, Mat dst, float low_threshold, float high_threshold, int kernel_size)`	By retaining only the gradients at edge locations, before integrating with the Poisson solver, one washes out the texture of the selected region, giving its contents a flat aspect.

Method parameters in org.opencv.photo with type arguments of type Mat
Modifier and Type	Method	Description
`static void`	Photo.`denoise_TVL1(List<Mat> observations, Mat result)`	Primal-dual algorithm is an algorithm for solving special types of variational problems (that is, finding a function to minimize some functional).
`static void`	Photo.`denoise_TVL1(List<Mat> observations, Mat result, double lambda)`	Primal-dual algorithm is an algorithm for solving special types of variational problems (that is, finding a function to minimize some functional).
`static void`	Photo.`denoise_TVL1(List<Mat> observations, Mat result, double lambda, int niters)`	Primal-dual algorithm is an algorithm for solving special types of variational problems (that is, finding a function to minimize some functional).
`static void`	Photo.`fastNlMeansDenoisingColoredMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize)`	Modification of fastNlMeansDenoisingMulti function for colored images sequences
`static void`	Photo.`fastNlMeansDenoisingColoredMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h)`	Modification of fastNlMeansDenoisingMulti function for colored images sequences
`static void`	Photo.`fastNlMeansDenoisingColoredMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h, float hColor)`	Modification of fastNlMeansDenoisingMulti function for colored images sequences
`static void`	Photo.`fastNlMeansDenoisingColoredMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h, float hColor, int templateWindowSize)`	Modification of fastNlMeansDenoisingMulti function for colored images sequences
`static void`	Photo.`fastNlMeansDenoisingColoredMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h, float hColor, int templateWindowSize, int searchWindowSize)`	Modification of fastNlMeansDenoisingMulti function for colored images sequences
`static void`	Photo.`fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize)`	Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time.
`static void`	Photo.`fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h)`	Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time.
`static void`	Photo.`fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h, int templateWindowSize)`	Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time.
`static void`	Photo.`fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h, int templateWindowSize, int searchWindowSize)`	Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time.
`static void`	Photo.`fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, MatOfFloat h)`	Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time.
`static void`	Photo.`fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, MatOfFloat h, int templateWindowSize)`	Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time.
`static void`	Photo.`fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, MatOfFloat h, int templateWindowSize, int searchWindowSize)`	Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time.
`static void`	Photo.`fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, MatOfFloat h, int templateWindowSize, int searchWindowSize, int normType)`	Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time.
`void`	AlignExposures.`process(List<Mat> src, List<Mat> dst, Mat times, Mat response)`	Aligns images
`void`	AlignMTB.`process(List<Mat> src, List<Mat> dst)`	Short version of process, that doesn't take extra arguments.
`void`	AlignMTB.`process(List<Mat> src, List<Mat> dst, Mat times, Mat response)`
`void`	CalibrateCRF.`process(List<Mat> src, Mat dst, Mat times)`	Recovers inverse camera response.
`void`	MergeDebevec.`process(List<Mat> src, Mat dst, Mat times)`
`void`	MergeDebevec.`process(List<Mat> src, Mat dst, Mat times, Mat response)`
`void`	MergeExposures.`process(List<Mat> src, Mat dst, Mat times, Mat response)`	Merges images.
`void`	MergeMertens.`process(List<Mat> src, Mat dst)`	Short version of process, that doesn't take extra arguments.
`void`	MergeMertens.`process(List<Mat> src, Mat dst, Mat times, Mat response)`
`void`	MergeRobertson.`process(List<Mat> src, Mat dst, Mat times)`
`void`	MergeRobertson.`process(List<Mat> src, Mat dst, Mat times, Mat response)`

Uses of Mat in org.opencv.plot

Methods in org.opencv.plot with parameters of type Mat
Modifier and Type	Method	Description
`static Plot2d`	Plot2d.`create(Mat data)`	Creates Plot2d object
`static Plot2d`	Plot2d.`create(Mat dataX, Mat dataY)`	Creates Plot2d object
`void`	Plot2d.`render(Mat _plotResult)`

Uses of Mat in org.opencv.structured_light

Methods in org.opencv.structured_light with parameters of type Mat
Modifier and Type	Method	Description
`void`	SinusoidalPattern.`computeDataModulationTerm(List<Mat> patternImages, Mat dataModulationTerm, Mat shadowMask)`	compute the data modulation term.
`void`	SinusoidalPattern.`computePhaseMap(List<Mat> patternImages, Mat wrappedPhaseMap)`	Compute a wrapped phase map from sinusoidal patterns.
`void`	SinusoidalPattern.`computePhaseMap(List<Mat> patternImages, Mat wrappedPhaseMap, Mat shadowMask)`	Compute a wrapped phase map from sinusoidal patterns.
`void`	SinusoidalPattern.`computePhaseMap(List<Mat> patternImages, Mat wrappedPhaseMap, Mat shadowMask, Mat fundamental)`	Compute a wrapped phase map from sinusoidal patterns.
`void`	SinusoidalPattern.`findProCamMatches(Mat projUnwrappedPhaseMap, Mat camUnwrappedPhaseMap, List<Mat> matches)`	Find correspondences between the two devices thanks to unwrapped phase maps.
`void`	GrayCodePattern.`getImagesForShadowMasks(Mat blackImage, Mat whiteImage)`	Generates the all-black and all-white images needed for shadowMasks computation.
`void`	SinusoidalPattern.`unwrapPhaseMap(Mat wrappedPhaseMap, Mat unwrappedPhaseMap, Size camSize)`	Unwrap the wrapped phase map to remove phase ambiguities.
`void`	SinusoidalPattern.`unwrapPhaseMap(Mat wrappedPhaseMap, Mat unwrappedPhaseMap, Size camSize, Mat shadowMask)`	Unwrap the wrapped phase map to remove phase ambiguities.

Method parameters in org.opencv.structured_light with type arguments of type Mat
Modifier and Type	Method	Description
`void`	SinusoidalPattern.`computeDataModulationTerm(List<Mat> patternImages, Mat dataModulationTerm, Mat shadowMask)`	compute the data modulation term.
`void`	SinusoidalPattern.`computePhaseMap(List<Mat> patternImages, Mat wrappedPhaseMap)`	Compute a wrapped phase map from sinusoidal patterns.
`void`	SinusoidalPattern.`computePhaseMap(List<Mat> patternImages, Mat wrappedPhaseMap, Mat shadowMask)`	Compute a wrapped phase map from sinusoidal patterns.
`void`	SinusoidalPattern.`computePhaseMap(List<Mat> patternImages, Mat wrappedPhaseMap, Mat shadowMask, Mat fundamental)`	Compute a wrapped phase map from sinusoidal patterns.
`void`	SinusoidalPattern.`findProCamMatches(Mat projUnwrappedPhaseMap, Mat camUnwrappedPhaseMap, List<Mat> matches)`	Find correspondences between the two devices thanks to unwrapped phase maps.
`boolean`	StructuredLightPattern.`generate(List<Mat> patternImages)`	Generates the structured light pattern to project.
`boolean`	GrayCodePattern.`getProjPixel(List<Mat> patternImages, int x, int y, Point projPix)`	For a (x,y) pixel of a camera returns the corresponding projector pixel.

Uses of Mat in org.opencv.text

Methods in org.opencv.text that return Mat
Modifier and Type	Method	Description
`static Mat`	Text.`createOCRHMMTransitionsTable(String vocabulary, List<String> lexicon)`	Utility function to create a tailored language model transitions table from a given list of words (lexicon).

Methods in org.opencv.text with parameters of type Mat
Modifier and Type	Method	Description
`static void`	Text.`computeNMChannels(Mat _src, List<Mat> _channels)`	Compute the different channels to be processed independently in the N&M algorithm CITE: Neumann12.
`static void`	Text.`computeNMChannels(Mat _src, List<Mat> _channels, int _mode)`	Compute the different channels to be processed independently in the N&M algorithm CITE: Neumann12.
`static OCRBeamSearchDecoder`	OCRBeamSearchDecoder.`create(OCRBeamSearchDecoder_ClassifierCallback classifier, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table)`	Creates an instance of the OCRBeamSearchDecoder class.
`static OCRBeamSearchDecoder`	OCRBeamSearchDecoder.`create(OCRBeamSearchDecoder_ClassifierCallback classifier, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode)`	Creates an instance of the OCRBeamSearchDecoder class.
`static OCRBeamSearchDecoder`	OCRBeamSearchDecoder.`create(OCRBeamSearchDecoder_ClassifierCallback classifier, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode, int beam_size)`	Creates an instance of the OCRBeamSearchDecoder class.
`static OCRHMMDecoder`	OCRHMMDecoder.`create(String filename, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table)`	Creates an instance of the OCRHMMDecoder class.
`static OCRHMMDecoder`	OCRHMMDecoder.`create(String filename, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode)`	Creates an instance of the OCRHMMDecoder class.
`static OCRHMMDecoder`	OCRHMMDecoder.`create(String filename, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode, int classifier)`	Creates an instance of the OCRHMMDecoder class.
`static OCRHMMDecoder`	OCRHMMDecoder.`create(OCRHMMDecoder_ClassifierCallback classifier, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table)`	Creates an instance of the OCRHMMDecoder class.
`static OCRHMMDecoder`	OCRHMMDecoder.`create(OCRHMMDecoder_ClassifierCallback classifier, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode)`	Creates an instance of the OCRHMMDecoder class.
`void`	TextDetector.`detect(Mat inputImage, MatOfRect Bbox, MatOfFloat confidence)`	Method that provides a quick and simple interface to detect text inside an image
`void`	TextDetectorCNN.`detect(Mat inputImage, MatOfRect Bbox, MatOfFloat confidence)`
`static void`	Text.`detectRegions(Mat image, ERFilter er_filter1, ERFilter er_filter2, List<MatOfPoint> regions)`	Converts MSER contours (vector<Point>) to ERStat regions.
`static void`	Text.`detectRegions(Mat image, ERFilter er_filter1, ERFilter er_filter2, MatOfRect groups_rects)`	Extracts text regions from image.
`static void`	Text.`detectRegions(Mat image, ERFilter er_filter1, ERFilter er_filter2, MatOfRect groups_rects, int method)`	Extracts text regions from image.
`static void`	Text.`detectRegions(Mat image, ERFilter er_filter1, ERFilter er_filter2, MatOfRect groups_rects, int method, String filename)`	Extracts text regions from image.
`static void`	Text.`detectRegions(Mat image, ERFilter er_filter1, ERFilter er_filter2, MatOfRect groups_rects, int method, String filename, float minProbability)`	Extracts text regions from image.
`static void`	Text.`detectTextSWT(Mat input, MatOfRect result, boolean dark_on_light)`	Applies the Stroke Width Transform operator followed by filtering of connected components of similar Stroke Widths to return letter candidates.
`static void`	Text.`detectTextSWT(Mat input, MatOfRect result, boolean dark_on_light, Mat draw)`	Applies the Stroke Width Transform operator followed by filtering of connected components of similar Stroke Widths to return letter candidates.
`static void`	Text.`detectTextSWT(Mat input, MatOfRect result, boolean dark_on_light, Mat draw, Mat chainBBs)`	Applies the Stroke Width Transform operator followed by filtering of connected components of similar Stroke Widths to return letter candidates.
`static void`	Text.`erGrouping(Mat image, Mat channel, List<MatOfPoint> regions, MatOfRect groups_rects)`	Find groups of Extremal Regions that are organized as text blocks.
`static void`	Text.`erGrouping(Mat image, Mat channel, List<MatOfPoint> regions, MatOfRect groups_rects, int method)`	Find groups of Extremal Regions that are organized as text blocks.
`static void`	Text.`erGrouping(Mat image, Mat channel, List<MatOfPoint> regions, MatOfRect groups_rects, int method, String filename)`	Find groups of Extremal Regions that are organized as text blocks.
`static void`	Text.`erGrouping(Mat image, Mat channel, List<MatOfPoint> regions, MatOfRect groups_rects, int method, String filename, float minProbablity)`	Find groups of Extremal Regions that are organized as text blocks.
`String`	OCRBeamSearchDecoder.`run(Mat image, int min_confidence)`	Recognize text using Beam Search.
`String`	OCRBeamSearchDecoder.`run(Mat image, int min_confidence, int component_level)`	Recognize text using Beam Search.
`String`	OCRBeamSearchDecoder.`run(Mat image, Mat mask, int min_confidence)`
`String`	OCRBeamSearchDecoder.`run(Mat image, Mat mask, int min_confidence, int component_level)`
`String`	OCRHMMDecoder.`run(Mat image, int min_confidence)`	Recognize text using HMM.
`String`	OCRHMMDecoder.`run(Mat image, int min_confidence, int component_level)`	Recognize text using HMM.
`String`	OCRHMMDecoder.`run(Mat image, Mat mask, int min_confidence)`
`String`	OCRHMMDecoder.`run(Mat image, Mat mask, int min_confidence, int component_level)`
`String`	OCRTesseract.`run(Mat image, int min_confidence)`	Recognize text using the tesseract-ocr API.
`String`	OCRTesseract.`run(Mat image, int min_confidence, int component_level)`	Recognize text using the tesseract-ocr API.
`String`	OCRTesseract.`run(Mat image, Mat mask, int min_confidence)`
`String`	OCRTesseract.`run(Mat image, Mat mask, int min_confidence, int component_level)`

Method parameters in org.opencv.text with type arguments of type Mat
Modifier and Type	Method	Description
`static void`	Text.`computeNMChannels(Mat _src, List<Mat> _channels)`	Compute the different channels to be processed independently in the N&M algorithm CITE: Neumann12.
`static void`	Text.`computeNMChannels(Mat _src, List<Mat> _channels, int _mode)`	Compute the different channels to be processed independently in the N&M algorithm CITE: Neumann12.

Uses of Mat in org.opencv.tracking

Methods in org.opencv.tracking with parameters of type Mat
Modifier and Type	Method	Description
`boolean`	legacy_MultiTracker.`add(legacy_Tracker newTracker, Mat image, Rect2d boundingBox)`	Add a new object to be tracked.
`boolean`	legacy_Tracker.`init(Mat image, Rect2d boundingBox)`	Initialize the tracker with a known bounding box that surrounded the target
`void`	legacy_TrackerCSRT.`setInitialMask(Mat mask)`
`void`	TrackerCSRT.`setInitialMask(Mat mask)`
`boolean`	legacy_MultiTracker.`update(Mat image, MatOfRect2d boundingBox)`	Update the current tracking status.
`boolean`	legacy_Tracker.`update(Mat image, Rect2d boundingBox)`	Update the tracker, find the new most likely bounding box for the target

Uses of Mat in org.opencv.utils

Methods in org.opencv.utils that return Mat
Modifier and Type	Method	Description
`static Mat`	Converters.`vector_char_to_Mat(List<Byte> bs)`
`static Mat`	Converters.`vector_DMatch_to_Mat(List<DMatch> matches)`
`static Mat`	Converters.`vector_double_to_Mat(List<Double> ds)`
`static Mat`	Converters.`vector_float_to_Mat(List<Float> fs)`
`static Mat`	Converters.`vector_int_to_Mat(List<Integer> is)`
`static Mat`	Converters.`vector_KeyPoint_to_Mat(List<KeyPoint> kps)`
`static Mat`	Converters.`vector_Mat_to_Mat(List<Mat> mats)`
`static Mat`	Converters.`vector_Point_to_Mat(List<Point> pts)`
`static Mat`	Converters.`vector_Point_to_Mat(List<Point> pts, int typeDepth)`
`static Mat`	Converters.`vector_Point2d_to_Mat(List<Point> pts)`
`static Mat`	Converters.`vector_Point2f_to_Mat(List<Point> pts)`
`static Mat`	Converters.`vector_Point3_to_Mat(List<Point3> pts, int typeDepth)`
`static Mat`	Converters.`vector_Point3d_to_Mat(List<Point3> pts)`
`static Mat`	Converters.`vector_Point3f_to_Mat(List<Point3> pts)`
`static Mat`	Converters.`vector_Point3i_to_Mat(List<Point3> pts)`
`static Mat`	Converters.`vector_Rect_to_Mat(List<Rect> rs)`
`static Mat`	Converters.`vector_Rect2d_to_Mat(List<Rect2d> rs)`
`static Mat`	Converters.`vector_RotatedRect_to_Mat(List<RotatedRect> rs)`
`static Mat`	Converters.`vector_uchar_to_Mat(List<Byte> bs)`
`static Mat`	Converters.`vector_vector_char_to_Mat(List<MatOfByte> lvb, List<Mat> mats)`
`static Mat`	Converters.`vector_vector_DMatch_to_Mat(List<MatOfDMatch> lvdm, List<Mat> mats)`
`static Mat`	Converters.`vector_vector_KeyPoint_to_Mat(List<MatOfKeyPoint> kps, List<Mat> mats)`
`static Mat`	Converters.`vector_vector_Point_to_Mat(List<MatOfPoint> pts, List<Mat> mats)`
`static Mat`	Converters.`vector_vector_Point2f_to_Mat(List<MatOfPoint2f> pts, List<Mat> mats)`
`static Mat`	Converters.`vector_vector_Point3f_to_Mat(List<MatOfPoint3f> pts, List<Mat> mats)`

Methods in org.opencv.utils with parameters of type Mat
Modifier and Type	Method	Description
`static void`	Converters.`Mat_to_vector_char(Mat m, List<Byte> bs)`
`static void`	Converters.`Mat_to_vector_DMatch(Mat m, List<DMatch> matches)`
`static void`	Converters.`Mat_to_vector_double(Mat m, List<Double> ds)`
`static void`	Converters.`Mat_to_vector_float(Mat m, List<Float> fs)`
`static void`	Converters.`Mat_to_vector_int(Mat m, List<Integer> is)`
`static void`	Converters.`Mat_to_vector_KeyPoint(Mat m, List<KeyPoint> kps)`
`static void`	Converters.`Mat_to_vector_Mat(Mat m, List<Mat> mats)`
`static void`	Converters.`Mat_to_vector_Point(Mat m, List<Point> pts)`
`static void`	Converters.`Mat_to_vector_Point2d(Mat m, List<Point> pts)`
`static void`	Converters.`Mat_to_vector_Point2f(Mat m, List<Point> pts)`
`static void`	Converters.`Mat_to_vector_Point3(Mat m, List<Point3> pts)`
`static void`	Converters.`Mat_to_vector_Point3d(Mat m, List<Point3> pts)`
`static void`	Converters.`Mat_to_vector_Point3f(Mat m, List<Point3> pts)`
`static void`	Converters.`Mat_to_vector_Point3i(Mat m, List<Point3> pts)`
`static void`	Converters.`Mat_to_vector_Rect(Mat m, List<Rect> rs)`
`static void`	Converters.`Mat_to_vector_Rect2d(Mat m, List<Rect2d> rs)`
`static void`	Converters.`Mat_to_vector_RotatedRect(Mat m, List<RotatedRect> rs)`
`static void`	Converters.`Mat_to_vector_uchar(Mat m, List<Byte> us)`
`static void`	Converters.`Mat_to_vector_vector_char(Mat m, List<List<Byte>> llb)`
`static void`	Converters.`Mat_to_vector_vector_DMatch(Mat m, List<MatOfDMatch> lvdm)`
`static void`	Converters.`Mat_to_vector_vector_KeyPoint(Mat m, List<MatOfKeyPoint> kps)`
`static void`	Converters.`Mat_to_vector_vector_Point(Mat m, List<MatOfPoint> pts)`
`static void`	Converters.`Mat_to_vector_vector_Point2f(Mat m, List<MatOfPoint2f> pts)`
`static void`	Converters.`Mat_to_vector_vector_Point3f(Mat m, List<MatOfPoint3f> pts)`

Method parameters in org.opencv.utils with type arguments of type Mat
Modifier and Type	Method	Description
`static void`	Converters.`Mat_to_vector_Mat(Mat m, List<Mat> mats)`
`static Mat`	Converters.`vector_Mat_to_Mat(List<Mat> mats)`

Uses of Mat in org.opencv.video

Methods in org.opencv.video that return Mat
Modifier and Type	Method	Description
`Mat`	KalmanFilter.`correct(Mat measurement)`	Updates the predicted state from the measurement.
`Mat`	KalmanFilter.`get_controlMatrix()`
`Mat`	KalmanFilter.`get_errorCovPost()`
`Mat`	KalmanFilter.`get_errorCovPre()`
`Mat`	KalmanFilter.`get_gain()`
`Mat`	KalmanFilter.`get_measurementMatrix()`
`Mat`	KalmanFilter.`get_measurementNoiseCov()`
`Mat`	KalmanFilter.`get_processNoiseCov()`
`Mat`	KalmanFilter.`get_statePost()`
`Mat`	KalmanFilter.`get_statePre()`
`Mat`	KalmanFilter.`get_transitionMatrix()`
`Mat`	KalmanFilter.`predict()`	Computes a predicted state.
`Mat`	KalmanFilter.`predict(Mat control)`	Computes a predicted state.
`static Mat`	Video.`readOpticalFlow(String path)`	Read a .flo file

Methods in org.opencv.video with parameters of type Mat
Modifier and Type	Method	Description
`void`	BackgroundSubtractor.`apply(Mat image, Mat fgmask)`	Computes a foreground mask.
`void`	BackgroundSubtractor.`apply(Mat image, Mat fgmask, double learningRate)`	Computes a foreground mask.
`void`	BackgroundSubtractorMOG2.`apply(Mat image, Mat fgmask)`	Computes a foreground mask.
`void`	BackgroundSubtractorMOG2.`apply(Mat image, Mat fgmask, double learningRate)`	Computes a foreground mask.
`static int`	Video.`buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel)`	Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
`static int`	Video.`buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel, boolean withDerivatives)`	Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
`static int`	Video.`buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel, boolean withDerivatives, int pyrBorder)`	Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
`static int`	Video.`buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel, boolean withDerivatives, int pyrBorder, int derivBorder)`	Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
`static int`	Video.`buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel, boolean withDerivatives, int pyrBorder, int derivBorder, boolean tryReuseInputImage)`	Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
`void`	DenseOpticalFlow.`calc(Mat I0, Mat I1, Mat flow)`	Calculates an optical flow.
`void`	SparseOpticalFlow.`calc(Mat prevImg, Mat nextImg, Mat prevPts, Mat nextPts, Mat status)`	Calculates a sparse optical flow.
`void`	SparseOpticalFlow.`calc(Mat prevImg, Mat nextImg, Mat prevPts, Mat nextPts, Mat status, Mat err)`	Calculates a sparse optical flow.
`static void`	Video.`calcOpticalFlowFarneback(Mat prev, Mat next, Mat flow, double pyr_scale, int levels, int winsize, int iterations, int poly_n, double poly_sigma, int flags)`	Computes a dense optical flow using the Gunnar Farneback's algorithm.
`static void`	Video.`calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err)`	Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with pyramids.
`static void`	Video.`calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err, Size winSize)`	Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with pyramids.
`static void`	Video.`calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err, Size winSize, int maxLevel)`	Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with pyramids.
`static void`	Video.`calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err, Size winSize, int maxLevel, TermCriteria criteria)`	Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with pyramids.
`static void`	Video.`calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err, Size winSize, int maxLevel, TermCriteria criteria, int flags)`	Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with pyramids.
`static void`	Video.`calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err, Size winSize, int maxLevel, TermCriteria criteria, int flags, double minEigThreshold)`	Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with pyramids.
`void`	VariationalRefinement.`calcUV(Mat I0, Mat I1, Mat flow_u, Mat flow_v)`	REF: calc function overload to handle separate horizontal (u) and vertical (v) flow components (to avoid extra splits/merges)
`static RotatedRect`	Video.`CamShift(Mat probImage, Rect window, TermCriteria criteria)`	Finds an object center, size, and orientation.
`static double`	Video.`computeECC(Mat templateImage, Mat inputImage)`	Computes the Enhanced Correlation Coefficient value between two images CITE: EP08 .
`static double`	Video.`computeECC(Mat templateImage, Mat inputImage, Mat inputMask)`	Computes the Enhanced Correlation Coefficient value between two images CITE: EP08 .
`Mat`	KalmanFilter.`correct(Mat measurement)`	Updates the predicted state from the measurement.
`static double`	Video.`findTransformECC(Mat templateImage, Mat inputImage, Mat warpMatrix)`
`static double`	Video.`findTransformECC(Mat templateImage, Mat inputImage, Mat warpMatrix, int motionType)`
`static double`	Video.`findTransformECC(Mat templateImage, Mat inputImage, Mat warpMatrix, int motionType, TermCriteria criteria)`
`static double`	Video.`findTransformECC(Mat templateImage, Mat inputImage, Mat warpMatrix, int motionType, TermCriteria criteria, Mat inputMask)`
`static double`	Video.`findTransformECC(Mat templateImage, Mat inputImage, Mat warpMatrix, int motionType, TermCriteria criteria, Mat inputMask, int gaussFiltSize)`	Finds the geometric transform (warp) between two images in terms of the ECC criterion CITE: EP08 .
`void`	BackgroundSubtractor.`getBackgroundImage(Mat backgroundImage)`	Computes a background image.
`void`	Tracker.`init(Mat image, Rect boundingBox)`	Initialize the tracker with a known bounding box that surrounded the target
`static int`	Video.`meanShift(Mat probImage, Rect window, TermCriteria criteria)`	Finds an object on a back projection image.
`Mat`	KalmanFilter.`predict(Mat control)`	Computes a predicted state.
`void`	KalmanFilter.`set_controlMatrix(Mat controlMatrix)`
`void`	KalmanFilter.`set_errorCovPost(Mat errorCovPost)`
`void`	KalmanFilter.`set_errorCovPre(Mat errorCovPre)`
`void`	KalmanFilter.`set_gain(Mat gain)`
`void`	KalmanFilter.`set_measurementMatrix(Mat measurementMatrix)`
`void`	KalmanFilter.`set_measurementNoiseCov(Mat measurementNoiseCov)`
`void`	KalmanFilter.`set_processNoiseCov(Mat processNoiseCov)`
`void`	KalmanFilter.`set_statePost(Mat statePost)`
`void`	KalmanFilter.`set_statePre(Mat statePre)`
`void`	KalmanFilter.`set_transitionMatrix(Mat transitionMatrix)`
`boolean`	Tracker.`update(Mat image, Rect boundingBox)`	Update the tracker, find the new most likely bounding box for the target
`static boolean`	Video.`writeOpticalFlow(String path, Mat flow)`	Write a .flo to disk

Method parameters in org.opencv.video with type arguments of type Mat
Modifier and Type	Method	Description
`static int`	Video.`buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel)`	Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
`static int`	Video.`buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel, boolean withDerivatives)`	Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
`static int`	Video.`buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel, boolean withDerivatives, int pyrBorder)`	Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
`static int`	Video.`buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel, boolean withDerivatives, int pyrBorder, int derivBorder)`	Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
`static int`	Video.`buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel, boolean withDerivatives, int pyrBorder, int derivBorder, boolean tryReuseInputImage)`	Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.

Uses of Mat in org.opencv.videoio

Methods in org.opencv.videoio with parameters of type Mat
Modifier and Type	Method	Description
`boolean`	VideoCapture.`read(Mat image)`	Grabs, decodes and returns the next video frame.
`boolean`	VideoCapture.`retrieve(Mat image)`	Decodes and returns the grabbed video frame.
`boolean`	VideoCapture.`retrieve(Mat image, int flag)`	Decodes and returns the grabbed video frame.
`void`	VideoWriter.`write(Mat image)`	Writes the next video frame

Uses of Mat in org.opencv.wechat_qrcode

Methods in org.opencv.wechat_qrcode with parameters of type Mat
Modifier and Type	Method	Description
`List<String>`	WeChatQRCode.`detectAndDecode(Mat img)`	Both detects and decodes QR code.
`List<String>`	WeChatQRCode.`detectAndDecode(Mat img, List<Mat> points)`	Both detects and decodes QR code.

Method parameters in org.opencv.wechat_qrcode with type arguments of type Mat
Modifier and Type	Method	Description
`List<String>`	WeChatQRCode.`detectAndDecode(Mat img, List<Mat> points)`	Both detects and decodes QR code.

Uses of Mat in org.opencv.xfeatures2d

Methods in org.opencv.xfeatures2d with parameters of type Mat
Modifier and Type	Method	Description
`float`	PCTSignaturesSQFD.`computeQuadraticFormDistance(Mat _signature0, Mat _signature1)`	Computes Signature Quadratic Form Distance of two signatures.
`void`	PCTSignaturesSQFD.`computeQuadraticFormDistances(Mat sourceSignature, List<Mat> imageSignatures, MatOfFloat distances)`	Computes Signature Quadratic Form Distance between the reference signature and each of the other image signatures.
`void`	PCTSignatures.`computeSignature(Mat image, Mat signature)`	Computes signature of given image.
`static DAISY`	DAISY.`create(float radius, int q_radius, int q_theta, int q_hist, Mat H)`
`static DAISY`	DAISY.`create(float radius, int q_radius, int q_theta, int q_hist, Mat H, boolean interpolation)`
`static DAISY`	DAISY.`create(float radius, int q_radius, int q_theta, int q_hist, Mat H, boolean interpolation, boolean use_orientation)`
`static void`	PCTSignatures.`drawSignature(Mat source, Mat signature, Mat result)`	Draws signature in the source image and outputs the result.
`static void`	PCTSignatures.`drawSignature(Mat source, Mat signature, Mat result, float radiusToShorterSideRatio)`	Draws signature in the source image and outputs the result.
`static void`	PCTSignatures.`drawSignature(Mat source, Mat signature, Mat result, float radiusToShorterSideRatio, int borderThickness)`	Draws signature in the source image and outputs the result.

Method parameters in org.opencv.xfeatures2d with type arguments of type Mat
Modifier and Type	Method	Description
`void`	PCTSignaturesSQFD.`computeQuadraticFormDistances(Mat sourceSignature, List<Mat> imageSignatures, MatOfFloat distances)`	Computes Signature Quadratic Form Distance between the reference signature and each of the other image signatures.
`void`	PCTSignatures.`computeSignatures(List<Mat> images, List<Mat> signatures)`	Computes signatures for multiple images in parallel.

Uses of Mat in org.opencv.ximgproc

Methods in org.opencv.ximgproc that return Mat
Modifier and Type	Method	Description
`Mat`	DisparityWLSFilter.`getConfidenceMap()`	Get the confidence map that was used in the last filter call.

Methods in org.opencv.ximgproc with parameters of type Mat
Modifier and Type	Method	Description
`void`	SelectiveSearchSegmentation.`addImage(Mat img)`	Add a new image in the list of images to process.
`static void`	Ximgproc.`amFilter(Mat joint, Mat src, Mat dst, double sigma_s, double sigma_r)`	Simple one-line Adaptive Manifold Filter call.
`static void`	Ximgproc.`amFilter(Mat joint, Mat src, Mat dst, double sigma_s, double sigma_r, boolean adjust_outliers)`	Simple one-line Adaptive Manifold Filter call.
`static void`	Ximgproc.`anisotropicDiffusion(Mat src, Mat dst, float alpha, float K, int niters)`	Performs anisotropic diffusion on an image.
`static void`	Ximgproc.`bilateralTextureFilter(Mat src, Mat dst)`	Applies the bilateral texture filter to an image.
`static void`	Ximgproc.`bilateralTextureFilter(Mat src, Mat dst, int fr)`	Applies the bilateral texture filter to an image.
`static void`	Ximgproc.`bilateralTextureFilter(Mat src, Mat dst, int fr, int numIter)`	Applies the bilateral texture filter to an image.
`static void`	Ximgproc.`bilateralTextureFilter(Mat src, Mat dst, int fr, int numIter, double sigmaAlpha)`	Applies the bilateral texture filter to an image.
`static void`	Ximgproc.`bilateralTextureFilter(Mat src, Mat dst, int fr, int numIter, double sigmaAlpha, double sigmaAvg)`	Applies the bilateral texture filter to an image.
`static void`	Ximgproc.`colorMatchTemplate(Mat img, Mat templ, Mat result)`	Compares a color template against overlapped color image regions.
`static double`	Ximgproc.`computeBadPixelPercent(Mat GT, Mat src, Rect ROI)`	Function for computing the percent of "bad" pixels in the disparity map (pixels where error is higher than a specified threshold)
`static double`	Ximgproc.`computeBadPixelPercent(Mat GT, Mat src, Rect ROI, int thresh)`	Function for computing the percent of "bad" pixels in the disparity map (pixels where error is higher than a specified threshold)
`static double`	Ximgproc.`computeMSE(Mat GT, Mat src, Rect ROI)`	Function for computing mean square error for disparity maps
`void`	StructuredEdgeDetection.`computeOrientation(Mat _src, Mat _dst)`	The function computes orientation from edge image.
`static void`	Ximgproc.`contourSampling(Mat src, Mat out, int nbElt)`	Contour sampling .
`static void`	Ximgproc.`covarianceEstimation(Mat src, Mat dst, int windowRows, int windowCols)`	Computes the estimated covariance matrix of an image using the sliding window forumlation.
`static DTFilter`	Ximgproc.`createDTFilter(Mat guide, double sigmaSpatial, double sigmaColor)`	Factory method, create instance of DTFilter and produce initialization routines.
`static DTFilter`	Ximgproc.`createDTFilter(Mat guide, double sigmaSpatial, double sigmaColor, int mode)`	Factory method, create instance of DTFilter and produce initialization routines.
`static DTFilter`	Ximgproc.`createDTFilter(Mat guide, double sigmaSpatial, double sigmaColor, int mode, int numIters)`	Factory method, create instance of DTFilter and produce initialization routines.
`static FastBilateralSolverFilter`	Ximgproc.`createFastBilateralSolverFilter(Mat guide, double sigma_spatial, double sigma_luma, double sigma_chroma)`	Factory method, create instance of FastBilateralSolverFilter and execute the initialization routines.
`static FastBilateralSolverFilter`	Ximgproc.`createFastBilateralSolverFilter(Mat guide, double sigma_spatial, double sigma_luma, double sigma_chroma, double lambda)`	Factory method, create instance of FastBilateralSolverFilter and execute the initialization routines.
`static FastBilateralSolverFilter`	Ximgproc.`createFastBilateralSolverFilter(Mat guide, double sigma_spatial, double sigma_luma, double sigma_chroma, double lambda, int num_iter)`	Factory method, create instance of FastBilateralSolverFilter and execute the initialization routines.
`static FastBilateralSolverFilter`	Ximgproc.`createFastBilateralSolverFilter(Mat guide, double sigma_spatial, double sigma_luma, double sigma_chroma, double lambda, int num_iter, double max_tol)`	Factory method, create instance of FastBilateralSolverFilter and execute the initialization routines.
`static FastGlobalSmootherFilter`	Ximgproc.`createFastGlobalSmootherFilter(Mat guide, double lambda, double sigma_color)`	Factory method, create instance of FastGlobalSmootherFilter and execute the initialization routines.
`static FastGlobalSmootherFilter`	Ximgproc.`createFastGlobalSmootherFilter(Mat guide, double lambda, double sigma_color, double lambda_attenuation)`	Factory method, create instance of FastGlobalSmootherFilter and execute the initialization routines.
`static FastGlobalSmootherFilter`	Ximgproc.`createFastGlobalSmootherFilter(Mat guide, double lambda, double sigma_color, double lambda_attenuation, int num_iter)`	Factory method, create instance of FastGlobalSmootherFilter and execute the initialization routines.
`static GuidedFilter`	Ximgproc.`createGuidedFilter(Mat guide, int radius, double eps)`	Factory method, create instance of GuidedFilter and produce initialization routines.
`static void`	Ximgproc.`createQuaternionImage(Mat img, Mat qimg)`	creates a quaternion image.
`static SuperpixelLSC`	Ximgproc.`createSuperpixelLSC(Mat image)`	Class implementing the LSC (Linear Spectral Clustering) superpixels
`static SuperpixelLSC`	Ximgproc.`createSuperpixelLSC(Mat image, int region_size)`	Class implementing the LSC (Linear Spectral Clustering) superpixels
`static SuperpixelLSC`	Ximgproc.`createSuperpixelLSC(Mat image, int region_size, float ratio)`	Class implementing the LSC (Linear Spectral Clustering) superpixels
`static SuperpixelSLIC`	Ximgproc.`createSuperpixelSLIC(Mat image)`	Initialize a SuperpixelSLIC object
`static SuperpixelSLIC`	Ximgproc.`createSuperpixelSLIC(Mat image, int algorithm)`	Initialize a SuperpixelSLIC object
`static SuperpixelSLIC`	Ximgproc.`createSuperpixelSLIC(Mat image, int algorithm, int region_size)`	Initialize a SuperpixelSLIC object
`static SuperpixelSLIC`	Ximgproc.`createSuperpixelSLIC(Mat image, int algorithm, int region_size, float ruler)`	Initialize a SuperpixelSLIC object
`void`	FastLineDetector.`detect(Mat image, Mat lines)`	Finds lines in the input image.
`void`	EdgeDrawing.`detectEdges(Mat src)`	Detects edges and prepares them to detect lines and ellipses.
`void`	StructuredEdgeDetection.`detectEdges(Mat _src, Mat _dst)`	The function detects edges in src and draw them to dst.
`void`	EdgeDrawing.`detectEllipses(Mat ellipses)`	Detects circles and ellipses.
`void`	EdgeDrawing.`detectLines(Mat lines)`	Detects lines.
`void`	FastLineDetector.`drawSegments(Mat image, Mat lines)`	Draws the line segments on a given image.
`void`	FastLineDetector.`drawSegments(Mat image, Mat lines, boolean draw_arrow)`	Draws the line segments on a given image.
`void`	FastLineDetector.`drawSegments(Mat image, Mat lines, boolean draw_arrow, Scalar linecolor)`	Draws the line segments on a given image.
`void`	FastLineDetector.`drawSegments(Mat image, Mat lines, boolean draw_arrow, Scalar linecolor, int linethickness)`	Draws the line segments on a given image.
`static void`	Ximgproc.`dtFilter(Mat guide, Mat src, Mat dst, double sigmaSpatial, double sigmaColor)`	Simple one-line Domain Transform filter call.
`static void`	Ximgproc.`dtFilter(Mat guide, Mat src, Mat dst, double sigmaSpatial, double sigmaColor, int mode)`	Simple one-line Domain Transform filter call.
`static void`	Ximgproc.`dtFilter(Mat guide, Mat src, Mat dst, double sigmaSpatial, double sigmaColor, int mode, int numIters)`	Simple one-line Domain Transform filter call.
`static void`	Ximgproc.`edgePreservingFilter(Mat src, Mat dst, int d, double threshold)`	Smoothes an image using the Edge-Preserving filter.
`void`	StructuredEdgeDetection.`edgesNms(Mat edge_image, Mat orientation_image, Mat _dst)`	The function edgenms in edge image and suppress edges where edge is stronger in orthogonal direction.
`void`	StructuredEdgeDetection.`edgesNms(Mat edge_image, Mat orientation_image, Mat _dst, int r)`	The function edgenms in edge image and suppress edges where edge is stronger in orthogonal direction.
`void`	StructuredEdgeDetection.`edgesNms(Mat edge_image, Mat orientation_image, Mat _dst, int r, int s)`	The function edgenms in edge image and suppress edges where edge is stronger in orthogonal direction.
`void`	StructuredEdgeDetection.`edgesNms(Mat edge_image, Mat orientation_image, Mat _dst, int r, int s, float m)`	The function edgenms in edge image and suppress edges where edge is stronger in orthogonal direction.
`void`	StructuredEdgeDetection.`edgesNms(Mat edge_image, Mat orientation_image, Mat _dst, int r, int s, float m, boolean isParallel)`	The function edgenms in edge image and suppress edges where edge is stronger in orthogonal direction.
`void`	ContourFitting.`estimateTransformation(Mat src, Mat dst, Mat alphaPhiST, double[] dist)`	Fit two closed curves using fourier descriptors.
`void`	ContourFitting.`estimateTransformation(Mat src, Mat dst, Mat alphaPhiST, double[] dist, boolean fdContour)`	Fit two closed curves using fourier descriptors.
`static void`	Ximgproc.`fastBilateralSolverFilter(Mat guide, Mat src, Mat confidence, Mat dst)`	Simple one-line Fast Bilateral Solver filter call.
`static void`	Ximgproc.`fastBilateralSolverFilter(Mat guide, Mat src, Mat confidence, Mat dst, double sigma_spatial)`	Simple one-line Fast Bilateral Solver filter call.
`static void`	Ximgproc.`fastBilateralSolverFilter(Mat guide, Mat src, Mat confidence, Mat dst, double sigma_spatial, double sigma_luma)`	Simple one-line Fast Bilateral Solver filter call.
`static void`	Ximgproc.`fastBilateralSolverFilter(Mat guide, Mat src, Mat confidence, Mat dst, double sigma_spatial, double sigma_luma, double sigma_chroma)`	Simple one-line Fast Bilateral Solver filter call.
`static void`	Ximgproc.`fastBilateralSolverFilter(Mat guide, Mat src, Mat confidence, Mat dst, double sigma_spatial, double sigma_luma, double sigma_chroma, double lambda)`	Simple one-line Fast Bilateral Solver filter call.
`static void`	Ximgproc.`fastBilateralSolverFilter(Mat guide, Mat src, Mat confidence, Mat dst, double sigma_spatial, double sigma_luma, double sigma_chroma, double lambda, int num_iter)`	Simple one-line Fast Bilateral Solver filter call.
`static void`	Ximgproc.`fastBilateralSolverFilter(Mat guide, Mat src, Mat confidence, Mat dst, double sigma_spatial, double sigma_luma, double sigma_chroma, double lambda, int num_iter, double max_tol)`	Simple one-line Fast Bilateral Solver filter call.
`static void`	Ximgproc.`fastGlobalSmootherFilter(Mat guide, Mat src, Mat dst, double lambda, double sigma_color)`	Simple one-line Fast Global Smoother filter call.
`static void`	Ximgproc.`fastGlobalSmootherFilter(Mat guide, Mat src, Mat dst, double lambda, double sigma_color, double lambda_attenuation)`	Simple one-line Fast Global Smoother filter call.
`static void`	Ximgproc.`fastGlobalSmootherFilter(Mat guide, Mat src, Mat dst, double lambda, double sigma_color, double lambda_attenuation, int num_iter)`	Simple one-line Fast Global Smoother filter call.
`static void`	Ximgproc.`FastHoughTransform(Mat src, Mat dst, int dstMatDepth)`	Calculates 2D Fast Hough transform of an image.
`static void`	Ximgproc.`FastHoughTransform(Mat src, Mat dst, int dstMatDepth, int angleRange)`	Calculates 2D Fast Hough transform of an image.
`static void`	Ximgproc.`FastHoughTransform(Mat src, Mat dst, int dstMatDepth, int angleRange, int op)`	Calculates 2D Fast Hough transform of an image.
`static void`	Ximgproc.`FastHoughTransform(Mat src, Mat dst, int dstMatDepth, int angleRange, int op, int makeSkew)`	Calculates 2D Fast Hough transform of an image.
`void`	AdaptiveManifoldFilter.`filter(Mat src, Mat dst)`	Apply high-dimensional filtering using adaptive manifolds.
`void`	AdaptiveManifoldFilter.`filter(Mat src, Mat dst, Mat joint)`	Apply high-dimensional filtering using adaptive manifolds.
`void`	DisparityFilter.`filter(Mat disparity_map_left, Mat left_view, Mat filtered_disparity_map)`	Apply filtering to the disparity map.
`void`	DisparityFilter.`filter(Mat disparity_map_left, Mat left_view, Mat filtered_disparity_map, Mat disparity_map_right)`	Apply filtering to the disparity map.
`void`	DisparityFilter.`filter(Mat disparity_map_left, Mat left_view, Mat filtered_disparity_map, Mat disparity_map_right, Rect ROI)`	Apply filtering to the disparity map.
`void`	DisparityFilter.`filter(Mat disparity_map_left, Mat left_view, Mat filtered_disparity_map, Mat disparity_map_right, Rect ROI, Mat right_view)`	Apply filtering to the disparity map.
`void`	DTFilter.`filter(Mat src, Mat dst)`	Produce domain transform filtering operation on source image.
`void`	DTFilter.`filter(Mat src, Mat dst, int dDepth)`	Produce domain transform filtering operation on source image.
`void`	FastBilateralSolverFilter.`filter(Mat src, Mat confidence, Mat dst)`	Apply smoothing operation to the source image.
`void`	FastGlobalSmootherFilter.`filter(Mat src, Mat dst)`	Apply smoothing operation to the source image.
`void`	GuidedFilter.`filter(Mat src, Mat dst)`	Apply Guided Filter to the filtering image.
`void`	GuidedFilter.`filter(Mat src, Mat dst, int dDepth)`	Apply Guided Filter to the filtering image.
`static void`	Ximgproc.`fourierDescriptor(Mat src, Mat dst)`	Fourier descriptors for planed closed curves For more details about this implementation, please see CITE: PersoonFu1977
`static void`	Ximgproc.`fourierDescriptor(Mat src, Mat dst, int nbElt)`	Fourier descriptors for planed closed curves For more details about this implementation, please see CITE: PersoonFu1977
`static void`	Ximgproc.`fourierDescriptor(Mat src, Mat dst, int nbElt, int nbFD)`	Fourier descriptors for planed closed curves For more details about this implementation, please see CITE: PersoonFu1977
`void`	EdgeBoxes.`getBoundingBoxes(Mat edge_map, Mat orientation_map, MatOfRect boxes)`	Returns array containing proposal boxes.
`void`	EdgeBoxes.`getBoundingBoxes(Mat edge_map, Mat orientation_map, MatOfRect boxes, Mat scores)`	Returns array containing proposal boxes.
`static void`	Ximgproc.`getDisparityVis(Mat src, Mat dst)`	Function for creating a disparity map visualization (clamped CV_8U image)
`static void`	Ximgproc.`getDisparityVis(Mat src, Mat dst, double scale)`	Function for creating a disparity map visualization (clamped CV_8U image)
`void`	EdgeDrawing.`getEdgeImage(Mat dst)`
`void`	RFFeatureGetter.`getFeatures(Mat src, Mat features, int gnrmRad, int gsmthRad, int shrink, int outNum, int gradNum)`
`void`	EdgeDrawing.`getGradientImage(Mat dst)`
`void`	SuperpixelLSC.`getLabelContourMask(Mat image)`	Returns the mask of the superpixel segmentation stored in SuperpixelLSC object.
`void`	SuperpixelLSC.`getLabelContourMask(Mat image, boolean thick_line)`	Returns the mask of the superpixel segmentation stored in SuperpixelLSC object.
`void`	SuperpixelSEEDS.`getLabelContourMask(Mat image)`	Returns the mask of the superpixel segmentation stored in SuperpixelSEEDS object.
`void`	SuperpixelSEEDS.`getLabelContourMask(Mat image, boolean thick_line)`	Returns the mask of the superpixel segmentation stored in SuperpixelSEEDS object.
`void`	SuperpixelSLIC.`getLabelContourMask(Mat image)`	Returns the mask of the superpixel segmentation stored in SuperpixelSLIC object.
`void`	SuperpixelSLIC.`getLabelContourMask(Mat image, boolean thick_line)`	Returns the mask of the superpixel segmentation stored in SuperpixelSLIC object.
`void`	SuperpixelLSC.`getLabels(Mat labels_out)`	Returns the segmentation labeling of the image.
`void`	SuperpixelSEEDS.`getLabels(Mat labels_out)`	Returns the segmentation labeling of the image.
`void`	SuperpixelSLIC.`getLabels(Mat labels_out)`	Returns the segmentation labeling of the image.
`void`	RidgeDetectionFilter.`getRidgeFilteredImage(Mat _img, Mat out)`	Apply Ridge detection filter on input image.
`static void`	Ximgproc.`GradientDericheX(Mat op, Mat dst, double alpha, double omega)`	Applies X Deriche filter to an image.
`static void`	Ximgproc.`GradientDericheY(Mat op, Mat dst, double alpha, double omega)`	Applies Y Deriche filter to an image.
`static void`	Ximgproc.`guidedFilter(Mat guide, Mat src, Mat dst, int radius, double eps)`	Simple one-line Guided Filter call.
`static void`	Ximgproc.`guidedFilter(Mat guide, Mat src, Mat dst, int radius, double eps, int dDepth)`	Simple one-line Guided Filter call.
`void`	SparseMatchInterpolator.`interpolate(Mat from_image, Mat from_points, Mat to_image, Mat to_points, Mat dense_flow)`	Interpolate input sparse matches.
`void`	SuperpixelSEEDS.`iterate(Mat img)`	Calculates the superpixel segmentation on a given image with the initialized parameters in the SuperpixelSEEDS object.
`void`	SuperpixelSEEDS.`iterate(Mat img, int num_iterations)`	Calculates the superpixel segmentation on a given image with the initialized parameters in the SuperpixelSEEDS object.
`static void`	Ximgproc.`jointBilateralFilter(Mat joint, Mat src, Mat dst, int d, double sigmaColor, double sigmaSpace)`	Applies the joint bilateral filter to an image.
`static void`	Ximgproc.`jointBilateralFilter(Mat joint, Mat src, Mat dst, int d, double sigmaColor, double sigmaSpace, int borderType)`	Applies the joint bilateral filter to an image.
`static void`	Ximgproc.`l0Smooth(Mat src, Mat dst)`	Global image smoothing via L0 gradient minimization.
`static void`	Ximgproc.`l0Smooth(Mat src, Mat dst, double lambda)`	Global image smoothing via L0 gradient minimization.
`static void`	Ximgproc.`l0Smooth(Mat src, Mat dst, double lambda, double kappa)`	Global image smoothing via L0 gradient minimization.
`static void`	Ximgproc.`niBlackThreshold(Mat _src, Mat _dst, double maxValue, int type, int blockSize, double k)`	Performs thresholding on input images using Niblack's technique or some of the popular variations it inspired.
`static void`	Ximgproc.`niBlackThreshold(Mat _src, Mat _dst, double maxValue, int type, int blockSize, double k, int binarizationMethod)`	Performs thresholding on input images using Niblack's technique or some of the popular variations it inspired.
`static void`	Ximgproc.`niBlackThreshold(Mat _src, Mat _dst, double maxValue, int type, int blockSize, double k, int binarizationMethod, double r)`	Performs thresholding on input images using Niblack's technique or some of the popular variations it inspired.
`static void`	Ximgproc.`PeiLinNormalization(Mat I, Mat T)`
`void`	GraphSegmentation.`processImage(Mat src, Mat dst)`	Segment an image and store output in dst
`static void`	Ximgproc.`qconj(Mat qimg, Mat qcimg)`	calculates conjugate of a quaternion image.
`static void`	Ximgproc.`qdft(Mat img, Mat qimg, int flags, boolean sideLeft)`	Performs a forward or inverse Discrete quaternion Fourier transform of a 2D quaternion array.
`static void`	Ximgproc.`qmultiply(Mat src1, Mat src2, Mat dst)`	Calculates the per-element quaternion product of two arrays
`static void`	Ximgproc.`qunitary(Mat qimg, Mat qnimg)`	divides each element by its modulus.
`static int`	Ximgproc.`readGT(String src_path, Mat dst)`	Function for reading ground truth disparity maps.
`static void`	Ximgproc.`rollingGuidanceFilter(Mat src, Mat dst)`	Applies the rolling guidance filter to an image.
`static void`	Ximgproc.`rollingGuidanceFilter(Mat src, Mat dst, int d)`	Applies the rolling guidance filter to an image.
`static void`	Ximgproc.`rollingGuidanceFilter(Mat src, Mat dst, int d, double sigmaColor)`	Applies the rolling guidance filter to an image.
`static void`	Ximgproc.`rollingGuidanceFilter(Mat src, Mat dst, int d, double sigmaColor, double sigmaSpace)`	Applies the rolling guidance filter to an image.
`static void`	Ximgproc.`rollingGuidanceFilter(Mat src, Mat dst, int d, double sigmaColor, double sigmaSpace, int numOfIter)`	Applies the rolling guidance filter to an image.
`static void`	Ximgproc.`rollingGuidanceFilter(Mat src, Mat dst, int d, double sigmaColor, double sigmaSpace, int numOfIter, int borderType)`	Applies the rolling guidance filter to an image.
`void`	SelectiveSearchSegmentation.`setBaseImage(Mat img)`	Set a image used by switch* functions to initialize the class
`void`	EdgeAwareInterpolator.`setCostMap(Mat _costMap)`	Interface to provide a more elaborated cost map, i.e.
`void`	RICInterpolator.`setCostMap(Mat costMap)`	Interface to provide a more elaborated cost map, i.e.
`void`	SelectiveSearchSegmentationStrategy.`setImage(Mat img, Mat regions, Mat sizes)`	Set a initial image, with a segmentation.
`void`	SelectiveSearchSegmentationStrategy.`setImage(Mat img, Mat regions, Mat sizes, int image_id)`	Set a initial image, with a segmentation.
`static void`	Ximgproc.`thinning(Mat src, Mat dst)`	Applies a binary blob thinning operation, to achieve a skeletization of the input image.
`static void`	Ximgproc.`thinning(Mat src, Mat dst, int thinningType)`	Applies a binary blob thinning operation, to achieve a skeletization of the input image.
`static void`	Ximgproc.`transformFD(Mat src, Mat t, Mat dst)`	transform a contour
`static void`	Ximgproc.`transformFD(Mat src, Mat t, Mat dst, boolean fdContour)`	transform a contour
`static void`	Ximgproc.`weightedMedianFilter(Mat joint, Mat src, Mat dst, int r)`	Applies weighted median filter to an image.
`static void`	Ximgproc.`weightedMedianFilter(Mat joint, Mat src, Mat dst, int r, double sigma)`	Applies weighted median filter to an image.
`static void`	Ximgproc.`weightedMedianFilter(Mat joint, Mat src, Mat dst, int r, double sigma, int weightType)`	Applies weighted median filter to an image.
`static void`	Ximgproc.`weightedMedianFilter(Mat joint, Mat src, Mat dst, int r, double sigma, int weightType, Mat mask)`	Applies weighted median filter to an image.

Uses of Mat in org.opencv.xphoto

Methods in org.opencv.xphoto with parameters of type Mat
Modifier and Type	Method	Description
`static void`	Xphoto.`applyChannelGains(Mat src, Mat dst, float gainB, float gainG, float gainR)`	Implements an efficient fixed-point approximation for applying channel gains, which is the last step of multiple white balance algorithms.
`void`	WhiteBalancer.`balanceWhite(Mat src, Mat dst)`	Applies white balancing to the input image
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dst)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dst, float h)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dst, float h, int templateWindowSize)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dst, float h, int templateWindowSize, int searchWindowSize)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dst, float h, int templateWindowSize, int searchWindowSize, int blockMatchingStep1)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dst, float h, int templateWindowSize, int searchWindowSize, int blockMatchingStep1, int blockMatchingStep2)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dst, float h, int templateWindowSize, int searchWindowSize, int blockMatchingStep1, int blockMatchingStep2, int groupSize)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dst, float h, int templateWindowSize, int searchWindowSize, int blockMatchingStep1, int blockMatchingStep2, int groupSize, int slidingStep)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dst, float h, int templateWindowSize, int searchWindowSize, int blockMatchingStep1, int blockMatchingStep2, int groupSize, int slidingStep, float beta)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dst, float h, int templateWindowSize, int searchWindowSize, int blockMatchingStep1, int blockMatchingStep2, int groupSize, int slidingStep, float beta, int normType)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dst, float h, int templateWindowSize, int searchWindowSize, int blockMatchingStep1, int blockMatchingStep2, int groupSize, int slidingStep, float beta, int normType, int step)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dst, float h, int templateWindowSize, int searchWindowSize, int blockMatchingStep1, int blockMatchingStep2, int groupSize, int slidingStep, float beta, int normType, int step, int transformType)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dstStep1, Mat dstStep2)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dstStep1, Mat dstStep2, float h)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dstStep1, Mat dstStep2, float h, int templateWindowSize)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dstStep1, Mat dstStep2, float h, int templateWindowSize, int searchWindowSize)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dstStep1, Mat dstStep2, float h, int templateWindowSize, int searchWindowSize, int blockMatchingStep1)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dstStep1, Mat dstStep2, float h, int templateWindowSize, int searchWindowSize, int blockMatchingStep1, int blockMatchingStep2)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dstStep1, Mat dstStep2, float h, int templateWindowSize, int searchWindowSize, int blockMatchingStep1, int blockMatchingStep2, int groupSize)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dstStep1, Mat dstStep2, float h, int templateWindowSize, int searchWindowSize, int blockMatchingStep1, int blockMatchingStep2, int groupSize, int slidingStep)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dstStep1, Mat dstStep2, float h, int templateWindowSize, int searchWindowSize, int blockMatchingStep1, int blockMatchingStep2, int groupSize, int slidingStep, float beta)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dstStep1, Mat dstStep2, float h, int templateWindowSize, int searchWindowSize, int blockMatchingStep1, int blockMatchingStep2, int groupSize, int slidingStep, float beta, int normType)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dstStep1, Mat dstStep2, float h, int templateWindowSize, int searchWindowSize, int blockMatchingStep1, int blockMatchingStep2, int groupSize, int slidingStep, float beta, int normType, int step)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`bm3dDenoising(Mat src, Mat dstStep1, Mat dstStep2, float h, int templateWindowSize, int searchWindowSize, int blockMatchingStep1, int blockMatchingStep2, int groupSize, int slidingStep, float beta, int normType, int step, int transformType)`	Performs image denoising using the Block-Matching and 3D-filtering algorithm <http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> with several computational optimizations.
`static void`	Xphoto.`dctDenoising(Mat src, Mat dst, double sigma)`	The function implements simple dct-based denoising <http://www.ipol.im/pub/art/2011/ys-dct/>.
`static void`	Xphoto.`dctDenoising(Mat src, Mat dst, double sigma, int psize)`	The function implements simple dct-based denoising <http://www.ipol.im/pub/art/2011/ys-dct/>.
`void`	LearningBasedWB.`extractSimpleFeatures(Mat src, Mat dst)`	Implements the feature extraction part of the algorithm.
`static void`	Xphoto.`inpaint(Mat src, Mat mask, Mat dst, int algorithmType)`	The function implements different single-image inpainting algorithms.
`static void`	Xphoto.`oilPainting(Mat src, Mat dst, int size, int dynRatio)`	oilPainting See the book CITE: Holzmann1988 for details.
`static void`	Xphoto.`oilPainting(Mat src, Mat dst, int size, int dynRatio, int code)`	oilPainting See the book CITE: Holzmann1988 for details.

Uses of Classorg.opencv.core.Mat

Uses of Mat in org.opencv.aruco

Uses of Mat in org.opencv.barcode

Uses of Mat in org.opencv.bgsegm

Uses of Mat in org.opencv.bioinspired

Uses of Mat in org.opencv.calib3d

Uses of Mat in org.opencv.core

Uses of Mat in org.opencv.dnn

Uses of Mat in org.opencv.face

Uses of Mat in org.opencv.features2d

Uses of Mat in org.opencv.highgui

Uses of Mat in org.opencv.img_hash

Uses of Mat in org.opencv.imgcodecs

Uses of Mat in org.opencv.imgproc

Uses of Mat in org.opencv.ml

Uses of Mat in org.opencv.objdetect

Uses of Mat in org.opencv.phase_unwrapping

Uses of Mat in org.opencv.photo

Uses of Mat in org.opencv.plot

Uses of Mat in org.opencv.structured_light

Uses of Mat in org.opencv.text

Uses of Mat in org.opencv.tracking

Uses of Mat in org.opencv.utils

Uses of Mat in org.opencv.video

Uses of Mat in org.opencv.videoio

Uses of Mat in org.opencv.wechat_qrcode

Uses of Mat in org.opencv.xfeatures2d

Uses of Mat in org.opencv.ximgproc

Uses of Mat in org.opencv.xphoto

Uses of Class
org.opencv.core.Mat