terric/Health
terric
/
Health
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity
Health/Assets/OpenCVForUnity/org/opencv_contrib/aruco/Aruco.cs

1737 lines
118 KiB
C#
Raw Permalink Blame History

using OpenCVForUnity.CoreModule;
using OpenCVForUnity.ObjdetectModule;
using OpenCVForUnity.UtilsModule;
using System;
using System.Collections.Generic;
using System.Runtime.InteropServices;
namespace OpenCVForUnity.ArucoModule
{
// C++: class Aruco
public class Aruco
{
// C++: enum cv.aruco.PatternPositionType
public const int ARUCO_CCW_CENTER = 0;
public const int ARUCO_CW_TOP_LEFT_CORNER = 1;
//
// C++: void cv::aruco::detectMarkers(Mat image, Ptr_Dictionary dictionary, vector_Mat& corners, Mat& ids, Ptr_DetectorParameters parameters = makePtr<DetectorParameters>(), vector_Mat& rejectedImgPoints = vector_Mat())
//
/**
* detect markers
* deprecated Use class ArucoDetector::detectMarkers
* param image automatically generated
* param dictionary automatically generated
* param corners automatically generated
* param ids automatically generated
* param parameters automatically generated
* param rejectedImgPoints automatically generated
*/
[Obsolete("This method is deprecated.")]
public static void detectMarkers(Mat image, Dictionary dictionary, List<Mat> corners, Mat ids, DetectorParameters parameters, List<Mat> rejectedImgPoints)
{
if (image != null) image.ThrowIfDisposed();
if (dictionary != null) dictionary.ThrowIfDisposed();
if (ids != null) ids.ThrowIfDisposed();
if (parameters != null) parameters.ThrowIfDisposed();
Mat corners_mat = new Mat();
Mat rejectedImgPoints_mat = new Mat();
aruco_Aruco_detectMarkers_10(image.nativeObj, dictionary.getNativeObjAddr(), corners_mat.nativeObj, ids.nativeObj, parameters.getNativeObjAddr(), rejectedImgPoints_mat.nativeObj);
Converters.Mat_to_vector_Mat(corners_mat, corners);
corners_mat.release();
Converters.Mat_to_vector_Mat(rejectedImgPoints_mat, rejectedImgPoints);
rejectedImgPoints_mat.release();
}
/**
* detect markers
* deprecated Use class ArucoDetector::detectMarkers
* param image automatically generated
* param dictionary automatically generated
* param corners automatically generated
* param ids automatically generated
* param parameters automatically generated
*/
[Obsolete("This method is deprecated.")]
public static void detectMarkers(Mat image, Dictionary dictionary, List<Mat> corners, Mat ids, DetectorParameters parameters)
{
if (image != null) image.ThrowIfDisposed();
if (dictionary != null) dictionary.ThrowIfDisposed();
if (ids != null) ids.ThrowIfDisposed();
if (parameters != null) parameters.ThrowIfDisposed();
Mat corners_mat = new Mat();
aruco_Aruco_detectMarkers_11(image.nativeObj, dictionary.getNativeObjAddr(), corners_mat.nativeObj, ids.nativeObj, parameters.getNativeObjAddr());
Converters.Mat_to_vector_Mat(corners_mat, corners);
corners_mat.release();
}
/**
* detect markers
* deprecated Use class ArucoDetector::detectMarkers
* param image automatically generated
* param dictionary automatically generated
* param corners automatically generated
* param ids automatically generated
*/
[Obsolete("This method is deprecated.")]
public static void detectMarkers(Mat image, Dictionary dictionary, List<Mat> corners, Mat ids)
{
if (image != null) image.ThrowIfDisposed();
if (dictionary != null) dictionary.ThrowIfDisposed();
if (ids != null) ids.ThrowIfDisposed();
Mat corners_mat = new Mat();
aruco_Aruco_detectMarkers_12(image.nativeObj, dictionary.getNativeObjAddr(), corners_mat.nativeObj, ids.nativeObj);
Converters.Mat_to_vector_Mat(corners_mat, corners);
corners_mat.release();
}
//
// C++: void cv::aruco::refineDetectedMarkers(Mat image, Ptr_Board board, vector_Mat& detectedCorners, Mat& detectedIds, vector_Mat& rejectedCorners, Mat cameraMatrix = Mat(), Mat distCoeffs = Mat(), float minRepDistance = 10.f, float errorCorrectionRate = 3.f, bool checkAllOrders = true, Mat& recoveredIdxs = Mat(), Ptr_DetectorParameters parameters = makePtr<DetectorParameters>())
//
/**
* refine detected markers
* deprecated Use class ArucoDetector::refineDetectedMarkers
* param image automatically generated
* param board automatically generated
* param detectedCorners automatically generated
* param detectedIds automatically generated
* param rejectedCorners automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param minRepDistance automatically generated
* param errorCorrectionRate automatically generated
* param checkAllOrders automatically generated
* param recoveredIdxs automatically generated
* param parameters automatically generated
*/
[Obsolete("This method is deprecated.")]
public static void refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, float minRepDistance, float errorCorrectionRate, bool checkAllOrders, Mat recoveredIdxs, DetectorParameters parameters)
{
if (image != null) image.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (detectedIds != null) detectedIds.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
if (recoveredIdxs != null) recoveredIdxs.ThrowIfDisposed();
if (parameters != null) parameters.ThrowIfDisposed();
Mat detectedCorners_mat = Converters.vector_Mat_to_Mat(detectedCorners);
Mat rejectedCorners_mat = Converters.vector_Mat_to_Mat(rejectedCorners);
aruco_Aruco_refineDetectedMarkers_10(image.nativeObj, board.getNativeObjAddr(), detectedCorners_mat.nativeObj, detectedIds.nativeObj, rejectedCorners_mat.nativeObj, cameraMatrix.nativeObj, distCoeffs.nativeObj, minRepDistance, errorCorrectionRate, checkAllOrders, recoveredIdxs.nativeObj, parameters.getNativeObjAddr());
Converters.Mat_to_vector_Mat(detectedCorners_mat, detectedCorners);
detectedCorners_mat.release();
Converters.Mat_to_vector_Mat(rejectedCorners_mat, rejectedCorners);
rejectedCorners_mat.release();
}
/**
* refine detected markers
* deprecated Use class ArucoDetector::refineDetectedMarkers
* param image automatically generated
* param board automatically generated
* param detectedCorners automatically generated
* param detectedIds automatically generated
* param rejectedCorners automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param minRepDistance automatically generated
* param errorCorrectionRate automatically generated
* param checkAllOrders automatically generated
* param recoveredIdxs automatically generated
*/
[Obsolete("This method is deprecated.")]
public static void refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, float minRepDistance, float errorCorrectionRate, bool checkAllOrders, Mat recoveredIdxs)
{
if (image != null) image.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (detectedIds != null) detectedIds.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
if (recoveredIdxs != null) recoveredIdxs.ThrowIfDisposed();
Mat detectedCorners_mat = Converters.vector_Mat_to_Mat(detectedCorners);
Mat rejectedCorners_mat = Converters.vector_Mat_to_Mat(rejectedCorners);
aruco_Aruco_refineDetectedMarkers_11(image.nativeObj, board.getNativeObjAddr(), detectedCorners_mat.nativeObj, detectedIds.nativeObj, rejectedCorners_mat.nativeObj, cameraMatrix.nativeObj, distCoeffs.nativeObj, minRepDistance, errorCorrectionRate, checkAllOrders, recoveredIdxs.nativeObj);
Converters.Mat_to_vector_Mat(detectedCorners_mat, detectedCorners);
detectedCorners_mat.release();
Converters.Mat_to_vector_Mat(rejectedCorners_mat, rejectedCorners);
rejectedCorners_mat.release();
}
/**
* refine detected markers
* deprecated Use class ArucoDetector::refineDetectedMarkers
* param image automatically generated
* param board automatically generated
* param detectedCorners automatically generated
* param detectedIds automatically generated
* param rejectedCorners automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param minRepDistance automatically generated
* param errorCorrectionRate automatically generated
* param checkAllOrders automatically generated
*/
[Obsolete("This method is deprecated.")]
public static void refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, float minRepDistance, float errorCorrectionRate, bool checkAllOrders)
{
if (image != null) image.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (detectedIds != null) detectedIds.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat detectedCorners_mat = Converters.vector_Mat_to_Mat(detectedCorners);
Mat rejectedCorners_mat = Converters.vector_Mat_to_Mat(rejectedCorners);
aruco_Aruco_refineDetectedMarkers_12(image.nativeObj, board.getNativeObjAddr(), detectedCorners_mat.nativeObj, detectedIds.nativeObj, rejectedCorners_mat.nativeObj, cameraMatrix.nativeObj, distCoeffs.nativeObj, minRepDistance, errorCorrectionRate, checkAllOrders);
Converters.Mat_to_vector_Mat(detectedCorners_mat, detectedCorners);
detectedCorners_mat.release();
Converters.Mat_to_vector_Mat(rejectedCorners_mat, rejectedCorners);
rejectedCorners_mat.release();
}
/**
* refine detected markers
* deprecated Use class ArucoDetector::refineDetectedMarkers
* param image automatically generated
* param board automatically generated
* param detectedCorners automatically generated
* param detectedIds automatically generated
* param rejectedCorners automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param minRepDistance automatically generated
* param errorCorrectionRate automatically generated
*/
[Obsolete("This method is deprecated.")]
public static void refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, float minRepDistance, float errorCorrectionRate)
{
if (image != null) image.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (detectedIds != null) detectedIds.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat detectedCorners_mat = Converters.vector_Mat_to_Mat(detectedCorners);
Mat rejectedCorners_mat = Converters.vector_Mat_to_Mat(rejectedCorners);
aruco_Aruco_refineDetectedMarkers_13(image.nativeObj, board.getNativeObjAddr(), detectedCorners_mat.nativeObj, detectedIds.nativeObj, rejectedCorners_mat.nativeObj, cameraMatrix.nativeObj, distCoeffs.nativeObj, minRepDistance, errorCorrectionRate);
Converters.Mat_to_vector_Mat(detectedCorners_mat, detectedCorners);
detectedCorners_mat.release();
Converters.Mat_to_vector_Mat(rejectedCorners_mat, rejectedCorners);
rejectedCorners_mat.release();
}
/**
* refine detected markers
* deprecated Use class ArucoDetector::refineDetectedMarkers
* param image automatically generated
* param board automatically generated
* param detectedCorners automatically generated
* param detectedIds automatically generated
* param rejectedCorners automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param minRepDistance automatically generated
*/
[Obsolete("This method is deprecated.")]
public static void refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, float minRepDistance)
{
if (image != null) image.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (detectedIds != null) detectedIds.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat detectedCorners_mat = Converters.vector_Mat_to_Mat(detectedCorners);
Mat rejectedCorners_mat = Converters.vector_Mat_to_Mat(rejectedCorners);
aruco_Aruco_refineDetectedMarkers_14(image.nativeObj, board.getNativeObjAddr(), detectedCorners_mat.nativeObj, detectedIds.nativeObj, rejectedCorners_mat.nativeObj, cameraMatrix.nativeObj, distCoeffs.nativeObj, minRepDistance);
Converters.Mat_to_vector_Mat(detectedCorners_mat, detectedCorners);
detectedCorners_mat.release();
Converters.Mat_to_vector_Mat(rejectedCorners_mat, rejectedCorners);
rejectedCorners_mat.release();
}
/**
* refine detected markers
* deprecated Use class ArucoDetector::refineDetectedMarkers
* param image automatically generated
* param board automatically generated
* param detectedCorners automatically generated
* param detectedIds automatically generated
* param rejectedCorners automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
*/
[Obsolete("This method is deprecated.")]
public static void refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs)
{
if (image != null) image.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (detectedIds != null) detectedIds.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat detectedCorners_mat = Converters.vector_Mat_to_Mat(detectedCorners);
Mat rejectedCorners_mat = Converters.vector_Mat_to_Mat(rejectedCorners);
aruco_Aruco_refineDetectedMarkers_15(image.nativeObj, board.getNativeObjAddr(), detectedCorners_mat.nativeObj, detectedIds.nativeObj, rejectedCorners_mat.nativeObj, cameraMatrix.nativeObj, distCoeffs.nativeObj);
Converters.Mat_to_vector_Mat(detectedCorners_mat, detectedCorners);
detectedCorners_mat.release();
Converters.Mat_to_vector_Mat(rejectedCorners_mat, rejectedCorners);
rejectedCorners_mat.release();
}
/**
* refine detected markers
* deprecated Use class ArucoDetector::refineDetectedMarkers
* param image automatically generated
* param board automatically generated
* param detectedCorners automatically generated
* param detectedIds automatically generated
* param rejectedCorners automatically generated
* param cameraMatrix automatically generated
*/
[Obsolete("This method is deprecated.")]
public static void refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix)
{
if (image != null) image.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (detectedIds != null) detectedIds.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
Mat detectedCorners_mat = Converters.vector_Mat_to_Mat(detectedCorners);
Mat rejectedCorners_mat = Converters.vector_Mat_to_Mat(rejectedCorners);
aruco_Aruco_refineDetectedMarkers_16(image.nativeObj, board.getNativeObjAddr(), detectedCorners_mat.nativeObj, detectedIds.nativeObj, rejectedCorners_mat.nativeObj, cameraMatrix.nativeObj);
Converters.Mat_to_vector_Mat(detectedCorners_mat, detectedCorners);
detectedCorners_mat.release();
Converters.Mat_to_vector_Mat(rejectedCorners_mat, rejectedCorners);
rejectedCorners_mat.release();
}
/**
* refine detected markers
* deprecated Use class ArucoDetector::refineDetectedMarkers
* param image automatically generated
* param board automatically generated
* param detectedCorners automatically generated
* param detectedIds automatically generated
* param rejectedCorners automatically generated
*/
[Obsolete("This method is deprecated.")]
public static void refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners)
{
if (image != null) image.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (detectedIds != null) detectedIds.ThrowIfDisposed();
Mat detectedCorners_mat = Converters.vector_Mat_to_Mat(detectedCorners);
Mat rejectedCorners_mat = Converters.vector_Mat_to_Mat(rejectedCorners);
aruco_Aruco_refineDetectedMarkers_17(image.nativeObj, board.getNativeObjAddr(), detectedCorners_mat.nativeObj, detectedIds.nativeObj, rejectedCorners_mat.nativeObj);
Converters.Mat_to_vector_Mat(detectedCorners_mat, detectedCorners);
detectedCorners_mat.release();
Converters.Mat_to_vector_Mat(rejectedCorners_mat, rejectedCorners);
rejectedCorners_mat.release();
}
//
// C++: void cv::aruco::drawPlanarBoard(Ptr_Board board, Size outSize, Mat& img, int marginSize, int borderBits)
//
/**
* draw planar board
* deprecated Use Board::generateImage
* param board automatically generated
* param outSize automatically generated
* param img automatically generated
* param marginSize automatically generated
* param borderBits automatically generated
*/
[Obsolete("This method is deprecated.")]
public static void drawPlanarBoard(Board board, Size outSize, Mat img, int marginSize, int borderBits)
{
if (board != null) board.ThrowIfDisposed();
if (img != null) img.ThrowIfDisposed();
aruco_Aruco_drawPlanarBoard_10(board.getNativeObjAddr(), outSize.width, outSize.height, img.nativeObj, marginSize, borderBits);
}
//
// C++: void cv::aruco::getBoardObjectAndImagePoints(Ptr_Board board, vector_Mat detectedCorners, Mat detectedIds, Mat& objPoints, Mat& imgPoints)
//
/**
* get board object and image points
* deprecated Use Board::matchImagePoints
* param board automatically generated
* param detectedCorners automatically generated
* param detectedIds automatically generated
* param objPoints automatically generated
* param imgPoints automatically generated
*/
[Obsolete("This method is deprecated.")]
public static void getBoardObjectAndImagePoints(Board board, List<Mat> detectedCorners, Mat detectedIds, Mat objPoints, Mat imgPoints)
{
if (board != null) board.ThrowIfDisposed();
if (detectedIds != null) detectedIds.ThrowIfDisposed();
if (objPoints != null) objPoints.ThrowIfDisposed();
if (imgPoints != null) imgPoints.ThrowIfDisposed();
Mat detectedCorners_mat = Converters.vector_Mat_to_Mat(detectedCorners);
aruco_Aruco_getBoardObjectAndImagePoints_10(board.getNativeObjAddr(), detectedCorners_mat.nativeObj, detectedIds.nativeObj, objPoints.nativeObj, imgPoints.nativeObj);
}
//
// C++: int cv::aruco::estimatePoseBoard(vector_Mat corners, Mat ids, Ptr_Board board, Mat cameraMatrix, Mat distCoeffs, Mat& rvec, Mat& tvec, bool useExtrinsicGuess = false)
//
/**
* deprecated Use cv::solvePnP
* param corners automatically generated
* param ids automatically generated
* param board automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param rvec automatically generated
* param tvec automatically generated
* param useExtrinsicGuess automatically generated
* return automatically generated
*/
[Obsolete("This method is deprecated.")]
public static int estimatePoseBoard(List<Mat> corners, Mat ids, Board board, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, bool useExtrinsicGuess)
{
if (ids != null) ids.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
if (rvec != null) rvec.ThrowIfDisposed();
if (tvec != null) tvec.ThrowIfDisposed();
Mat corners_mat = Converters.vector_Mat_to_Mat(corners);
return aruco_Aruco_estimatePoseBoard_10(corners_mat.nativeObj, ids.nativeObj, board.getNativeObjAddr(), cameraMatrix.nativeObj, distCoeffs.nativeObj, rvec.nativeObj, tvec.nativeObj, useExtrinsicGuess);
}
/**
* deprecated Use cv::solvePnP
* param corners automatically generated
* param ids automatically generated
* param board automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param rvec automatically generated
* param tvec automatically generated
* return automatically generated
*/
[Obsolete("This method is deprecated.")]
public static int estimatePoseBoard(List<Mat> corners, Mat ids, Board board, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec)
{
if (ids != null) ids.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
if (rvec != null) rvec.ThrowIfDisposed();
if (tvec != null) tvec.ThrowIfDisposed();
Mat corners_mat = Converters.vector_Mat_to_Mat(corners);
return aruco_Aruco_estimatePoseBoard_11(corners_mat.nativeObj, ids.nativeObj, board.getNativeObjAddr(), cameraMatrix.nativeObj, distCoeffs.nativeObj, rvec.nativeObj, tvec.nativeObj);
}
//
// C++: bool cv::aruco::estimatePoseCharucoBoard(Mat charucoCorners, Mat charucoIds, Ptr_CharucoBoard board, Mat cameraMatrix, Mat distCoeffs, Mat& rvec, Mat& tvec, bool useExtrinsicGuess = false)
//
/**
* Pose estimation for a ChArUco board given some of their corners
* param charucoCorners vector of detected charuco corners
* param charucoIds list of identifiers for each corner in charucoCorners
* param board layout of ChArUco board.
* param cameraMatrix input 3x3 floating-point camera matrix
* \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\)
* param distCoeffs vector of distortion coefficients
* \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) of 4, 5, 8 or 12 elements
* param rvec Output vector (e.g. cv::Mat) corresponding to the rotation vector of the board
* (see cv::Rodrigues).
* param tvec Output vector (e.g. cv::Mat) corresponding to the translation vector of the board.
* param useExtrinsicGuess defines whether initial guess for \b rvec and \b tvec will be used or not.
*
* This function estimates a Charuco board pose from some detected corners.
* The function checks if the input corners are enough and valid to perform pose estimation.
* If pose estimation is valid, returns true, else returns false.
* SEE: use cv::drawFrameAxes to get world coordinate system axis for object points
* return automatically generated
*/
public static bool estimatePoseCharucoBoard(Mat charucoCorners, Mat charucoIds, CharucoBoard board, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, bool useExtrinsicGuess)
{
if (charucoCorners != null) charucoCorners.ThrowIfDisposed();
if (charucoIds != null) charucoIds.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
if (rvec != null) rvec.ThrowIfDisposed();
if (tvec != null) tvec.ThrowIfDisposed();
return aruco_Aruco_estimatePoseCharucoBoard_10(charucoCorners.nativeObj, charucoIds.nativeObj, board.getNativeObjAddr(), cameraMatrix.nativeObj, distCoeffs.nativeObj, rvec.nativeObj, tvec.nativeObj, useExtrinsicGuess);
}
/**
* Pose estimation for a ChArUco board given some of their corners
* param charucoCorners vector of detected charuco corners
* param charucoIds list of identifiers for each corner in charucoCorners
* param board layout of ChArUco board.
* param cameraMatrix input 3x3 floating-point camera matrix
* \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\)
* param distCoeffs vector of distortion coefficients
* \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) of 4, 5, 8 or 12 elements
* param rvec Output vector (e.g. cv::Mat) corresponding to the rotation vector of the board
* (see cv::Rodrigues).
* param tvec Output vector (e.g. cv::Mat) corresponding to the translation vector of the board.
*
* This function estimates a Charuco board pose from some detected corners.
* The function checks if the input corners are enough and valid to perform pose estimation.
* If pose estimation is valid, returns true, else returns false.
* SEE: use cv::drawFrameAxes to get world coordinate system axis for object points
* return automatically generated
*/
public static bool estimatePoseCharucoBoard(Mat charucoCorners, Mat charucoIds, CharucoBoard board, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec)
{
if (charucoCorners != null) charucoCorners.ThrowIfDisposed();
if (charucoIds != null) charucoIds.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
if (rvec != null) rvec.ThrowIfDisposed();
if (tvec != null) tvec.ThrowIfDisposed();
return aruco_Aruco_estimatePoseCharucoBoard_11(charucoCorners.nativeObj, charucoIds.nativeObj, board.getNativeObjAddr(), cameraMatrix.nativeObj, distCoeffs.nativeObj, rvec.nativeObj, tvec.nativeObj);
}
//
// C++: void cv::aruco::estimatePoseSingleMarkers(vector_Mat corners, float markerLength, Mat cameraMatrix, Mat distCoeffs, Mat& rvecs, Mat& tvecs, Mat& objPoints = Mat(), Ptr_EstimateParameters estimateParameters = makePtr<EstimateParameters>())
//
/**
* deprecated Use cv::solvePnP
* param corners automatically generated
* param markerLength automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param rvecs automatically generated
* param tvecs automatically generated
* param objPoints automatically generated
* param estimateParameters automatically generated
*/
[Obsolete("This method is deprecated.")]
public static void estimatePoseSingleMarkers(List<Mat> corners, float markerLength, Mat cameraMatrix, Mat distCoeffs, Mat rvecs, Mat tvecs, Mat objPoints, EstimateParameters estimateParameters)
{
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
if (rvecs != null) rvecs.ThrowIfDisposed();
if (tvecs != null) tvecs.ThrowIfDisposed();
if (objPoints != null) objPoints.ThrowIfDisposed();
if (estimateParameters != null) estimateParameters.ThrowIfDisposed();
Mat corners_mat = Converters.vector_Mat_to_Mat(corners);
aruco_Aruco_estimatePoseSingleMarkers_10(corners_mat.nativeObj, markerLength, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs.nativeObj, tvecs.nativeObj, objPoints.nativeObj, estimateParameters.getNativeObjAddr());
}
/**
* deprecated Use cv::solvePnP
* param corners automatically generated
* param markerLength automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param rvecs automatically generated
* param tvecs automatically generated
* param objPoints automatically generated
*/
[Obsolete("This method is deprecated.")]
public static void estimatePoseSingleMarkers(List<Mat> corners, float markerLength, Mat cameraMatrix, Mat distCoeffs, Mat rvecs, Mat tvecs, Mat objPoints)
{
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
if (rvecs != null) rvecs.ThrowIfDisposed();
if (tvecs != null) tvecs.ThrowIfDisposed();
if (objPoints != null) objPoints.ThrowIfDisposed();
Mat corners_mat = Converters.vector_Mat_to_Mat(corners);
aruco_Aruco_estimatePoseSingleMarkers_11(corners_mat.nativeObj, markerLength, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs.nativeObj, tvecs.nativeObj, objPoints.nativeObj);
}
/**
* deprecated Use cv::solvePnP
* param corners automatically generated
* param markerLength automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param rvecs automatically generated
* param tvecs automatically generated
*/
[Obsolete("This method is deprecated.")]
public static void estimatePoseSingleMarkers(List<Mat> corners, float markerLength, Mat cameraMatrix, Mat distCoeffs, Mat rvecs, Mat tvecs)
{
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
if (rvecs != null) rvecs.ThrowIfDisposed();
if (tvecs != null) tvecs.ThrowIfDisposed();
Mat corners_mat = Converters.vector_Mat_to_Mat(corners);
aruco_Aruco_estimatePoseSingleMarkers_12(corners_mat.nativeObj, markerLength, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs.nativeObj, tvecs.nativeObj);
}
//
// C++: bool cv::aruco::testCharucoCornersCollinear(Ptr_CharucoBoard board, Mat charucoIds)
//
/**
* deprecated Use CharucoBoard::checkCharucoCornersCollinear
* param board automatically generated
* param charucoIds automatically generated
* return automatically generated
*/
[Obsolete("This method is deprecated.")]
public static bool testCharucoCornersCollinear(CharucoBoard board, Mat charucoIds)
{
if (board != null) board.ThrowIfDisposed();
if (charucoIds != null) charucoIds.ThrowIfDisposed();
return aruco_Aruco_testCharucoCornersCollinear_10(board.getNativeObjAddr(), charucoIds.nativeObj);
}
//
// C++: double cv::aruco::calibrateCameraAruco(vector_Mat corners, Mat ids, Mat counter, Ptr_Board board, Size imageSize, Mat& cameraMatrix, Mat& distCoeffs, vector_Mat& rvecs, vector_Mat& tvecs, Mat& stdDeviationsIntrinsics, Mat& stdDeviationsExtrinsics, Mat& perViewErrors, int flags = 0, TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON))
//
/**
* Calibrate a camera using aruco markers
*
* param corners vector of detected marker corners in all frames.
* The corners should have the same format returned by detectMarkers (see #detectMarkers).
* param ids list of identifiers for each marker in corners
* param counter number of markers in each frame so that corners and ids can be split
* param board Marker Board layout
* param imageSize Size of the image used only to initialize the intrinsic camera matrix.
* param cameraMatrix Output 3x3 floating-point camera matrix
* \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\) . If CV\_CALIB\_USE\_INTRINSIC\_GUESS
* and/or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of fx, fy, cx, cy must be
* initialized before calling the function.
* param distCoeffs Output vector of distortion coefficients
* \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) of 4, 5, 8 or 12 elements
* param rvecs Output vector of rotation vectors (see Rodrigues ) estimated for each board view
* (e.g. std::vector&lt;cv::Mat&gt;&gt;). That is, each k-th rotation vector together with the corresponding
* k-th translation vector (see the next output parameter description) brings the board pattern
* from the model coordinate space (in which object points are specified) to the world coordinate
* space, that is, a real position of the board pattern in the k-th pattern view (k=0.. *M* -1).
* param tvecs Output vector of translation vectors estimated for each pattern view.
* param stdDeviationsIntrinsics Output vector of standard deviations estimated for intrinsic parameters.
* Order of deviations values:
* \((f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3,
* s_4, \tau_x, \tau_y)\) If one of parameters is not estimated, it's deviation is equals to zero.
* param stdDeviationsExtrinsics Output vector of standard deviations estimated for extrinsic parameters.
* Order of deviations values: \((R_1, T_1, \dotsc , R_M, T_M)\) where M is number of pattern views,
* \(R_i, T_i\) are concatenated 1x3 vectors.
* param perViewErrors Output vector of average re-projection errors estimated for each pattern view.
* param flags flags Different flags for the calibration process (see #calibrateCamera for details).
* param criteria Termination criteria for the iterative optimization algorithm.
*
* This function calibrates a camera using an Aruco Board. The function receives a list of
* detected markers from several views of the Board. The process is similar to the chessboard
* calibration in calibrateCamera(). The function returns the final re-projection error.
* return automatically generated
*/
public static double 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)
{
if (ids != null) ids.ThrowIfDisposed();
if (counter != null) counter.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
if (stdDeviationsIntrinsics != null) stdDeviationsIntrinsics.ThrowIfDisposed();
if (stdDeviationsExtrinsics != null) stdDeviationsExtrinsics.ThrowIfDisposed();
if (perViewErrors != null) perViewErrors.ThrowIfDisposed();
Mat corners_mat = Converters.vector_Mat_to_Mat(corners);
Mat rvecs_mat = new Mat();
Mat tvecs_mat = new Mat();
double retVal = aruco_Aruco_calibrateCameraArucoExtended_10(corners_mat.nativeObj, ids.nativeObj, counter.nativeObj, board.getNativeObjAddr(), imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs_mat.nativeObj, tvecs_mat.nativeObj, stdDeviationsIntrinsics.nativeObj, stdDeviationsExtrinsics.nativeObj, perViewErrors.nativeObj, flags, criteria.type, criteria.maxCount, criteria.epsilon);
Converters.Mat_to_vector_Mat(rvecs_mat, rvecs);
rvecs_mat.release();
Converters.Mat_to_vector_Mat(tvecs_mat, tvecs);
tvecs_mat.release();
return retVal;
}
/**
* Calibrate a camera using aruco markers
*
* param corners vector of detected marker corners in all frames.
* The corners should have the same format returned by detectMarkers (see #detectMarkers).
* param ids list of identifiers for each marker in corners
* param counter number of markers in each frame so that corners and ids can be split
* param board Marker Board layout
* param imageSize Size of the image used only to initialize the intrinsic camera matrix.
* param cameraMatrix Output 3x3 floating-point camera matrix
* \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\) . If CV\_CALIB\_USE\_INTRINSIC\_GUESS
* and/or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of fx, fy, cx, cy must be
* initialized before calling the function.
* param distCoeffs Output vector of distortion coefficients
* \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) of 4, 5, 8 or 12 elements
* param rvecs Output vector of rotation vectors (see Rodrigues ) estimated for each board view
* (e.g. std::vector&lt;cv::Mat&gt;&gt;). That is, each k-th rotation vector together with the corresponding
* k-th translation vector (see the next output parameter description) brings the board pattern
* from the model coordinate space (in which object points are specified) to the world coordinate
* space, that is, a real position of the board pattern in the k-th pattern view (k=0.. *M* -1).
* param tvecs Output vector of translation vectors estimated for each pattern view.
* param stdDeviationsIntrinsics Output vector of standard deviations estimated for intrinsic parameters.
* Order of deviations values:
* \((f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3,
* s_4, \tau_x, \tau_y)\) If one of parameters is not estimated, it's deviation is equals to zero.
* param stdDeviationsExtrinsics Output vector of standard deviations estimated for extrinsic parameters.
* Order of deviations values: \((R_1, T_1, \dotsc , R_M, T_M)\) where M is number of pattern views,
* \(R_i, T_i\) are concatenated 1x3 vectors.
* param perViewErrors Output vector of average re-projection errors estimated for each pattern view.
* param flags flags Different flags for the calibration process (see #calibrateCamera for details).
*
* This function calibrates a camera using an Aruco Board. The function receives a list of
* detected markers from several views of the Board. The process is similar to the chessboard
* calibration in calibrateCamera(). The function returns the final re-projection error.
* return automatically generated
*/
public static double 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)
{
if (ids != null) ids.ThrowIfDisposed();
if (counter != null) counter.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
if (stdDeviationsIntrinsics != null) stdDeviationsIntrinsics.ThrowIfDisposed();
if (stdDeviationsExtrinsics != null) stdDeviationsExtrinsics.ThrowIfDisposed();
if (perViewErrors != null) perViewErrors.ThrowIfDisposed();
Mat corners_mat = Converters.vector_Mat_to_Mat(corners);
Mat rvecs_mat = new Mat();
Mat tvecs_mat = new Mat();
double retVal = aruco_Aruco_calibrateCameraArucoExtended_11(corners_mat.nativeObj, ids.nativeObj, counter.nativeObj, board.getNativeObjAddr(), imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs_mat.nativeObj, tvecs_mat.nativeObj, stdDeviationsIntrinsics.nativeObj, stdDeviationsExtrinsics.nativeObj, perViewErrors.nativeObj, flags);
Converters.Mat_to_vector_Mat(rvecs_mat, rvecs);
rvecs_mat.release();
Converters.Mat_to_vector_Mat(tvecs_mat, tvecs);
tvecs_mat.release();
return retVal;
}
/**
* Calibrate a camera using aruco markers
*
* param corners vector of detected marker corners in all frames.
* The corners should have the same format returned by detectMarkers (see #detectMarkers).
* param ids list of identifiers for each marker in corners
* param counter number of markers in each frame so that corners and ids can be split
* param board Marker Board layout
* param imageSize Size of the image used only to initialize the intrinsic camera matrix.
* param cameraMatrix Output 3x3 floating-point camera matrix
* \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\) . If CV\_CALIB\_USE\_INTRINSIC\_GUESS
* and/or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of fx, fy, cx, cy must be
* initialized before calling the function.
* param distCoeffs Output vector of distortion coefficients
* \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) of 4, 5, 8 or 12 elements
* param rvecs Output vector of rotation vectors (see Rodrigues ) estimated for each board view
* (e.g. std::vector&lt;cv::Mat&gt;&gt;). That is, each k-th rotation vector together with the corresponding
* k-th translation vector (see the next output parameter description) brings the board pattern
* from the model coordinate space (in which object points are specified) to the world coordinate
* space, that is, a real position of the board pattern in the k-th pattern view (k=0.. *M* -1).
* param tvecs Output vector of translation vectors estimated for each pattern view.
* param stdDeviationsIntrinsics Output vector of standard deviations estimated for intrinsic parameters.
* Order of deviations values:
* \((f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3,
* s_4, \tau_x, \tau_y)\) If one of parameters is not estimated, it's deviation is equals to zero.
* param stdDeviationsExtrinsics Output vector of standard deviations estimated for extrinsic parameters.
* Order of deviations values: \((R_1, T_1, \dotsc , R_M, T_M)\) where M is number of pattern views,
* \(R_i, T_i\) are concatenated 1x3 vectors.
* param perViewErrors Output vector of average re-projection errors estimated for each pattern view.
*
* This function calibrates a camera using an Aruco Board. The function receives a list of
* detected markers from several views of the Board. The process is similar to the chessboard
* calibration in calibrateCamera(). The function returns the final re-projection error.
* return automatically generated
*/
public static double 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)
{
if (ids != null) ids.ThrowIfDisposed();
if (counter != null) counter.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
if (stdDeviationsIntrinsics != null) stdDeviationsIntrinsics.ThrowIfDisposed();
if (stdDeviationsExtrinsics != null) stdDeviationsExtrinsics.ThrowIfDisposed();
if (perViewErrors != null) perViewErrors.ThrowIfDisposed();
Mat corners_mat = Converters.vector_Mat_to_Mat(corners);
Mat rvecs_mat = new Mat();
Mat tvecs_mat = new Mat();
double retVal = aruco_Aruco_calibrateCameraArucoExtended_12(corners_mat.nativeObj, ids.nativeObj, counter.nativeObj, board.getNativeObjAddr(), imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs_mat.nativeObj, tvecs_mat.nativeObj, stdDeviationsIntrinsics.nativeObj, stdDeviationsExtrinsics.nativeObj, perViewErrors.nativeObj);
Converters.Mat_to_vector_Mat(rvecs_mat, rvecs);
rvecs_mat.release();
Converters.Mat_to_vector_Mat(tvecs_mat, tvecs);
tvecs_mat.release();
return retVal;
}
//
// C++: double cv::aruco::calibrateCameraAruco(vector_Mat corners, Mat ids, Mat counter, Ptr_Board board, Size imageSize, Mat& cameraMatrix, Mat& distCoeffs, vector_Mat& rvecs = vector_Mat(), vector_Mat& tvecs = vector_Mat(), int flags = 0, TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON))
//
/**
*
* It's the same function as #calibrateCameraAruco but without calibration error estimation.
* param corners automatically generated
* param ids automatically generated
* param counter automatically generated
* param board automatically generated
* param imageSize automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param rvecs automatically generated
* param tvecs automatically generated
* param flags automatically generated
* param criteria automatically generated
* return automatically generated
*/
public static double 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)
{
if (ids != null) ids.ThrowIfDisposed();
if (counter != null) counter.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat corners_mat = Converters.vector_Mat_to_Mat(corners);
Mat rvecs_mat = new Mat();
Mat tvecs_mat = new Mat();
double retVal = aruco_Aruco_calibrateCameraAruco_10(corners_mat.nativeObj, ids.nativeObj, counter.nativeObj, board.getNativeObjAddr(), imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs_mat.nativeObj, tvecs_mat.nativeObj, flags, criteria.type, criteria.maxCount, criteria.epsilon);
Converters.Mat_to_vector_Mat(rvecs_mat, rvecs);
rvecs_mat.release();
Converters.Mat_to_vector_Mat(tvecs_mat, tvecs);
tvecs_mat.release();
return retVal;
}
/**
*
* It's the same function as #calibrateCameraAruco but without calibration error estimation.
* param corners automatically generated
* param ids automatically generated
* param counter automatically generated
* param board automatically generated
* param imageSize automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param rvecs automatically generated
* param tvecs automatically generated
* param flags automatically generated
* return automatically generated
*/
public static double calibrateCameraAruco(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags)
{
if (ids != null) ids.ThrowIfDisposed();
if (counter != null) counter.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat corners_mat = Converters.vector_Mat_to_Mat(corners);
Mat rvecs_mat = new Mat();
Mat tvecs_mat = new Mat();
double retVal = aruco_Aruco_calibrateCameraAruco_11(corners_mat.nativeObj, ids.nativeObj, counter.nativeObj, board.getNativeObjAddr(), imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs_mat.nativeObj, tvecs_mat.nativeObj, flags);
Converters.Mat_to_vector_Mat(rvecs_mat, rvecs);
rvecs_mat.release();
Converters.Mat_to_vector_Mat(tvecs_mat, tvecs);
tvecs_mat.release();
return retVal;
}
/**
*
* It's the same function as #calibrateCameraAruco but without calibration error estimation.
* param corners automatically generated
* param ids automatically generated
* param counter automatically generated
* param board automatically generated
* param imageSize automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param rvecs automatically generated
* param tvecs automatically generated
* return automatically generated
*/
public static double calibrateCameraAruco(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs)
{
if (ids != null) ids.ThrowIfDisposed();
if (counter != null) counter.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat corners_mat = Converters.vector_Mat_to_Mat(corners);
Mat rvecs_mat = new Mat();
Mat tvecs_mat = new Mat();
double retVal = aruco_Aruco_calibrateCameraAruco_12(corners_mat.nativeObj, ids.nativeObj, counter.nativeObj, board.getNativeObjAddr(), imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs_mat.nativeObj, tvecs_mat.nativeObj);
Converters.Mat_to_vector_Mat(rvecs_mat, rvecs);
rvecs_mat.release();
Converters.Mat_to_vector_Mat(tvecs_mat, tvecs);
tvecs_mat.release();
return retVal;
}
/**
*
* It's the same function as #calibrateCameraAruco but without calibration error estimation.
* param corners automatically generated
* param ids automatically generated
* param counter automatically generated
* param board automatically generated
* param imageSize automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param rvecs automatically generated
* return automatically generated
*/
public static double calibrateCameraAruco(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs)
{
if (ids != null) ids.ThrowIfDisposed();
if (counter != null) counter.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat corners_mat = Converters.vector_Mat_to_Mat(corners);
Mat rvecs_mat = new Mat();
double retVal = aruco_Aruco_calibrateCameraAruco_13(corners_mat.nativeObj, ids.nativeObj, counter.nativeObj, board.getNativeObjAddr(), imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs_mat.nativeObj);
Converters.Mat_to_vector_Mat(rvecs_mat, rvecs);
rvecs_mat.release();
return retVal;
}
/**
*
* It's the same function as #calibrateCameraAruco but without calibration error estimation.
* param corners automatically generated
* param ids automatically generated
* param counter automatically generated
* param board automatically generated
* param imageSize automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* return automatically generated
*/
public static double calibrateCameraAruco(List<Mat> corners, Mat ids, Mat counter, Board board, Size imageSize, Mat cameraMatrix, Mat distCoeffs)
{
if (ids != null) ids.ThrowIfDisposed();
if (counter != null) counter.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat corners_mat = Converters.vector_Mat_to_Mat(corners);
return aruco_Aruco_calibrateCameraAruco_14(corners_mat.nativeObj, ids.nativeObj, counter.nativeObj, board.getNativeObjAddr(), imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj);
}
//
// C++: double cv::aruco::calibrateCameraCharuco(vector_Mat charucoCorners, vector_Mat charucoIds, Ptr_CharucoBoard board, Size imageSize, Mat& cameraMatrix, Mat& distCoeffs, vector_Mat& rvecs, vector_Mat& tvecs, Mat& stdDeviationsIntrinsics, Mat& stdDeviationsExtrinsics, Mat& perViewErrors, int flags = 0, TermCriteria criteria = TermCriteria( TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON))
//
/**
* Calibrate a camera using Charuco corners
*
* param charucoCorners vector of detected charuco corners per frame
* param charucoIds list of identifiers for each corner in charucoCorners per frame
* param board Marker Board layout
* param imageSize input image size
* param cameraMatrix Output 3x3 floating-point camera matrix
* \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\) . If CV\_CALIB\_USE\_INTRINSIC\_GUESS
* and/or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of fx, fy, cx, cy must be
* initialized before calling the function.
* param distCoeffs Output vector of distortion coefficients
* \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) of 4, 5, 8 or 12 elements
* param rvecs Output vector of rotation vectors (see Rodrigues ) estimated for each board view
* (e.g. std::vector&lt;cv::Mat&gt;&gt;). That is, each k-th rotation vector together with the corresponding
* k-th translation vector (see the next output parameter description) brings the board pattern
* from the model coordinate space (in which object points are specified) to the world coordinate
* space, that is, a real position of the board pattern in the k-th pattern view (k=0.. *M* -1).
* param tvecs Output vector of translation vectors estimated for each pattern view.
* param stdDeviationsIntrinsics Output vector of standard deviations estimated for intrinsic parameters.
* Order of deviations values:
* \((f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3,
* s_4, \tau_x, \tau_y)\) If one of parameters is not estimated, it's deviation is equals to zero.
* param stdDeviationsExtrinsics Output vector of standard deviations estimated for extrinsic parameters.
* Order of deviations values: \((R_1, T_1, \dotsc , R_M, T_M)\) where M is number of pattern views,
* \(R_i, T_i\) are concatenated 1x3 vectors.
* param perViewErrors Output vector of average re-projection errors estimated for each pattern view.
* param flags flags Different flags for the calibration process (see #calibrateCamera for details).
* param criteria Termination criteria for the iterative optimization algorithm.
*
* This function calibrates a camera using a set of corners of a Charuco Board. The function
* receives a list of detected corners and its identifiers from several views of the Board.
* The function returns the final re-projection error.
* return automatically generated
*/
public static double 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)
{
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
if (stdDeviationsIntrinsics != null) stdDeviationsIntrinsics.ThrowIfDisposed();
if (stdDeviationsExtrinsics != null) stdDeviationsExtrinsics.ThrowIfDisposed();
if (perViewErrors != null) perViewErrors.ThrowIfDisposed();
Mat charucoCorners_mat = Converters.vector_Mat_to_Mat(charucoCorners);
Mat charucoIds_mat = Converters.vector_Mat_to_Mat(charucoIds);
Mat rvecs_mat = new Mat();
Mat tvecs_mat = new Mat();
double retVal = aruco_Aruco_calibrateCameraCharucoExtended_10(charucoCorners_mat.nativeObj, charucoIds_mat.nativeObj, board.getNativeObjAddr(), imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs_mat.nativeObj, tvecs_mat.nativeObj, stdDeviationsIntrinsics.nativeObj, stdDeviationsExtrinsics.nativeObj, perViewErrors.nativeObj, flags, criteria.type, criteria.maxCount, criteria.epsilon);
Converters.Mat_to_vector_Mat(rvecs_mat, rvecs);
rvecs_mat.release();
Converters.Mat_to_vector_Mat(tvecs_mat, tvecs);
tvecs_mat.release();
return retVal;
}
/**
* Calibrate a camera using Charuco corners
*
* param charucoCorners vector of detected charuco corners per frame
* param charucoIds list of identifiers for each corner in charucoCorners per frame
* param board Marker Board layout
* param imageSize input image size
* param cameraMatrix Output 3x3 floating-point camera matrix
* \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\) . If CV\_CALIB\_USE\_INTRINSIC\_GUESS
* and/or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of fx, fy, cx, cy must be
* initialized before calling the function.
* param distCoeffs Output vector of distortion coefficients
* \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) of 4, 5, 8 or 12 elements
* param rvecs Output vector of rotation vectors (see Rodrigues ) estimated for each board view
* (e.g. std::vector&lt;cv::Mat&gt;&gt;). That is, each k-th rotation vector together with the corresponding
* k-th translation vector (see the next output parameter description) brings the board pattern
* from the model coordinate space (in which object points are specified) to the world coordinate
* space, that is, a real position of the board pattern in the k-th pattern view (k=0.. *M* -1).
* param tvecs Output vector of translation vectors estimated for each pattern view.
* param stdDeviationsIntrinsics Output vector of standard deviations estimated for intrinsic parameters.
* Order of deviations values:
* \((f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3,
* s_4, \tau_x, \tau_y)\) If one of parameters is not estimated, it's deviation is equals to zero.
* param stdDeviationsExtrinsics Output vector of standard deviations estimated for extrinsic parameters.
* Order of deviations values: \((R_1, T_1, \dotsc , R_M, T_M)\) where M is number of pattern views,
* \(R_i, T_i\) are concatenated 1x3 vectors.
* param perViewErrors Output vector of average re-projection errors estimated for each pattern view.
* param flags flags Different flags for the calibration process (see #calibrateCamera for details).
*
* This function calibrates a camera using a set of corners of a Charuco Board. The function
* receives a list of detected corners and its identifiers from several views of the Board.
* The function returns the final re-projection error.
* return automatically generated
*/
public static double 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)
{
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
if (stdDeviationsIntrinsics != null) stdDeviationsIntrinsics.ThrowIfDisposed();
if (stdDeviationsExtrinsics != null) stdDeviationsExtrinsics.ThrowIfDisposed();
if (perViewErrors != null) perViewErrors.ThrowIfDisposed();
Mat charucoCorners_mat = Converters.vector_Mat_to_Mat(charucoCorners);
Mat charucoIds_mat = Converters.vector_Mat_to_Mat(charucoIds);
Mat rvecs_mat = new Mat();
Mat tvecs_mat = new Mat();
double retVal = aruco_Aruco_calibrateCameraCharucoExtended_11(charucoCorners_mat.nativeObj, charucoIds_mat.nativeObj, board.getNativeObjAddr(), imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs_mat.nativeObj, tvecs_mat.nativeObj, stdDeviationsIntrinsics.nativeObj, stdDeviationsExtrinsics.nativeObj, perViewErrors.nativeObj, flags);
Converters.Mat_to_vector_Mat(rvecs_mat, rvecs);
rvecs_mat.release();
Converters.Mat_to_vector_Mat(tvecs_mat, tvecs);
tvecs_mat.release();
return retVal;
}
/**
* Calibrate a camera using Charuco corners
*
* param charucoCorners vector of detected charuco corners per frame
* param charucoIds list of identifiers for each corner in charucoCorners per frame
* param board Marker Board layout
* param imageSize input image size
* param cameraMatrix Output 3x3 floating-point camera matrix
* \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\) . If CV\_CALIB\_USE\_INTRINSIC\_GUESS
* and/or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of fx, fy, cx, cy must be
* initialized before calling the function.
* param distCoeffs Output vector of distortion coefficients
* \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) of 4, 5, 8 or 12 elements
* param rvecs Output vector of rotation vectors (see Rodrigues ) estimated for each board view
* (e.g. std::vector&lt;cv::Mat&gt;&gt;). That is, each k-th rotation vector together with the corresponding
* k-th translation vector (see the next output parameter description) brings the board pattern
* from the model coordinate space (in which object points are specified) to the world coordinate
* space, that is, a real position of the board pattern in the k-th pattern view (k=0.. *M* -1).
* param tvecs Output vector of translation vectors estimated for each pattern view.
* param stdDeviationsIntrinsics Output vector of standard deviations estimated for intrinsic parameters.
* Order of deviations values:
* \((f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3,
* s_4, \tau_x, \tau_y)\) If one of parameters is not estimated, it's deviation is equals to zero.
* param stdDeviationsExtrinsics Output vector of standard deviations estimated for extrinsic parameters.
* Order of deviations values: \((R_1, T_1, \dotsc , R_M, T_M)\) where M is number of pattern views,
* \(R_i, T_i\) are concatenated 1x3 vectors.
* param perViewErrors Output vector of average re-projection errors estimated for each pattern view.
*
* This function calibrates a camera using a set of corners of a Charuco Board. The function
* receives a list of detected corners and its identifiers from several views of the Board.
* The function returns the final re-projection error.
* return automatically generated
*/
public static double 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)
{
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
if (stdDeviationsIntrinsics != null) stdDeviationsIntrinsics.ThrowIfDisposed();
if (stdDeviationsExtrinsics != null) stdDeviationsExtrinsics.ThrowIfDisposed();
if (perViewErrors != null) perViewErrors.ThrowIfDisposed();
Mat charucoCorners_mat = Converters.vector_Mat_to_Mat(charucoCorners);
Mat charucoIds_mat = Converters.vector_Mat_to_Mat(charucoIds);
Mat rvecs_mat = new Mat();
Mat tvecs_mat = new Mat();
double retVal = aruco_Aruco_calibrateCameraCharucoExtended_12(charucoCorners_mat.nativeObj, charucoIds_mat.nativeObj, board.getNativeObjAddr(), imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs_mat.nativeObj, tvecs_mat.nativeObj, stdDeviationsIntrinsics.nativeObj, stdDeviationsExtrinsics.nativeObj, perViewErrors.nativeObj);
Converters.Mat_to_vector_Mat(rvecs_mat, rvecs);
rvecs_mat.release();
Converters.Mat_to_vector_Mat(tvecs_mat, tvecs);
tvecs_mat.release();
return retVal;
}
//
// C++: double cv::aruco::calibrateCameraCharuco(vector_Mat charucoCorners, vector_Mat charucoIds, Ptr_CharucoBoard board, Size imageSize, Mat& cameraMatrix, Mat& distCoeffs, vector_Mat& rvecs = vector_Mat(), vector_Mat& tvecs = vector_Mat(), int flags = 0, TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON))
//
/**
* It's the same function as #calibrateCameraCharuco but without calibration error estimation.
* param charucoCorners automatically generated
* param charucoIds automatically generated
* param board automatically generated
* param imageSize automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param rvecs automatically generated
* param tvecs automatically generated
* param flags automatically generated
* param criteria automatically generated
* return automatically generated
*/
public static double 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)
{
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat charucoCorners_mat = Converters.vector_Mat_to_Mat(charucoCorners);
Mat charucoIds_mat = Converters.vector_Mat_to_Mat(charucoIds);
Mat rvecs_mat = new Mat();
Mat tvecs_mat = new Mat();
double retVal = aruco_Aruco_calibrateCameraCharuco_10(charucoCorners_mat.nativeObj, charucoIds_mat.nativeObj, board.getNativeObjAddr(), imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs_mat.nativeObj, tvecs_mat.nativeObj, flags, criteria.type, criteria.maxCount, criteria.epsilon);
Converters.Mat_to_vector_Mat(rvecs_mat, rvecs);
rvecs_mat.release();
Converters.Mat_to_vector_Mat(tvecs_mat, tvecs);
tvecs_mat.release();
return retVal;
}
/**
* It's the same function as #calibrateCameraCharuco but without calibration error estimation.
* param charucoCorners automatically generated
* param charucoIds automatically generated
* param board automatically generated
* param imageSize automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param rvecs automatically generated
* param tvecs automatically generated
* param flags automatically generated
* return automatically generated
*/
public static double calibrateCameraCharuco(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags)
{
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat charucoCorners_mat = Converters.vector_Mat_to_Mat(charucoCorners);
Mat charucoIds_mat = Converters.vector_Mat_to_Mat(charucoIds);
Mat rvecs_mat = new Mat();
Mat tvecs_mat = new Mat();
double retVal = aruco_Aruco_calibrateCameraCharuco_11(charucoCorners_mat.nativeObj, charucoIds_mat.nativeObj, board.getNativeObjAddr(), imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs_mat.nativeObj, tvecs_mat.nativeObj, flags);
Converters.Mat_to_vector_Mat(rvecs_mat, rvecs);
rvecs_mat.release();
Converters.Mat_to_vector_Mat(tvecs_mat, tvecs);
tvecs_mat.release();
return retVal;
}
/**
* It's the same function as #calibrateCameraCharuco but without calibration error estimation.
* param charucoCorners automatically generated
* param charucoIds automatically generated
* param board automatically generated
* param imageSize automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param rvecs automatically generated
* param tvecs automatically generated
* return automatically generated
*/
public static double calibrateCameraCharuco(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs)
{
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat charucoCorners_mat = Converters.vector_Mat_to_Mat(charucoCorners);
Mat charucoIds_mat = Converters.vector_Mat_to_Mat(charucoIds);
Mat rvecs_mat = new Mat();
Mat tvecs_mat = new Mat();
double retVal = aruco_Aruco_calibrateCameraCharuco_12(charucoCorners_mat.nativeObj, charucoIds_mat.nativeObj, board.getNativeObjAddr(), imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs_mat.nativeObj, tvecs_mat.nativeObj);
Converters.Mat_to_vector_Mat(rvecs_mat, rvecs);
rvecs_mat.release();
Converters.Mat_to_vector_Mat(tvecs_mat, tvecs);
tvecs_mat.release();
return retVal;
}
/**
* It's the same function as #calibrateCameraCharuco but without calibration error estimation.
* param charucoCorners automatically generated
* param charucoIds automatically generated
* param board automatically generated
* param imageSize automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* param rvecs automatically generated
* return automatically generated
*/
public static double calibrateCameraCharuco(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs)
{
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat charucoCorners_mat = Converters.vector_Mat_to_Mat(charucoCorners);
Mat charucoIds_mat = Converters.vector_Mat_to_Mat(charucoIds);
Mat rvecs_mat = new Mat();
double retVal = aruco_Aruco_calibrateCameraCharuco_13(charucoCorners_mat.nativeObj, charucoIds_mat.nativeObj, board.getNativeObjAddr(), imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs_mat.nativeObj);
Converters.Mat_to_vector_Mat(rvecs_mat, rvecs);
rvecs_mat.release();
return retVal;
}
/**
* It's the same function as #calibrateCameraCharuco but without calibration error estimation.
* param charucoCorners automatically generated
* param charucoIds automatically generated
* param board automatically generated
* param imageSize automatically generated
* param cameraMatrix automatically generated
* param distCoeffs automatically generated
* return automatically generated
*/
public static double calibrateCameraCharuco(List<Mat> charucoCorners, List<Mat> charucoIds, CharucoBoard board, Size imageSize, Mat cameraMatrix, Mat distCoeffs)
{
if (board != null) board.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat charucoCorners_mat = Converters.vector_Mat_to_Mat(charucoCorners);
Mat charucoIds_mat = Converters.vector_Mat_to_Mat(charucoIds);
return aruco_Aruco_calibrateCameraCharuco_14(charucoCorners_mat.nativeObj, charucoIds_mat.nativeObj, board.getNativeObjAddr(), imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj);
}
//
// C++: int cv::aruco::interpolateCornersCharuco(vector_Mat markerCorners, Mat markerIds, Mat image, Ptr_CharucoBoard board, Mat& charucoCorners, Mat& charucoIds, Mat cameraMatrix = Mat(), Mat distCoeffs = Mat(), int minMarkers = 2)
//
/**
* Interpolate position of ChArUco board corners
* param markerCorners vector of already detected markers corners. For each marker, its four
* corners are provided, (e.g std::vector&lt;std::vector&lt;cv::Point2f&gt; &gt; ). For N detected markers, the
* dimensions of this array should be Nx4. The order of the corners should be clockwise.
* param markerIds list of identifiers for each marker in corners
* param image input image necesary for corner refinement. Note that markers are not detected and
* should be sent in corners and ids parameters.
* param board layout of ChArUco board.
* param charucoCorners interpolated chessboard corners
* param charucoIds interpolated chessboard corners identifiers
* param cameraMatrix optional 3x3 floating-point camera matrix
* \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\)
* param distCoeffs optional vector of distortion coefficients
* \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) of 4, 5, 8 or 12 elements
* param minMarkers number of adjacent markers that must be detected to return a charuco corner
*
* This function receives the detected markers and returns the 2D position of the chessboard corners
* from a ChArUco board using the detected Aruco markers. If camera parameters are provided,
* the process is based in an approximated pose estimation, else it is based on local homography.
* Only visible corners are returned. For each corner, its corresponding identifier is
* also returned in charucoIds.
* The function returns the number of interpolated corners.
*
* deprecated Use CharucoDetector::detectBoard
* return automatically generated
*/
[Obsolete("This method is deprecated.")]
public static int interpolateCornersCharuco(List<Mat> markerCorners, Mat markerIds, Mat image, CharucoBoard board, Mat charucoCorners, Mat charucoIds, Mat cameraMatrix, Mat distCoeffs, int minMarkers)
{
if (markerIds != null) markerIds.ThrowIfDisposed();
if (image != null) image.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (charucoCorners != null) charucoCorners.ThrowIfDisposed();
if (charucoIds != null) charucoIds.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat markerCorners_mat = Converters.vector_Mat_to_Mat(markerCorners);
return aruco_Aruco_interpolateCornersCharuco_10(markerCorners_mat.nativeObj, markerIds.nativeObj, image.nativeObj, board.getNativeObjAddr(), charucoCorners.nativeObj, charucoIds.nativeObj, cameraMatrix.nativeObj, distCoeffs.nativeObj, minMarkers);
}
/**
* Interpolate position of ChArUco board corners
* param markerCorners vector of already detected markers corners. For each marker, its four
* corners are provided, (e.g std::vector&lt;std::vector&lt;cv::Point2f&gt; &gt; ). For N detected markers, the
* dimensions of this array should be Nx4. The order of the corners should be clockwise.
* param markerIds list of identifiers for each marker in corners
* param image input image necesary for corner refinement. Note that markers are not detected and
* should be sent in corners and ids parameters.
* param board layout of ChArUco board.
* param charucoCorners interpolated chessboard corners
* param charucoIds interpolated chessboard corners identifiers
* param cameraMatrix optional 3x3 floating-point camera matrix
* \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\)
* param distCoeffs optional vector of distortion coefficients
* \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) of 4, 5, 8 or 12 elements
*
* This function receives the detected markers and returns the 2D position of the chessboard corners
* from a ChArUco board using the detected Aruco markers. If camera parameters are provided,
* the process is based in an approximated pose estimation, else it is based on local homography.
* Only visible corners are returned. For each corner, its corresponding identifier is
* also returned in charucoIds.
* The function returns the number of interpolated corners.
*
* deprecated Use CharucoDetector::detectBoard
* return automatically generated
*/
[Obsolete("This method is deprecated.")]
public static int interpolateCornersCharuco(List<Mat> markerCorners, Mat markerIds, Mat image, CharucoBoard board, Mat charucoCorners, Mat charucoIds, Mat cameraMatrix, Mat distCoeffs)
{
if (markerIds != null) markerIds.ThrowIfDisposed();
if (image != null) image.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (charucoCorners != null) charucoCorners.ThrowIfDisposed();
if (charucoIds != null) charucoIds.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat markerCorners_mat = Converters.vector_Mat_to_Mat(markerCorners);
return aruco_Aruco_interpolateCornersCharuco_11(markerCorners_mat.nativeObj, markerIds.nativeObj, image.nativeObj, board.getNativeObjAddr(), charucoCorners.nativeObj, charucoIds.nativeObj, cameraMatrix.nativeObj, distCoeffs.nativeObj);
}
/**
* Interpolate position of ChArUco board corners
* param markerCorners vector of already detected markers corners. For each marker, its four
* corners are provided, (e.g std::vector&lt;std::vector&lt;cv::Point2f&gt; &gt; ). For N detected markers, the
* dimensions of this array should be Nx4. The order of the corners should be clockwise.
* param markerIds list of identifiers for each marker in corners
* param image input image necesary for corner refinement. Note that markers are not detected and
* should be sent in corners and ids parameters.
* param board layout of ChArUco board.
* param charucoCorners interpolated chessboard corners
* param charucoIds interpolated chessboard corners identifiers
* param cameraMatrix optional 3x3 floating-point camera matrix
* \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\)
* \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) of 4, 5, 8 or 12 elements
*
* This function receives the detected markers and returns the 2D position of the chessboard corners
* from a ChArUco board using the detected Aruco markers. If camera parameters are provided,
* the process is based in an approximated pose estimation, else it is based on local homography.
* Only visible corners are returned. For each corner, its corresponding identifier is
* also returned in charucoIds.
* The function returns the number of interpolated corners.
*
* deprecated Use CharucoDetector::detectBoard
* return automatically generated
*/
[Obsolete("This method is deprecated.")]
public static int interpolateCornersCharuco(List<Mat> markerCorners, Mat markerIds, Mat image, CharucoBoard board, Mat charucoCorners, Mat charucoIds, Mat cameraMatrix)
{
if (markerIds != null) markerIds.ThrowIfDisposed();
if (image != null) image.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (charucoCorners != null) charucoCorners.ThrowIfDisposed();
if (charucoIds != null) charucoIds.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
Mat markerCorners_mat = Converters.vector_Mat_to_Mat(markerCorners);
return aruco_Aruco_interpolateCornersCharuco_12(markerCorners_mat.nativeObj, markerIds.nativeObj, image.nativeObj, board.getNativeObjAddr(), charucoCorners.nativeObj, charucoIds.nativeObj, cameraMatrix.nativeObj);
}
/**
* Interpolate position of ChArUco board corners
* param markerCorners vector of already detected markers corners. For each marker, its four
* corners are provided, (e.g std::vector&lt;std::vector&lt;cv::Point2f&gt; &gt; ). For N detected markers, the
* dimensions of this array should be Nx4. The order of the corners should be clockwise.
* param markerIds list of identifiers for each marker in corners
* param image input image necesary for corner refinement. Note that markers are not detected and
* should be sent in corners and ids parameters.
* param board layout of ChArUco board.
* param charucoCorners interpolated chessboard corners
* param charucoIds interpolated chessboard corners identifiers
* \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\)
* \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) of 4, 5, 8 or 12 elements
*
* This function receives the detected markers and returns the 2D position of the chessboard corners
* from a ChArUco board using the detected Aruco markers. If camera parameters are provided,
* the process is based in an approximated pose estimation, else it is based on local homography.
* Only visible corners are returned. For each corner, its corresponding identifier is
* also returned in charucoIds.
* The function returns the number of interpolated corners.
*
* deprecated Use CharucoDetector::detectBoard
* return automatically generated
*/
[Obsolete("This method is deprecated.")]
public static int interpolateCornersCharuco(List<Mat> markerCorners, Mat markerIds, Mat image, CharucoBoard board, Mat charucoCorners, Mat charucoIds)
{
if (markerIds != null) markerIds.ThrowIfDisposed();
if (image != null) image.ThrowIfDisposed();
if (board != null) board.ThrowIfDisposed();
if (charucoCorners != null) charucoCorners.ThrowIfDisposed();
if (charucoIds != null) charucoIds.ThrowIfDisposed();
Mat markerCorners_mat = Converters.vector_Mat_to_Mat(markerCorners);
return aruco_Aruco_interpolateCornersCharuco_13(markerCorners_mat.nativeObj, markerIds.nativeObj, image.nativeObj, board.getNativeObjAddr(), charucoCorners.nativeObj, charucoIds.nativeObj);
}
//
// C++: void cv::aruco::detectCharucoDiamond(Mat image, vector_Mat markerCorners, Mat markerIds, float squareMarkerLengthRate, vector_Mat& diamondCorners, Mat& diamondIds, Mat cameraMatrix = Mat(), Mat distCoeffs = Mat(), Ptr_Dictionary dictionary = makePtr<Dictionary> (getPredefinedDictionary(PredefinedDictionaryType::DICT_4X4_50)))
//
/**
* Detect ChArUco Diamond markers
*
* param image input image necessary for corner subpixel.
* param markerCorners list of detected marker corners from detectMarkers function.
* param markerIds list of marker ids in markerCorners.
* param squareMarkerLengthRate rate between square and marker length:
* squareMarkerLengthRate = squareLength/markerLength. The real units are not necessary.
* param diamondCorners output list of detected diamond corners (4 corners per diamond). The order
* is the same than in marker corners: top left, top right, bottom right and bottom left. Similar
* format than the corners returned by detectMarkers (e.g std::vector&lt;std::vector&lt;cv::Point2f&gt; &gt; ).
* param diamondIds ids of the diamonds in diamondCorners. The id of each diamond is in fact of
* type Vec4i, so each diamond has 4 ids, which are the ids of the aruco markers composing the
* diamond.
* param cameraMatrix Optional camera calibration matrix.
* param distCoeffs Optional camera distortion coefficients.
* param dictionary dictionary of markers indicating the type of markers.
*
* This function detects Diamond markers from the previous detected ArUco markers. The diamonds
* are returned in the diamondCorners and diamondIds parameters. If camera calibration parameters
* are provided, the diamond search is based on reprojection. If not, diamond search is based on
* homography. Homography is faster than reprojection, but less accurate.
*
* deprecated Use CharucoDetector::detectDiamonds
*/
[Obsolete("This method is deprecated.")]
public static void detectCharucoDiamond(Mat image, List<Mat> markerCorners, Mat markerIds, float squareMarkerLengthRate, List<Mat> diamondCorners, Mat diamondIds, Mat cameraMatrix, Mat distCoeffs, Dictionary dictionary)
{
if (image != null) image.ThrowIfDisposed();
if (markerIds != null) markerIds.ThrowIfDisposed();
if (diamondIds != null) diamondIds.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
if (dictionary != null) dictionary.ThrowIfDisposed();
Mat markerCorners_mat = Converters.vector_Mat_to_Mat(markerCorners);
Mat diamondCorners_mat = new Mat();
aruco_Aruco_detectCharucoDiamond_10(image.nativeObj, markerCorners_mat.nativeObj, markerIds.nativeObj, squareMarkerLengthRate, diamondCorners_mat.nativeObj, diamondIds.nativeObj, cameraMatrix.nativeObj, distCoeffs.nativeObj, dictionary.getNativeObjAddr());
Converters.Mat_to_vector_Mat(diamondCorners_mat, diamondCorners);
diamondCorners_mat.release();
}
/**
* Detect ChArUco Diamond markers
*
* param image input image necessary for corner subpixel.
* param markerCorners list of detected marker corners from detectMarkers function.
* param markerIds list of marker ids in markerCorners.
* param squareMarkerLengthRate rate between square and marker length:
* squareMarkerLengthRate = squareLength/markerLength. The real units are not necessary.
* param diamondCorners output list of detected diamond corners (4 corners per diamond). The order
* is the same than in marker corners: top left, top right, bottom right and bottom left. Similar
* format than the corners returned by detectMarkers (e.g std::vector&lt;std::vector&lt;cv::Point2f&gt; &gt; ).
* param diamondIds ids of the diamonds in diamondCorners. The id of each diamond is in fact of
* type Vec4i, so each diamond has 4 ids, which are the ids of the aruco markers composing the
* diamond.
* param cameraMatrix Optional camera calibration matrix.
* param distCoeffs Optional camera distortion coefficients.
*
* This function detects Diamond markers from the previous detected ArUco markers. The diamonds
* are returned in the diamondCorners and diamondIds parameters. If camera calibration parameters
* are provided, the diamond search is based on reprojection. If not, diamond search is based on
* homography. Homography is faster than reprojection, but less accurate.
*
* deprecated Use CharucoDetector::detectDiamonds
*/
[Obsolete("This method is deprecated.")]
public static void detectCharucoDiamond(Mat image, List<Mat> markerCorners, Mat markerIds, float squareMarkerLengthRate, List<Mat> diamondCorners, Mat diamondIds, Mat cameraMatrix, Mat distCoeffs)
{
if (image != null) image.ThrowIfDisposed();
if (markerIds != null) markerIds.ThrowIfDisposed();
if (diamondIds != null) diamondIds.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
if (distCoeffs != null) distCoeffs.ThrowIfDisposed();
Mat markerCorners_mat = Converters.vector_Mat_to_Mat(markerCorners);
Mat diamondCorners_mat = new Mat();
aruco_Aruco_detectCharucoDiamond_11(image.nativeObj, markerCorners_mat.nativeObj, markerIds.nativeObj, squareMarkerLengthRate, diamondCorners_mat.nativeObj, diamondIds.nativeObj, cameraMatrix.nativeObj, distCoeffs.nativeObj);
Converters.Mat_to_vector_Mat(diamondCorners_mat, diamondCorners);
diamondCorners_mat.release();
}
/**
* Detect ChArUco Diamond markers
*
* param image input image necessary for corner subpixel.
* param markerCorners list of detected marker corners from detectMarkers function.
* param markerIds list of marker ids in markerCorners.
* param squareMarkerLengthRate rate between square and marker length:
* squareMarkerLengthRate = squareLength/markerLength. The real units are not necessary.
* param diamondCorners output list of detected diamond corners (4 corners per diamond). The order
* is the same than in marker corners: top left, top right, bottom right and bottom left. Similar
* format than the corners returned by detectMarkers (e.g std::vector&lt;std::vector&lt;cv::Point2f&gt; &gt; ).
* param diamondIds ids of the diamonds in diamondCorners. The id of each diamond is in fact of
* type Vec4i, so each diamond has 4 ids, which are the ids of the aruco markers composing the
* diamond.
* param cameraMatrix Optional camera calibration matrix.
*
* This function detects Diamond markers from the previous detected ArUco markers. The diamonds
* are returned in the diamondCorners and diamondIds parameters. If camera calibration parameters
* are provided, the diamond search is based on reprojection. If not, diamond search is based on
* homography. Homography is faster than reprojection, but less accurate.
*
* deprecated Use CharucoDetector::detectDiamonds
*/
[Obsolete("This method is deprecated.")]
public static void detectCharucoDiamond(Mat image, List<Mat> markerCorners, Mat markerIds, float squareMarkerLengthRate, List<Mat> diamondCorners, Mat diamondIds, Mat cameraMatrix)
{
if (image != null) image.ThrowIfDisposed();
if (markerIds != null) markerIds.ThrowIfDisposed();
if (diamondIds != null) diamondIds.ThrowIfDisposed();
if (cameraMatrix != null) cameraMatrix.ThrowIfDisposed();
Mat markerCorners_mat = Converters.vector_Mat_to_Mat(markerCorners);
Mat diamondCorners_mat = new Mat();
aruco_Aruco_detectCharucoDiamond_12(image.nativeObj, markerCorners_mat.nativeObj, markerIds.nativeObj, squareMarkerLengthRate, diamondCorners_mat.nativeObj, diamondIds.nativeObj, cameraMatrix.nativeObj);
Converters.Mat_to_vector_Mat(diamondCorners_mat, diamondCorners);
diamondCorners_mat.release();
}
/**
* Detect ChArUco Diamond markers
*
* param image input image necessary for corner subpixel.
* param markerCorners list of detected marker corners from detectMarkers function.
* param markerIds list of marker ids in markerCorners.
* param squareMarkerLengthRate rate between square and marker length:
* squareMarkerLengthRate = squareLength/markerLength. The real units are not necessary.
* param diamondCorners output list of detected diamond corners (4 corners per diamond). The order
* is the same than in marker corners: top left, top right, bottom right and bottom left. Similar
* format than the corners returned by detectMarkers (e.g std::vector&lt;std::vector&lt;cv::Point2f&gt; &gt; ).
* param diamondIds ids of the diamonds in diamondCorners. The id of each diamond is in fact of
* type Vec4i, so each diamond has 4 ids, which are the ids of the aruco markers composing the
* diamond.
*
* This function detects Diamond markers from the previous detected ArUco markers. The diamonds
* are returned in the diamondCorners and diamondIds parameters. If camera calibration parameters
* are provided, the diamond search is based on reprojection. If not, diamond search is based on
* homography. Homography is faster than reprojection, but less accurate.
*
* deprecated Use CharucoDetector::detectDiamonds
*/
[Obsolete("This method is deprecated.")]
public static void detectCharucoDiamond(Mat image, List<Mat> markerCorners, Mat markerIds, float squareMarkerLengthRate, List<Mat> diamondCorners, Mat diamondIds)
{
if (image != null) image.ThrowIfDisposed();
if (markerIds != null) markerIds.ThrowIfDisposed();
if (diamondIds != null) diamondIds.ThrowIfDisposed();
Mat markerCorners_mat = Converters.vector_Mat_to_Mat(markerCorners);
Mat diamondCorners_mat = new Mat();
aruco_Aruco_detectCharucoDiamond_13(image.nativeObj, markerCorners_mat.nativeObj, markerIds.nativeObj, squareMarkerLengthRate, diamondCorners_mat.nativeObj, diamondIds.nativeObj);
Converters.Mat_to_vector_Mat(diamondCorners_mat, diamondCorners);
diamondCorners_mat.release();
}
//
// C++: void cv::aruco::drawCharucoDiamond(Ptr_Dictionary dictionary, Vec4i ids, int squareLength, int markerLength, Mat& img, int marginSize = 0, int borderBits = 1)
//
// Unknown type 'Vec4i' (I), skipping the function
#if (UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR
const string LIBNAME = "__Internal";
#else
const string LIBNAME = "opencvforunity";
#endif
// C++: void cv::aruco::detectMarkers(Mat image, Ptr_Dictionary dictionary, vector_Mat& corners, Mat& ids, Ptr_DetectorParameters parameters = makePtr<DetectorParameters>(), vector_Mat& rejectedImgPoints = vector_Mat())
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_detectMarkers_10(IntPtr image_nativeObj, IntPtr dictionary_nativeObj, IntPtr corners_mat_nativeObj, IntPtr ids_nativeObj, IntPtr parameters_nativeObj, IntPtr rejectedImgPoints_mat_nativeObj);
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_detectMarkers_11(IntPtr image_nativeObj, IntPtr dictionary_nativeObj, IntPtr corners_mat_nativeObj, IntPtr ids_nativeObj, IntPtr parameters_nativeObj);
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_detectMarkers_12(IntPtr image_nativeObj, IntPtr dictionary_nativeObj, IntPtr corners_mat_nativeObj, IntPtr ids_nativeObj);
// C++: void cv::aruco::refineDetectedMarkers(Mat image, Ptr_Board board, vector_Mat& detectedCorners, Mat& detectedIds, vector_Mat& rejectedCorners, Mat cameraMatrix = Mat(), Mat distCoeffs = Mat(), float minRepDistance = 10.f, float errorCorrectionRate = 3.f, bool checkAllOrders = true, Mat& recoveredIdxs = Mat(), Ptr_DetectorParameters parameters = makePtr<DetectorParameters>())
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_refineDetectedMarkers_10(IntPtr image_nativeObj, IntPtr board_nativeObj, IntPtr detectedCorners_mat_nativeObj, IntPtr detectedIds_nativeObj, IntPtr rejectedCorners_mat_nativeObj, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, float minRepDistance, float errorCorrectionRate, [MarshalAs(UnmanagedType.U1)] bool checkAllOrders, IntPtr recoveredIdxs_nativeObj, IntPtr parameters_nativeObj);
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_refineDetectedMarkers_11(IntPtr image_nativeObj, IntPtr board_nativeObj, IntPtr detectedCorners_mat_nativeObj, IntPtr detectedIds_nativeObj, IntPtr rejectedCorners_mat_nativeObj, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, float minRepDistance, float errorCorrectionRate, [MarshalAs(UnmanagedType.U1)] bool checkAllOrders, IntPtr recoveredIdxs_nativeObj);
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_refineDetectedMarkers_12(IntPtr image_nativeObj, IntPtr board_nativeObj, IntPtr detectedCorners_mat_nativeObj, IntPtr detectedIds_nativeObj, IntPtr rejectedCorners_mat_nativeObj, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, float minRepDistance, float errorCorrectionRate, [MarshalAs(UnmanagedType.U1)] bool checkAllOrders);
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_refineDetectedMarkers_13(IntPtr image_nativeObj, IntPtr board_nativeObj, IntPtr detectedCorners_mat_nativeObj, IntPtr detectedIds_nativeObj, IntPtr rejectedCorners_mat_nativeObj, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, float minRepDistance, float errorCorrectionRate);
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_refineDetectedMarkers_14(IntPtr image_nativeObj, IntPtr board_nativeObj, IntPtr detectedCorners_mat_nativeObj, IntPtr detectedIds_nativeObj, IntPtr rejectedCorners_mat_nativeObj, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, float minRepDistance);
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_refineDetectedMarkers_15(IntPtr image_nativeObj, IntPtr board_nativeObj, IntPtr detectedCorners_mat_nativeObj, IntPtr detectedIds_nativeObj, IntPtr rejectedCorners_mat_nativeObj, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj);
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_refineDetectedMarkers_16(IntPtr image_nativeObj, IntPtr board_nativeObj, IntPtr detectedCorners_mat_nativeObj, IntPtr detectedIds_nativeObj, IntPtr rejectedCorners_mat_nativeObj, IntPtr cameraMatrix_nativeObj);
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_refineDetectedMarkers_17(IntPtr image_nativeObj, IntPtr board_nativeObj, IntPtr detectedCorners_mat_nativeObj, IntPtr detectedIds_nativeObj, IntPtr rejectedCorners_mat_nativeObj);
// C++: void cv::aruco::drawPlanarBoard(Ptr_Board board, Size outSize, Mat& img, int marginSize, int borderBits)
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_drawPlanarBoard_10(IntPtr board_nativeObj, double outSize_width, double outSize_height, IntPtr img_nativeObj, int marginSize, int borderBits);
// C++: void cv::aruco::getBoardObjectAndImagePoints(Ptr_Board board, vector_Mat detectedCorners, Mat detectedIds, Mat& objPoints, Mat& imgPoints)
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_getBoardObjectAndImagePoints_10(IntPtr board_nativeObj, IntPtr detectedCorners_mat_nativeObj, IntPtr detectedIds_nativeObj, IntPtr objPoints_nativeObj, IntPtr imgPoints_nativeObj);
// C++: int cv::aruco::estimatePoseBoard(vector_Mat corners, Mat ids, Ptr_Board board, Mat cameraMatrix, Mat distCoeffs, Mat& rvec, Mat& tvec, bool useExtrinsicGuess = false)
[DllImport(LIBNAME)]
private static extern int aruco_Aruco_estimatePoseBoard_10(IntPtr corners_mat_nativeObj, IntPtr ids_nativeObj, IntPtr board_nativeObj, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvec_nativeObj, IntPtr tvec_nativeObj, [MarshalAs(UnmanagedType.U1)] bool useExtrinsicGuess);
[DllImport(LIBNAME)]
private static extern int aruco_Aruco_estimatePoseBoard_11(IntPtr corners_mat_nativeObj, IntPtr ids_nativeObj, IntPtr board_nativeObj, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvec_nativeObj, IntPtr tvec_nativeObj);
// C++: bool cv::aruco::estimatePoseCharucoBoard(Mat charucoCorners, Mat charucoIds, Ptr_CharucoBoard board, Mat cameraMatrix, Mat distCoeffs, Mat& rvec, Mat& tvec, bool useExtrinsicGuess = false)
[DllImport(LIBNAME)]
[return: MarshalAs(UnmanagedType.U1)]
private static extern bool aruco_Aruco_estimatePoseCharucoBoard_10(IntPtr charucoCorners_nativeObj, IntPtr charucoIds_nativeObj, IntPtr board_nativeObj, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvec_nativeObj, IntPtr tvec_nativeObj, [MarshalAs(UnmanagedType.U1)] bool useExtrinsicGuess);
[DllImport(LIBNAME)]
[return: MarshalAs(UnmanagedType.U1)]
private static extern bool aruco_Aruco_estimatePoseCharucoBoard_11(IntPtr charucoCorners_nativeObj, IntPtr charucoIds_nativeObj, IntPtr board_nativeObj, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvec_nativeObj, IntPtr tvec_nativeObj);
// C++: void cv::aruco::estimatePoseSingleMarkers(vector_Mat corners, float markerLength, Mat cameraMatrix, Mat distCoeffs, Mat& rvecs, Mat& tvecs, Mat& objPoints = Mat(), Ptr_EstimateParameters estimateParameters = makePtr<EstimateParameters>())
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_estimatePoseSingleMarkers_10(IntPtr corners_mat_nativeObj, float markerLength, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_nativeObj, IntPtr tvecs_nativeObj, IntPtr objPoints_nativeObj, IntPtr estimateParameters_nativeObj);
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_estimatePoseSingleMarkers_11(IntPtr corners_mat_nativeObj, float markerLength, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_nativeObj, IntPtr tvecs_nativeObj, IntPtr objPoints_nativeObj);
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_estimatePoseSingleMarkers_12(IntPtr corners_mat_nativeObj, float markerLength, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_nativeObj, IntPtr tvecs_nativeObj);
// C++: bool cv::aruco::testCharucoCornersCollinear(Ptr_CharucoBoard board, Mat charucoIds)
[DllImport(LIBNAME)]
[return: MarshalAs(UnmanagedType.U1)]
private static extern bool aruco_Aruco_testCharucoCornersCollinear_10(IntPtr board_nativeObj, IntPtr charucoIds_nativeObj);
// C++: double cv::aruco::calibrateCameraAruco(vector_Mat corners, Mat ids, Mat counter, Ptr_Board board, Size imageSize, Mat& cameraMatrix, Mat& distCoeffs, vector_Mat& rvecs, vector_Mat& tvecs, Mat& stdDeviationsIntrinsics, Mat& stdDeviationsExtrinsics, Mat& perViewErrors, int flags = 0, TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON))
[DllImport(LIBNAME)]
private static extern double aruco_Aruco_calibrateCameraArucoExtended_10(IntPtr corners_mat_nativeObj, IntPtr ids_nativeObj, IntPtr counter_nativeObj, IntPtr board_nativeObj, double imageSize_width, double imageSize_height, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_mat_nativeObj, IntPtr tvecs_mat_nativeObj, IntPtr stdDeviationsIntrinsics_nativeObj, IntPtr stdDeviationsExtrinsics_nativeObj, IntPtr perViewErrors_nativeObj, int flags, int criteria_type, int criteria_maxCount, double criteria_epsilon);
[DllImport(LIBNAME)]
private static extern double aruco_Aruco_calibrateCameraArucoExtended_11(IntPtr corners_mat_nativeObj, IntPtr ids_nativeObj, IntPtr counter_nativeObj, IntPtr board_nativeObj, double imageSize_width, double imageSize_height, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_mat_nativeObj, IntPtr tvecs_mat_nativeObj, IntPtr stdDeviationsIntrinsics_nativeObj, IntPtr stdDeviationsExtrinsics_nativeObj, IntPtr perViewErrors_nativeObj, int flags);
[DllImport(LIBNAME)]
private static extern double aruco_Aruco_calibrateCameraArucoExtended_12(IntPtr corners_mat_nativeObj, IntPtr ids_nativeObj, IntPtr counter_nativeObj, IntPtr board_nativeObj, double imageSize_width, double imageSize_height, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_mat_nativeObj, IntPtr tvecs_mat_nativeObj, IntPtr stdDeviationsIntrinsics_nativeObj, IntPtr stdDeviationsExtrinsics_nativeObj, IntPtr perViewErrors_nativeObj);
// C++: double cv::aruco::calibrateCameraAruco(vector_Mat corners, Mat ids, Mat counter, Ptr_Board board, Size imageSize, Mat& cameraMatrix, Mat& distCoeffs, vector_Mat& rvecs = vector_Mat(), vector_Mat& tvecs = vector_Mat(), int flags = 0, TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON))
[DllImport(LIBNAME)]
private static extern double aruco_Aruco_calibrateCameraAruco_10(IntPtr corners_mat_nativeObj, IntPtr ids_nativeObj, IntPtr counter_nativeObj, IntPtr board_nativeObj, double imageSize_width, double imageSize_height, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_mat_nativeObj, IntPtr tvecs_mat_nativeObj, int flags, int criteria_type, int criteria_maxCount, double criteria_epsilon);
[DllImport(LIBNAME)]
private static extern double aruco_Aruco_calibrateCameraAruco_11(IntPtr corners_mat_nativeObj, IntPtr ids_nativeObj, IntPtr counter_nativeObj, IntPtr board_nativeObj, double imageSize_width, double imageSize_height, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_mat_nativeObj, IntPtr tvecs_mat_nativeObj, int flags);
[DllImport(LIBNAME)]
private static extern double aruco_Aruco_calibrateCameraAruco_12(IntPtr corners_mat_nativeObj, IntPtr ids_nativeObj, IntPtr counter_nativeObj, IntPtr board_nativeObj, double imageSize_width, double imageSize_height, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_mat_nativeObj, IntPtr tvecs_mat_nativeObj);
[DllImport(LIBNAME)]
private static extern double aruco_Aruco_calibrateCameraAruco_13(IntPtr corners_mat_nativeObj, IntPtr ids_nativeObj, IntPtr counter_nativeObj, IntPtr board_nativeObj, double imageSize_width, double imageSize_height, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_mat_nativeObj);
[DllImport(LIBNAME)]
private static extern double aruco_Aruco_calibrateCameraAruco_14(IntPtr corners_mat_nativeObj, IntPtr ids_nativeObj, IntPtr counter_nativeObj, IntPtr board_nativeObj, double imageSize_width, double imageSize_height, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj);
// C++: double cv::aruco::calibrateCameraCharuco(vector_Mat charucoCorners, vector_Mat charucoIds, Ptr_CharucoBoard board, Size imageSize, Mat& cameraMatrix, Mat& distCoeffs, vector_Mat& rvecs, vector_Mat& tvecs, Mat& stdDeviationsIntrinsics, Mat& stdDeviationsExtrinsics, Mat& perViewErrors, int flags = 0, TermCriteria criteria = TermCriteria( TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON))
[DllImport(LIBNAME)]
private static extern double aruco_Aruco_calibrateCameraCharucoExtended_10(IntPtr charucoCorners_mat_nativeObj, IntPtr charucoIds_mat_nativeObj, IntPtr board_nativeObj, double imageSize_width, double imageSize_height, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_mat_nativeObj, IntPtr tvecs_mat_nativeObj, IntPtr stdDeviationsIntrinsics_nativeObj, IntPtr stdDeviationsExtrinsics_nativeObj, IntPtr perViewErrors_nativeObj, int flags, int criteria_type, int criteria_maxCount, double criteria_epsilon);
[DllImport(LIBNAME)]
private static extern double aruco_Aruco_calibrateCameraCharucoExtended_11(IntPtr charucoCorners_mat_nativeObj, IntPtr charucoIds_mat_nativeObj, IntPtr board_nativeObj, double imageSize_width, double imageSize_height, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_mat_nativeObj, IntPtr tvecs_mat_nativeObj, IntPtr stdDeviationsIntrinsics_nativeObj, IntPtr stdDeviationsExtrinsics_nativeObj, IntPtr perViewErrors_nativeObj, int flags);
[DllImport(LIBNAME)]
private static extern double aruco_Aruco_calibrateCameraCharucoExtended_12(IntPtr charucoCorners_mat_nativeObj, IntPtr charucoIds_mat_nativeObj, IntPtr board_nativeObj, double imageSize_width, double imageSize_height, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_mat_nativeObj, IntPtr tvecs_mat_nativeObj, IntPtr stdDeviationsIntrinsics_nativeObj, IntPtr stdDeviationsExtrinsics_nativeObj, IntPtr perViewErrors_nativeObj);
// C++: double cv::aruco::calibrateCameraCharuco(vector_Mat charucoCorners, vector_Mat charucoIds, Ptr_CharucoBoard board, Size imageSize, Mat& cameraMatrix, Mat& distCoeffs, vector_Mat& rvecs = vector_Mat(), vector_Mat& tvecs = vector_Mat(), int flags = 0, TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON))
[DllImport(LIBNAME)]
private static extern double aruco_Aruco_calibrateCameraCharuco_10(IntPtr charucoCorners_mat_nativeObj, IntPtr charucoIds_mat_nativeObj, IntPtr board_nativeObj, double imageSize_width, double imageSize_height, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_mat_nativeObj, IntPtr tvecs_mat_nativeObj, int flags, int criteria_type, int criteria_maxCount, double criteria_epsilon);
[DllImport(LIBNAME)]
private static extern double aruco_Aruco_calibrateCameraCharuco_11(IntPtr charucoCorners_mat_nativeObj, IntPtr charucoIds_mat_nativeObj, IntPtr board_nativeObj, double imageSize_width, double imageSize_height, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_mat_nativeObj, IntPtr tvecs_mat_nativeObj, int flags);
[DllImport(LIBNAME)]
private static extern double aruco_Aruco_calibrateCameraCharuco_12(IntPtr charucoCorners_mat_nativeObj, IntPtr charucoIds_mat_nativeObj, IntPtr board_nativeObj, double imageSize_width, double imageSize_height, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_mat_nativeObj, IntPtr tvecs_mat_nativeObj);
[DllImport(LIBNAME)]
private static extern double aruco_Aruco_calibrateCameraCharuco_13(IntPtr charucoCorners_mat_nativeObj, IntPtr charucoIds_mat_nativeObj, IntPtr board_nativeObj, double imageSize_width, double imageSize_height, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr rvecs_mat_nativeObj);
[DllImport(LIBNAME)]
private static extern double aruco_Aruco_calibrateCameraCharuco_14(IntPtr charucoCorners_mat_nativeObj, IntPtr charucoIds_mat_nativeObj, IntPtr board_nativeObj, double imageSize_width, double imageSize_height, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj);
// C++: int cv::aruco::interpolateCornersCharuco(vector_Mat markerCorners, Mat markerIds, Mat image, Ptr_CharucoBoard board, Mat& charucoCorners, Mat& charucoIds, Mat cameraMatrix = Mat(), Mat distCoeffs = Mat(), int minMarkers = 2)
[DllImport(LIBNAME)]
private static extern int aruco_Aruco_interpolateCornersCharuco_10(IntPtr markerCorners_mat_nativeObj, IntPtr markerIds_nativeObj, IntPtr image_nativeObj, IntPtr board_nativeObj, IntPtr charucoCorners_nativeObj, IntPtr charucoIds_nativeObj, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, int minMarkers);
[DllImport(LIBNAME)]
private static extern int aruco_Aruco_interpolateCornersCharuco_11(IntPtr markerCorners_mat_nativeObj, IntPtr markerIds_nativeObj, IntPtr image_nativeObj, IntPtr board_nativeObj, IntPtr charucoCorners_nativeObj, IntPtr charucoIds_nativeObj, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj);
[DllImport(LIBNAME)]
private static extern int aruco_Aruco_interpolateCornersCharuco_12(IntPtr markerCorners_mat_nativeObj, IntPtr markerIds_nativeObj, IntPtr image_nativeObj, IntPtr board_nativeObj, IntPtr charucoCorners_nativeObj, IntPtr charucoIds_nativeObj, IntPtr cameraMatrix_nativeObj);
[DllImport(LIBNAME)]
private static extern int aruco_Aruco_interpolateCornersCharuco_13(IntPtr markerCorners_mat_nativeObj, IntPtr markerIds_nativeObj, IntPtr image_nativeObj, IntPtr board_nativeObj, IntPtr charucoCorners_nativeObj, IntPtr charucoIds_nativeObj);
// C++: void cv::aruco::detectCharucoDiamond(Mat image, vector_Mat markerCorners, Mat markerIds, float squareMarkerLengthRate, vector_Mat& diamondCorners, Mat& diamondIds, Mat cameraMatrix = Mat(), Mat distCoeffs = Mat(), Ptr_Dictionary dictionary = makePtr<Dictionary> (getPredefinedDictionary(PredefinedDictionaryType::DICT_4X4_50)))
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_detectCharucoDiamond_10(IntPtr image_nativeObj, IntPtr markerCorners_mat_nativeObj, IntPtr markerIds_nativeObj, float squareMarkerLengthRate, IntPtr diamondCorners_mat_nativeObj, IntPtr diamondIds_nativeObj, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj, IntPtr dictionary_nativeObj);
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_detectCharucoDiamond_11(IntPtr image_nativeObj, IntPtr markerCorners_mat_nativeObj, IntPtr markerIds_nativeObj, float squareMarkerLengthRate, IntPtr diamondCorners_mat_nativeObj, IntPtr diamondIds_nativeObj, IntPtr cameraMatrix_nativeObj, IntPtr distCoeffs_nativeObj);
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_detectCharucoDiamond_12(IntPtr image_nativeObj, IntPtr markerCorners_mat_nativeObj, IntPtr markerIds_nativeObj, float squareMarkerLengthRate, IntPtr diamondCorners_mat_nativeObj, IntPtr diamondIds_nativeObj, IntPtr cameraMatrix_nativeObj);
[DllImport(LIBNAME)]
private static extern void aruco_Aruco_detectCharucoDiamond_13(IntPtr image_nativeObj, IntPtr markerCorners_mat_nativeObj, IntPtr markerIds_nativeObj, float squareMarkerLengthRate, IntPtr diamondCorners_mat_nativeObj, IntPtr diamondIds_nativeObj);
}
}
Reference in New Issue View Git Blame Copy Permalink