Java tutorial
// // This file is auto-generated. Please don't modify it! // package org.opencv.video; import org.opencv.core.Mat; import org.opencv.core.MatOfByte; import org.opencv.core.MatOfFloat; import org.opencv.core.MatOfPoint2f; import org.opencv.core.Rect; import org.opencv.core.RotatedRect; import org.opencv.core.Size; import org.opencv.core.TermCriteria; import org.opencv.utils.Converters; import java.util.List; public class Video { private static final int CV_LKFLOW_INITIAL_GUESSES = 4, CV_LKFLOW_GET_MIN_EIGENVALS = 8; public static final int OPTFLOW_USE_INITIAL_FLOW = 4, OPTFLOW_LK_GET_MIN_EIGENVALS = 8, OPTFLOW_FARNEBACK_GAUSSIAN = 256, MOTION_TRANSLATION = 0, MOTION_EUCLIDEAN = 1, MOTION_AFFINE = 2, MOTION_HOMOGRAPHY = 3; // // C++: Mat estimateRigidTransform(Mat src, Mat dst, bool fullAffine) // //javadoc: estimateRigidTransform(src, dst, fullAffine) public static Mat estimateRigidTransform(Mat src, Mat dst, boolean fullAffine) { Mat retVal = new Mat(estimateRigidTransform_0(src.nativeObj, dst.nativeObj, fullAffine)); return retVal; } // // C++: Ptr_BackgroundSubtractorKNN createBackgroundSubtractorKNN(int history = 500, double dist2Threshold = 400.0, bool detectShadows = true) // //javadoc: createBackgroundSubtractorKNN(history, dist2Threshold, detectShadows) public static BackgroundSubtractorKNN createBackgroundSubtractorKNN(int history, double dist2Threshold, boolean detectShadows) { BackgroundSubtractorKNN retVal = new BackgroundSubtractorKNN( createBackgroundSubtractorKNN_0(history, dist2Threshold, detectShadows)); return retVal; } //javadoc: createBackgroundSubtractorKNN() public static BackgroundSubtractorKNN createBackgroundSubtractorKNN() { BackgroundSubtractorKNN retVal = new BackgroundSubtractorKNN(createBackgroundSubtractorKNN_1()); return retVal; } // // C++: Ptr_BackgroundSubtractorMOG2 createBackgroundSubtractorMOG2(int history = 500, double varThreshold = 16, bool detectShadows = true) // //javadoc: createBackgroundSubtractorMOG2(history, varThreshold, detectShadows) public static BackgroundSubtractorMOG2 createBackgroundSubtractorMOG2(int history, double varThreshold, boolean detectShadows) { BackgroundSubtractorMOG2 retVal = new BackgroundSubtractorMOG2( createBackgroundSubtractorMOG2_0(history, varThreshold, detectShadows)); return retVal; } //javadoc: createBackgroundSubtractorMOG2() public static BackgroundSubtractorMOG2 createBackgroundSubtractorMOG2() { BackgroundSubtractorMOG2 retVal = new BackgroundSubtractorMOG2(createBackgroundSubtractorMOG2_1()); return retVal; } // // C++: Ptr_DualTVL1OpticalFlow createOptFlow_DualTVL1() // //javadoc: createOptFlow_DualTVL1() public static DualTVL1OpticalFlow createOptFlow_DualTVL1() { DualTVL1OpticalFlow retVal = new DualTVL1OpticalFlow(createOptFlow_DualTVL1_0()); return retVal; } // // C++: RotatedRect CamShift(Mat probImage, Rect& window, TermCriteria criteria) // //javadoc: CamShift(probImage, window, criteria) public static RotatedRect CamShift(Mat probImage, Rect window, TermCriteria criteria) { double[] window_out = new double[4]; RotatedRect retVal = new RotatedRect(CamShift_0(probImage.nativeObj, window.x, window.y, window.width, window.height, window_out, criteria.type, criteria.maxCount, criteria.epsilon)); if (window != null) { window.x = (int) window_out[0]; window.y = (int) window_out[1]; window.width = (int) window_out[2]; window.height = (int) window_out[3]; } return retVal; } // // C++: double findTransformECC(Mat templateImage, Mat inputImage, Mat& warpMatrix, int motionType = MOTION_AFFINE, TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 50, 0.001), Mat inputMask = Mat()) // //javadoc: findTransformECC(templateImage, inputImage, warpMatrix, motionType, criteria, inputMask) public static double findTransformECC(Mat templateImage, Mat inputImage, Mat warpMatrix, int motionType, TermCriteria criteria, Mat inputMask) { double retVal = findTransformECC_0(templateImage.nativeObj, inputImage.nativeObj, warpMatrix.nativeObj, motionType, criteria.type, criteria.maxCount, criteria.epsilon, inputMask.nativeObj); return retVal; } //javadoc: findTransformECC(templateImage, inputImage, warpMatrix, motionType) public static double findTransformECC(Mat templateImage, Mat inputImage, Mat warpMatrix, int motionType) { double retVal = findTransformECC_1(templateImage.nativeObj, inputImage.nativeObj, warpMatrix.nativeObj, motionType); return retVal; } //javadoc: findTransformECC(templateImage, inputImage, warpMatrix) public static double findTransformECC(Mat templateImage, Mat inputImage, Mat warpMatrix) { double retVal = findTransformECC_2(templateImage.nativeObj, inputImage.nativeObj, warpMatrix.nativeObj); return retVal; } // // C++: int buildOpticalFlowPyramid(Mat img, vector_Mat& pyramid, Size winSize, int maxLevel, bool withDerivatives = true, int pyrBorder = BORDER_REFLECT_101, int derivBorder = BORDER_CONSTANT, bool tryReuseInputImage = true) // //javadoc: buildOpticalFlowPyramid(img, pyramid, winSize, maxLevel, withDerivatives, pyrBorder, derivBorder, tryReuseInputImage) public static int buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel, boolean withDerivatives, int pyrBorder, int derivBorder, boolean tryReuseInputImage) { Mat pyramid_mat = new Mat(); int retVal = buildOpticalFlowPyramid_0(img.nativeObj, pyramid_mat.nativeObj, winSize.width, winSize.height, maxLevel, withDerivatives, pyrBorder, derivBorder, tryReuseInputImage); Converters.Mat_to_vector_Mat(pyramid_mat, pyramid); pyramid_mat.release(); return retVal; } //javadoc: buildOpticalFlowPyramid(img, pyramid, winSize, maxLevel) public static int buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel) { Mat pyramid_mat = new Mat(); int retVal = buildOpticalFlowPyramid_1(img.nativeObj, pyramid_mat.nativeObj, winSize.width, winSize.height, maxLevel); Converters.Mat_to_vector_Mat(pyramid_mat, pyramid); pyramid_mat.release(); return retVal; } // // C++: int meanShift(Mat probImage, Rect& window, TermCriteria criteria) // //javadoc: meanShift(probImage, window, criteria) public static int meanShift(Mat probImage, Rect window, TermCriteria criteria) { double[] window_out = new double[4]; int retVal = meanShift_0(probImage.nativeObj, window.x, window.y, window.width, window.height, window_out, criteria.type, criteria.maxCount, criteria.epsilon); if (window != null) { window.x = (int) window_out[0]; window.y = (int) window_out[1]; window.width = (int) window_out[2]; window.height = (int) window_out[3]; } return retVal; } // // C++: void calcOpticalFlowFarneback(Mat prev, Mat next, Mat& flow, double pyr_scale, int levels, int winsize, int iterations, int poly_n, double poly_sigma, int flags) // //javadoc: calcOpticalFlowFarneback(prev, next, flow, pyr_scale, levels, winsize, iterations, poly_n, poly_sigma, flags) public static void calcOpticalFlowFarneback(Mat prev, Mat next, Mat flow, double pyr_scale, int levels, int winsize, int iterations, int poly_n, double poly_sigma, int flags) { calcOpticalFlowFarneback_0(prev.nativeObj, next.nativeObj, flow.nativeObj, pyr_scale, levels, winsize, iterations, poly_n, poly_sigma, flags); return; } // // C++: void calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, vector_Point2f prevPts, vector_Point2f& nextPts, vector_uchar& status, vector_float& err, Size winSize = Size(21,21), int maxLevel = 3, TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 0.01), int flags = 0, double minEigThreshold = 1e-4) // //javadoc: calcOpticalFlowPyrLK(prevImg, nextImg, prevPts, nextPts, status, err, winSize, maxLevel, criteria, flags, minEigThreshold) public static void calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err, Size winSize, int maxLevel, TermCriteria criteria, int flags, double minEigThreshold) { Mat prevPts_mat = prevPts; Mat nextPts_mat = nextPts; Mat status_mat = status; Mat err_mat = err; calcOpticalFlowPyrLK_0(prevImg.nativeObj, nextImg.nativeObj, prevPts_mat.nativeObj, nextPts_mat.nativeObj, status_mat.nativeObj, err_mat.nativeObj, winSize.width, winSize.height, maxLevel, criteria.type, criteria.maxCount, criteria.epsilon, flags, minEigThreshold); return; } //javadoc: calcOpticalFlowPyrLK(prevImg, nextImg, prevPts, nextPts, status, err, winSize, maxLevel) public static void calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err, Size winSize, int maxLevel) { Mat prevPts_mat = prevPts; Mat nextPts_mat = nextPts; Mat status_mat = status; Mat err_mat = err; calcOpticalFlowPyrLK_1(prevImg.nativeObj, nextImg.nativeObj, prevPts_mat.nativeObj, nextPts_mat.nativeObj, status_mat.nativeObj, err_mat.nativeObj, winSize.width, winSize.height, maxLevel); return; } //javadoc: calcOpticalFlowPyrLK(prevImg, nextImg, prevPts, nextPts, status, err) public static void calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err) { Mat prevPts_mat = prevPts; Mat nextPts_mat = nextPts; Mat status_mat = status; Mat err_mat = err; calcOpticalFlowPyrLK_2(prevImg.nativeObj, nextImg.nativeObj, prevPts_mat.nativeObj, nextPts_mat.nativeObj, status_mat.nativeObj, err_mat.nativeObj); return; } // C++: Mat estimateRigidTransform(Mat src, Mat dst, bool fullAffine) private static native long estimateRigidTransform_0(long src_nativeObj, long dst_nativeObj, boolean fullAffine); // C++: Ptr_BackgroundSubtractorKNN createBackgroundSubtractorKNN(int history = 500, double dist2Threshold = 400.0, bool detectShadows = true) private static native long createBackgroundSubtractorKNN_0(int history, double dist2Threshold, boolean detectShadows); private static native long createBackgroundSubtractorKNN_1(); // C++: Ptr_BackgroundSubtractorMOG2 createBackgroundSubtractorMOG2(int history = 500, double varThreshold = 16, bool detectShadows = true) private static native long createBackgroundSubtractorMOG2_0(int history, double varThreshold, boolean detectShadows); private static native long createBackgroundSubtractorMOG2_1(); // C++: Ptr_DualTVL1OpticalFlow createOptFlow_DualTVL1() private static native long createOptFlow_DualTVL1_0(); // C++: RotatedRect CamShift(Mat probImage, Rect& window, TermCriteria criteria) private static native double[] CamShift_0(long probImage_nativeObj, int window_x, int window_y, int window_width, int window_height, double[] window_out, int criteria_type, int criteria_maxCount, double criteria_epsilon); // C++: double findTransformECC(Mat templateImage, Mat inputImage, Mat& warpMatrix, int motionType = MOTION_AFFINE, TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 50, 0.001), Mat inputMask = Mat()) private static native double findTransformECC_0(long templateImage_nativeObj, long inputImage_nativeObj, long warpMatrix_nativeObj, int motionType, int criteria_type, int criteria_maxCount, double criteria_epsilon, long inputMask_nativeObj); private static native double findTransformECC_1(long templateImage_nativeObj, long inputImage_nativeObj, long warpMatrix_nativeObj, int motionType); private static native double findTransformECC_2(long templateImage_nativeObj, long inputImage_nativeObj, long warpMatrix_nativeObj); // C++: int buildOpticalFlowPyramid(Mat img, vector_Mat& pyramid, Size winSize, int maxLevel, bool withDerivatives = true, int pyrBorder = BORDER_REFLECT_101, int derivBorder = BORDER_CONSTANT, bool tryReuseInputImage = true) private static native int buildOpticalFlowPyramid_0(long img_nativeObj, long pyramid_mat_nativeObj, double winSize_width, double winSize_height, int maxLevel, boolean withDerivatives, int pyrBorder, int derivBorder, boolean tryReuseInputImage); private static native int buildOpticalFlowPyramid_1(long img_nativeObj, long pyramid_mat_nativeObj, double winSize_width, double winSize_height, int maxLevel); // C++: int meanShift(Mat probImage, Rect& window, TermCriteria criteria) private static native int meanShift_0(long probImage_nativeObj, int window_x, int window_y, int window_width, int window_height, double[] window_out, int criteria_type, int criteria_maxCount, double criteria_epsilon); // C++: void calcOpticalFlowFarneback(Mat prev, Mat next, Mat& flow, double pyr_scale, int levels, int winsize, int iterations, int poly_n, double poly_sigma, int flags) private static native void calcOpticalFlowFarneback_0(long prev_nativeObj, long next_nativeObj, long flow_nativeObj, double pyr_scale, int levels, int winsize, int iterations, int poly_n, double poly_sigma, int flags); // C++: void calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, vector_Point2f prevPts, vector_Point2f& nextPts, vector_uchar& status, vector_float& err, Size winSize = Size(21,21), int maxLevel = 3, TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 0.01), int flags = 0, double minEigThreshold = 1e-4) private static native void calcOpticalFlowPyrLK_0(long prevImg_nativeObj, long nextImg_nativeObj, long prevPts_mat_nativeObj, long nextPts_mat_nativeObj, long status_mat_nativeObj, long err_mat_nativeObj, double winSize_width, double winSize_height, int maxLevel, int criteria_type, int criteria_maxCount, double criteria_epsilon, int flags, double minEigThreshold); private static native void calcOpticalFlowPyrLK_1(long prevImg_nativeObj, long nextImg_nativeObj, long prevPts_mat_nativeObj, long nextPts_mat_nativeObj, long status_mat_nativeObj, long err_mat_nativeObj, double winSize_width, double winSize_height, int maxLevel); private static native void calcOpticalFlowPyrLK_2(long prevImg_nativeObj, long nextImg_nativeObj, long prevPts_mat_nativeObj, long nextPts_mat_nativeObj, long status_mat_nativeObj, long err_mat_nativeObj); }