public static void calcHist(List<Mat> images, MatOfInt channels, Mat mask, Mat hist, MatOfInt histSize, MatOfFloat ranges, boolean accumulate) { Mat images_mat = Converters.vector_Mat_to_Mat(images); Mat channels_mat = channels; Mat histSize_mat = histSize; Mat ranges_mat = ranges; calcHist_0(images_mat.nativeObj, channels_mat.nativeObj, mask.nativeObj, hist.nativeObj, histSize_mat.nativeObj, ranges_mat.nativeObj, accumulate); return; }
public void compute(Mat img, MatOfFloat descriptors) { Mat descriptors_mat = descriptors; compute_1(nativeObj, img.nativeObj, descriptors_mat.nativeObj); return; }
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; }
public void setTranslations(MatOfFloat translations) { Mat translations_mat = translations; setTranslations_0(nativeObj, translations_mat.nativeObj); return; }
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; }
public static void calcHist(List<Mat> images, MatOfInt channels, Mat mask, Mat hist, MatOfInt histSize, MatOfFloat ranges) { Mat images_mat = Converters.vector_Mat_to_Mat(images); Mat channels_mat = channels; Mat histSize_mat = histSize; Mat ranges_mat = ranges; calcHist_1(images_mat.nativeObj, channels_mat.nativeObj, mask.nativeObj, hist.nativeObj, histSize_mat.nativeObj, ranges_mat.nativeObj); return; }
public void compute(Mat img, MatOfFloat descriptors, Size winStride, Size padding, MatOfPoint locations) { Mat descriptors_mat = descriptors; Mat locations_mat = locations; compute_0(nativeObj, img.nativeObj, descriptors_mat.nativeObj, winStride.width, winStride.height, padding.width, padding.height, locations_mat.nativeObj); return; }
public static int chamerMatching(Mat img, Mat templ, List<MatOfPoint> results, MatOfFloat cost) { Mat results_mat = new Mat(); Mat cost_mat = cost; int retVal = chamerMatching_1(img.nativeObj, templ.nativeObj, results_mat.nativeObj, cost_mat.nativeObj); Converters.Mat_to_vector_vector_Point(results_mat, results); results_mat.release(); return retVal; }
public static void NMSBoxes(MatOfRect bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices) { Mat bboxes_mat = bboxes; Mat scores_mat = scores; Mat indices_mat = indices; NMSBoxes_1(bboxes_mat.nativeObj, scores_mat.nativeObj, score_threshold, nms_threshold, indices_mat.nativeObj); return; }
public static void fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, MatOfFloat h, int templateWindowSize, int searchWindowSize, int normType) { Mat srcImgs_mat = Converters.vector_Mat_to_Mat(srcImgs); Mat h_mat = h; fastNlMeansDenoisingMulti_2(srcImgs_mat.nativeObj, dst.nativeObj, imgToDenoiseIndex, temporalWindowSize, h_mat.nativeObj, templateWindowSize, searchWindowSize, normType); return; }
public static BRISK create(int thresh, int octaves, MatOfFloat radiusList, MatOfInt numberList, float dMax, float dMin, MatOfInt indexChange) { Mat radiusList_mat = radiusList; Mat numberList_mat = numberList; Mat indexChange_mat = indexChange; BRISK retVal = new BRISK(create_0(thresh, octaves, radiusList_mat.nativeObj, numberList_mat.nativeObj, dMax, dMin, indexChange_mat.nativeObj)); return retVal; }
public static BRISK create(int thresh, int octaves, MatOfFloat radiusList, MatOfInt numberList) { Mat radiusList_mat = radiusList; Mat numberList_mat = numberList; BRISK retVal = new BRISK(create_1(thresh, octaves, radiusList_mat.nativeObj, numberList_mat.nativeObj)); return retVal; }
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; }
public static void fastNlMeansDenoising(Mat src, Mat dst, MatOfFloat h, int templateWindowSize, int searchWindowSize, int normType) { Mat h_mat = h; fastNlMeansDenoising_2(src.nativeObj, dst.nativeObj, h_mat.nativeObj, templateWindowSize, searchWindowSize, normType); return; }
public static void calcBackProject(List<Mat> images, MatOfInt channels, Mat hist, Mat dst, MatOfFloat ranges, double scale) { Mat images_mat = Converters.vector_Mat_to_Mat(images); Mat channels_mat = channels; Mat ranges_mat = ranges; calcBackProject_0(images_mat.nativeObj, channels_mat.nativeObj, hist.nativeObj, dst.nativeObj, ranges_mat.nativeObj, scale); return; }
public static int getMedian(Mat mat) { ArrayList<Mat> listOfMat = new ArrayList<>(); listOfMat.add(mat); MatOfInt channels = new MatOfInt(0); Mat mask = new Mat(); Mat hist = new Mat(256, 1, CvType.CV_8UC1); MatOfInt histSize = new MatOfInt(256); MatOfFloat ranges = new MatOfFloat(0, 256); Imgproc.calcHist(listOfMat, channels, mask, hist, histSize, ranges); double t = mat.rows() * mat.cols() / 2; double total = 0; int med = -1; for (int row = 0; row < hist.rows(); row++) { double val = hist.get(row, 0)[0]; if ((total <= t) && (total + val >= t)) { med = row; break; } total += val; } // Log.d(TAG, String.format("getMedian() = %d", med)); return med; }
public static void fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, MatOfFloat h) { Mat srcImgs_mat = Converters.vector_Mat_to_Mat(srcImgs); Mat h_mat = h; fastNlMeansDenoisingMulti_3(srcImgs_mat.nativeObj, dst.nativeObj, imgToDenoiseIndex, temporalWindowSize, h_mat.nativeObj); return; }
public static BRISK create(MatOfFloat radiusList, MatOfInt numberList, float dMax, float dMin, MatOfInt indexChange) { Mat radiusList_mat = radiusList; Mat numberList_mat = numberList; Mat indexChange_mat = indexChange; BRISK retVal = new BRISK(create_2(radiusList_mat.nativeObj, numberList_mat.nativeObj, dMax, dMin, indexChange_mat.nativeObj)); return retVal; }
public static void fastNlMeansDenoising(Mat src, Mat dst, MatOfFloat h) { Mat h_mat = h; fastNlMeansDenoising_3(src.nativeObj, dst.nativeObj, h_mat.nativeObj); return; }
public void computeQuadraticFormDistances(Mat sourceSignature, List<Mat> imageSignatures, MatOfFloat distances) { Mat imageSignatures_mat = Converters.vector_Mat_to_Mat(imageSignatures); Mat distances_mat = distances; computeQuadraticFormDistances_0(nativeObj, sourceSignature.nativeObj, imageSignatures_mat.nativeObj, distances_mat.nativeObj); return; }
