public static void Mat_to_vector_KeyPoint(Mat m, List<KeyPoint> kps) { if (kps == null) throw new java.lang.IllegalArgumentException("Output List can't be null"); int count = m.rows(); if (CvType.CV_64FC(7) != m.type() || m.cols() != 1) throw new java.lang.IllegalArgumentException( "CvType.CV_64FC(7) != m.type() || m.cols()!=1\n" + m); kps.clear(); double[] buff = new double[7 * count]; m.get(0, 0, buff); for (int i = 0; i < count; i++) { kps.add(new KeyPoint((float) buff[7 * i], (float) buff[7 * i + 1], (float) buff[7 * i + 2], (float) buff[7 * i + 3], (float) buff[7 * i + 4], (int) buff[7 * i + 5], (int) buff[7 * i + 6])); } }
public static Mat findHomography(MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, int method, double ransacReprojThreshold, Mat mask, int maxIters, double confidence) { Mat srcPoints_mat = srcPoints; Mat dstPoints_mat = dstPoints; Mat retVal = new Mat(findHomography_0(srcPoints_mat.nativeObj, dstPoints_mat.nativeObj, method, ransacReprojThreshold, mask.nativeObj, maxIters, confidence)); return retVal; }
public static void drawMatchesKnn(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, List<MatOfDMatch> matches1to2, Mat outImg) { Mat keypoints1_mat = keypoints1; Mat keypoints2_mat = keypoints2; List<Mat> matches1to2_tmplm = new ArrayList<Mat>((matches1to2 != null) ? matches1to2.size() : 0); Mat matches1to2_mat = Converters.vector_vector_DMatch_to_Mat(matches1to2, matches1to2_tmplm); drawMatchesKnn_1(img1.nativeObj, keypoints1_mat.nativeObj, img2.nativeObj, keypoints2_mat.nativeObj, matches1to2_mat.nativeObj, outImg.nativeObj); return; }
public static boolean imencode(String ext, Mat img, MatOfByte buf) { Mat buf_mat = buf; boolean retVal = imencode_1(ext, img.nativeObj, buf_mat.nativeObj); return retVal; }
public void detectAndCompute(Mat image, Mat mask, MatOfKeyPoint keypoints, Mat descriptors) { Mat keypoints_mat = keypoints; detectAndCompute_1(nativeObj, image.nativeObj, mask.nativeObj, keypoints_mat.nativeObj, descriptors.nativeObj); return; }
public static void fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h, int templateWindowSize, int searchWindowSize) { Mat srcImgs_mat = Converters.vector_Mat_to_Mat(srcImgs); fastNlMeansDenoisingMulti_0(srcImgs_mat.nativeObj, dst.nativeObj, imgToDenoiseIndex, temporalWindowSize, h, templateWindowSize, searchWindowSize); return; }
public void compute(Mat image, MatOfKeyPoint keypoints, Mat imgDescriptor) { Mat keypoints_mat = keypoints; compute_0(nativeObj, image.nativeObj, keypoints_mat.nativeObj, imgDescriptor.nativeObj); return; }
public void detect(Mat image, MatOfKeyPoint keypoints, Mat mask) { Mat keypoints_mat = keypoints; detect_0(nativeObj, image.nativeObj, keypoints_mat.nativeObj, mask.nativeObj); return; }
public static void drawMatchesKnn(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, List<MatOfDMatch> matches1to2, Mat outImg, Scalar matchColor, Scalar singlePointColor, List<MatOfByte> matchesMask, int flags) { Mat keypoints1_mat = keypoints1; Mat keypoints2_mat = keypoints2; List<Mat> matches1to2_tmplm = new ArrayList<Mat>((matches1to2 != null) ? matches1to2.size() : 0); Mat matches1to2_mat = Converters.vector_vector_DMatch_to_Mat(matches1to2, matches1to2_tmplm); List<Mat> matchesMask_tmplm = new ArrayList<Mat>((matchesMask != null) ? matchesMask.size() : 0); Mat matchesMask_mat = Converters.vector_vector_char_to_Mat(matchesMask, matchesMask_tmplm); drawMatchesKnn_0(img1.nativeObj, keypoints1_mat.nativeObj, img2.nativeObj, keypoints2_mat.nativeObj, matches1to2_mat.nativeObj, outImg.nativeObj, matchColor.val[0], matchColor.val[1], matchColor.val[2], matchColor.val[3], singlePointColor.val[0], singlePointColor.val[1], singlePointColor.val[2], singlePointColor.val[3], matchesMask_mat.nativeObj, flags); return; }
public static boolean solvePnPRansac(MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, boolean useExtrinsicGuess, int iterationsCount, float reprojectionError, double confidence, Mat inliers, int flags) { Mat objectPoints_mat = objectPoints; Mat imagePoints_mat = imagePoints; Mat distCoeffs_mat = distCoeffs; boolean retVal = solvePnPRansac_0(objectPoints_mat.nativeObj, imagePoints_mat.nativeObj, cameraMatrix.nativeObj, distCoeffs_mat.nativeObj, rvec.nativeObj, tvec.nativeObj, useExtrinsicGuess, iterationsCount, reprojectionError, confidence, inliers.nativeObj, flags); return retVal; }
public void match(Mat queryDescriptors, MatOfDMatch matches) { Mat matches_mat = matches; match_3(nativeObj, queryDescriptors.nativeObj, matches_mat.nativeObj); return; }
public static void polylines(Mat img, List<MatOfPoint> pts, boolean isClosed, Scalar color, int thickness) { List<Mat> pts_tmplm = new ArrayList<Mat>((pts != null) ? pts.size() : 0); Mat pts_mat = Converters.vector_vector_Point_to_Mat(pts, pts_tmplm); polylines_1(img.nativeObj, pts_mat.nativeObj, isClosed, color.val[0], color.val[1], color.val[2], color.val[3], thickness); return; }
public static void cornerSubPix(Mat image, MatOfPoint2f corners, Size winSize, Size zeroZone, TermCriteria criteria) { Mat corners_mat = corners; cornerSubPix_0(image.nativeObj, corners_mat.nativeObj, winSize.width, winSize.height, zeroZone.width, zeroZone.height, criteria.type, criteria.maxCount, criteria.epsilon); return; }
public void detect(Mat img, MatOfPoint foundLocations, MatOfDouble weights) { Mat foundLocations_mat = foundLocations; Mat weights_mat = weights; detect_1(nativeObj, img.nativeObj, foundLocations_mat.nativeObj, weights_mat.nativeObj); return; }
public static Point phaseCorrelate(Mat src1, Mat src2, Mat window, double[] response) { double[] response_out = new double[1]; Point retVal = new Point(phaseCorrelate_0(src1.nativeObj, src2.nativeObj, window.nativeObj, response_out)); if(response!=null) response[0] = (double)response_out[0]; return retVal; }
public static double calibrateCamera(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, int flags, TermCriteria criteria) { Mat objectPoints_mat = Converters.vector_Mat_to_Mat(objectPoints); Mat imagePoints_mat = Converters.vector_Mat_to_Mat(imagePoints); Mat rvecs_mat = new Mat(); Mat tvecs_mat = new Mat(); double retVal = calibrateCamera_0(objectPoints_mat.nativeObj, imagePoints_mat.nativeObj, 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; }
public static double stereoCalibrate(List<Mat> objectPoints, List<Mat> imagePoints1, List<Mat> imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, int flags) { Mat objectPoints_mat = Converters.vector_Mat_to_Mat(objectPoints); Mat imagePoints1_mat = Converters.vector_Mat_to_Mat(imagePoints1); Mat imagePoints2_mat = Converters.vector_Mat_to_Mat(imagePoints2); double retVal = stereoCalibrate_1(objectPoints_mat.nativeObj, imagePoints1_mat.nativeObj, imagePoints2_mat.nativeObj, cameraMatrix1.nativeObj, distCoeffs1.nativeObj, cameraMatrix2.nativeObj, distCoeffs2.nativeObj, imageSize.width, imageSize.height, R.nativeObj, T.nativeObj, E.nativeObj, F.nativeObj, flags); return retVal; }
public void process(List<Mat> src, List<Mat> dst, Mat times, Mat response) { Mat src_mat = Converters.vector_Mat_to_Mat(src); Mat dst_mat = Converters.vector_Mat_to_Mat(dst); process_0(nativeObj, src_mat.nativeObj, dst_mat.nativeObj, times.nativeObj, response.nativeObj); return; }
public static boolean imwrite(String filename, Mat img, MatOfInt params) { Mat params_mat = params; boolean retVal = imwrite_0(filename, img.nativeObj, params_mat.nativeObj); return retVal; }
public static void undistortPoints(MatOfPoint2f src, MatOfPoint2f dst, Mat cameraMatrix, Mat distCoeffs) { Mat src_mat = src; Mat dst_mat = dst; undistortPoints_1(src_mat.nativeObj, dst_mat.nativeObj, cameraMatrix.nativeObj, distCoeffs.nativeObj); return; }
public static void mixChannels(List<Mat> src, List<Mat> dst, MatOfInt fromTo) { Mat src_mat = Converters.vector_Mat_to_Mat(src); Mat dst_mat = Converters.vector_Mat_to_Mat(dst); Mat fromTo_mat = fromTo; mixChannels_0(src_mat.nativeObj, dst_mat.nativeObj, fromTo_mat.nativeObj); return; }
public void radiusMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, float maxDistance, Mat mask, boolean compactResult) { Mat matches_mat = new Mat(); radiusMatch_0(nativeObj, queryDescriptors.nativeObj, trainDescriptors.nativeObj, matches_mat.nativeObj, maxDistance, mask.nativeObj, compactResult); Converters.Mat_to_vector_vector_DMatch(matches_mat, matches); matches_mat.release(); return; }
public static void Mat_to_vector_DMatch(Mat m, List<DMatch> matches) { if (matches == null) throw new java.lang.IllegalArgumentException("Output List can't be null"); int count = m.rows(); if (CvType.CV_64FC4 != m.type() || m.cols() != 1) throw new java.lang.IllegalArgumentException( "CvType.CV_64FC4 != m.type() || m.cols()!=1\n" + m); matches.clear(); double[] buff = new double[4 * count]; m.get(0, 0, buff); for (int i = 0; i < count; i++) { matches.add(new DMatch((int) buff[4 * i], (int) buff[4 * i + 1], (int) buff[4 * i + 2], (float) buff[4 * i + 3])); } }
public static void drawKeypoints(Mat image, MatOfKeyPoint keypoints, Mat outImage, Scalar color, int flags) { Mat keypoints_mat = keypoints; drawKeypoints_0(image.nativeObj, keypoints_mat.nativeObj, outImage.nativeObj, color.val[0], color.val[1], color.val[2], color.val[3], flags); return; }
public static void projectPoints(MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat rvec, Mat tvec, Mat K, Mat D) { Mat objectPoints_mat = objectPoints; Mat imagePoints_mat = imagePoints; projectPoints_3(objectPoints_mat.nativeObj, imagePoints_mat.nativeObj, rvec.nativeObj, tvec.nativeObj, K.nativeObj, D.nativeObj); return; }
public Rotacao (Mat imagem){ this.original = imagem; }
public static Mat vector_Point3f_to_Mat(List<Point3> pts) { return vector_Point3_to_Mat(pts, CvType.CV_32F); }
public static Mat vector_Point3d_to_Mat(List<Point3> pts) { return vector_Point3_to_Mat(pts, CvType.CV_64F); }
/** * This method shall be called by the subclasses when they have valid * object and want it to be delivered to external client (via callback) and * then displayed on the screen. * @param frame - the current frame to be delivered */ protected void deliverAndDrawFrame(CvCameraViewFrame frame) { Mat modified; if (mListener != null) { modified = mListener.onCameraFrame(frame); } else { modified = frame.rgba(); } boolean bmpValid = true; if (modified != null) { try { Utils.matToBitmap(modified, mCacheBitmap); } catch(Exception e) { Log.e(TAG, "Mat type: " + modified); Log.e(TAG, "Bitmap type: " + mCacheBitmap.getWidth() + "*" + mCacheBitmap.getHeight()); Log.e(TAG, "Utils.matToBitmap() throws an exception: " + e.getMessage()); bmpValid = false; } } if (bmpValid && mCacheBitmap != null) { Canvas canvas = getHolder().lockCanvas(); if (canvas != null) { canvas.drawColor(0, android.graphics.PorterDuff.Mode.CLEAR); if (BuildConfig.DEBUG) Log.d(TAG, "mStretch value: " + mScale); if (mScale != 0) { canvas.drawBitmap(mCacheBitmap, new Rect(0,0,mCacheBitmap.getWidth(), mCacheBitmap.getHeight()), new Rect((int)((canvas.getWidth() - mScale*mCacheBitmap.getWidth()) / 2), (int)((canvas.getHeight() - mScale*mCacheBitmap.getHeight()) / 2), (int)((canvas.getWidth() - mScale*mCacheBitmap.getWidth()) / 2 + mScale*mCacheBitmap.getWidth()), (int)((canvas.getHeight() - mScale*mCacheBitmap.getHeight()) / 2 + mScale*mCacheBitmap.getHeight())), null); } else { canvas.drawBitmap(mCacheBitmap, new Rect(0,0,mCacheBitmap.getWidth(), mCacheBitmap.getHeight()), new Rect((canvas.getWidth() - mCacheBitmap.getWidth()) / 2, (canvas.getHeight() - mCacheBitmap.getHeight()) / 2, (canvas.getWidth() - mCacheBitmap.getWidth()) / 2 + mCacheBitmap.getWidth(), (canvas.getHeight() - mCacheBitmap.getHeight()) / 2 + mCacheBitmap.getHeight()), null); } if (mFpsMeter != null) { mFpsMeter.measure(); mFpsMeter.draw(canvas, 20, 30); } getHolder().unlockCanvasAndPost(canvas); } } }
public static void Mat_to_vector_Point3i(Mat m, List<Point3> pts) { Mat_to_vector_Point3(m, pts); }
public static void Mat_to_vector_Point2f(Mat m, List<Point> pts) { Mat_to_vector_Point(m, pts); }
public static Mat abrirImagem(String path) { System.loadLibrary(Core.NATIVE_LIBRARY_NAME); return Imgcodecs.imread(path, IMREAD_COLOR); }
public Mat findStudentPhotoByID(String sID) { // return this.StudentDaoImptOfService.findPhotoByID(sID); return Highgui.imread(" "); }
public static void Mat_to_vector_Point3d(Mat m, List<Point3> pts) { Mat_to_vector_Point3(m, pts); }
public Mat getTrainNormCatResponses() { Mat retVal = new Mat(getTrainNormCatResponses_0(nativeObj)); return retVal; }
public static void stylization(Mat src, Mat dst) { stylization_1(src.nativeObj, dst.nativeObj); return; }
public static void preCornerDetect(Mat src, Mat dst, int ksize, int borderType) { preCornerDetect_0(src.nativeObj, dst.nativeObj, ksize, borderType); return; }
public static void LUT(Mat src, Mat lut, Mat dst) { LUT_0(src.nativeObj, lut.nativeObj, dst.nativeObj); return; }