openCVORB.java

  public Meta getMatch(Mat frame) {
        try {

            FeatureDetector detector = FeatureDetector.create(FeatureDetector.ORB);
            DescriptorExtractor descriptor = DescriptorExtractor.create(DescriptorExtractor.ORB);;
            DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);

            //first image
            Mat img1 = frame.clone();//Imgcodecs.imread("C:\\Users\\Dexter\\Desktop\\opencv\\2\\333.png", 0);

          Mat descriptors1 = new Mat();
            MatOfKeyPoint keypoints1 = new MatOfKeyPoint();

            detector.detect(img1, keypoints1);
            descriptor.compute(img1, keypoints1, descriptors1);

            //second image
            Mat img2 = tamplate.clone(); //Imgcodecs.imread("C:\\Users\\Dexter\\Desktop\\opencv\\2\\222.png", 0);
            Mat descriptors2 = new Mat();
            MatOfKeyPoint keypoints2 = new MatOfKeyPoint();

            detector.detect(img2, keypoints2);
            descriptor.compute(img2, keypoints2, descriptors2);

            //matcher should include 2 different image's descriptors
            MatOfDMatch matches = new MatOfDMatch();
            matcher.match(descriptors1, descriptors2, matches);

            List<DMatch> good_matches = matches.toList();
            List<DMatch> good_matches2 = new ArrayList<>();
            System.out.println(" mataches : " + good_matches.size());
          // if there < 450 point matches don't continue 
            if (good_matches.size() < 450) {
                return frame;

            }

            Comparator<DMatch> bySizeDifferent = Comparator.comparing(user -> user.distance);
          
       // from the > 450 get 100 to do homography on them and sort them by the distance
            good_matches.stream().sorted(bySizeDifferent).limit(100).forEach(u -> {
                good_matches2.add(u);
            });
          
            System.out.println("good matache : " + good_matches2.get(0).distance + " " + good_matches2.get(good_matches2.size() - 1).distance);
            if (good_matches2.get(0).distance > 25) { // if the best keypoint match score < 85% drop the proces, change the value whaever you want
                 return frame;
            }
            MatOfDMatch gm = new MatOfDMatch();

            gm.fromList(good_matches2);
/*
            //this will draw all matches,
             Scalar RED = new Scalar(255, 0, 0);
            Scalar GREEN = new Scalar(0, 255, 0);
            //output image
             Mat outputImg = new Mat();
            MatOfByte drawnMatches = new MatOfByte();
            Features2d.drawMatches(img1, keypoints1, img2, keypoints2, gm, outputImg, GREEN, RED, drawnMatches, Features2d.NOT_DRAW_SINGLE_POINTS);
            return outputImg;
            */
            LinkedList<Point> objList = new LinkedList<Point>();
            LinkedList<Point> sceneList = new LinkedList<Point>();

            List<KeyPoint> keypoints_objectList = keypoints1.toList();
            List<KeyPoint> keypoints_sceneList = keypoints2.toList();

            //System.err.println(good_matches2.get(0).distance);
            for (int i = 0; i < good_matches2.size(); i++) {
                objList.addLast(keypoints_sceneList.get(good_matches2.get(i).trainIdx).pt);
                sceneList.addLast(keypoints_objectList.get(good_matches2.get(i).queryIdx).pt);
            }
            MatOfPoint2f obj = new MatOfPoint2f();
            obj.fromList(objList);

            MatOfPoint2f scene = new MatOfPoint2f();
            scene.fromList(sceneList);

            Mat hg = Calib3d.findHomography(obj, scene, Calib3d.RANSAC, 3);
            Mat obj_corners = new Mat(4, 1, CvType.CV_32FC2);
            Mat scene_corners = new Mat(4, 1, CvType.CV_32FC2);

            obj_corners.put(0, 0, new double[]{0, 0});
            obj_corners.put(1, 0, new double[]{img2.cols(), 0});
            obj_corners.put(2, 0, new double[]{img2.cols(), img2.rows()});
            obj_corners.put(3, 0, new double[]{0, img2.rows()});

            Core.perspectiveTransform(obj_corners, scene_corners, hg);
          // Draw ROI
               Imgproc.line(img1, new Point(scene_corners.get(0, 0)), new Point(scene_corners.get(1, 0)), new Scalar(255, 255, 0), 4);
               Imgproc.line(img1, new Point(scene_corners.get(1, 0)), new Point(scene_corners.get(2, 0)), new Scalar(255, 255, 0), 4);
              Imgproc.line(img1, new Point(scene_corners.get(2, 0)), new Point(scene_corners.get(3, 0)), new Scalar(255, 255, 0), 4);
              Imgproc.line(img1, new Point(scene_corners.get(3, 0)), new Point(scene_corners.get(0, 0)), new Scalar(255, 255, 0), 4);
          return img1;
          
        }catch(Exception e){
        return frame;
        }
  }