content: package org.opencv.test.features2d;
  
  import java.util.ArrayList;
  import java.util.Arrays;
  import java.util.Collections;
  import java.util.Comparator;
  import java.util.List;
  
  import org.opencv.core.CvType;
  import org.opencv.core.Mat;
  import org.opencv.core.MatOfKeyPoint;
  import org.opencv.core.Point;
  import org.opencv.core.Scalar;
  import org.opencv.core.KeyPoint;
  import org.opencv.test.OpenCVTestCase;
  import org.opencv.test.OpenCVTestRunner;
  import org.opencv.imgproc.Imgproc;
  import org.opencv.features2d.Feature2D;
  
  public class SURFFeatureDetectorTest extends OpenCVTestCase {
  
      Feature2D detector;
      int matSize;
      KeyPoint[] truth;
  
      private Mat getMaskImg() {
          Mat mask = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
          Mat right = mask.submat(0, matSize, matSize / 2, matSize);
          right.setTo(new Scalar(0));
          return mask;
      }
  
      private Mat getTestImg() {
          Mat cross = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
          Imgproc.line(cross, new Point(20, matSize / 2), new Point(matSize - 21, matSize / 2), new Scalar(100), 2);
          Imgproc.line(cross, new Point(matSize / 2, 20), new Point(matSize / 2, matSize - 21), new Scalar(100), 2);
  
          return cross;
      }
  
      private void order(List<KeyPoint> points) {
          Collections.sort(points, new Comparator<KeyPoint>() {
              public int compare(KeyPoint p1, KeyPoint p2) {
                  if (p1.angle < p2.angle)
                      return -1;
                  if (p1.angle > p2.angle)
                      return 1;
                  return 0;
              }
          });
      }
  
      @Override
      protected void setUp() throws Exception {
          super.setUp();
          detector = createClassInstance(XFEATURES2D+"SURF", DEFAULT_FACTORY, null, null);
          matSize = 100;
          truth = new KeyPoint[] {
                  new KeyPoint(55.775578f, 55.775578f, 16, 80.245735f, 8617.8633f, 0, -1),
                  new KeyPoint(44.224422f, 55.775578f, 16, 170.24574f, 8617.8633f, 0, -1),
                  new KeyPoint(44.224422f, 44.224422f, 16, 260.24573f, 8617.8633f, 0, -1),
                  new KeyPoint(55.775578f, 44.224422f, 16, 350.24573f, 8617.8633f, 0, -1)
              };
      }
  
      public void testCreate() {
          assertNotNull(detector);
      }
  
      public void testDetectListOfMatListOfListOfKeyPoint() {
  
          setProperty(detector, "hessianThreshold", "double", 8000);
          setProperty(detector, "nOctaves", "int", 3);
          setProperty(detector, "nOctaveLayers", "int", 4);
          setProperty(detector, "upright", "boolean", false);
  
          List<MatOfKeyPoint> keypoints = new ArrayList<MatOfKeyPoint>();
          Mat cross = getTestImg();
          List<Mat> crosses = new ArrayList<Mat>(3);
          crosses.add(cross);
          crosses.add(cross);
          crosses.add(cross);
  
          detector.detect(crosses, keypoints);
  
          assertEquals(3, keypoints.size());
  
          for (MatOfKeyPoint mkp : keypoints) {
              List<KeyPoint> lkp = mkp.toList();
              order(lkp);
              assertListKeyPointEquals(Arrays.asList(truth), lkp, EPS);
          }
      }
  
      public void testDetectListOfMatListOfListOfKeyPointListOfMat() {
          fail("Not yet implemented");
      }
  
      public void testDetectMatListOfKeyPoint() {
  
          setProperty(detector, "hessianThreshold", "double", 8000);
          setProperty(detector, "nOctaves", "int", 3);
          setProperty(detector, "nOctaveLayers", "int", 4);
          setProperty(detector, "upright", "boolean", false);
  
          MatOfKeyPoint keypoints = new MatOfKeyPoint();
          Mat cross = getTestImg();
  
          detector.detect(cross, keypoints);
  
          List<KeyPoint> lkp = keypoints.toList();
          order(lkp);
          assertListKeyPointEquals(Arrays.asList(truth), lkp, EPS);
      }
  
      public void testDetectMatListOfKeyPointMat() {
  
          setProperty(detector, "hessianThreshold", "double", 8000);
          setProperty(detector, "nOctaves", "int", 3);
          setProperty(detector, "nOctaveLayers", "int", 4);
          setProperty(detector, "upright", "boolean", false);
  
          Mat img = getTestImg();
          Mat mask = getMaskImg();
          MatOfKeyPoint keypoints = new MatOfKeyPoint();
  
          detector.detect(img, keypoints, mask);
  
          List<KeyPoint> lkp = keypoints.toList();
          order(lkp);
          assertListKeyPointEquals(Arrays.asList(truth[1], truth[2]), lkp, EPS);
      }
  
      public void testEmpty() {
  //        assertFalse(detector.empty());
          fail("Not yet implemented");
      }
  
      public void testRead() {
          Mat cross = getTestImg();
  
          MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
          detector.detect(cross, keypoints1);
  
          String filename = OpenCVTestRunner.getTempFileName("yml");
          writeFile(filename, "%YAML:1.0\n---\nhessianThreshold: 8000.\noctaves: 3\noctaveLayers: 4\nupright: 0\n");
          detector.read(filename);
  
          MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
          detector.detect(cross, keypoints2);
  
          assertTrue(keypoints2.total() <= keypoints1.total());
      }
  
      public void testWrite() {
          String filename = OpenCVTestRunner.getTempFileName("xml");
  
          detector.write(filename);
  
  //        String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n<name>Feature2D.SURF</name>\n<extended>0</extended>\n<hessianThreshold>100.</hessianThreshold>\n<nOctaveLayers>3</nOctaveLayers>\n<nOctaves>4</nOctaves>\n<upright>0</upright>\n</opencv_storage>\n";
          String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n</opencv_storage>\n";
          assertEquals(truth, readFile(filename));
      }
  
      public void testWriteYml() {
          String filename = OpenCVTestRunner.getTempFileName("yml");
  
          detector.write(filename);
  
  //        String truth = "%YAML:1.0\n---\nname: \"Feature2D.SURF\"\nextended: 0\nhessianThreshold: 100.\nnOctaveLayers: 3\nnOctaves: 4\nupright: 0\n";
          String truth = "%YAML:1.0\n---\n";
          assertEquals(truth, readFile(filename));
      }
  
  }
  