content: package org.opencv.test.features2d;
  
  import java.util.Arrays;
  import java.util.List;
  
  import org.opencv.core.CvType;
  import org.opencv.core.Mat;
  import org.opencv.core.MatOfDMatch;
  import org.opencv.core.MatOfKeyPoint;
  import org.opencv.core.Point;
  import org.opencv.core.Scalar;
  import org.opencv.core.DMatch;
  import org.opencv.features2d.DescriptorMatcher;
  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 BruteForceL1DescriptorMatcherTest extends OpenCVTestCase {
  
      DescriptorMatcher matcher;
      int matSize;
      DMatch[] truth;
  
      private Mat getMaskImg() {
          return new Mat(5, 2, CvType.CV_8U, new Scalar(0)) {
              {
                  put(0, 0, 1, 1, 1, 1);
              }
          };
      }
  
      private Mat getQueryDescriptors() {
          Mat img = getQueryImg();
          MatOfKeyPoint keypoints = new MatOfKeyPoint();
          Mat descriptors = new Mat();
  
          Feature2D detector = createClassInstance(XFEATURES2D+"SURF", DEFAULT_FACTORY, null, null);
          Feature2D extractor = createClassInstance(XFEATURES2D+"SURF", DEFAULT_FACTORY, null, null);
  
          setProperty(detector, "extended", "boolean", true);
          setProperty(detector, "hessianThreshold", "double", 8000);
          setProperty(detector, "nOctaveLayers", "int", 2);
          setProperty(detector, "nOctaves", "int", 3);
          setProperty(detector, "upright", "boolean", false);
  
          detector.detect(img, keypoints);
          extractor.compute(img, keypoints, descriptors);
  
          return descriptors;
      }
  
      private Mat getQueryImg() {
          Mat cross = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
          Imgproc.line(cross, new Point(30, matSize / 2), new Point(matSize - 31, matSize / 2), new Scalar(100), 3);
          Imgproc.line(cross, new Point(matSize / 2, 30), new Point(matSize / 2, matSize - 31), new Scalar(100), 3);
  
          return cross;
      }
  
      private Mat getTrainDescriptors() {
          Mat img = getTrainImg();
          MatOfKeyPoint keypoints = new MatOfKeyPoint(new KeyPoint(50, 50, 16, 0, 20000, 1, -1), new KeyPoint(42, 42, 16, 160, 10000, 1, -1));
          Mat descriptors = new Mat();
  
          Feature2D extractor = createClassInstance(XFEATURES2D+"SURF", DEFAULT_FACTORY, null, null);
  
          extractor.compute(img, keypoints, descriptors);
  
          return descriptors;
      }
  
      private Mat getTrainImg() {
          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;
      }
  
      protected void setUp() throws Exception {
          super.setUp();
          matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_L1);
          matSize = 100;
  
          truth = new DMatch[] {
                  new DMatch(0, 0, 0, 3.0710702f),
                  new DMatch(1, 1, 0, 3.562016f),
                  new DMatch(2, 1, 0, 1.3682679f),
                  new DMatch(3, 1, 0, 1.3012862f),
                  new DMatch(4, 1, 0, 1.1852086f)
                  };
      }
  
      public void testAdd() {
          matcher.add(Arrays.asList(new Mat()));
          assertFalse(matcher.empty());
      }
  
      public void testClear() {
          matcher.add(Arrays.asList(new Mat()));
  
          matcher.clear();
  
          assertTrue(matcher.empty());
      }
  
      public void testClone() {
          Mat train = new Mat(1, 1, CvType.CV_8U, new Scalar(123));
          Mat truth = train.clone();
          matcher.add(Arrays.asList(train));
  
          DescriptorMatcher cloned = matcher.clone();
  
          assertNotNull(cloned);
  
          List<Mat> descriptors = cloned.getTrainDescriptors();
          assertEquals(1, descriptors.size());
          assertMatEqual(truth, descriptors.get(0));
      }
  
      public void testCloneBoolean() {
          matcher.add(Arrays.asList(new Mat()));
  
          DescriptorMatcher cloned = matcher.clone(true);
  
          assertNotNull(cloned);
          assertTrue(cloned.empty());
      }
  
      public void testCreate() {
          assertNotNull(matcher);
      }
  
      public void testEmpty() {
          assertTrue(matcher.empty());
      }
  
      public void testGetTrainDescriptors() {
          Mat train = new Mat(1, 1, CvType.CV_8U, new Scalar(123));
          Mat truth = train.clone();
          matcher.add(Arrays.asList(train));
  
          List<Mat> descriptors = matcher.getTrainDescriptors();
  
          assertEquals(1, descriptors.size());
          assertMatEqual(truth, descriptors.get(0));
      }
  
      public void testIsMaskSupported() {
          assertTrue(matcher.isMaskSupported());
      }
  
      public void testKnnMatchMatListOfListOfDMatchInt() {
          fail("Not yet implemented");
      }
  
      public void testKnnMatchMatListOfListOfDMatchIntListOfMat() {
          fail("Not yet implemented");
      }
  
      public void testKnnMatchMatListOfListOfDMatchIntListOfMatBoolean() {
          fail("Not yet implemented");
      }
  
      public void testKnnMatchMatMatListOfListOfDMatchInt() {
          fail("Not yet implemented");
      }
  
      public void testKnnMatchMatMatListOfListOfDMatchIntMat() {
          fail("Not yet implemented");
      }
  
      public void testKnnMatchMatMatListOfListOfDMatchIntMatBoolean() {
          fail("Not yet implemented");
      }
  
      public void testMatchMatListOfDMatch() {
          Mat train = getTrainDescriptors();
          Mat query = getQueryDescriptors();
          MatOfDMatch matches = new MatOfDMatch();
          matcher.add(Arrays.asList(train));
  
          matcher.match(query, matches);
  
          assertArrayDMatchEquals(truth, matches.toArray(), EPS);
      }
  
      public void testMatchMatListOfDMatchListOfMat() {
          Mat train = getTrainDescriptors();
          Mat query = getQueryDescriptors();
          Mat mask = getMaskImg();
          MatOfDMatch matches = new MatOfDMatch();
          matcher.add(Arrays.asList(train));
  
          matcher.match(query, matches, Arrays.asList(mask));
  
          assertListDMatchEquals(Arrays.asList(truth[0], truth[1]), matches.toList(), EPS);
      }
  
      public void testMatchMatMatListOfDMatch() {
          Mat train = getTrainDescriptors();
          Mat query = getQueryDescriptors();
          MatOfDMatch matches = new MatOfDMatch();
  
          matcher.match(query, train, matches);
  
          assertArrayDMatchEquals(truth, matches.toArray(), EPS);
      }
  
      public void testMatchMatMatListOfDMatchMat() {
          Mat train = getTrainDescriptors();
          Mat query = getQueryDescriptors();
          Mat mask = getMaskImg();
          MatOfDMatch matches = new MatOfDMatch();
  
          matcher.match(query, train, matches, mask);
  
          assertListDMatchEquals(Arrays.asList(truth[0], truth[1]), matches.toList(), EPS);
      }
  
      public void testRadiusMatchMatListOfListOfDMatchFloat() {
          fail("Not yet implemented");
      }
  
      public void testRadiusMatchMatListOfListOfDMatchFloatListOfMat() {
          fail("Not yet implemented");
      }
  
      public void testRadiusMatchMatListOfListOfDMatchFloatListOfMatBoolean() {
          fail("Not yet implemented");
      }
  
      public void testRadiusMatchMatMatListOfListOfDMatchFloat() {
          fail("Not yet implemented");
      }
  
      public void testRadiusMatchMatMatListOfListOfDMatchFloatMat() {
          fail("Not yet implemented");
      }
  
      public void testRadiusMatchMatMatListOfListOfDMatchFloatMatBoolean() {
          fail("Not yet implemented");
      }
  
      public void testRead() {
          String filename = OpenCVTestRunner.getTempFileName("yml");
          writeFile(filename, "%YAML:1.0\n---\n");
  
          matcher.read(filename);
          assertTrue(true);// BruteforceMatcher has no settings
      }
  
      public void testTrain() {
          matcher.train();// BruteforceMatcher does not need to train
      }
  
      public void testWrite() {
          String filename = OpenCVTestRunner.getTempFileName("yml");
  
          matcher.write(filename);
  
          String truth = "%YAML:1.0\n---\n";
          assertEquals(truth, readFile(filename));
      }
  
  }
  