content: package org.opencv.test.features2d;
  
  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.features2d.SIFT;
  import org.opencv.test.OpenCVTestCase;
  import org.opencv.test.OpenCVTestRunner;
  import org.opencv.imgproc.Imgproc;
  import org.opencv.features2d.Feature2D;
  
  public class SIFTDescriptorExtractorTest extends OpenCVTestCase {
  
      Feature2D extractor;
      KeyPoint keypoint;
      int matSize;
      Mat truth;
  
      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;
      }
  
      @Override
      protected void setUp() throws Exception {
          super.setUp();
          extractor = SIFT.create();
          keypoint = new KeyPoint(55.775577545166016f, 44.224422454833984f, 16, 9.754629f, 8617.863f, 1, -1);
          matSize = 100;
          truth = new Mat(1, 128, CvType.CV_32FC1) {
              {
                  put(0, 0,
                            0, 0, 0, 1, 3, 0, 0, 0, 15, 23, 22, 20, 24, 2, 0, 0, 7, 8, 2, 0,
                            0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 27, 16, 13, 2, 0, 0, 117,
                            86, 79, 68, 117, 42, 5, 5, 79, 60, 117, 25, 9, 2, 28, 19, 11, 13,
                            20, 2, 0, 0, 5, 8, 0, 0, 76, 58, 34, 31, 97, 16, 95, 49, 117, 92,
                            117, 112, 117, 76, 117, 54, 117, 25, 29, 22, 117, 117, 16, 11, 14,
                            1, 0, 0, 22, 26, 0, 0, 0, 0, 1, 4, 15, 2, 47, 8, 0, 0, 82, 56, 31,
                            17, 81, 12, 0, 0, 26, 23, 18, 23, 0, 0, 0, 0, 0, 0, 0, 0
                     );
              }
          };
      }
  
      public void testComputeListOfMatListOfListOfKeyPointListOfMat() {
          fail("Not yet implemented");
      }
  
      public void testComputeMatListOfKeyPointMat() {
          MatOfKeyPoint keypoints = new MatOfKeyPoint(keypoint);
          Mat img = getTestImg();
          Mat descriptors = new Mat();
  
          extractor.compute(img, keypoints, descriptors);
  
          assertMatEqual(truth, descriptors, EPS);
      }
  
      public void testCreate() {
          assertNotNull(extractor);
      }
  
      public void testDescriptorSize() {
          assertEquals(128, extractor.descriptorSize());
      }
  
      public void testDescriptorType() {
          assertEquals(CvType.CV_32F, extractor.descriptorType());
      }
  
      public void testEmpty() {
  //        assertFalse(extractor.empty());
          fail("Not yet implemented"); //SIFT does not override empty() method
      }
  
      public void testRead() {
          fail("Not yet implemented");
      }
  
      public void testWrite() {
          String filename = OpenCVTestRunner.getTempFileName("xml");
  
          extractor.write(filename);
  
  //        String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n<name>Feature2D.SIFT</name>\n<contrastThreshold>4.0000000000000001e-02</contrastThreshold>\n<edgeThreshold>10.</edgeThreshold>\n<nFeatures>0</nFeatures>\n<nOctaveLayers>3</nOctaveLayers>\n<sigma>1.6000000000000001e+00</sigma>\n</opencv_storage>\n";
          String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n</opencv_storage>\n";
          String actual = readFile(filename);
          actual = actual.replaceAll("e([+-])0(\\d\\d)", "e$1$2"); // NOTE: workaround for different platforms double representation
          assertEquals(truth, actual);
      }
  
      public void testWriteYml() {
          String filename = OpenCVTestRunner.getTempFileName("yml");
  
          extractor.write(filename);
  
  //        String truth = "%YAML:1.0\n---\nname: \"Feature2D.SIFT\"\ncontrastThreshold: 4.0000000000000001e-02\nedgeThreshold: 10.\nnFeatures: 0\nnOctaveLayers: 3\nsigma: 1.6000000000000001e+00\n";
          String truth = "%YAML:1.0\n---\n";
          String actual = readFile(filename);
          actual = actual.replaceAll("e([+-])0(\\d\\d)", "e$1$2"); // NOTE: workaround for different platforms double representation
          assertEquals(truth, actual);
      }
  
  }
  