package org.opencv.test.features2d; import org.opencv.core.Core; 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.features2d.DescriptorExtractor; import org.opencv.core.KeyPoint; import org.opencv.test.OpenCVTestCase; import org.opencv.test.OpenCVTestRunner; import org.opencv.imgproc.Imgproc; public class SIFTDescriptorExtractorTest extends OpenCVTestCase { DescriptorExtractor 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 = DescriptorExtractor.create(DescriptorExtractor.SIFT); 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()); } public void testRead() { fail("Not yet implemented"); } public void testWrite() { String filename = OpenCVTestRunner.getTempFileName("xml"); extractor.write(filename); String truth = "\n\nFeature2D.SIFT\n4.0000000000000001e-02\n10.\n0\n3\n1.6000000000000001e+00\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); } public void testWriteYml() { String filename = OpenCVTestRunner.getTempFileName("yml"); extractor.write(filename); String truth = "%YAML:1.0\nname: \"Feature2D.SIFT\"\ncontrastThreshold: 4.0000000000000001e-02\nedgeThreshold: 10.\nnFeatures: 0\nnOctaveLayers: 3\nsigma: 1.6000000000000001e+00\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); } }