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Open Source Computer Vision Library
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109 lines
4.0 KiB
109 lines
4.0 KiB
package org.opencv.test.features2d; |
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import org.opencv.core.CvType; |
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import org.opencv.core.Mat; |
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import org.opencv.core.MatOfKeyPoint; |
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import org.opencv.core.Point; |
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import org.opencv.core.Scalar; |
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import org.opencv.core.KeyPoint; |
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import org.opencv.features2d.SIFT; |
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import org.opencv.test.OpenCVTestCase; |
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import org.opencv.test.OpenCVTestRunner; |
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import org.opencv.imgproc.Imgproc; |
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import org.opencv.features2d.SIFT; |
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public class SIFTDescriptorExtractorTest extends OpenCVTestCase { |
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SIFT extractor; |
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KeyPoint keypoint; |
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int matSize; |
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Mat truth; |
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private Mat getTestImg() { |
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Mat cross = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255)); |
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Imgproc.line(cross, new Point(20, matSize / 2), new Point(matSize - 21, matSize / 2), new Scalar(100), 2); |
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Imgproc.line(cross, new Point(matSize / 2, 20), new Point(matSize / 2, matSize - 21), new Scalar(100), 2); |
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return cross; |
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} |
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@Override |
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protected void setUp() throws Exception { |
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super.setUp(); |
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extractor = SIFT.create(); |
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keypoint = new KeyPoint(55.775577545166016f, 44.224422454833984f, 16, 9.754629f, 8617.863f, 1, -1); |
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matSize = 100; |
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truth = new Mat(1, 128, CvType.CV_32FC1) { |
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{ |
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put(0, 0, |
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0, 0, 0, 1, 3, 0, 0, 0, 15, 23, 22, 20, 24, 2, 0, 0, 7, 8, 2, 0, |
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 27, 16, 13, 2, 0, 0, 117, |
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86, 79, 68, 117, 42, 5, 5, 79, 60, 117, 25, 9, 2, 28, 19, 11, 13, |
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20, 2, 0, 0, 5, 8, 0, 0, 76, 58, 34, 31, 97, 16, 95, 49, 117, 92, |
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117, 112, 117, 76, 117, 54, 117, 25, 29, 22, 117, 117, 16, 11, 14, |
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1, 0, 0, 22, 26, 0, 0, 0, 0, 1, 4, 15, 2, 47, 8, 0, 0, 82, 56, 31, |
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17, 81, 12, 0, 0, 26, 23, 18, 23, 0, 0, 0, 0, 0, 0, 0, 0 |
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); |
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} |
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}; |
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} |
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public void testComputeListOfMatListOfListOfKeyPointListOfMat() { |
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fail("Not yet implemented"); |
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} |
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public void testComputeMatListOfKeyPointMat() { |
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MatOfKeyPoint keypoints = new MatOfKeyPoint(keypoint); |
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Mat img = getTestImg(); |
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Mat descriptors = new Mat(); |
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extractor.compute(img, keypoints, descriptors); |
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assertMatEqual(truth, descriptors, EPS); |
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} |
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public void testCreate() { |
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assertNotNull(extractor); |
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} |
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public void testDescriptorSize() { |
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assertEquals(128, extractor.descriptorSize()); |
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} |
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public void testDescriptorType() { |
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assertEquals(CvType.CV_32F, extractor.descriptorType()); |
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} |
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public void testEmpty() { |
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// assertFalse(extractor.empty()); |
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fail("Not yet implemented"); // SIFT does not override empty() method |
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} |
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public void testReadYml() { |
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String filename = OpenCVTestRunner.getTempFileName("yml"); |
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writeFile(filename, "%YAML:1.0\n---\nname: \"Feature2D.SIFT\"\nnfeatures: 100\nnOctaveLayers: 4\ncontrastThreshold: 5.0000000000000001e-02\nedgeThreshold: 11\nsigma: 1.7\ndescriptorType: 5\n"); |
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extractor.read(filename); |
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assertEquals(128, extractor.descriptorSize()); |
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assertEquals(100, extractor.getNFeatures()); |
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assertEquals(4, extractor.getNOctaveLayers()); |
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assertEquals(0.05, extractor.getContrastThreshold()); |
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assertEquals(11., extractor.getEdgeThreshold()); |
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assertEquals(1.7, extractor.getSigma()); |
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assertEquals(5, extractor.descriptorType()); |
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} |
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public void testWriteYml() { |
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String filename = OpenCVTestRunner.getTempFileName("yml"); |
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extractor.write(filename); |
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String truth = "%YAML:1.0\n---\nname: \"Feature2D.SIFT\"\nnfeatures: 0\nnOctaveLayers: 3\ncontrastThreshold: 4.0000000000000001e-02\nedgeThreshold: 10.\nsigma: 1.6000000000000001e+00\ndescriptorType: 5\n"; |
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String actual = readFile(filename); |
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actual = actual.replaceAll("e([+-])0(\\d\\d)", "e$1$2"); // NOTE: workaround for different platforms double representation |
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assertEquals(truth, actual); |
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} |
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}
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