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Merge pull request #25292 from kaingwade:features2d_parts_to_contrib
Features2d cleanup: Move several feature detectors and descriptors to opencv_contrib #25292 features2d cleanup: #24999 The PR moves KAZE, AKAZE, AgastFeatureDetector, BRISK and BOW to opencv_contrib/xfeatures2d. Related PR: opencv/opencv_contrib#3709
This commit is contained in:
WU Jia
GitHub
@@ -1,85 +0,0 @@
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package org.opencv.test.features2d;
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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.features2d.AgastFeatureDetector;
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public class AGASTFeatureDetectorTest extends OpenCVTestCase {
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AgastFeatureDetector detector;
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@Override
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protected void setUp() throws Exception {
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super.setUp();
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detector = AgastFeatureDetector.create(); // default (10,true,3)
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}
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public void testCreate() {
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assertNotNull(detector);
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}
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public void testDetectListOfMatListOfListOfKeyPoint() {
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fail("Not yet implemented");
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}
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public void testDetectListOfMatListOfListOfKeyPointListOfMat() {
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fail("Not yet implemented");
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}
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public void testDetectMatListOfKeyPoint() {
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fail("Not yet implemented");
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}
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public void testDetectMatListOfKeyPointMat() {
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fail("Not yet implemented");
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}
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public void testEmpty() {
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fail("Not yet implemented");
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}
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public void testRead() {
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String filename = OpenCVTestRunner.getTempFileName("xml");
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writeFile(filename, "<?xml version=\"1.0\"?>\n<opencv_storage>\n<name>Feature2D.AgastFeatureDetector</name>\n<threshold>11</threshold>\n<nonmaxSuppression>0</nonmaxSuppression>\n<type>2</type>\n</opencv_storage>\n");
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detector.read(filename);
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assertEquals(11, detector.getThreshold());
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assertEquals(false, detector.getNonmaxSuppression());
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assertEquals(2, detector.getType());
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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.AgastFeatureDetector\"\nthreshold: 11\nnonmaxSuppression: 0\ntype: 2\n");
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detector.read(filename);
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assertEquals(11, detector.getThreshold());
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assertEquals(false, detector.getNonmaxSuppression());
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assertEquals(2, detector.getType());
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}
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public void testWrite() {
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String filename = OpenCVTestRunner.getTempFileName("xml");
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detector.write(filename);
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String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n<name>Feature2D.AgastFeatureDetector</name>\n<threshold>10</threshold>\n<nonmaxSuppression>1</nonmaxSuppression>\n<type>3</type>\n</opencv_storage>\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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public void testWriteYml() {
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String filename = OpenCVTestRunner.getTempFileName("yml");
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detector.write(filename);
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String truth = "%YAML:1.0\n---\nname: \"Feature2D.AgastFeatureDetector\"\nthreshold: 10\nnonmaxSuppression: 1\ntype: 3\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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@@ -1,67 +0,0 @@
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package org.opencv.test.features2d;
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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.features2d.AKAZE;
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public class AKAZEDescriptorExtractorTest extends OpenCVTestCase {
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AKAZE extractor;
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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 = AKAZE.create(); // default (5,0,3,0.001f,4,4,1)
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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 testDetectListOfMatListOfListOfKeyPoint() {
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fail("Not yet implemented");
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}
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public void testDetectListOfMatListOfListOfKeyPointListOfMat() {
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fail("Not yet implemented");
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}
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public void testDetectMatListOfKeyPoint() {
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fail("Not yet implemented");
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}
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public void testDetectMatListOfKeyPointMat() {
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fail("Not yet implemented");
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}
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public void testEmpty() {
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fail("Not yet implemented");
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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---\nformat: 3\nname: \"Feature2D.AKAZE\"\ndescriptor: 4\ndescriptor_channels: 2\ndescriptor_size: 32\nthreshold: 0.125\noctaves: 3\nsublevels: 5\ndiffusivity: 2\n");
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extractor.read(filename);
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assertEquals(4, extractor.getDescriptorType());
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assertEquals(2, extractor.getDescriptorChannels());
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assertEquals(32, extractor.getDescriptorSize());
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assertEquals(0.125, extractor.getThreshold());
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assertEquals(3, extractor.getNOctaves());
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assertEquals(5, extractor.getNOctaveLayers());
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assertEquals(2, extractor.getDiffusivity());
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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---\nformat: 3\nname: \"Feature2D.AKAZE\"\ndescriptor: 5\ndescriptor_channels: 3\ndescriptor_size: 0\nthreshold: 0.0010000000474974513\noctaves: 4\nsublevels: 4\ndiffusivity: 1\nmax_points: -1\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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@@ -1,48 +0,0 @@
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package org.opencv.test.features2d;
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import org.opencv.core.Core;
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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.ORB;
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import org.opencv.features2d.DescriptorMatcher;
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import org.opencv.features2d.BOWImgDescriptorExtractor;
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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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public class BOWImgDescriptorExtractorTest extends OpenCVTestCase {
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ORB extractor;
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DescriptorMatcher matcher;
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int matSize;
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public static void assertDescriptorsClose(Mat expected, Mat actual, int allowedDistance) {
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double distance = Core.norm(expected, actual, Core.NORM_HAMMING);
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assertTrue("expected:<" + allowedDistance + "> but was:<" + distance + ">", distance <= allowedDistance);
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}
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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 = ORB.create();
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matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE);
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matSize = 100;
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}
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public void testCreate() {
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BOWImgDescriptorExtractor bow = new BOWImgDescriptorExtractor(extractor, matcher);
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}
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}
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@@ -1,102 +0,0 @@
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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.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.Feature2D;
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public class BRIEFDescriptorExtractorTest extends OpenCVTestCase {
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Feature2D extractor;
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int matSize;
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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 = createClassInstance(XFEATURES2D+"BriefDescriptorExtractor", DEFAULT_FACTORY, null, null);
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matSize = 100;
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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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KeyPoint point = new KeyPoint(55.775577545166016f, 44.224422454833984f, 16, 9.754629f, 8617.863f, 1, -1);
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MatOfKeyPoint keypoints = new MatOfKeyPoint(point);
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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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Mat truth = new Mat(1, 32, CvType.CV_8UC1) {
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{
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put(0, 0, 96, 0, 76, 24, 47, 182, 68, 137,
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149, 195, 67, 16, 187, 224, 74, 8,
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82, 169, 87, 70, 44, 4, 192, 56,
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13, 128, 44, 106, 146, 72, 194, 245);
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}
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};
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assertMatEqual(truth, descriptors);
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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(32, extractor.descriptorSize());
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}
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public void testDescriptorType() {
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assertEquals(CvType.CV_8U, 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"); // BRIEF does not override empty() method
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}
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public void testRead() {
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String filename = OpenCVTestRunner.getTempFileName("yml");
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writeFile(filename, "%YAML:1.0\n---\ndescriptorSize: 64\n");
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extractor.read(filename);
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assertEquals(64, extractor.descriptorSize());
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}
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public void testWrite() {
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String filename = OpenCVTestRunner.getTempFileName("xml");
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extractor.write(filename);
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String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n<name>Feature2D.BRIEF</name>\n<descriptorSize>32</descriptorSize>\n<use_orientation>0</use_orientation>\n</opencv_storage>\n";
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assertEquals(truth, readFile(filename));
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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.BRIEF\"\ndescriptorSize: 32\nuse_orientation: 0\n";
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assertEquals(truth, readFile(filename));
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}
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}
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@@ -1,63 +0,0 @@
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package org.opencv.test.features2d;
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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.features2d.BRISK;
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public class BRISKDescriptorExtractorTest extends OpenCVTestCase {
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BRISK extractor;
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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 = BRISK.create(); // default (30,3,1)
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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 testDetectListOfMatListOfListOfKeyPoint() {
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fail("Not yet implemented");
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}
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public void testDetectListOfMatListOfListOfKeyPointListOfMat() {
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fail("Not yet implemented");
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}
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public void testDetectMatListOfKeyPoint() {
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fail("Not yet implemented");
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}
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public void testDetectMatListOfKeyPointMat() {
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fail("Not yet implemented");
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}
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public void testEmpty() {
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fail("Not yet implemented");
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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.BRISK\"\nthreshold: 31\noctaves: 4\npatternScale: 1.1\n");
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extractor.read(filename);
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assertEquals(31, extractor.getThreshold());
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assertEquals(4, extractor.getOctaves());
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assertEquals(1.1f, extractor.getPatternScale());
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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.BRISK\"\nthreshold: 30\noctaves: 3\npatternScale: 1.\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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@@ -1,66 +0,0 @@
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package org.opencv.test.features2d;
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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.features2d.KAZE;
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public class KAZEDescriptorExtractorTest extends OpenCVTestCase {
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KAZE extractor;
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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 = KAZE.create(); // default (false,false,0.001f,4,4,1)
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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 testDetectListOfMatListOfListOfKeyPoint() {
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fail("Not yet implemented");
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}
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public void testDetectListOfMatListOfListOfKeyPointListOfMat() {
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fail("Not yet implemented");
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}
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public void testDetectMatListOfKeyPoint() {
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fail("Not yet implemented");
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}
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public void testDetectMatListOfKeyPointMat() {
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fail("Not yet implemented");
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}
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public void testEmpty() {
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fail("Not yet implemented");
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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---\nformat: 3\nname: \"Feature2D.KAZE\"\nextended: 1\nupright: 1\nthreshold: 0.125\noctaves: 3\nsublevels: 5\ndiffusivity: 2\n");
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extractor.read(filename);
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assertEquals(true, extractor.getExtended());
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assertEquals(true, extractor.getUpright());
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assertEquals(0.125, extractor.getThreshold());
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assertEquals(3, extractor.getNOctaves());
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assertEquals(5, extractor.getNOctaveLayers());
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assertEquals(2, extractor.getDiffusivity());
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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---\nformat: 3\nname: \"Feature2D.KAZE\"\nextended: 0\nupright: 0\nthreshold: 0.0010000000474974513\noctaves: 4\nsublevels: 4\ndiffusivity: 1\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
|
||||
assertEquals(truth, actual);
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}
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||||
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||||
}
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@@ -2,16 +2,12 @@
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"whitelist":
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||||
{
|
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"Feature2D": ["detect", "compute", "detectAndCompute", "descriptorSize", "descriptorType", "defaultNorm", "empty", "getDefaultName"],
|
||||
"BRISK": ["create", "getDefaultName"],
|
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"ORB": ["create", "setMaxFeatures", "setScaleFactor", "setNLevels", "setEdgeThreshold", "setFastThreshold", "setFirstLevel", "setWTA_K", "setScoreType", "setPatchSize", "getFastThreshold", "getDefaultName"],
|
||||
"MSER": ["create", "detectRegions", "setDelta", "getDelta", "setMinArea", "getMinArea", "setMaxArea", "getMaxArea", "setPass2Only", "getPass2Only", "getDefaultName"],
|
||||
"FastFeatureDetector": ["create", "setThreshold", "getThreshold", "setNonmaxSuppression", "getNonmaxSuppression", "setType", "getType", "getDefaultName"],
|
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"AgastFeatureDetector": ["create", "setThreshold", "getThreshold", "setNonmaxSuppression", "getNonmaxSuppression", "setType", "getType", "getDefaultName"],
|
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"GFTTDetector": ["create", "setMaxFeatures", "getMaxFeatures", "setQualityLevel", "getQualityLevel", "setMinDistance", "getMinDistance", "setBlockSize", "getBlockSize", "setHarrisDetector", "getHarrisDetector", "setK", "getK", "getDefaultName"],
|
||||
"SimpleBlobDetector": ["create", "setParams", "getParams", "getDefaultName"],
|
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"SimpleBlobDetector_Params": [],
|
||||
"KAZE": ["create", "setExtended", "getExtended", "setUpright", "getUpright", "setThreshold", "getThreshold", "setNOctaves", "getNOctaves", "setNOctaveLayers", "getNOctaveLayers", "setDiffusivity", "getDiffusivity", "getDefaultName"],
|
||||
"AKAZE": ["create", "setDescriptorType", "getDescriptorType", "setDescriptorSize", "getDescriptorSize", "setDescriptorChannels", "getDescriptorChannels", "setThreshold", "getThreshold", "setNOctaves", "getNOctaves", "setNOctaveLayers", "getNOctaveLayers", "setDiffusivity", "getDiffusivity", "getDefaultName"],
|
||||
"DescriptorMatcher": ["add", "clear", "empty", "isMaskSupported", "train", "match", "knnMatch", "radiusMatch", "clone", "create"],
|
||||
"BFMatcher": ["isMaskSupported", "create"],
|
||||
"": ["drawKeypoints", "drawMatches", "drawMatchesKnn"]
|
||||
|
||||
@@ -6,8 +6,7 @@
|
||||
}
|
||||
},
|
||||
"enum_fix" : {
|
||||
"FastFeatureDetector" : { "DetectorType": "FastDetectorType" },
|
||||
"AgastFeatureDetector" : { "DetectorType": "AgastDetectorType" }
|
||||
"FastFeatureDetector" : { "DetectorType": "FastDetectorType" }
|
||||
},
|
||||
"func_arg_fix" : {
|
||||
"Feature2D": {
|
||||
|
||||
@@ -1,9 +1,6 @@
|
||||
#ifdef HAVE_OPENCV_FEATURES2D
|
||||
typedef SimpleBlobDetector::Params SimpleBlobDetector_Params;
|
||||
typedef AKAZE::DescriptorType AKAZE_DescriptorType;
|
||||
typedef AgastFeatureDetector::DetectorType AgastFeatureDetector_DetectorType;
|
||||
typedef FastFeatureDetector::DetectorType FastFeatureDetector_DetectorType;
|
||||
typedef DescriptorMatcher::MatcherType DescriptorMatcher_MatcherType;
|
||||
typedef KAZE::DiffusivityType KAZE_DiffusivityType;
|
||||
typedef ORB::ScoreType ORB_ScoreType;
|
||||
#endif
|
||||
@@ -92,7 +92,7 @@ TrackedTarget = namedtuple('TrackedTarget', 'target, p0, p1, H, quad')
|
||||
|
||||
class PlaneTracker:
|
||||
def __init__(self):
|
||||
self.detector = cv.AKAZE_create(threshold = 0.003)
|
||||
self.detector = cv.ORB_create( nfeatures = 1000 )
|
||||
self.matcher = cv.FlannBasedMatcher(flann_params, {}) # bug : need to pass empty dict (#1329)
|
||||
self.targets = []
|
||||
self.frame_points = []
|
||||
|
||||
Reference in New Issue
Block a user