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b14ea19466
core: persistence: output reals as human-friendly expression. #25351 Close #25073 Related https://github.com/opencv/opencv/pull/25087 This patch is need to merge same time with https://github.com/opencv/opencv_contrib/pull/3714 ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake
122 lines
4.5 KiB
Java
122 lines
4.5 KiB
Java
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.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 ORBDescriptorExtractorTest extends OpenCVTestCase {
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ORB extractor;
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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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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,
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6, 74, 6, 129, 2, 130, 56, 0, 44, 132, 66, 165, 172, 6, 3, 72, 102, 61, 171, 214, 0, 144, 65, 232, 4, 32, 138, 131, 4, 21, 37, 217);
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}
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};
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assertDescriptorsClose(truth, descriptors, 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 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"); // ORB does not override empty() method
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}
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public void testReadYml() {
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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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String filename = OpenCVTestRunner.getTempFileName("yml");
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writeFile(filename, "%YAML:1.0\n---\nnfeatures: 500\nscaleFactor: 1.1\nnlevels: 3\nedgeThreshold: 31\nfirstLevel: 0\nwta_k: 2\nscoreType: 0\npatchSize: 31\nfastThreshold: 20\n");
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extractor.read(filename);
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assertEquals(500, extractor.getMaxFeatures());
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assertEquals(1.1, extractor.getScaleFactor());
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assertEquals(3, extractor.getNLevels());
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assertEquals(31, extractor.getEdgeThreshold());
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assertEquals(0, extractor.getFirstLevel());
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assertEquals(2, extractor.getWTA_K());
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assertEquals(0, extractor.getScoreType());
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assertEquals(31, extractor.getPatchSize());
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assertEquals(20, extractor.getFastThreshold());
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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,
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6, 10, 22, 5, 2, 130, 56, 0, 44, 164, 66, 165, 140, 6, 1, 72, 38, 61, 163, 210, 0, 208, 1, 104, 4, 32, 74, 131, 0, 37, 37, 67);
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}
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};
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assertDescriptorsClose(truth, descriptors, 1);
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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.ORB\"\nnfeatures: 500\nscaleFactor: 1.2000000476837158\nnlevels: 8\nedgeThreshold: 31\nfirstLevel: 0\nwta_k: 2\nscoreType: 0\npatchSize: 31\nfastThreshold: 20\n";
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// String truth = "%YAML:1.0\n---\n";
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String actual = readFile(filename);
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actual = actual.replaceAll("e\\+000", "e+00"); // 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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