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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
110 lines
4.0 KiB
Java
110 lines
4.0 KiB
Java
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: 0.040000000000000001\nedgeThreshold: 10.\nsigma: 1.6000000000000001\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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