opencv/modules/features2d/misc/java/test/ORBDescriptorExtractorTest.java
Kumataro b14ea19466
Merge pull request #25351 from Kumataro:fix25073_format_g
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
2024-04-10 15:17:15 +03:00

122 lines
4.5 KiB
Java

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.core.KeyPoint;
import org.opencv.features2d.ORB;
import org.opencv.test.OpenCVTestCase;
import org.opencv.test.OpenCVTestRunner;
import org.opencv.imgproc.Imgproc;
public class ORBDescriptorExtractorTest extends OpenCVTestCase {
ORB extractor;
int matSize;
public static void assertDescriptorsClose(Mat expected, Mat actual, int allowedDistance) {
double distance = Core.norm(expected, actual, Core.NORM_HAMMING);
assertTrue("expected:<" + allowedDistance + "> but was:<" + distance + ">", distance <= allowedDistance);
}
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 = ORB.create();
matSize = 100;
}
public void testComputeListOfMatListOfListOfKeyPointListOfMat() {
fail("Not yet implemented");
}
public void testComputeMatListOfKeyPointMat() {
KeyPoint point = new KeyPoint(55.775577545166016f, 44.224422454833984f, 16, 9.754629f, 8617.863f, 1, -1);
MatOfKeyPoint keypoints = new MatOfKeyPoint(point);
Mat img = getTestImg();
Mat descriptors = new Mat();
extractor.compute(img, keypoints, descriptors);
Mat truth = new Mat(1, 32, CvType.CV_8UC1) {
{
put(0, 0,
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);
}
};
assertDescriptorsClose(truth, descriptors, 1);
}
public void testCreate() {
assertNotNull(extractor);
}
public void testDescriptorSize() {
assertEquals(32, extractor.descriptorSize());
}
public void testDescriptorType() {
assertEquals(CvType.CV_8U, extractor.descriptorType());
}
public void testEmpty() {
// assertFalse(extractor.empty());
fail("Not yet implemented"); // ORB does not override empty() method
}
public void testReadYml() {
KeyPoint point = new KeyPoint(55.775577545166016f, 44.224422454833984f, 16, 9.754629f, 8617.863f, 1, -1);
MatOfKeyPoint keypoints = new MatOfKeyPoint(point);
Mat img = getTestImg();
Mat descriptors = new Mat();
String filename = OpenCVTestRunner.getTempFileName("yml");
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");
extractor.read(filename);
assertEquals(500, extractor.getMaxFeatures());
assertEquals(1.1, extractor.getScaleFactor());
assertEquals(3, extractor.getNLevels());
assertEquals(31, extractor.getEdgeThreshold());
assertEquals(0, extractor.getFirstLevel());
assertEquals(2, extractor.getWTA_K());
assertEquals(0, extractor.getScoreType());
assertEquals(31, extractor.getPatchSize());
assertEquals(20, extractor.getFastThreshold());
extractor.compute(img, keypoints, descriptors);
Mat truth = new Mat(1, 32, CvType.CV_8UC1) {
{
put(0, 0,
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);
}
};
assertDescriptorsClose(truth, descriptors, 1);
}
public void testWriteYml() {
String filename = OpenCVTestRunner.getTempFileName("yml");
extractor.write(filename);
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";
// String truth = "%YAML:1.0\n---\n";
String actual = readFile(filename);
actual = actual.replaceAll("e\\+000", "e+00"); // NOTE: workaround for different platforms double representation
assertEquals(truth, actual);
}
}