mirror of
https://github.com/opencv/opencv.git
synced 2024-12-22 23:28:00 +08:00
0bd54a60e9
**Merge with contrib**: https://github.com/opencv/opencv_contrib/pull/3003 ### 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 other license that is incompatible with OpenCV - [x] The PR is proposed to proper branch - [ ] There is reference to 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. - [ ] 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;
|
|
|
|
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: 1.2000000476837158e+00\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);
|
|
}
|
|
|
|
}
|