opencv/modules/features2d/misc/java/test/ORBDescriptorExtractorTest.java
2015-03-02 18:12:30 +03:00

121 lines
4.6 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.features2d.DescriptorExtractor;
import org.opencv.core.KeyPoint;
import org.opencv.test.OpenCVTestCase;
import org.opencv.test.OpenCVTestRunner;
import org.opencv.imgproc.Imgproc;
public class ORBDescriptorExtractorTest extends OpenCVTestCase {
DescriptorExtractor 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 = DescriptorExtractor.create(DescriptorExtractor.ORB);
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, 36, 132, 66, 165, 172, 6, 3, 72, 102, 61, 163, 214, 0, 144, 65, 232, 4, 32, 138, 129, 4, 21, 37, 88);
}
};
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());
}
public void testRead() {
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\nscaleFactor: 1.1\nnLevels: 3\nfirstLevel: 0\nedgeThreshold: 31\npatchSize: 31\n");
extractor.read(filename);
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, 10, 131, 0, 37, 37, 67);
}
};
assertDescriptorsClose(truth, descriptors, 1);
}
public void testWrite() {
String filename = OpenCVTestRunner.getTempFileName("xml");
extractor.write(filename);
String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n<name>Feature2D.ORB</name>\n<WTA_K>2</WTA_K>\n<edgeThreshold>31</edgeThreshold>\n<firstLevel>0</firstLevel>\n<nFeatures>500</nFeatures>\n<nLevels>8</nLevels>\n<patchSize>31</patchSize>\n<scaleFactor>1.2000000476837158e+00</scaleFactor>\n<scoreType>0</scoreType>\n</opencv_storage>\n";
String actual = readFile(filename);
actual = actual.replaceAll("e\\+000", "e+00"); // NOTE: workaround for different platforms double representation
assertEquals(truth, actual);
}
public void testWriteYml() {
String filename = OpenCVTestRunner.getTempFileName("yml");
extractor.write(filename);
String truth = "%YAML:1.0\nname: \"Feature2D.ORB\"\nWTA_K: 2\nedgeThreshold: 31\nfirstLevel: 0\nnFeatures: 500\nnLevels: 8\npatchSize: 31\nscaleFactor: 1.2000000476837158e+00\nscoreType: 0\n";
String actual = readFile(filename);
actual = actual.replaceAll("e\\+000", "e+00"); // NOTE: workaround for different platforms double representation
assertEquals(truth, actual);
}
}