Open Source Computer Vision Library https://opencv.org/
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package org.opencv.test.features2d;
import java.util.Arrays;
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.FeatureDetector;
import org.opencv.core.KeyPoint;
import org.opencv.test.OpenCVTestCase;
import org.opencv.test.OpenCVTestRunner;
import org.opencv.imgproc.Imgproc;
public class FASTFeatureDetectorTest extends OpenCVTestCase {
FeatureDetector detector;
KeyPoint[] truth;
private Mat getMaskImg() {
Mat mask = new Mat(100, 100, CvType.CV_8U, new Scalar(255));
Mat right = mask.submat(0, 100, 50, 100);
right.setTo(new Scalar(0));
return mask;
}
private Mat getTestImg() {
Mat img = new Mat(100, 100, CvType.CV_8U, new Scalar(255));
Imgproc.line(img, new Point(30, 30), new Point(70, 70), new Scalar(0), 8);
return img;
}
@Override
protected void setUp() throws Exception {
super.setUp();
detector = FeatureDetector.create(FeatureDetector.FAST);
truth = new KeyPoint[] { new KeyPoint(32, 27, 7, -1, 254, 0, -1), new KeyPoint(27, 32, 7, -1, 254, 0, -1), new KeyPoint(73, 68, 7, -1, 254, 0, -1),
new KeyPoint(68, 73, 7, -1, 254, 0, -1) };
}
public void testCreate() {
assertNotNull(detector);
}
public void testDetectListOfMatListOfListOfKeyPoint() {
fail("Not yet implemented");
}
public void testDetectListOfMatListOfListOfKeyPointListOfMat() {
fail("Not yet implemented");
}
public void testDetectMatListOfKeyPoint() {
Mat img = getTestImg();
MatOfKeyPoint keypoints = new MatOfKeyPoint();
detector.detect(img, keypoints);
assertListKeyPointEquals(Arrays.asList(truth), keypoints.toList(), EPS);
// OpenCVTestRunner.Log("points found: " + keypoints.size());
// for (KeyPoint kp : keypoints)
// OpenCVTestRunner.Log(kp.toString());
}
public void testDetectMatListOfKeyPointMat() {
Mat img = getTestImg();
Mat mask = getMaskImg();
MatOfKeyPoint keypoints = new MatOfKeyPoint();
detector.detect(img, keypoints, mask);
assertListKeyPointEquals(Arrays.asList(truth[0], truth[1]), keypoints.toList(), EPS);
}
public void testEmpty() {
assertFalse(detector.empty());
}
public void testRead() {
String filename = OpenCVTestRunner.getTempFileName("yml");
writeFile(filename, "%YAML:1.0\nthreshold: 130\nnonmaxSuppression: 1\n");
detector.read(filename);
MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
detector.detect(grayChess, keypoints1);
writeFile(filename, "%YAML:1.0\nthreshold: 150\nnonmaxSuppression: 1\n");
detector.read(filename);
MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
detector.detect(grayChess, keypoints2);
assertTrue(keypoints2.total() <= keypoints1.total());
}
public void testReadYml() {
String filename = OpenCVTestRunner.getTempFileName("yml");
writeFile(filename,
"<?xml version=\"1.0\"?>\n<opencv_storage>\n<threshold>130</threshold>\n<nonmaxSuppression>1</nonmaxSuppression>\n</opencv_storage>\n");
detector.read(filename);
MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
detector.detect(grayChess, keypoints1);
writeFile(filename,
"<?xml version=\"1.0\"?>\n<opencv_storage>\n<threshold>150</threshold>\n<nonmaxSuppression>1</nonmaxSuppression>\n</opencv_storage>\n");
detector.read(filename);
MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
detector.detect(grayChess, keypoints2);
assertTrue(keypoints2.total() <= keypoints1.total());
}
public void testWrite() {
String filename = OpenCVTestRunner.getTempFileName("xml");
detector.write(filename);
String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n<name>Feature2D.FAST</name>\n<nonmaxSuppression>1</nonmaxSuppression>\n<threshold>10</threshold>\n<type>2</type>\n</opencv_storage>\n";
String data = readFile(filename);
//Log.d("qqq", "\"" + data + "\"");
assertEquals(truth, data);
}
public void testWriteYml() {
String filename = OpenCVTestRunner.getTempFileName("yml");
detector.write(filename);
String truth = "%YAML:1.0\nname: \"Feature2D.FAST\"\nnonmaxSuppression: 1\nthreshold: 10\ntype: 2\n";
String data = readFile(filename);
//Log.d("qqq", "\"" + data + "\"");
assertEquals(truth, data);
}
}