This source file includes following definitions.
- getMaskImg
- getQueryDescriptors
- getQueryImg
- getTrainDescriptors
- getTrainImg
- setUp
- testAdd
- testClear
- testClone
- testCloneBoolean
- testCreate
- testEmpty
- testGetTrainDescriptors
- testIsMaskSupported
- testKnnMatchMatListOfListOfDMatchInt
- testKnnMatchMatListOfListOfDMatchIntListOfMat
- testKnnMatchMatListOfListOfDMatchIntListOfMatBoolean
- testKnnMatchMatMatListOfListOfDMatchInt
- testKnnMatchMatMatListOfListOfDMatchIntMat
- testKnnMatchMatMatListOfListOfDMatchIntMatBoolean
- testMatchMatListOfDMatch
- testMatchMatListOfDMatchListOfMat
- testMatchMatMatListOfDMatch
- testMatchMatMatListOfDMatchMat
- testRadiusMatchMatListOfListOfDMatchFloat
- testRadiusMatchMatListOfListOfDMatchFloatListOfMat
- testRadiusMatchMatListOfListOfDMatchFloatListOfMatBoolean
- testRadiusMatchMatMatListOfListOfDMatchFloat
- testRadiusMatchMatMatListOfListOfDMatchFloatMat
- testRadiusMatchMatMatListOfListOfDMatchFloatMatBoolean
- testRead
- testTrain
- testTrainNoData
- testWrite
- testWriteYml
package org.opencv.test.features2d;
import java.util.Arrays;
import java.util.List;
import org.opencv.core.Core;
import org.opencv.core.CvException;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.MatOfDMatch;
import org.opencv.core.MatOfKeyPoint;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.core.DMatch;
import org.opencv.features2d.DescriptorExtractor;
import org.opencv.features2d.DescriptorMatcher;
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 FlannBasedDescriptorMatcherTest extends OpenCVTestCase {
static final String xmlParamsDefault = "<?xml version=\"1.0\"?>\n"
+ "<opencv_storage>\n"
+ "<indexParams>\n"
+ " <_>\n"
+ " <name>algorithm</name>\n"
+ " <type>23</type>\n"
+ " <value>1</value></_>\n"
+ " <_>\n"
+ " <name>trees</name>\n"
+ " <type>4</type>\n"
+ " <value>4</value></_></indexParams>\n"
+ "<searchParams>\n"
+ " <_>\n"
+ " <name>checks</name>\n"
+ " <type>4</type>\n"
+ " <value>32</value></_>\n"
+ " <_>\n"
+ " <name>eps</name>\n"
+ " <type>5</type>\n"
+ " <value>0.</value></_>\n"
+ " <_>\n"
+ " <name>sorted</name>\n"
+ " <type>15</type>\n"
+ " <value>1</value></_></searchParams>\n"
+ "</opencv_storage>\n";
static final String ymlParamsDefault = "%YAML:1.0\n"
+ "indexParams:\n"
+ " -\n"
+ " name: algorithm\n"
+ " type: 23\n"
+ " value: 1\n"
+ " -\n"
+ " name: trees\n"
+ " type: 4\n"
+ " value: 4\n"
+ "searchParams:\n"
+ " -\n"
+ " name: checks\n"
+ " type: 4\n"
+ " value: 32\n"
+ " -\n"
+ " name: eps\n"
+ " type: 5\n"
+ " value: 0.\n"
+ " -\n"
+ " name: sorted\n"
+ " type: 15\n"
+ " value: 1\n";
static final String ymlParamsModified = "%YAML:1.0\n"
+ "indexParams:\n"
+ " -\n"
+ " name: algorithm\n"
+ " type: 23\n"
+ " value: 6\n"
+ " -\n"
+ " name: trees\n"
+ " type: 4\n"
+ " value: 4\n"
+ "searchParams:\n"
+ " -\n"
+ " name: checks\n"
+ " type: 4\n"
+ " value: 32\n"
+ " -\n"
+ " name: eps\n"
+ " type: 5\n"
+ " value: 4.\n"
+ " -\n"
+ " name: sorted\n"
+ " type: 15\n"
+ " value: 1\n";
DescriptorMatcher matcher;
int matSize;
DMatch[] truth;
private Mat getMaskImg() {
return new Mat(5, 2, CvType.CV_8U, new Scalar(0)) {
{
put(0, 0, 1, 1, 1, 1);
}
};
}
private Mat getQueryDescriptors() {
Mat img = getQueryImg();
MatOfKeyPoint keypoints = new MatOfKeyPoint();
Mat descriptors = new Mat();
FeatureDetector detector = FeatureDetector.create(FeatureDetector.SURF);
DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.SURF);
String filename = OpenCVTestRunner.getTempFileName("yml");
writeFile(filename, "%YAML:1.0\nhessianThreshold: 8000.\noctaves: 3\noctaveLayers: 4\nupright: 0\n");
detector.read(filename);
detector.detect(img, keypoints);
extractor.compute(img, keypoints, descriptors);
return descriptors;
}
private Mat getQueryImg() {
Mat cross = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
Imgproc.line(cross, new Point(30, matSize / 2), new Point(matSize - 31, matSize / 2), new Scalar(100), 3);
Imgproc.line(cross, new Point(matSize / 2, 30), new Point(matSize / 2, matSize - 31), new Scalar(100), 3);
return cross;
}
private Mat getTrainDescriptors() {
Mat img = getTrainImg();
MatOfKeyPoint keypoints = new MatOfKeyPoint(new KeyPoint(50, 50, 16, 0, 20000, 1, -1), new KeyPoint(42, 42, 16, 160, 10000, 1, -1));
Mat descriptors = new Mat();
DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.SURF);
extractor.compute(img, keypoints, descriptors);
return descriptors;
}
private Mat getTrainImg() {
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;
}
protected void setUp() throws Exception {
super.setUp();
matcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED);
matSize = 100;
truth = new DMatch[] {
new DMatch(0, 0, 0, 0.6211397f),
new DMatch(1, 1, 0, 0.9177120f),
new DMatch(2, 1, 0, 0.3112163f),
new DMatch(3, 1, 0, 0.2925075f),
new DMatch(4, 1, 0, 0.9309179f)
};
}
public void testAdd() {
matcher.add(Arrays.asList(new Mat()));
assertFalse(matcher.empty());
}
public void testClear() {
matcher.add(Arrays.asList(new Mat()));
matcher.clear();
assertTrue(matcher.empty());
}
public void testClone() {
Mat train = new Mat(1, 1, CvType.CV_8U, new Scalar(123));
matcher.add(Arrays.asList(train));
try {
matcher.clone();
fail("Expected CvException (CV_StsNotImplemented)");
} catch (CvException cverr) {
}
}
public void testCloneBoolean() {
matcher.add(Arrays.asList(new Mat()));
DescriptorMatcher cloned = matcher.clone(true);
assertNotNull(cloned);
assertTrue(cloned.empty());
}
public void testCreate() {
assertNotNull(matcher);
}
public void testEmpty() {
assertTrue(matcher.empty());
}
public void testGetTrainDescriptors() {
Mat train = new Mat(1, 1, CvType.CV_8U, new Scalar(123));
Mat truth = train.clone();
matcher.add(Arrays.asList(train));
List<Mat> descriptors = matcher.getTrainDescriptors();
assertEquals(1, descriptors.size());
assertMatEqual(truth, descriptors.get(0));
}
public void testIsMaskSupported() {
assertFalse(matcher.isMaskSupported());
}
public void testKnnMatchMatListOfListOfDMatchInt() {
fail("Not yet implemented");
}
public void testKnnMatchMatListOfListOfDMatchIntListOfMat() {
fail("Not yet implemented");
}
public void testKnnMatchMatListOfListOfDMatchIntListOfMatBoolean() {
fail("Not yet implemented");
}
public void testKnnMatchMatMatListOfListOfDMatchInt() {
fail("Not yet implemented");
}
public void testKnnMatchMatMatListOfListOfDMatchIntMat() {
fail("Not yet implemented");
}
public void testKnnMatchMatMatListOfListOfDMatchIntMatBoolean() {
fail("Not yet implemented");
}
public void testMatchMatListOfDMatch() {
Mat train = getTrainDescriptors();
Mat query = getQueryDescriptors();
MatOfDMatch matches = new MatOfDMatch();
matcher.add(Arrays.asList(train));
matcher.train();
matcher.match(query, matches);
assertArrayDMatchEquals(truth, matches.toArray(), EPS);
}
public void testMatchMatListOfDMatchListOfMat() {
Mat train = getTrainDescriptors();
Mat query = getQueryDescriptors();
Mat mask = getMaskImg();
MatOfDMatch matches = new MatOfDMatch();
matcher.add(Arrays.asList(train));
matcher.train();
matcher.match(query, matches, Arrays.asList(mask));
assertArrayDMatchEquals(truth, matches.toArray(), EPS);
}
public void testMatchMatMatListOfDMatch() {
Mat train = getTrainDescriptors();
Mat query = getQueryDescriptors();
MatOfDMatch matches = new MatOfDMatch();
matcher.match(query, train, matches);
assertArrayDMatchEquals(truth, matches.toArray(), EPS);
}
public void testMatchMatMatListOfDMatchMat() {
Mat train = getTrainDescriptors();
Mat query = getQueryDescriptors();
Mat mask = getMaskImg();
MatOfDMatch matches = new MatOfDMatch();
matcher.match(query, train, matches, mask);
assertListDMatchEquals(Arrays.asList(truth), matches.toList(), EPS);
}
public void testRadiusMatchMatListOfListOfDMatchFloat() {
fail("Not yet implemented");
}
public void testRadiusMatchMatListOfListOfDMatchFloatListOfMat() {
fail("Not yet implemented");
}
public void testRadiusMatchMatListOfListOfDMatchFloatListOfMatBoolean() {
fail("Not yet implemented");
}
public void testRadiusMatchMatMatListOfListOfDMatchFloat() {
fail("Not yet implemented");
}
public void testRadiusMatchMatMatListOfListOfDMatchFloatMat() {
fail("Not yet implemented");
}
public void testRadiusMatchMatMatListOfListOfDMatchFloatMatBoolean() {
fail("Not yet implemented");
}
public void testRead() {
String filenameR = OpenCVTestRunner.getTempFileName("yml");
String filenameW = OpenCVTestRunner.getTempFileName("yml");
writeFile(filenameR, ymlParamsModified);
matcher.read(filenameR);
matcher.write(filenameW);
assertEquals(ymlParamsModified, readFile(filenameW));
}
public void testTrain() {
Mat train = getTrainDescriptors();
matcher.add(Arrays.asList(train));
matcher.train();
}
public void testTrainNoData() {
try {
matcher.train();
fail("Expected CvException - FlannBasedMatcher::train should fail on empty train set");
} catch (CvException cverr) {
}
}
public void testWrite() {
String filename = OpenCVTestRunner.getTempFileName("xml");
matcher.write(filename);
assertEquals(xmlParamsDefault, readFile(filename));
}
public void testWriteYml() {
String filename = OpenCVTestRunner.getTempFileName("yml");
matcher.write(filename);
assertEquals(ymlParamsDefault, readFile(filename));
}
}