root/modules/features2d/misc/java/test/BruteForceDescriptorMatcherTest.java

DEFINITIONS

1. getMaskImg
2. getQueryDescriptors
3. getQueryImg
4. getTrainDescriptors
5. getTrainImg
6. setUp
7. testAdd
8. testClear
9. testClone
10. testCloneBoolean
11. testCreate
12. testEmpty
13. testGetTrainDescriptors
14. testIsMaskSupported
15. testKnnMatchMatListOfListOfDMatchInt
16. testKnnMatchMatListOfListOfDMatchIntListOfMat
17. testKnnMatchMatListOfListOfDMatchIntListOfMatBoolean
18. testKnnMatchMatMatListOfListOfDMatchInt
19. testKnnMatchMatMatListOfListOfDMatchIntMat
20. testKnnMatchMatMatListOfListOfDMatchIntMatBoolean
21. testMatchMatListOfDMatch
22. testMatchMatListOfDMatchListOfMat
23. testMatchMatMatListOfDMatch
24. testMatchMatMatListOfDMatchMat
25. testRadiusMatchMatListOfListOfDMatchFloat
26. testRadiusMatchMatListOfListOfDMatchFloatListOfMat
27. testRadiusMatchMatListOfListOfDMatchFloatListOfMatBoolean
28. testRadiusMatchMatMatListOfListOfDMatchFloat
29. testRadiusMatchMatMatListOfListOfDMatchFloatMat
30. testRadiusMatchMatMatListOfListOfDMatchFloatMatBoolean
31. testRead
32. testTrain
33. testWrite

package org.opencv.test.features2d;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;

import org.opencv.core.Core;
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 BruteForceDescriptorMatcherTest extends OpenCVTestCase {

    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.BRUTEFORCE);
        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, 0.2925074f),
                new DMatch(4, 1, 0, 0.9309178f)
                };
    }

    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));
        Mat truth = train.clone();
        matcher.add(Arrays.asList(train));

        DescriptorMatcher cloned = matcher.clone();

        assertNotNull(cloned);

        List<Mat> descriptors = cloned.getTrainDescriptors();
        assertEquals(1, descriptors.size());
        assertMatEqual(truth, descriptors.get(0));
    }

    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() {
        assertTrue(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() {
        final int k = 3;
        Mat train = getTrainDescriptors();
        Mat query = getQueryDescriptors();
        List<MatOfDMatch> matches = new ArrayList<MatOfDMatch>();
        matcher.knnMatch(query, train, matches, k);
        /*
        Log.d("knnMatch", "train = " + train);
        Log.d("knnMatch", "query = " + query);

        matcher.add(train);
        matcher.knnMatch(query, matches, k);
        */
        assertEquals(query.rows(), matches.size());
        for(int i = 0; i<matches.size(); i++)
        {
            MatOfDMatch vdm = matches.get(i);
            //Log.d("knn", "vdm["+i+"]="+vdm.dump());
            assertTrue(Math.min(k, train.rows()) >= vdm.total());
            for(DMatch dm : vdm.toArray())
            {
                assertEquals(dm.queryIdx, i);
            }
        }
    }

    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.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.match(query, matches, Arrays.asList(mask));

        assertListDMatchEquals(Arrays.asList(truth[0], truth[1]), matches.toList(), EPS);
    }

    public void testMatchMatMatListOfDMatch() {
        Mat train = getTrainDescriptors();
        Mat query = getQueryDescriptors();
        MatOfDMatch matches = new MatOfDMatch();

        matcher.match(query, train, matches);

        assertArrayDMatchEquals(truth, matches.toArray(), EPS);

        // OpenCVTestRunner.Log("matches found: " + matches.size());
        // for (DMatch m : matches)
        // OpenCVTestRunner.Log(m.toString());
    }

    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[0], truth[1]), 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 filename = OpenCVTestRunner.getTempFileName("yml");
        writeFile(filename, "%YAML:1.0\n");

        matcher.read(filename);
        assertTrue(true);// BruteforceMatcher has no settings
    }

    public void testTrain() {
        matcher.train();// BruteforceMatcher does not need to train
    }

    public void testWrite() {
        String filename = OpenCVTestRunner.getTempFileName("yml");

        matcher.write(filename);

        String truth = "%YAML:1.0\n";
        assertEquals(truth, readFile(filename));
    }

}