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JavaAPI: fixed typo; some constants are moved to private section; added tests for BruteForceMatcher-Hamming

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This commit is contained in:
Andrey Kamaev 2011-08-03 19:46:30 +00:00
parent cc6b7edf95
commit 6944c0dba4
4 changed files with 418 additions and 4 deletions
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203
modules/java/android_test/src/org/opencv/test/features2d/BruteForceHammingDescriptorMatcherTest.java Normal file
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@ -0,0 +1,203 @@
package org.opencv.test.features2d;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.features2d.DMatch;
import org.opencv.features2d.DescriptorExtractor;
import org.opencv.features2d.DescriptorMatcher;
import org.opencv.features2d.FeatureDetector;
import org.opencv.features2d.KeyPoint;
import org.opencv.test.OpenCVTestCase;
import org.opencv.test.OpenCVTestRunner;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
public class BruteForceHammingDescriptorMatcherTest extends OpenCVTestCase {
DescriptorMatcher matcher;
int matSize;
DMatch[] truth;
protected void setUp() throws Exception {
matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
matSize = 100;
truth = new DMatch[] {
new DMatch (0, 0, 0, 51),
new DMatch (1, 2, 0, 42),
new DMatch (2, 1, 0, 40),
new DMatch (3, 3, 0, 53) };
super.setUp();
}
private Mat getTrainImg() {
Mat img = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
Core.line(img, new Point(40, 40), new Point(matSize - 40, matSize - 40), new Scalar(0), 8);
return img;
}
private Mat getQueryImg() {
Mat img = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
Core.line(img, new Point(40, matSize - 40), new Point(matSize - 50, 50), new Scalar(0), 8);
return img;
}
private Mat getTestDescriptors(Mat img) {
List<KeyPoint> keypoints = new ArrayList<KeyPoint>();
Mat descriptors = new Mat();
FeatureDetector detector = FeatureDetector.create(FeatureDetector.FAST);
DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.BRIEF);
detector.detect(img, keypoints);
extractor.compute(img, keypoints, descriptors);
return descriptors;
}
private Mat getQueryDescriptors() {
return getTestDescriptors(getQueryImg());
}
private Mat getTrainDescriptors() {
return getTestDescriptors(getTrainImg());
}
private Mat getMaskImg() {
return new Mat(4, 4, CvType.CV_8U, new Scalar(0)) {
{
put(0, 0, 1, 1, 1, 1, 1, 1, 1, 1);
}
};
}
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 testCloneBoolean() {
matcher.add(Arrays.asList(new Mat()));
DescriptorMatcher cloned = matcher.clone(true);
assertNotNull(cloned);
assertTrue(cloned.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 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 testMatchMatMatListOfDMatchMat() {
Mat train = getTrainDescriptors();
Mat query = getQueryDescriptors();
Mat mask = getMaskImg();
List<DMatch> matches = new ArrayList<DMatch>();
matcher.match(query, train, matches, mask);
assertListDMatchEquals(Arrays.asList(truth[0], truth[1]), matches, EPS);
}
public void testMatchMatMatListOfDMatch() {
Mat train = getTrainDescriptors();
Mat query = getQueryDescriptors();
List<DMatch> matches = new ArrayList<DMatch>();
matcher.match(query, train, matches);
assertListDMatchEquals(Arrays.asList(truth), matches, EPS);
}
public void testMatchMatListOfDMatchListOfMat() {
Mat train = getTrainDescriptors();
Mat query = getQueryDescriptors();
Mat mask = getMaskImg();
List<DMatch> matches = new ArrayList<DMatch>();
matcher.add(Arrays.asList(train));
matcher.match(query, matches, Arrays.asList(mask));
assertListDMatchEquals(Arrays.asList(truth[0], truth[1]), matches, EPS);
}
public void testMatchMatListOfDMatch() {
Mat train = getTrainDescriptors();
Mat query = getQueryDescriptors();
List<DMatch> matches = new ArrayList<DMatch>();
matcher.add(Arrays.asList(train));
matcher.match(query, matches);
assertListDMatchEquals(Arrays.asList(truth), matches, EPS);
}
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));
}
}

207
modules/java/android_test/src/org/opencv/test/features2d/BruteForceHammingLUTDescriptorMatcherTest.java Normal file
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@ -0,0 +1,207 @@
package org.opencv.test.features2d;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.features2d.DMatch;
import org.opencv.features2d.DescriptorExtractor;
import org.opencv.features2d.DescriptorMatcher;
import org.opencv.features2d.FeatureDetector;
import org.opencv.features2d.KeyPoint;
import org.opencv.test.OpenCVTestCase;
import org.opencv.test.OpenCVTestRunner;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
public class BruteForceHammingLUTDescriptorMatcherTest extends OpenCVTestCase {
DescriptorMatcher matcher;
int matSize;
DMatch[] truth;
protected void setUp() throws Exception {
matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMINGLUT);
matSize = 100;
truth = new DMatch[] {
new DMatch (0, 0, 0, 51),
new DMatch (1, 2, 0, 42),
new DMatch (2, 1, 0, 40),
new DMatch (3, 3, 0, 53) };
super.setUp();
}
private Mat getTrainImg() {
Mat img = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
Core.line(img, new Point(40, 40), new Point(matSize - 40, matSize - 40), new Scalar(0), 8);
return img;
}
private Mat getQueryImg() {
Mat img = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
Core.line(img, new Point(40, matSize - 40), new Point(matSize - 50, 50), new Scalar(0), 8);
return img;
}
private Mat getTestDescriptors(Mat img) {
List<KeyPoint> keypoints = new ArrayList<KeyPoint>();
Mat descriptors = new Mat();
FeatureDetector detector = FeatureDetector.create(FeatureDetector.FAST);
DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.BRIEF);
detector.detect(img, keypoints);
extractor.compute(img, keypoints, descriptors);
return descriptors;
}
private Mat getQueryDescriptors() {
return getTestDescriptors(getQueryImg());
}
private Mat getTrainDescriptors() {
return getTestDescriptors(getTrainImg());
}
private Mat getMaskImg() {
return new Mat(4, 4, CvType.CV_8U, new Scalar(0)) {
{
put(0, 0, 1, 1, 1, 1, 1, 1, 1, 1);
}
};
}
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 testCloneBoolean() {
matcher.add(Arrays.asList(new Mat()));
DescriptorMatcher cloned = matcher.clone(true);
assertNotNull(cloned);
assertTrue(cloned.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 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 testMatchMatMatListOfDMatchMat() {
Mat train = getTrainDescriptors();
Mat query = getQueryDescriptors();
Mat mask = getMaskImg();
List<DMatch> matches = new ArrayList<DMatch>();
matcher.match(query, train, matches, mask);
assertListDMatchEquals(Arrays.asList(truth[0], truth[1]), matches, EPS);
}
public void testMatchMatMatListOfDMatch() {
Mat train = getTrainDescriptors();
Mat query = getQueryDescriptors();
List<DMatch> matches = new ArrayList<DMatch>();
matcher.match(query, train, matches);
OpenCVTestRunner.Log("matches found: " + matches.size());
for (DMatch m : matches)
OpenCVTestRunner.Log(m.toString());
assertListDMatchEquals(Arrays.asList(truth), matches, EPS);
}
public void testMatchMatListOfDMatchListOfMat() {
Mat train = getTrainDescriptors();
Mat query = getQueryDescriptors();
Mat mask = getMaskImg();
List<DMatch> matches = new ArrayList<DMatch>();
matcher.add(Arrays.asList(train));
matcher.match(query, matches, Arrays.asList(mask));
assertListDMatchEquals(Arrays.asList(truth[0], truth[1]), matches, EPS);
}
public void testMatchMatListOfDMatch() {
Mat train = getTrainDescriptors();
Mat query = getQueryDescriptors();
List<DMatch> matches = new ArrayList<DMatch>();
matcher.add(Arrays.asList(train));
matcher.match(query, matches);
assertListDMatchEquals(Arrays.asList(truth), matches, EPS);
}
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));
}
}

4
modules/java/gen_java.py
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@ -100,6 +100,10 @@ const_private_list = (
"CV_INPAINT_.+", "CV_INPAINT_.+",
"CV_RETR_.+", "CV_RETR_.+",
"CV_CHAIN_APPROX_.+", "CV_CHAIN_APPROX_.+",
"OPPONENTEXTRACTOR",
"GRIDRETECTOR",
"PYRAMIDDETECTOR",
"DYNAMICDETECTOR",
) )
# { Module : { public : [[name, val],...], private : [[]...] } } # { Module : { public : [[name, val],...], private : [[]...] } }

8
modules/java/src/cpp/features2d_manual.hpp
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@ -245,10 +245,10 @@ public:
OPPONENTEXTRACTOR = 1000, OPPONENTEXTRACTOR = 1000,
OPPENENT_SIFT = OPPONENTEXTRACTOR + SIFT, OPPONENT_SIFT = OPPONENTEXTRACTOR + SIFT,
OPPENENT_SURF = OPPONENTEXTRACTOR + SURF, OPPONENT_SURF = OPPONENTEXTRACTOR + SURF,
OPPENENT_ORB = OPPONENTEXTRACTOR + ORB, OPPONENT_ORB = OPPONENTEXTRACTOR + ORB,
OPPENENT_BRIEF = OPPONENTEXTRACTOR + BRIEF OPPONENT_BRIEF = OPPONENTEXTRACTOR + BRIEF
}; };
//supported SIFT, SURF, ORB, BRIEF, Opponent(XXXX) //supported SIFT, SURF, ORB, BRIEF, Opponent(XXXX)