Merge pull request #20367 from augustinmanecy:features2d-rw
**Merge with contrib**: https://github.com/opencv/opencv_contrib/pull/3003 ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or other license that is incompatible with OpenCV - [x] The PR is proposed to proper branch - [ ] There is reference to original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [ ] The feature is well documented and sample code can be built with the project CMake
This commit is contained in:
augustinmanecy
@@ -0,0 +1,85 @@
|
||||
package org.opencv.test.features2d;
|
||||
|
||||
import org.opencv.test.OpenCVTestCase;
|
||||
import org.opencv.test.OpenCVTestRunner;
|
||||
import org.opencv.features2d.AgastFeatureDetector;
|
||||
|
||||
public class AGASTFeatureDetectorTest extends OpenCVTestCase {
|
||||
|
||||
AgastFeatureDetector detector;
|
||||
|
||||
@Override
|
||||
protected void setUp() throws Exception {
|
||||
super.setUp();
|
||||
detector = AgastFeatureDetector.create(); // default (10,true,3)
|
||||
}
|
||||
|
||||
public void testCreate() {
|
||||
assertNotNull(detector);
|
||||
}
|
||||
|
||||
public void testDetectListOfMatListOfListOfKeyPoint() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testDetectListOfMatListOfListOfKeyPointListOfMat() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testDetectMatListOfKeyPoint() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testDetectMatListOfKeyPointMat() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testEmpty() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testRead() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("xml");
|
||||
writeFile(filename, "<?xml version=\"1.0\"?>\n<opencv_storage>\n<name>Feature2D.AgastFeatureDetector</name>\n<threshold>11</threshold>\n<nonmaxSuppression>0</nonmaxSuppression>\n<type>2</type>\n</opencv_storage>\n");
|
||||
|
||||
detector.read(filename);
|
||||
|
||||
assertEquals(11, detector.getThreshold());
|
||||
assertEquals(false, detector.getNonmaxSuppression());
|
||||
assertEquals(2, detector.getType());
|
||||
}
|
||||
|
||||
public void testReadYml() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
writeFile(filename, "%YAML:1.0\n---\nname: \"Feature2D.AgastFeatureDetector\"\nthreshold: 11\nnonmaxSuppression: 0\ntype: 2\n");
|
||||
|
||||
detector.read(filename);
|
||||
|
||||
assertEquals(11, detector.getThreshold());
|
||||
assertEquals(false, detector.getNonmaxSuppression());
|
||||
assertEquals(2, detector.getType());
|
||||
}
|
||||
|
||||
public void testWrite() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("xml");
|
||||
|
||||
detector.write(filename);
|
||||
|
||||
String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n<name>Feature2D.AgastFeatureDetector</name>\n<threshold>10</threshold>\n<nonmaxSuppression>1</nonmaxSuppression>\n<type>3</type>\n</opencv_storage>\n";
|
||||
String actual = readFile(filename);
|
||||
actual = actual.replaceAll("e([+-])0(\\d\\d)", "e$1$2"); // NOTE: workaround for different platforms double representation
|
||||
assertEquals(truth, actual);
|
||||
}
|
||||
|
||||
public void testWriteYml() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
|
||||
detector.write(filename);
|
||||
|
||||
String truth = "%YAML:1.0\n---\nname: \"Feature2D.AgastFeatureDetector\"\nthreshold: 10\nnonmaxSuppression: 1\ntype: 3\n";
|
||||
String actual = readFile(filename);
|
||||
actual = actual.replaceAll("e([+-])0(\\d\\d)", "e$1$2"); // NOTE: workaround for different platforms double representation
|
||||
assertEquals(truth, actual);
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,67 @@
|
||||
package org.opencv.test.features2d;
|
||||
|
||||
import org.opencv.test.OpenCVTestCase;
|
||||
import org.opencv.test.OpenCVTestRunner;
|
||||
import org.opencv.features2d.AKAZE;
|
||||
|
||||
public class AKAZEDescriptorExtractorTest extends OpenCVTestCase {
|
||||
|
||||
AKAZE extractor;
|
||||
|
||||
@Override
|
||||
protected void setUp() throws Exception {
|
||||
super.setUp();
|
||||
extractor = AKAZE.create(); // default (5,0,3,0.001f,4,4,1)
|
||||
}
|
||||
|
||||
public void testCreate() {
|
||||
assertNotNull(extractor);
|
||||
}
|
||||
|
||||
public void testDetectListOfMatListOfListOfKeyPoint() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testDetectListOfMatListOfListOfKeyPointListOfMat() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testDetectMatListOfKeyPoint() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testDetectMatListOfKeyPointMat() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testEmpty() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testReadYml() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
writeFile(filename, "%YAML:1.0\n---\nformat: 3\nname: \"Feature2D.AKAZE\"\ndescriptor: 4\ndescriptor_channels: 2\ndescriptor_size: 32\nthreshold: 0.125\noctaves: 3\nsublevels: 5\ndiffusivity: 2\n");
|
||||
|
||||
extractor.read(filename);
|
||||
|
||||
assertEquals(4, extractor.getDescriptorType());
|
||||
assertEquals(2, extractor.getDescriptorChannels());
|
||||
assertEquals(32, extractor.getDescriptorSize());
|
||||
assertEquals(0.125, extractor.getThreshold());
|
||||
assertEquals(3, extractor.getNOctaves());
|
||||
assertEquals(5, extractor.getNOctaveLayers());
|
||||
assertEquals(2, extractor.getDiffusivity());
|
||||
}
|
||||
|
||||
public void testWriteYml() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
|
||||
extractor.write(filename);
|
||||
|
||||
String truth = "%YAML:1.0\n---\nformat: 3\nname: \"Feature2D.AKAZE\"\ndescriptor: 5\ndescriptor_channels: 3\ndescriptor_size: 0\nthreshold: 1.0000000474974513e-03\noctaves: 4\nsublevels: 4\ndiffusivity: 1\n";
|
||||
String actual = readFile(filename);
|
||||
actual = actual.replaceAll("e([+-])0(\\d\\d)", "e$1$2"); // NOTE: workaround for different platforms double representation
|
||||
assertEquals(truth, actual);
|
||||
}
|
||||
|
||||
}
|
||||
@@ -86,7 +86,7 @@ public class BRIEFDescriptorExtractorTest extends OpenCVTestCase {
|
||||
|
||||
extractor.write(filename);
|
||||
|
||||
String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n<descriptorSize>32</descriptorSize>\n</opencv_storage>\n";
|
||||
String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n<name>Feature2D.BRIEF</name>\n<descriptorSize>32</descriptorSize>\n<use_orientation>0</use_orientation>\n</opencv_storage>\n";
|
||||
assertEquals(truth, readFile(filename));
|
||||
}
|
||||
|
||||
@@ -95,7 +95,7 @@ public class BRIEFDescriptorExtractorTest extends OpenCVTestCase {
|
||||
|
||||
extractor.write(filename);
|
||||
|
||||
String truth = "%YAML:1.0\n---\ndescriptorSize: 32\n";
|
||||
String truth = "%YAML:1.0\n---\nname: \"Feature2D.BRIEF\"\ndescriptorSize: 32\nuse_orientation: 0\n";
|
||||
assertEquals(truth, readFile(filename));
|
||||
}
|
||||
|
||||
|
||||
@@ -0,0 +1,63 @@
|
||||
package org.opencv.test.features2d;
|
||||
|
||||
import org.opencv.test.OpenCVTestCase;
|
||||
import org.opencv.test.OpenCVTestRunner;
|
||||
import org.opencv.features2d.BRISK;
|
||||
|
||||
public class BRISKDescriptorExtractorTest extends OpenCVTestCase {
|
||||
|
||||
BRISK extractor;
|
||||
|
||||
@Override
|
||||
protected void setUp() throws Exception {
|
||||
super.setUp();
|
||||
extractor = BRISK.create(); // default (30,3,1)
|
||||
}
|
||||
|
||||
public void testCreate() {
|
||||
assertNotNull(extractor);
|
||||
}
|
||||
|
||||
public void testDetectListOfMatListOfListOfKeyPoint() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testDetectListOfMatListOfListOfKeyPointListOfMat() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testDetectMatListOfKeyPoint() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testDetectMatListOfKeyPointMat() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testEmpty() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testReadYml() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
writeFile(filename, "%YAML:1.0\n---\nname: \"Feature2D.BRISK\"\nthreshold: 31\noctaves: 4\npatternScale: 1.1\n");
|
||||
|
||||
extractor.read(filename);
|
||||
|
||||
assertEquals(31, extractor.getThreshold());
|
||||
assertEquals(4, extractor.getOctaves());
|
||||
assertEquals(1.1f, extractor.getPatternScale());
|
||||
}
|
||||
|
||||
public void testWriteYml() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
|
||||
extractor.write(filename);
|
||||
|
||||
String truth = "%YAML:1.0\n---\nname: \"Feature2D.BRISK\"\nthreshold: 30\noctaves: 3\npatternScale: 1.\n";
|
||||
String actual = readFile(filename);
|
||||
actual = actual.replaceAll("e([+-])0(\\d\\d)", "e$1$2"); // NOTE: workaround for different platforms double representation
|
||||
assertEquals(truth, actual);
|
||||
}
|
||||
|
||||
}
|
||||
@@ -8,7 +8,6 @@ import org.opencv.core.Mat;
|
||||
import org.opencv.core.MatOfKeyPoint;
|
||||
import org.opencv.core.Point;
|
||||
import org.opencv.core.Scalar;
|
||||
import org.opencv.features2d.Feature2D;
|
||||
import org.opencv.features2d.FastFeatureDetector;
|
||||
import org.opencv.core.KeyPoint;
|
||||
import org.opencv.test.OpenCVTestCase;
|
||||
@@ -17,7 +16,7 @@ import org.opencv.imgproc.Imgproc;
|
||||
|
||||
public class FASTFeatureDetectorTest extends OpenCVTestCase {
|
||||
|
||||
Feature2D detector;
|
||||
FastFeatureDetector detector;
|
||||
KeyPoint[] truth;
|
||||
|
||||
private Mat getMaskImg() {
|
||||
@@ -78,20 +77,24 @@ public class FASTFeatureDetectorTest extends OpenCVTestCase {
|
||||
|
||||
public void testEmpty() {
|
||||
// assertFalse(detector.empty());
|
||||
fail("Not yet implemented"); //FAST does not override empty() method
|
||||
fail("Not yet implemented"); // FAST does not override empty() method
|
||||
}
|
||||
|
||||
public void testRead() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
String filename = OpenCVTestRunner.getTempFileName("xml");
|
||||
|
||||
writeFile(filename, "%YAML:1.0\n---\nthreshold: 130\nnonmaxSuppression: 1\n");
|
||||
writeFile(filename, "<?xml version=\"1.0\"?>\n<opencv_storage>\n<name>Feature2D.FastFeatureDetector</name>\n<threshold>10</threshold>\n<nonmaxSuppression>1</nonmaxSuppression>\n<type>2</type>\n</opencv_storage>\n");
|
||||
detector.read(filename);
|
||||
|
||||
assertEquals(10, detector.getThreshold());
|
||||
assertEquals(true, detector.getNonmaxSuppression());
|
||||
assertEquals(2, detector.getType());
|
||||
|
||||
MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
|
||||
|
||||
detector.detect(grayChess, keypoints1);
|
||||
|
||||
writeFile(filename, "%YAML:1.0\n---\nthreshold: 150\nnonmaxSuppression: 1\n");
|
||||
writeFile(filename, "<?xml version=\"1.0\"?>\n<opencv_storage>\n<name>Feature2D.FastFeatureDetector</name>\n<threshold>150</threshold>\n<nonmaxSuppression>1</nonmaxSuppression>\n<type>2</type>\n</opencv_storage>\n");
|
||||
detector.read(filename);
|
||||
|
||||
MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
|
||||
@@ -104,16 +107,18 @@ public class FASTFeatureDetectorTest extends OpenCVTestCase {
|
||||
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");
|
||||
writeFile(filename, "%YAML:1.0\n---\nthreshold: 130\nnonmaxSuppression: 1\ntype: 2\n");
|
||||
detector.read(filename);
|
||||
|
||||
assertEquals(130, detector.getThreshold());
|
||||
assertEquals(true, detector.getNonmaxSuppression());
|
||||
assertEquals(2, detector.getType());
|
||||
|
||||
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");
|
||||
writeFile(filename, "%YAML:1.0\n---\nthreshold: 150\nnonmaxSuppression: 1\ntype: 2\n");
|
||||
detector.read(filename);
|
||||
|
||||
MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
|
||||
@@ -123,28 +128,14 @@ public class FASTFeatureDetectorTest extends OpenCVTestCase {
|
||||
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 truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\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\n---\nname: \"Feature2D.FAST\"\nnonmaxSuppression: 1\nthreshold: 10\ntype: 2\n";
|
||||
String truth = "%YAML:1.0\n---\n";
|
||||
String truth = "%YAML:1.0\n---\nname: \"Feature2D.FastFeatureDetector\"\nthreshold: 10\nnonmaxSuppression: 1\ntype: 2\n";
|
||||
String data = readFile(filename);
|
||||
|
||||
//Log.d("qqq", "\"" + data + "\"");
|
||||
assertEquals(truth, data);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -79,8 +79,8 @@ public class Features2dTest extends OpenCVTestCase {
|
||||
|
||||
public void testPTOD()
|
||||
{
|
||||
String detectorCfg = "%YAML:1.0\n---\nhessianThreshold: 4000.\noctaves: 3\noctaveLayers: 4\nupright: 0\n";
|
||||
String extractorCfg = "%YAML:1.0\n---\nnOctaves: 4\nnOctaveLayers: 2\nextended: 0\nupright: 0\n";
|
||||
String detectorCfg = "%YAML:1.0\n---\nhessianThreshold: 4000.\nextended: 0\nupright: 0\nOctaves: 4\nOctaveLayers: 3\n";
|
||||
String extractorCfg = "%YAML:1.0\n---\nhessianThreshold: 4000.\nextended: 0\nupright: 0\nOctaves: 4\nOctaveLayers: 3\n";
|
||||
|
||||
Feature2D detector = createClassInstance(XFEATURES2D+"SURF", DEFAULT_FACTORY, null, null);
|
||||
Feature2D extractor = createClassInstance(XFEATURES2D+"SURF", DEFAULT_FACTORY, null, null);
|
||||
|
||||
@@ -1,11 +1,21 @@
|
||||
package org.opencv.test.features2d;
|
||||
|
||||
import org.opencv.test.OpenCVTestCase;
|
||||
import org.opencv.test.OpenCVTestRunner;
|
||||
import org.opencv.features2d.GFTTDetector;
|
||||
|
||||
public class GFTTFeatureDetectorTest extends OpenCVTestCase {
|
||||
|
||||
GFTTDetector detector;
|
||||
|
||||
@Override
|
||||
protected void setUp() throws Exception {
|
||||
super.setUp();
|
||||
detector = GFTTDetector.create(); // default constructor have (1000, 0.01, 1, 3, 3, false, 0.04)
|
||||
}
|
||||
|
||||
public void testCreate() {
|
||||
fail("Not yet implemented");
|
||||
assertNotNull(detector);
|
||||
}
|
||||
|
||||
public void testDetectListOfMatListOfListOfKeyPoint() {
|
||||
@@ -28,12 +38,30 @@ public class GFTTFeatureDetectorTest extends OpenCVTestCase {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testRead() {
|
||||
fail("Not yet implemented");
|
||||
public void testReadYml() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
|
||||
writeFile(filename, "%YAML:1.0\n---\nname: \"Feature2D.GFTTDetector\"\nnfeatures: 500\nqualityLevel: 2.0000000000000000e-02\nminDistance: 2.\nblockSize: 4\ngradSize: 5\nuseHarrisDetector: 1\nk: 5.0000000000000000e-02\n");
|
||||
detector.read(filename);
|
||||
|
||||
assertEquals(500, detector.getMaxFeatures());
|
||||
assertEquals(0.02, detector.getQualityLevel());
|
||||
assertEquals(2.0, detector.getMinDistance());
|
||||
assertEquals(4, detector.getBlockSize());
|
||||
assertEquals(5, detector.getGradientSize());
|
||||
assertEquals(true, detector.getHarrisDetector());
|
||||
assertEquals(0.05, detector.getK());
|
||||
}
|
||||
|
||||
public void testWrite() {
|
||||
fail("Not yet implemented");
|
||||
public void testWriteYml() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
|
||||
detector.write(filename);
|
||||
|
||||
String truth = "%YAML:1.0\n---\nname: \"Feature2D.GFTTDetector\"\nnfeatures: 1000\nqualityLevel: 1.0000000000000000e-02\nminDistance: 1.\nblockSize: 3\ngradSize: 3\nuseHarrisDetector: 0\nk: 4.0000000000000001e-02\n";
|
||||
String actual = readFile(filename);
|
||||
actual = actual.replaceAll("e([+-])0(\\d\\d)", "e$1$2"); // NOTE: workaround for different platforms double representation
|
||||
assertEquals(truth, actual);
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
@@ -0,0 +1,66 @@
|
||||
package org.opencv.test.features2d;
|
||||
|
||||
import org.opencv.test.OpenCVTestCase;
|
||||
import org.opencv.test.OpenCVTestRunner;
|
||||
import org.opencv.features2d.KAZE;
|
||||
|
||||
public class KAZEDescriptorExtractorTest extends OpenCVTestCase {
|
||||
|
||||
KAZE extractor;
|
||||
|
||||
@Override
|
||||
protected void setUp() throws Exception {
|
||||
super.setUp();
|
||||
extractor = KAZE.create(); // default (false,false,0.001f,4,4,1)
|
||||
}
|
||||
|
||||
public void testCreate() {
|
||||
assertNotNull(extractor);
|
||||
}
|
||||
|
||||
public void testDetectListOfMatListOfListOfKeyPoint() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testDetectListOfMatListOfListOfKeyPointListOfMat() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testDetectMatListOfKeyPoint() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testDetectMatListOfKeyPointMat() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testEmpty() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testReadYml() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
writeFile(filename, "%YAML:1.0\n---\nformat: 3\nname: \"Feature2D.KAZE\"\nextended: 1\nupright: 1\nthreshold: 0.125\noctaves: 3\nsublevels: 5\ndiffusivity: 2\n");
|
||||
|
||||
extractor.read(filename);
|
||||
|
||||
assertEquals(true, extractor.getExtended());
|
||||
assertEquals(true, extractor.getUpright());
|
||||
assertEquals(0.125, extractor.getThreshold());
|
||||
assertEquals(3, extractor.getNOctaves());
|
||||
assertEquals(5, extractor.getNOctaveLayers());
|
||||
assertEquals(2, extractor.getDiffusivity());
|
||||
}
|
||||
|
||||
public void testWriteYml() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
|
||||
extractor.write(filename);
|
||||
|
||||
String truth = "%YAML:1.0\n---\nformat: 3\nname: \"Feature2D.KAZE\"\nextended: 0\nupright: 0\nthreshold: 1.0000000474974513e-03\noctaves: 4\nsublevels: 4\ndiffusivity: 1\n";
|
||||
String actual = readFile(filename);
|
||||
actual = actual.replaceAll("e([+-])0(\\d\\d)", "e$1$2"); // NOTE: workaround for different platforms double representation
|
||||
assertEquals(truth, actual);
|
||||
}
|
||||
|
||||
}
|
||||
@@ -1,11 +1,21 @@
|
||||
package org.opencv.test.features2d;
|
||||
|
||||
import org.opencv.test.OpenCVTestCase;
|
||||
import org.opencv.test.OpenCVTestRunner;
|
||||
import org.opencv.features2d.MSER;
|
||||
|
||||
public class MSERFeatureDetectorTest extends OpenCVTestCase {
|
||||
|
||||
MSER detector;
|
||||
|
||||
@Override
|
||||
protected void setUp() throws Exception {
|
||||
super.setUp();
|
||||
detector = MSER.create(); // default constructor have (5, 60, 14400, .25, .2, 200, 1.01, .003, 5)
|
||||
}
|
||||
|
||||
public void testCreate() {
|
||||
fail("Not yet implemented");
|
||||
assertNotNull(detector);
|
||||
}
|
||||
|
||||
public void testDetectListOfMatListOfListOfKeyPoint() {
|
||||
@@ -28,12 +38,33 @@ public class MSERFeatureDetectorTest extends OpenCVTestCase {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testRead() {
|
||||
fail("Not yet implemented");
|
||||
public void testReadYml() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
|
||||
writeFile(filename, "%YAML:1.0\n---\nname: \"Feature2D.MSER\"\ndelta: 6\nminArea: 62\nmaxArea: 14402\nmaxVariation: .26\nminDiversity: .3\nmaxEvolution: 201\nareaThreshold: 1.02\nminMargin: 3.0e-3\nedgeBlurSize: 3\npass2Only: 1\n");
|
||||
detector.read(filename);
|
||||
|
||||
assertEquals(6, detector.getDelta());
|
||||
assertEquals(62, detector.getMinArea());
|
||||
assertEquals(14402, detector.getMaxArea());
|
||||
assertEquals(.26, detector.getMaxVariation());
|
||||
assertEquals(.3, detector.getMinDiversity());
|
||||
assertEquals(201, detector.getMaxEvolution());
|
||||
assertEquals(1.02, detector.getAreaThreshold());
|
||||
assertEquals(0.003, detector.getMinMargin());
|
||||
assertEquals(3, detector.getEdgeBlurSize());
|
||||
assertEquals(true, detector.getPass2Only());
|
||||
}
|
||||
|
||||
public void testWrite() {
|
||||
fail("Not yet implemented");
|
||||
public void testWriteYml() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
|
||||
detector.write(filename);
|
||||
|
||||
String truth = "%YAML:1.0\n---\nname: \"Feature2D.MSER\"\ndelta: 5\nminArea: 60\nmaxArea: 14400\nmaxVariation: 2.5000000000000000e-01\nminDiversity: 2.0000000000000001e-01\nmaxEvolution: 200\nareaThreshold: 1.0100000000000000e+00\nminMargin: 3.0000000000000001e-03\nedgeBlurSize: 5\npass2Only: 0\n";
|
||||
String actual = readFile(filename);
|
||||
actual = actual.replaceAll("e([+-])0(\\d\\d)", "e$1$2"); // NOTE: workaround for different platforms double representation
|
||||
assertEquals(truth, actual);
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
@@ -75,16 +75,25 @@ public class ORBDescriptorExtractorTest extends OpenCVTestCase {
|
||||
fail("Not yet implemented"); // ORB does not override empty() method
|
||||
}
|
||||
|
||||
public void testRead() {
|
||||
public void testReadYml() {
|
||||
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\n---\nscaleFactor: 1.1\nnLevels: 3\nfirstLevel: 0\nedgeThreshold: 31\npatchSize: 31\n");
|
||||
// extractor.read(filename);
|
||||
extractor = ORB.create(500, 1.1f, 3, 31, 0, 2, ORB.HARRIS_SCORE, 31, 20);
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
writeFile(filename, "%YAML:1.0\n---\nnfeatures: 500\nscaleFactor: 1.1\nnlevels: 3\nedgeThreshold: 31\nfirstLevel: 0\nwta_k: 2\nscoreType: 0\npatchSize: 31\nfastThreshold: 20\n");
|
||||
extractor.read(filename);
|
||||
|
||||
assertEquals(500, extractor.getMaxFeatures());
|
||||
assertEquals(1.1, extractor.getScaleFactor());
|
||||
assertEquals(3, extractor.getNLevels());
|
||||
assertEquals(31, extractor.getEdgeThreshold());
|
||||
assertEquals(0, extractor.getFirstLevel());
|
||||
assertEquals(2, extractor.getWTA_K());
|
||||
assertEquals(0, extractor.getScoreType());
|
||||
assertEquals(31, extractor.getPatchSize());
|
||||
assertEquals(20, extractor.getFastThreshold());
|
||||
|
||||
extractor.compute(img, keypoints, descriptors);
|
||||
|
||||
@@ -97,25 +106,13 @@ public class ORBDescriptorExtractorTest extends OpenCVTestCase {
|
||||
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 truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\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\n---\nname: \"Feature2D.ORB\"\nWTA_K: 2\nedgeThreshold: 31\nfirstLevel: 0\nnFeatures: 500\nnLevels: 8\npatchSize: 31\nscaleFactor: 1.2000000476837158e+00\nscoreType: 0\n";
|
||||
String truth = "%YAML:1.0\n---\n";
|
||||
String truth = "%YAML:1.0\n---\nname: \"Feature2D.ORB\"\nnfeatures: 500\nscaleFactor: 1.2000000476837158e+00\nnlevels: 8\nedgeThreshold: 31\nfirstLevel: 0\nwta_k: 2\nscoreType: 0\npatchSize: 31\nfastThreshold: 20\n";
|
||||
// String truth = "%YAML:1.0\n---\n";
|
||||
String actual = readFile(filename);
|
||||
actual = actual.replaceAll("e\\+000", "e+00"); // NOTE: workaround for different platforms double representation
|
||||
assertEquals(truth, actual);
|
||||
|
||||
@@ -10,11 +10,11 @@ import org.opencv.features2d.SIFT;
|
||||
import org.opencv.test.OpenCVTestCase;
|
||||
import org.opencv.test.OpenCVTestRunner;
|
||||
import org.opencv.imgproc.Imgproc;
|
||||
import org.opencv.features2d.Feature2D;
|
||||
import org.opencv.features2d.SIFT;
|
||||
|
||||
public class SIFTDescriptorExtractorTest extends OpenCVTestCase {
|
||||
|
||||
Feature2D extractor;
|
||||
SIFT extractor;
|
||||
KeyPoint keypoint;
|
||||
int matSize;
|
||||
Mat truth;
|
||||
@@ -43,7 +43,7 @@ public class SIFTDescriptorExtractorTest extends OpenCVTestCase {
|
||||
117, 112, 117, 76, 117, 54, 117, 25, 29, 22, 117, 117, 16, 11, 14,
|
||||
1, 0, 0, 22, 26, 0, 0, 0, 0, 1, 4, 15, 2, 47, 8, 0, 0, 82, 56, 31,
|
||||
17, 81, 12, 0, 0, 26, 23, 18, 23, 0, 0, 0, 0, 0, 0, 0, 0
|
||||
);
|
||||
);
|
||||
}
|
||||
};
|
||||
}
|
||||
@@ -76,23 +76,23 @@ public class SIFTDescriptorExtractorTest extends OpenCVTestCase {
|
||||
|
||||
public void testEmpty() {
|
||||
// assertFalse(extractor.empty());
|
||||
fail("Not yet implemented"); //SIFT does not override empty() method
|
||||
fail("Not yet implemented"); // SIFT does not override empty() method
|
||||
}
|
||||
|
||||
public void testRead() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
public void testReadYml() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
writeFile(filename, "%YAML:1.0\n---\nname: \"Feature2D.SIFT\"\nnfeatures: 100\nnOctaveLayers: 4\ncontrastThreshold: 5.0000000000000001e-02\nedgeThreshold: 11\nsigma: 1.7\ndescriptorType: 5\n");
|
||||
|
||||
public void testWrite() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("xml");
|
||||
extractor.read(filename);
|
||||
|
||||
extractor.write(filename);
|
||||
assertEquals(128, extractor.descriptorSize());
|
||||
|
||||
// String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n<name>Feature2D.SIFT</name>\n<contrastThreshold>4.0000000000000001e-02</contrastThreshold>\n<edgeThreshold>10.</edgeThreshold>\n<nFeatures>0</nFeatures>\n<nOctaveLayers>3</nOctaveLayers>\n<sigma>1.6000000000000001e+00</sigma>\n</opencv_storage>\n";
|
||||
String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n</opencv_storage>\n";
|
||||
String actual = readFile(filename);
|
||||
actual = actual.replaceAll("e([+-])0(\\d\\d)", "e$1$2"); // NOTE: workaround for different platforms double representation
|
||||
assertEquals(truth, actual);
|
||||
assertEquals(100, extractor.getNFeatures());
|
||||
assertEquals(4, extractor.getNOctaveLayers());
|
||||
assertEquals(0.05, extractor.getContrastThreshold());
|
||||
assertEquals(11., extractor.getEdgeThreshold());
|
||||
assertEquals(1.7, extractor.getSigma());
|
||||
assertEquals(5, extractor.descriptorType());
|
||||
}
|
||||
|
||||
public void testWriteYml() {
|
||||
@@ -100,8 +100,7 @@ public class SIFTDescriptorExtractorTest extends OpenCVTestCase {
|
||||
|
||||
extractor.write(filename);
|
||||
|
||||
// String truth = "%YAML:1.0\n---\nname: \"Feature2D.SIFT\"\ncontrastThreshold: 4.0000000000000001e-02\nedgeThreshold: 10.\nnFeatures: 0\nnOctaveLayers: 3\nsigma: 1.6000000000000001e+00\n";
|
||||
String truth = "%YAML:1.0\n---\n";
|
||||
String truth = "%YAML:1.0\n---\nname: \"Feature2D.SIFT\"\nnfeatures: 0\nnOctaveLayers: 3\ncontrastThreshold: 4.0000000000000001e-02\nedgeThreshold: 10.\nsigma: 1.6000000000000001e+00\ndescriptorType: 5\n";
|
||||
String actual = readFile(filename);
|
||||
actual = actual.replaceAll("e([+-])0(\\d\\d)", "e$1$2"); // NOTE: workaround for different platforms double representation
|
||||
assertEquals(truth, actual);
|
||||
|
||||
@@ -11,12 +11,12 @@ import org.opencv.core.KeyPoint;
|
||||
import org.opencv.test.OpenCVTestCase;
|
||||
import org.opencv.test.OpenCVTestRunner;
|
||||
import org.opencv.imgproc.Imgproc;
|
||||
import org.opencv.features2d.Feature2D;
|
||||
import org.opencv.features2d.SimpleBlobDetector;
|
||||
import org.opencv.features2d.SimpleBlobDetector_Params;
|
||||
|
||||
public class SIMPLEBLOBFeatureDetectorTest extends OpenCVTestCase {
|
||||
|
||||
Feature2D detector;
|
||||
SimpleBlobDetector detector;
|
||||
int matSize;
|
||||
KeyPoint[] truth;
|
||||
|
||||
@@ -47,8 +47,8 @@ public class SIMPLEBLOBFeatureDetectorTest extends OpenCVTestCase {
|
||||
detector = SimpleBlobDetector.create();
|
||||
matSize = 200;
|
||||
truth = new KeyPoint[] {
|
||||
new KeyPoint( 140, 100, 41.036568f, -1, 0, 0, -1),
|
||||
new KeyPoint( 60, 100, 48.538486f, -1, 0, 0, -1),
|
||||
new KeyPoint(140, 100, 41.036568f, -1, 0, 0, -1),
|
||||
new KeyPoint(60, 100, 48.538486f, -1, 0, 0, -1),
|
||||
new KeyPoint(100, 60, 36.769554f, -1, 0, 0, -1),
|
||||
new KeyPoint(100, 140, 28.635643f, -1, 0, 0, -1),
|
||||
new KeyPoint(100, 100, 20.880613f, -1, 0, 0, -1)
|
||||
@@ -91,16 +91,38 @@ public class SIMPLEBLOBFeatureDetectorTest extends OpenCVTestCase {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testRead() {
|
||||
public void testReadYml() {
|
||||
Mat img = getTestImg();
|
||||
|
||||
MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
|
||||
detector.detect(img, keypoints1);
|
||||
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
writeFile(filename, "%YAML:1.0\nthresholdStep: 10\nminThreshold: 50\nmaxThreshold: 220\nminRepeatability: 2\nfilterByArea: true\nminArea: 800\nmaxArea: 5000\n");
|
||||
writeFile(filename, "%YAML:1.0\nthresholdStep: 10.0\nminThreshold: 50\nmaxThreshold: 220\nminRepeatability: 2\nminDistBetweenBlobs: 10.\nfilterByColor: 1\nblobColor: 0\nfilterByArea: 1\nminArea: 800\nmaxArea: 6000\nfilterByCircularity: 0\nminCircularity: 0.7\nmaxCircularity: 10.\nfilterByInertia: 1\nminInertiaRatio: 0.2\nmaxInertiaRatio: 11.\nfilterByConvexity: true\nminConvexity: 0.9\nmaxConvexity: 12.\n");
|
||||
detector.read(filename);
|
||||
|
||||
SimpleBlobDetector_Params params = detector.getParams();
|
||||
assertEquals(10.0f, params.get_thresholdStep());
|
||||
assertEquals(50f, params.get_minThreshold());
|
||||
assertEquals(220f, params.get_maxThreshold());
|
||||
assertEquals(2, params.get_minRepeatability());
|
||||
assertEquals(10.0f, params.get_minDistBetweenBlobs());
|
||||
assertEquals(true, params.get_filterByColor());
|
||||
// FIXME: blobColor field has uchar type in C++ and cannot be automatically wrapped to Java as it does not support unsigned types
|
||||
//assertEquals(0, params.get_blobColor());
|
||||
assertEquals(true, params.get_filterByArea());
|
||||
assertEquals(800f, params.get_minArea());
|
||||
assertEquals(6000f, params.get_maxArea());
|
||||
assertEquals(false, params.get_filterByCircularity());
|
||||
assertEquals(0.7f, params.get_minCircularity());
|
||||
assertEquals(10.0f, params.get_maxCircularity());
|
||||
assertEquals(true, params.get_filterByInertia());
|
||||
assertEquals(0.2f, params.get_minInertiaRatio());
|
||||
assertEquals(11.0f, params.get_maxInertiaRatio());
|
||||
assertEquals(true, params.get_filterByConvexity());
|
||||
assertEquals(0.9f, params.get_minConvexity());
|
||||
assertEquals(12.0f, params.get_maxConvexity());
|
||||
|
||||
MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
|
||||
detector.detect(img, keypoints2);
|
||||
|
||||
|
||||
@@ -1,133 +0,0 @@
|
||||
package org.opencv.test.features2d;
|
||||
|
||||
import java.util.Arrays;
|
||||
|
||||
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.core.KeyPoint;
|
||||
import org.opencv.test.OpenCVTestCase;
|
||||
import org.opencv.test.OpenCVTestRunner;
|
||||
import org.opencv.imgproc.Imgproc;
|
||||
import org.opencv.features2d.Feature2D;
|
||||
|
||||
public class STARFeatureDetectorTest extends OpenCVTestCase {
|
||||
|
||||
Feature2D detector;
|
||||
int matSize;
|
||||
KeyPoint[] truth;
|
||||
|
||||
private Mat getMaskImg() {
|
||||
Mat mask = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
|
||||
Mat right = mask.submat(0, matSize, matSize / 2, matSize);
|
||||
right.setTo(new Scalar(0));
|
||||
return mask;
|
||||
}
|
||||
|
||||
private Mat getTestImg() {
|
||||
Scalar color = new Scalar(0);
|
||||
int center = matSize / 2;
|
||||
int radius = 6;
|
||||
int offset = 40;
|
||||
|
||||
Mat img = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
|
||||
Imgproc.circle(img, new Point(center - offset, center), radius, color, -1);
|
||||
Imgproc.circle(img, new Point(center + offset, center), radius, color, -1);
|
||||
Imgproc.circle(img, new Point(center, center - offset), radius, color, -1);
|
||||
Imgproc.circle(img, new Point(center, center + offset), radius, color, -1);
|
||||
Imgproc.circle(img, new Point(center, center), radius, color, -1);
|
||||
return img;
|
||||
}
|
||||
|
||||
protected void setUp() throws Exception {
|
||||
super.setUp();
|
||||
detector = createClassInstance(XFEATURES2D+"StarDetector", DEFAULT_FACTORY, null, null);
|
||||
matSize = 200;
|
||||
truth = new KeyPoint[] {
|
||||
new KeyPoint( 95, 80, 22, -1, 31.5957f, 0, -1),
|
||||
new KeyPoint(105, 80, 22, -1, 31.5957f, 0, -1),
|
||||
new KeyPoint( 80, 95, 22, -1, 31.5957f, 0, -1),
|
||||
new KeyPoint(120, 95, 22, -1, 31.5957f, 0, -1),
|
||||
new KeyPoint(100, 100, 8, -1, 30.f, 0, -1),
|
||||
new KeyPoint( 80, 105, 22, -1, 31.5957f, 0, -1),
|
||||
new KeyPoint(120, 105, 22, -1, 31.5957f, 0, -1),
|
||||
new KeyPoint( 95, 120, 22, -1, 31.5957f, 0, -1),
|
||||
new KeyPoint(105, 120, 22, -1, 31.5957f, 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);
|
||||
}
|
||||
|
||||
public void testDetectMatListOfKeyPointMat() {
|
||||
Mat img = getTestImg();
|
||||
Mat mask = getMaskImg();
|
||||
MatOfKeyPoint keypoints = new MatOfKeyPoint();
|
||||
|
||||
detector.detect(img, keypoints, mask);
|
||||
|
||||
assertListKeyPointEquals(Arrays.asList(truth[0], truth[2], truth[5], truth[7]), keypoints.toList(), EPS);
|
||||
}
|
||||
|
||||
public void testEmpty() {
|
||||
// assertFalse(detector.empty());
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testRead() {
|
||||
Mat img = getTestImg();
|
||||
|
||||
MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
|
||||
detector.detect(img, keypoints1);
|
||||
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
writeFile(filename, "%YAML:1.0\n---\nmaxSize: 45\nresponseThreshold: 150\nlineThresholdProjected: 10\nlineThresholdBinarized: 8\nsuppressNonmaxSize: 5\n");
|
||||
detector.read(filename);
|
||||
|
||||
MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
|
||||
detector.detect(img, 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.STAR</name>\n<lineThresholdBinarized>8</lineThresholdBinarized>\n<lineThresholdProjected>10</lineThresholdProjected>\n<maxSize>45</maxSize>\n<responseThreshold>30</responseThreshold>\n<suppressNonmaxSize>5</suppressNonmaxSize>\n</opencv_storage>\n";
|
||||
String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n</opencv_storage>\n";
|
||||
assertEquals(truth, readFile(filename));
|
||||
}
|
||||
|
||||
public void testWriteYml() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
|
||||
detector.write(filename);
|
||||
|
||||
// String truth = "%YAML:1.0\n---\nname: \"Feature2D.STAR\"\nlineThresholdBinarized: 8\nlineThresholdProjected: 10\nmaxSize: 45\nresponseThreshold: 30\nsuppressNonmaxSize: 5\n";
|
||||
String truth = "%YAML:1.0\n---\n";
|
||||
assertEquals(truth, readFile(filename));
|
||||
}
|
||||
|
||||
}
|
||||
@@ -1,119 +0,0 @@
|
||||
package org.opencv.test.features2d;
|
||||
|
||||
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.core.KeyPoint;
|
||||
import org.opencv.test.OpenCVTestCase;
|
||||
import org.opencv.test.OpenCVTestRunner;
|
||||
import org.opencv.imgproc.Imgproc;
|
||||
import org.opencv.features2d.Feature2D;
|
||||
|
||||
public class SURFDescriptorExtractorTest extends OpenCVTestCase {
|
||||
|
||||
Feature2D extractor;
|
||||
int matSize;
|
||||
|
||||
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();
|
||||
|
||||
Class[] cParams = {double.class, int.class, int.class, boolean.class, boolean.class};
|
||||
Object[] oValues = {100, 2, 4, true, false};
|
||||
extractor = createClassInstance(XFEATURES2D+"SURF", DEFAULT_FACTORY, cParams, oValues);
|
||||
|
||||
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, 128, CvType.CV_32FC1) {
|
||||
{
|
||||
put(0, 0,
|
||||
0, 0, 0, 0, 0, 0, 0, 0, 0.058821894, 0.058821894, -0.045962855, 0.046261817, 0.0085156476,
|
||||
0.0085754395, -0.0064509804, 0.0064509804, 0.00044069235, 0.00044069235, 0, 0, 0.00025723741,
|
||||
0.00025723741, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.00025723741, 0.00025723741, -0.00044069235,
|
||||
0.00044069235, 0, 0, 0.36278215, 0.36278215, -0.24688604, 0.26173124, 0.052068226, 0.052662034,
|
||||
-0.032815345, 0.032815345, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.0064523756,
|
||||
0.0064523756, 0.0082002236, 0.0088908644, -0.059001274, 0.059001274, 0.045789491, 0.04648013,
|
||||
0.11961588, 0.22789426, -0.01322381, 0.18291828, -0.14042182, 0.23973691, 0.073782086, 0.23769434,
|
||||
-0.027880307, 0.027880307, 0.049587864, 0.049587864, -0.33991757, 0.33991757, 0.21437603, 0.21437603,
|
||||
-0.0020763327, 0.0020763327, 0.006245892, 0.006245892, -0.04067041, 0.04067041, 0.019361559,
|
||||
0.019361559, 0, 0, -0.0035977389, 0.0035977389, 0, 0, -0.00099993451, 0.00099993451, 0.040670406,
|
||||
0.040670406, -0.019361559, 0.019361559, 0.006245892, 0.006245892, -0.0020763327, 0.0020763327,
|
||||
-0.00034532088, 0.00034532088, 0, 0, 0, 0, 0.00034532088, 0.00034532088, -0.00099993451,
|
||||
0.00099993451, 0, 0, 0, 0, 0.0035977389, 0.0035977389
|
||||
);
|
||||
}
|
||||
};
|
||||
|
||||
assertMatEqual(truth, descriptors, EPS);
|
||||
}
|
||||
|
||||
public void testCreate() {
|
||||
assertNotNull(extractor);
|
||||
}
|
||||
|
||||
public void testDescriptorSize() {
|
||||
assertEquals(128, extractor.descriptorSize());
|
||||
}
|
||||
|
||||
public void testDescriptorType() {
|
||||
assertEquals(CvType.CV_32F, extractor.descriptorType());
|
||||
}
|
||||
|
||||
public void testEmpty() {
|
||||
// assertFalse(extractor.empty());
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testRead() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
writeFile(filename, "%YAML:1.0\n---\nnOctaves: 4\nnOctaveLayers: 2\nextended: 1\nupright: 0\n");
|
||||
|
||||
extractor.read(filename);
|
||||
|
||||
assertEquals(128, extractor.descriptorSize());
|
||||
}
|
||||
|
||||
public void testWrite() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("xml");
|
||||
|
||||
extractor.write(filename);
|
||||
|
||||
// String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n<name>Feature2D.SURF</name>\n<extended>1</extended>\n<hessianThreshold>100.</hessianThreshold>\n<nOctaveLayers>2</nOctaveLayers>\n<nOctaves>4</nOctaves>\n<upright>0</upright>\n</opencv_storage>\n";
|
||||
String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n</opencv_storage>\n";
|
||||
assertEquals(truth, readFile(filename));
|
||||
}
|
||||
|
||||
public void testWriteYml() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
|
||||
extractor.write(filename);
|
||||
|
||||
// String truth = "%YAML:1.0\n---\nname: \"Feature2D.SURF\"\nextended: 1\nhessianThreshold: 100.\nnOctaveLayers: 2\nnOctaves: 4\nupright: 0\n";
|
||||
String truth = "%YAML:1.0\n---\n";
|
||||
assertEquals(truth, readFile(filename));
|
||||
}
|
||||
|
||||
}
|
||||
@@ -1,175 +0,0 @@
|
||||
package org.opencv.test.features2d;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.Arrays;
|
||||
import java.util.Collections;
|
||||
import java.util.Comparator;
|
||||
import java.util.List;
|
||||
|
||||
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.core.KeyPoint;
|
||||
import org.opencv.test.OpenCVTestCase;
|
||||
import org.opencv.test.OpenCVTestRunner;
|
||||
import org.opencv.imgproc.Imgproc;
|
||||
import org.opencv.features2d.Feature2D;
|
||||
|
||||
public class SURFFeatureDetectorTest extends OpenCVTestCase {
|
||||
|
||||
Feature2D detector;
|
||||
int matSize;
|
||||
KeyPoint[] truth;
|
||||
|
||||
private Mat getMaskImg() {
|
||||
Mat mask = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
|
||||
Mat right = mask.submat(0, matSize, matSize / 2, matSize);
|
||||
right.setTo(new Scalar(0));
|
||||
return mask;
|
||||
}
|
||||
|
||||
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;
|
||||
}
|
||||
|
||||
private void order(List<KeyPoint> points) {
|
||||
Collections.sort(points, new Comparator<KeyPoint>() {
|
||||
public int compare(KeyPoint p1, KeyPoint p2) {
|
||||
if (p1.angle < p2.angle)
|
||||
return -1;
|
||||
if (p1.angle > p2.angle)
|
||||
return 1;
|
||||
return 0;
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
@Override
|
||||
protected void setUp() throws Exception {
|
||||
super.setUp();
|
||||
detector = createClassInstance(XFEATURES2D+"SURF", DEFAULT_FACTORY, null, null);
|
||||
matSize = 100;
|
||||
truth = new KeyPoint[] {
|
||||
new KeyPoint(55.775578f, 55.775578f, 16, 80.245735f, 8617.8633f, 0, -1),
|
||||
new KeyPoint(44.224422f, 55.775578f, 16, 170.24574f, 8617.8633f, 0, -1),
|
||||
new KeyPoint(44.224422f, 44.224422f, 16, 260.24573f, 8617.8633f, 0, -1),
|
||||
new KeyPoint(55.775578f, 44.224422f, 16, 350.24573f, 8617.8633f, 0, -1)
|
||||
};
|
||||
}
|
||||
|
||||
public void testCreate() {
|
||||
assertNotNull(detector);
|
||||
}
|
||||
|
||||
public void testDetectListOfMatListOfListOfKeyPoint() {
|
||||
|
||||
setProperty(detector, "hessianThreshold", "double", 8000);
|
||||
setProperty(detector, "nOctaves", "int", 3);
|
||||
setProperty(detector, "nOctaveLayers", "int", 4);
|
||||
setProperty(detector, "upright", "boolean", false);
|
||||
|
||||
List<MatOfKeyPoint> keypoints = new ArrayList<MatOfKeyPoint>();
|
||||
Mat cross = getTestImg();
|
||||
List<Mat> crosses = new ArrayList<Mat>(3);
|
||||
crosses.add(cross);
|
||||
crosses.add(cross);
|
||||
crosses.add(cross);
|
||||
|
||||
detector.detect(crosses, keypoints);
|
||||
|
||||
assertEquals(3, keypoints.size());
|
||||
|
||||
for (MatOfKeyPoint mkp : keypoints) {
|
||||
List<KeyPoint> lkp = mkp.toList();
|
||||
order(lkp);
|
||||
assertListKeyPointEquals(Arrays.asList(truth), lkp, EPS);
|
||||
}
|
||||
}
|
||||
|
||||
public void testDetectListOfMatListOfListOfKeyPointListOfMat() {
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testDetectMatListOfKeyPoint() {
|
||||
|
||||
setProperty(detector, "hessianThreshold", "double", 8000);
|
||||
setProperty(detector, "nOctaves", "int", 3);
|
||||
setProperty(detector, "nOctaveLayers", "int", 4);
|
||||
setProperty(detector, "upright", "boolean", false);
|
||||
|
||||
MatOfKeyPoint keypoints = new MatOfKeyPoint();
|
||||
Mat cross = getTestImg();
|
||||
|
||||
detector.detect(cross, keypoints);
|
||||
|
||||
List<KeyPoint> lkp = keypoints.toList();
|
||||
order(lkp);
|
||||
assertListKeyPointEquals(Arrays.asList(truth), lkp, EPS);
|
||||
}
|
||||
|
||||
public void testDetectMatListOfKeyPointMat() {
|
||||
|
||||
setProperty(detector, "hessianThreshold", "double", 8000);
|
||||
setProperty(detector, "nOctaves", "int", 3);
|
||||
setProperty(detector, "nOctaveLayers", "int", 4);
|
||||
setProperty(detector, "upright", "boolean", false);
|
||||
|
||||
Mat img = getTestImg();
|
||||
Mat mask = getMaskImg();
|
||||
MatOfKeyPoint keypoints = new MatOfKeyPoint();
|
||||
|
||||
detector.detect(img, keypoints, mask);
|
||||
|
||||
List<KeyPoint> lkp = keypoints.toList();
|
||||
order(lkp);
|
||||
assertListKeyPointEquals(Arrays.asList(truth[1], truth[2]), lkp, EPS);
|
||||
}
|
||||
|
||||
public void testEmpty() {
|
||||
// assertFalse(detector.empty());
|
||||
fail("Not yet implemented");
|
||||
}
|
||||
|
||||
public void testRead() {
|
||||
Mat cross = getTestImg();
|
||||
|
||||
MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
|
||||
detector.detect(cross, keypoints1);
|
||||
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
writeFile(filename, "%YAML:1.0\n---\nhessianThreshold: 8000.\noctaves: 3\noctaveLayers: 4\nupright: 0\n");
|
||||
detector.read(filename);
|
||||
|
||||
MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
|
||||
detector.detect(cross, 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.SURF</name>\n<extended>0</extended>\n<hessianThreshold>100.</hessianThreshold>\n<nOctaveLayers>3</nOctaveLayers>\n<nOctaves>4</nOctaves>\n<upright>0</upright>\n</opencv_storage>\n";
|
||||
String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n</opencv_storage>\n";
|
||||
assertEquals(truth, readFile(filename));
|
||||
}
|
||||
|
||||
public void testWriteYml() {
|
||||
String filename = OpenCVTestRunner.getTempFileName("yml");
|
||||
|
||||
detector.write(filename);
|
||||
|
||||
// String truth = "%YAML:1.0\n---\nname: \"Feature2D.SURF\"\nextended: 0\nhessianThreshold: 100.\nnOctaveLayers: 3\nnOctaves: 4\nupright: 0\n";
|
||||
String truth = "%YAML:1.0\n---\n";
|
||||
assertEquals(truth, readFile(filename));
|
||||
}
|
||||
|
||||
}
|
||||
Reference in New Issue
Block a user