Java API: added new tests for SURF and STAR feature detectors
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package org.opencv.test.features2d;
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import org.opencv.features2d.MSER;
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import org.opencv.test.OpenCVTestCase;
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public class MSERTest extends OpenCVTestCase {
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private MSER mser;
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@Override
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protected void setUp() throws Exception {
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super.setUp();
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mser = null;
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}
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public void test_1() {
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super.test_1("FEATURES2D.MSER");
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}
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public void testMSER() {
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mser = new MSER();
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assertTrue(null != mser);
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}
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public void testMSERIntIntIntDoubleDoubleIntDoubleDoubleInt() {
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mser = new MSER(5, 60, 14400, .25f, .2f, 200, 1.01, .003, 5);
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assertTrue(null != mser);
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}
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}
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package org.opencv.test.features2d;
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import org.opencv.core.Core;
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import org.opencv.core.CvType;
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import org.opencv.core.Mat;
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import org.opencv.core.Point;
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import org.opencv.core.Scalar;
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import org.opencv.features2d.FeatureDetector;
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import org.opencv.features2d.KeyPoint;
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import org.opencv.test.OpenCVTestCase;
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import org.opencv.test.OpenCVTestRunner;
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import java.util.ArrayList;
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import java.util.List;
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public class STARFeatureDetectorTest extends OpenCVTestCase {
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FeatureDetector detector;
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KeyPoint[] truth;
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int matSize;
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protected void setUp() throws Exception {
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detector = FeatureDetector.create(FeatureDetector.STAR);
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matSize = 200;
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truth = new KeyPoint[] {
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new KeyPoint(95, 80, 22, -1, 31.595734f, 0, -1),
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new KeyPoint(105, 80, 22, -1, 31.595734f, 0, -1),
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new KeyPoint(80, 95, 22, -1, 31.595734f, 0, -1),
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new KeyPoint(120, 95, 22, -1, 31.595734f, 0, -1),
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new KeyPoint(100, 100, 8, -1, -219.90825f, 0, -1),
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new KeyPoint(80, 105, 22, -1, 31.595734f, 0, -1),
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new KeyPoint(120, 105, 22, -1, 31.595734f, 0, -1),
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new KeyPoint(95, 120, 22, -1, 31.595734f, 0, -1),
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new KeyPoint(105, 120, 22, -1, 31.595734f, 0, -1) };
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super.setUp();
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}
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private Mat getTestImg() {
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Scalar color = new Scalar(0);
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int center = matSize / 2;
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int radius = 6;
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int offset = 40;
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Mat img = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
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Core.circle(img, new Point(center - offset, center), radius, color, -1);
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Core.circle(img, new Point(center + offset, center), radius, color, -1);
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Core.circle(img, new Point(center, center - offset), radius, color, -1);
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Core.circle(img, new Point(center, center + offset), radius, color, -1);
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Core.circle(img, new Point(center, center), radius, color, -1);
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return img;
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}
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private Mat getMaskImg() {
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Mat mask = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
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Mat right = mask.submat(0, matSize, matSize / 2, matSize);
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right.setTo(new Scalar(0));
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return mask;
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}
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public void testCreate() {
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assertNotNull(detector);
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}
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public void testDetectMatListOfKeyPointMat() {
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Mat img = getTestImg();
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Mat mask = getMaskImg();
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List<KeyPoint> keypoints = new ArrayList<KeyPoint>();
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detector.detect(img, keypoints, mask);
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KeyPoint[] _truth = new KeyPoint[] { truth[0], truth[2], truth[5], truth[7] };
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assertEquals(_truth.length, keypoints.size());
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for (int i = 0; i < _truth.length; i++)
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assertKeyPointEqual(_truth[i], keypoints.get(i), EPS);
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}
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public void testDetectMatListOfKeyPoint() {
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Mat img = getTestImg();
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List<KeyPoint> keypoints = new ArrayList<KeyPoint>();
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detector.detect(img, keypoints);
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assertEquals(truth.length, keypoints.size());
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for (int i = 0; i < truth.length; i++)
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assertKeyPointEqual(truth[i], keypoints.get(i), EPS);
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}
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public void testEmpty() {
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assertFalse(detector.empty());
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}
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public void testRead() {
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Mat img = getTestImg();
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List<KeyPoint> keypoints1 = new ArrayList<KeyPoint>();
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detector.detect(img, keypoints1);
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String filename = OpenCVTestRunner.getTempFileName("yml");
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writeFile(filename, "%YAML:1.0\nmaxSize: 45\nresponseThreshold: 150\nlineThresholdProjected: 10\nlineThresholdBinarized: 8\nsuppressNonmaxSize: 5\n");
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detector.read(filename);
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List<KeyPoint> keypoints2 = new ArrayList<KeyPoint>();
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detector.detect(img, keypoints2);
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assertTrue(keypoints2.size() <= keypoints1.size());
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}
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public void testWrite() {
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String filename = OpenCVTestRunner.getTempFileName("xml");
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detector.write(filename);
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String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n<maxSize>45</maxSize>\n<responseThreshold>30</responseThreshold>\n<lineThresholdProjected>10</lineThresholdProjected>\n<lineThresholdBinarized>8</lineThresholdBinarized>\n<suppressNonmaxSize>5</suppressNonmaxSize>\n</opencv_storage>\n";
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assertEquals(truth, readFile(filename));
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}
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public void testWriteYml() {
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String filename = OpenCVTestRunner.getTempFileName("yml");
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detector.write(filename);
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String truth = "%YAML:1.0\nmaxSize: 45\nresponseThreshold: 30\nlineThresholdProjected: 10\nlineThresholdBinarized: 8\nsuppressNonmaxSize: 5\n";
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assertEquals(truth, readFile(filename));
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}
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}
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package org.opencv.test.features2d;
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import org.opencv.core.Core;
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import org.opencv.core.CvType;
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import org.opencv.core.Mat;
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import org.opencv.core.Point;
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import org.opencv.core.Scalar;
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import org.opencv.features2d.FeatureDetector;
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import org.opencv.features2d.KeyPoint;
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import org.opencv.test.OpenCVTestCase;
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import org.opencv.test.OpenCVTestRunner;
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import java.util.ArrayList;
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import java.util.Collections;
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import java.util.Comparator;
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import java.util.List;
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public class SURFFeatureDetectorTest extends OpenCVTestCase {
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FeatureDetector detector;
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KeyPoint[] truth;
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int matSize;
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@Override
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protected void setUp() throws Exception {
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detector = FeatureDetector.create(FeatureDetector.SURF);
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matSize = 100;
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truth = new KeyPoint[] { new KeyPoint(55.775577545166016f, 44.224422454833984f, 16, 9.754629f, 8617.863f, 1, -1),
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new KeyPoint(44.224422454833984f, 44.224422454833984f, 16, 99.75463f, 8617.863f, 1, -1),
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new KeyPoint(44.224422454833984f, 55.775577545166016f, 16, 189.7546f, 8617.863f, 1, -1),
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new KeyPoint(55.775577545166016f, 55.775577545166016f, 16, 279.75464f, 8617.863f, 1, -1) };
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super.setUp();
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}
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private Mat getTestImg() {
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Mat cross = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
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Core.line(cross, new Point(20, matSize / 2), new Point(matSize - 21, matSize / 2), new Scalar(100), 2);
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Core.line(cross, new Point(matSize / 2, 20), new Point(matSize / 2, matSize - 21), new Scalar(100), 2);
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return cross;
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}
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private void order(List<KeyPoint> points) {
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Collections.sort(points, new Comparator<KeyPoint>() {
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public int compare(KeyPoint p1, KeyPoint p2) {
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if (p1.angle < p2.angle)
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return -1;
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if (p1.angle > p2.angle)
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return 1;
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return 0;
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}
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});
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}
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private Mat getMaskImg() {
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Mat mask = new Mat(matSize, matSize, CvType.CV_8U, new Scalar(255));
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Mat right = mask.submat(0, matSize, matSize / 2, matSize);
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right.setTo(new Scalar(0));
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return mask;
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}
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public void testCreate() {
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assertNotNull(detector);
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}
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public void testDetectMatListOfKeyPointMat() {
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String filename = OpenCVTestRunner.getTempFileName("yml");
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writeFile(filename, "%YAML:1.0\nhessianThreshold: 8000.\noctaves: 3\noctaveLayers: 4\nupright: 0\n");
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detector.read(filename);
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Mat img = getTestImg();
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Mat mask = getMaskImg();
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List<KeyPoint> keypoints = new ArrayList<KeyPoint>();
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detector.detect(img, keypoints, mask);
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KeyPoint[] _truth = new KeyPoint[] { truth[1], truth[2] };
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assertEquals(_truth.length, keypoints.size());
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order(keypoints);
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for (int i = 0; i < _truth.length; i++)
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assertKeyPointEqual(_truth[i], keypoints.get(i), EPS);
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}
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public void testDetectMatListOfKeyPoint() {
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String filename = OpenCVTestRunner.getTempFileName("yml");
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writeFile(filename, "%YAML:1.0\nhessianThreshold: 8000.\noctaves: 3\noctaveLayers: 4\nupright: 0\n");
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detector.read(filename);
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List<KeyPoint> keypoints = new ArrayList<KeyPoint>();
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Mat cross = getTestImg();
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detector.detect(cross, keypoints);
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assertEquals(truth.length, keypoints.size());
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order(keypoints);
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for (int i = 0; i < truth.length; i++)
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assertKeyPointEqual(truth[i], keypoints.get(i), EPS);
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}
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public void testEmpty() {
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assertFalse(detector.empty());
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}
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public void testRead() {
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Mat cross = getTestImg();
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List<KeyPoint> keypoints1 = new ArrayList<KeyPoint>();
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detector.detect(cross, keypoints1);
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String filename = OpenCVTestRunner.getTempFileName("yml");
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writeFile(filename, "%YAML:1.0\nhessianThreshold: 8000.\noctaves: 3\noctaveLayers: 4\nupright: 0\n");
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detector.read(filename);
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List<KeyPoint> keypoints2 = new ArrayList<KeyPoint>();
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detector.detect(cross, keypoints2);
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assertTrue(keypoints2.size() <= keypoints1.size());
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}
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public void testWrite() {
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String filename = OpenCVTestRunner.getTempFileName("xml");
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detector.write(filename);
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String truth = "<?xml version=\"1.0\"?>\n<opencv_storage>\n<hessianThreshold>400.</hessianThreshold>\n<octaves>3</octaves>\n<octaveLayers>4</octaveLayers>\n<upright>0</upright>\n</opencv_storage>\n";
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assertEquals(truth, readFile(filename));
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}
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public void testWriteYml() {
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String filename = OpenCVTestRunner.getTempFileName("yml");
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detector.write(filename);
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String truth = "%YAML:1.0\nhessianThreshold: 400.\noctaves: 3\noctaveLayers: 4\nupright: 0\n";
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assertEquals(truth, readFile(filename));
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}
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}
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package org.opencv.test.features2d;
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import java.util.LinkedList;
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import java.util.List;
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import org.opencv.core.Core;
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import org.opencv.core.CvType;
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import org.opencv.core.Mat;
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import org.opencv.core.Point;
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import org.opencv.core.Scalar;
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import org.opencv.features2d.KeyPoint;
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import org.opencv.features2d.StarDetector;
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import org.opencv.test.OpenCVTestCase;
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public class StarDetectorTest extends OpenCVTestCase {
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public void test_1() {
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super.test_1("FEATURES2D.StarDetector");
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}
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private Mat getStarImg() {
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Scalar color = new Scalar(0);
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int center = 100;
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int radius = 5;
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int offset = 40;
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Mat img = new Mat(200, 200, CvType.CV_8U, new Scalar(255));
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Core.circle(img, new Point(center - offset, center), radius, color, -1);
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Core.circle(img, new Point(center + offset, center), radius, color, -1);
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Core.circle(img, new Point(center, center - offset), radius, color, -1);
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Core.circle(img, new Point(center, center + offset), radius, color, -1);
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Core.circle(img, new Point(center, center), radius, color, -1);
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return img;
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}
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public void testDetect() {
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Mat img = getStarImg();
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List<KeyPoint> keypoints = new LinkedList<KeyPoint>();
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StarDetector star = new StarDetector();
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star.detect(img, keypoints);
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KeyPoint truth = new KeyPoint(100, 100, 8, -1, -223.40334f, 0, -1);
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assertEquals(1, keypoints.size());
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assertKeyPointEqual(truth, keypoints.get(0), EPS);
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}
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public void testStarDetector() {
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StarDetector star = new StarDetector();
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assertNotNull(star);
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}
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public void testStarDetectorIntIntIntIntInt() {
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StarDetector star = new StarDetector(45, 30, 10, 8, 5);
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assertNotNull(star);
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}
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}
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@ -14,6 +14,7 @@ class_ignore_list = (
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#features2d
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"KeyPoint",
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"MSER",
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"StarDetector",
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)
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const_ignore_list = (
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