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package org.opencv.test.features2d;
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import java.util.Arrays;
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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.MatOfKeyPoint;
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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.core.KeyPoint;
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import org.opencv.test.OpenCVTestCase;
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import org.opencv.test.OpenCVTestRunner;
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import org.opencv.imgproc.Imgproc;
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import org.opencv.features2d.Feature2D;
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import org.opencv.features2d.SimpleBlobDetector;
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public class SIMPLEBLOBFeatureDetectorTest extends OpenCVTestCase {
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Feature2D detector;
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int matSize;
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KeyPoint[] truth;
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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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private Mat getTestImg() {
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int center = matSize / 2;
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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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Imgproc.circle(img, new Point(center - offset, center), 24, new Scalar(0), -1);
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Imgproc.circle(img, new Point(center + offset, center), 20, new Scalar(50), -1);
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Imgproc.circle(img, new Point(center, center - offset), 18, new Scalar(100), -1);
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Imgproc.circle(img, new Point(center, center + offset), 14, new Scalar(150), -1);
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Imgproc.circle(img, new Point(center, center), 10, new Scalar(200), -1);
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return img;
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}
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@Override
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protected void setUp() throws Exception {
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super.setUp();
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detector = SimpleBlobDetector.create();
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matSize = 200;
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truth = new KeyPoint[] {
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new KeyPoint( 140, 100, 41.036568f, -1, 0, 0, -1),
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new KeyPoint( 60, 100, 48.538486f, -1, 0, 0, -1),
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new KeyPoint(100, 60, 36.769554f, -1, 0, 0, -1),
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new KeyPoint(100, 140, 28.635643f, -1, 0, 0, -1),
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new KeyPoint(100, 100, 20.880613f, -1, 0, 0, -1)
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};
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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 testDetectListOfMatListOfListOfKeyPoint() {
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fail("Not yet implemented");
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}
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public void testDetectListOfMatListOfListOfKeyPointListOfMat() {
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fail("Not yet implemented");
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}
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public void testDetectMatListOfKeyPoint() {
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Mat img = getTestImg();
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MatOfKeyPoint keypoints = new MatOfKeyPoint();
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detector.detect(img, keypoints);
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assertListKeyPointEquals(Arrays.asList(truth), keypoints.toList(), EPS);
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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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MatOfKeyPoint keypoints = new MatOfKeyPoint();
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detector.detect(img, keypoints, mask);
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assertListKeyPointEquals(Arrays.asList(truth[1]), keypoints.toList(), EPS);
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}
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public void testEmpty() {
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// assertFalse(detector.empty());
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fail("Not yet implemented");
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}
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public void testRead() {
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Mat img = getTestImg();
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MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
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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\nthresholdStep: 10\nminThreshold: 50\nmaxThreshold: 220\nminRepeatability: 2\nfilterByArea: true\nminArea: 800\nmaxArea: 5000\n");
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detector.read(filename);
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MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
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detector.detect(img, keypoints2);
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assertTrue(keypoints2.total() <= keypoints1.total());
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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<format>3</format>\n<thresholdStep>10.</thresholdStep>\n<minThreshold>50.</minThreshold>\n<maxThreshold>220.</maxThreshold>\n<minRepeatability>2</minRepeatability>\n<minDistBetweenBlobs>10.</minDistBetweenBlobs>\n<filterByColor>1</filterByColor>\n<blobColor>0</blobColor>\n<filterByArea>1</filterByArea>\n<minArea>25.</minArea>\n<maxArea>5000.</maxArea>\n<filterByCircularity>0</filterByCircularity>\n<minCircularity>8.0000001192092896e-01</minCircularity>\n<maxCircularity>3.4028234663852886e+38</maxCircularity>\n<filterByInertia>1</filterByInertia>\n<minInertiaRatio>1.0000000149011612e-01</minInertiaRatio>\n<maxInertiaRatio>3.4028234663852886e+38</maxInertiaRatio>\n<filterByConvexity>1</filterByConvexity>\n<minConvexity>9.4999998807907104e-01</minConvexity>\n<maxConvexity>3.4028234663852886e+38</maxConvexity>\n</opencv_storage>\n";
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assertEquals(truth, readFile(filename));
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}
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}
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