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Open Source Computer Vision Library
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70 lines
2.5 KiB
70 lines
2.5 KiB
package org.opencv.test.features2d; |
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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.features2d.MSER; |
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public class MSERFeatureDetectorTest extends OpenCVTestCase { |
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MSER detector; |
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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 = MSER.create(); // default constructor have (5, 60, 14400, .25, .2, 200, 1.01, .003, 5) |
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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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fail("Not yet implemented"); |
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} |
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public void testDetectMatListOfKeyPointMat() { |
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fail("Not yet implemented"); |
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} |
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public void testEmpty() { |
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fail("Not yet implemented"); |
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} |
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public void testReadYml() { |
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String filename = OpenCVTestRunner.getTempFileName("yml"); |
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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"); |
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detector.read(filename); |
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assertEquals(6, detector.getDelta()); |
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assertEquals(62, detector.getMinArea()); |
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assertEquals(14402, detector.getMaxArea()); |
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assertEquals(.26, detector.getMaxVariation()); |
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assertEquals(.3, detector.getMinDiversity()); |
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assertEquals(201, detector.getMaxEvolution()); |
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assertEquals(1.02, detector.getAreaThreshold()); |
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assertEquals(0.003, detector.getMinMargin()); |
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assertEquals(3, detector.getEdgeBlurSize()); |
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assertEquals(true, detector.getPass2Only()); |
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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\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"; |
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String actual = readFile(filename); |
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actual = actual.replaceAll("e([+-])0(\\d\\d)", "e$1$2"); // NOTE: workaround for different platforms double representation |
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assertEquals(truth, actual); |
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} |
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}
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