1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
|
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));
}
}
|
