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
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html
#include "test_precomp.hpp"
#include "test_invariance_utils.hpp"
using namespace std;
using namespace cv;
using std::tr1::make_tuple;
using std::tr1::get;
using namespace testing;
#define SHOW_DEBUG_LOG 1
typedef std::tr1::tuple<std::string, Ptr<FeatureDetector>, float, float> String_FeatureDetector_Float_Float_t;
const static std::string IMAGE_TSUKUBA = "features2d/tsukuba.png";
const static std::string IMAGE_BIKES = "detectors_descriptors_evaluation/images_datasets/bikes/img1.png";
#define Value(...) Values(String_FeatureDetector_Float_Float_t(__VA_ARGS__))
static
void matchKeyPoints(const vector<KeyPoint>& keypoints0, const Mat& H,
const vector<KeyPoint>& keypoints1,
vector<DMatch>& matches)
{
vector<Point2f> points0;
KeyPoint::convert(keypoints0, points0);
Mat points0t;
if(H.empty())
points0t = Mat(points0);
else
perspectiveTransform(Mat(points0), points0t, H);
matches.clear();
vector<uchar> usedMask(keypoints1.size(), 0);
for(int i0 = 0; i0 < static_cast<int>(keypoints0.size()); i0++)
{
int nearestPointIndex = -1;
float maxIntersectRatio = 0.f;
const float r0 = 0.5f * keypoints0[i0].size;
for(size_t i1 = 0; i1 < keypoints1.size(); i1++)
{
if(nearestPointIndex >= 0 && usedMask[i1])
continue;
float r1 = 0.5f * keypoints1[i1].size;
float intersectRatio = calcIntersectRatio(points0t.at<Point2f>(i0), r0,
keypoints1[i1].pt, r1);
if(intersectRatio > maxIntersectRatio)
{
maxIntersectRatio = intersectRatio;
nearestPointIndex = static_cast<int>(i1);
}
}
matches.push_back(DMatch(i0, nearestPointIndex, maxIntersectRatio));
if(nearestPointIndex >= 0)
usedMask[nearestPointIndex] = 1;
}
}
class DetectorInvariance : public TestWithParam<String_FeatureDetector_Float_Float_t>
{
protected:
virtual void SetUp() {
// Read test data
const std::string filename = cvtest::TS::ptr()->get_data_path() + get<0>(GetParam());
image0 = imread(filename);
ASSERT_FALSE(image0.empty()) << "couldn't read input image";
featureDetector = get<1>(GetParam());
minKeyPointMatchesRatio = get<2>(GetParam());
minInliersRatio = get<3>(GetParam());
}
Ptr<FeatureDetector> featureDetector;
float minKeyPointMatchesRatio;
float minInliersRatio;
Mat image0;
};
typedef DetectorInvariance DetectorScaleInvariance;
typedef DetectorInvariance DetectorRotationInvariance;
TEST_P(DetectorRotationInvariance, rotation)
{
Mat image1, mask1;
const int borderSize = 16;
Mat mask0(image0.size(), CV_8UC1, Scalar(0));
mask0(Rect(borderSize, borderSize, mask0.cols - 2*borderSize, mask0.rows - 2*borderSize)).setTo(Scalar(255));
vector<KeyPoint> keypoints0;
featureDetector->detect(image0, keypoints0, mask0);
EXPECT_GE(keypoints0.size(), 15u);
const int maxAngle = 360, angleStep = 15;
for(int angle = 0; angle < maxAngle; angle += angleStep)
{
Mat H = rotateImage(image0, mask0, static_cast<float>(angle), image1, mask1);
vector<KeyPoint> keypoints1;
featureDetector->detect(image1, keypoints1, mask1);
vector<DMatch> matches;
matchKeyPoints(keypoints0, H, keypoints1, matches);
int angleInliersCount = 0;
const float minIntersectRatio = 0.5f;
int keyPointMatchesCount = 0;
for(size_t m = 0; m < matches.size(); m++)
{
if(matches[m].distance < minIntersectRatio)
continue;
keyPointMatchesCount++;
// Check does this inlier have consistent angles
const float maxAngleDiff = 15.f; // grad
float angle0 = keypoints0[matches[m].queryIdx].angle;
float angle1 = keypoints1[matches[m].trainIdx].angle;
ASSERT_FALSE(angle0 == -1 || angle1 == -1) << "Given FeatureDetector is not rotation invariant, it can not be tested here.";
ASSERT_GE(angle0, 0.f);
ASSERT_LT(angle0, 360.f);
ASSERT_GE(angle1, 0.f);
ASSERT_LT(angle1, 360.f);
float rotAngle0 = angle0 + angle;
if(rotAngle0 >= 360.f)
rotAngle0 -= 360.f;
float angleDiff = std::max(rotAngle0, angle1) - std::min(rotAngle0, angle1);
angleDiff = std::min(angleDiff, static_cast<float>(360.f - angleDiff));
ASSERT_GE(angleDiff, 0.f);
bool isAngleCorrect = angleDiff < maxAngleDiff;
if(isAngleCorrect)
angleInliersCount++;
}
float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints0.size();
EXPECT_GE(keyPointMatchesRatio, minKeyPointMatchesRatio) << "angle: " << angle;
if(keyPointMatchesCount)
{
float angleInliersRatio = static_cast<float>(angleInliersCount) / keyPointMatchesCount;
EXPECT_GE(angleInliersRatio, minInliersRatio) << "angle: " << angle;
}
#if SHOW_DEBUG_LOG
std::cout
<< "angle = " << angle
<< ", keypoints = " << keypoints1.size()
<< ", keyPointMatchesRatio = " << keyPointMatchesRatio
<< ", angleInliersRatio = " << (keyPointMatchesCount ? (static_cast<float>(angleInliersCount) / keyPointMatchesCount) : 0)
<< std::endl;
#endif
}
}
TEST_P(DetectorScaleInvariance, scale)
{
vector<KeyPoint> keypoints0;
featureDetector->detect(image0, keypoints0);
EXPECT_GE(keypoints0.size(), 15u);
for(int scaleIdx = 1; scaleIdx <= 3; scaleIdx++)
{
float scale = 1.f + scaleIdx * 0.5f;
Mat image1;
resize(image0, image1, Size(), 1./scale, 1./scale, INTER_LINEAR_EXACT);
vector<KeyPoint> keypoints1, osiKeypoints1; // osi - original size image
featureDetector->detect(image1, keypoints1);
EXPECT_GE(keypoints1.size(), 15u);
EXPECT_LE(keypoints1.size(), keypoints0.size()) << "Strange behavior of the detector. "
"It gives more points count in an image of the smaller size.";
scaleKeyPoints(keypoints1, osiKeypoints1, scale);
vector<DMatch> matches;
// image1 is query image (it's reduced image0)
// image0 is train image
matchKeyPoints(osiKeypoints1, Mat(), keypoints0, matches);
const float minIntersectRatio = 0.5f;
int keyPointMatchesCount = 0;
int scaleInliersCount = 0;
for(size_t m = 0; m < matches.size(); m++)
{
if(matches[m].distance < minIntersectRatio)
continue;
keyPointMatchesCount++;
// Check does this inlier have consistent sizes
const float maxSizeDiff = 0.8f;//0.9f; // grad
float size0 = keypoints0[matches[m].trainIdx].size;
float size1 = osiKeypoints1[matches[m].queryIdx].size;
ASSERT_GT(size0, 0);
ASSERT_GT(size1, 0);
if(std::min(size0, size1) > maxSizeDiff * std::max(size0, size1))
scaleInliersCount++;
}
float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints1.size();
EXPECT_GE(keyPointMatchesRatio, minKeyPointMatchesRatio);
if(keyPointMatchesCount)
{
float scaleInliersRatio = static_cast<float>(scaleInliersCount) / keyPointMatchesCount;
EXPECT_GE(scaleInliersRatio, minInliersRatio);
}
#if SHOW_DEBUG_LOG
std::cout
<< "scale = " << scale
<< ", keyPointMatchesRatio = " << keyPointMatchesRatio
<< ", scaleInliersRatio = " << (keyPointMatchesCount ? static_cast<float>(scaleInliersCount) / keyPointMatchesCount : 0)
<< std::endl;
#endif
}
}
/*
* Detector's rotation invariance check
*/
INSTANTIATE_TEST_CASE_P(BRISK, DetectorRotationInvariance,
Value(IMAGE_TSUKUBA, BRISK::create(), 0.45f, 0.76f));
INSTANTIATE_TEST_CASE_P(ORB, DetectorRotationInvariance,
Value(IMAGE_TSUKUBA, ORB::create(), 0.5f, 0.76f));
INSTANTIATE_TEST_CASE_P(AKAZE, DetectorRotationInvariance,
Value(IMAGE_TSUKUBA, AKAZE::create(), 0.5f, 0.71f));
INSTANTIATE_TEST_CASE_P(AKAZE_DESCRIPTOR_KAZE, DetectorRotationInvariance,
Value(IMAGE_TSUKUBA, AKAZE::create(AKAZE::DESCRIPTOR_KAZE), 0.5f, 0.71f));
/*
* Detector's scale invariance check
*/
INSTANTIATE_TEST_CASE_P(BRISK, DetectorScaleInvariance,
Value(IMAGE_BIKES, BRISK::create(), 0.08f, 0.49f));
INSTANTIATE_TEST_CASE_P(ORB, DetectorScaleInvariance,
Value(IMAGE_BIKES, ORB::create(), 0.08f, 0.49f));
INSTANTIATE_TEST_CASE_P(KAZE, DetectorScaleInvariance,
Value(IMAGE_BIKES, KAZE::create(), 0.08f, 0.49f));
INSTANTIATE_TEST_CASE_P(AKAZE, DetectorScaleInvariance,
Value(IMAGE_BIKES, AKAZE::create(), 0.08f, 0.49f));
INSTANTIATE_TEST_CASE_P(AKAZE_DESCRIPTOR_KAZE, DetectorScaleInvariance,
Value(IMAGE_BIKES, AKAZE::create(AKAZE::DESCRIPTOR_KAZE), 0.08f, 0.49f));