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Commit ec23d9bb authored by Maria Dimashova's avatar Maria Dimashova
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added tests on scale invariance of detectors and descriptors

parent dc68a56b
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Showing with 595 additions and 23 deletions
modules/features2d/test/test_rotation_invariance.cpp → modules/features2d/test/test_rotation_and_scale_invariance.cpp
View file @ ec23d9bb
......@@ -45,8 +45,8 @@
using namespace std;
using namespace cv;
const string FEATURES2D_DIR = "features2d";
const string IMAGE_FILENAME = "tsukuba.png";
const string IMAGE_TSUKUBA = "/features2d/tsukuba.png";
const string IMAGE_BIKES = "/detectors_descriptors_evaluation/images_datasets/bikes/img1.png";
#define SHOW_DEBUG_LOG 0
......@@ -127,14 +127,17 @@ void matchKeyPoints(const vector<KeyPoint>& keypoints0, const Mat& H,
vector<Point2f> points0;
KeyPoint::convert(keypoints0, points0);
Mat points0t;
perspectiveTransform(Mat(points0), points0t, H);
if(H.empty())
points0t = Mat(points0);
else
perspectiveTransform(Mat(points0), points0t, H);
matches.clear();
vector<uchar> usedMask(keypoints1.size(), 0);
for(size_t i0 = 0; i0 < keypoints0.size(); i0++)
{
int nearestPointIndex = -1;
float maxIntersectRatio = -1.f;
float maxIntersectRatio = 0.f;
const float r0 = 0.5f * keypoints0[i0].size;
for(size_t i1 = 0; i1 < keypoints1.size(); i1++)
{
......@@ -174,7 +177,7 @@ protected:
void run(int)
{
const string imageFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
const string imageFilename = string(ts->get_data_path()) + IMAGE_TSUKUBA;
// Read test data
Mat image0 = imread(imageFilename), image1, mask1;
......@@ -187,8 +190,8 @@ protected:
vector<KeyPoint> keypoints0;
featureDetector->detect(image0, keypoints0);
CV_Assert(keypoints0.size() > 15);
if(keypoints0.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
const int maxAngle = 360, angleStep = 15;
for(int angle = 0; angle < maxAngle; angle += angleStep)
......@@ -266,6 +269,13 @@ protected:
float minAngleInliersRatio;
};
void scaleKeyPoints(const vector<KeyPoint>& src, vector<KeyPoint>& dst, float scale)
{
dst.resize(src.size());
for(size_t i = 0; i < src.size(); i++)
dst[i] = KeyPoint(src[i].pt.x * scale, src[i].pt.y * scale, src[i].size * scale);
}
class DescriptorRotationInvarianceTest : public cvtest::BaseTest
{
public:
......@@ -288,7 +298,7 @@ protected:
void run(int)
{
const string imageFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
const string imageFilename = string(ts->get_data_path()) + IMAGE_TSUKUBA;
// Read test data
Mat image0 = imread(imageFilename), image1, mask1;
......@@ -302,9 +312,10 @@ protected:
vector<KeyPoint> keypoints0;
Mat descriptors0;
featureDetector->detect(image0, keypoints0);
if(keypoints0.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
descriptorExtractor->compute(image0, keypoints0, descriptors0);
CV_Assert(keypoints0.size() > 15);
BFMatcher bfmatcher(normType);
const int maxAngle = 360, angleStep = 15;
......@@ -375,6 +386,258 @@ protected:
};
class DetectorScaleInvarianceTest : public cvtest::BaseTest
{
public:
DetectorScaleInvarianceTest(const Ptr<FeatureDetector>& _featureDetector,
float _minKeyPointMatchesRatio,
float _minScaleInliersRatio) :
featureDetector(_featureDetector),
minKeyPointMatchesRatio(_minKeyPointMatchesRatio),
minScaleInliersRatio(_minScaleInliersRatio)
{
CV_Assert(!featureDetector.empty());
}
protected:
void run(int)
{
const string imageFilename = string(ts->get_data_path()) + IMAGE_BIKES;
// Read test data
Mat image0 = imread(imageFilename);
if(image0.empty())
{
ts->printf(cvtest::TS::LOG, "Image %s can not be read.\n", imageFilename.c_str());
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
return;
}
vector<KeyPoint> keypoints0;
featureDetector->detect(image0, keypoints0);
if(keypoints0.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
for(int scale = 2; scale <= 4; scale++)
{
Mat image1;
resize(image0, image1, Size(), 1./scale, 1./scale);
vector<KeyPoint> keypoints1, osiKeypoints1; // osi - original size image
featureDetector->detect(image1, keypoints1);
if(keypoints1.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
if(keypoints1.size() > keypoints0.size())
{
ts->printf(cvtest::TS::LOG, "Strange behavior of the detector. "
"It gives more points count in an image of the smaller size.\n"
"original size (%d, %d), keypoints count = %d\n"
"reduced size (%d, %d), keypoints count = %d\n",
image0.cols, image0.rows, keypoints0.size(),
image1.cols, image1.rows, keypoints1.size());
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return;
}
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 = 0.8;//0.9f; // grad
float size0 = keypoints0[matches[m].trainIdx].size;
float size1 = osiKeypoints1[matches[m].queryIdx].size;
CV_Assert(size0 > 0 && size1 > 0);
if(std::min(size0, size1) > maxSizeDiff * std::max(size0, size1))
scaleInliersCount++;
}
float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints1.size();
if(keyPointMatchesRatio < minKeyPointMatchesRatio)
{
ts->printf(cvtest::TS::LOG, "Incorrect keyPointMatchesRatio: curr = %f, min = %f.\n",
keyPointMatchesRatio, minKeyPointMatchesRatio);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return;
}
if(keyPointMatchesCount)
{
float scaleInliersRatio = static_cast<float>(scaleInliersCount) / keyPointMatchesCount;
if(scaleInliersRatio < minScaleInliersRatio)
{
ts->printf(cvtest::TS::LOG, "Incorrect scaleInliersRatio: curr = %f, min = %f.\n",
scaleInliersRatio, minScaleInliersRatio);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return;
}
}
#if SHOW_DEBUG_LOG
std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio
<< " - scaleInliersRatio " << static_cast<float>(scaleInliersCount) / keyPointMatchesCount << std::endl;
#endif
/*vector<DMatch> filteredMatches;
for(size_t i = 0; i < matches.size(); i++)
{
if(matches[i].distance >= minIntersectRatio)
filteredMatches.push_back(matches[i]);
}
Mat out;
namedWindow("out", CV_WINDOW_NORMAL);
drawMatches(image1, keypoints1, image0, keypoints0, filteredMatches, out,
Scalar::all(-1), Scalar(-1), vector<char>(), DrawMatchesFlags::DEFAULT + DrawMatchesFlags::DRAW_RICH_KEYPOINTS);
imshow("out", out);
waitKey();*/
}
ts->set_failed_test_info( cvtest::TS::OK );
}
Ptr<FeatureDetector> featureDetector;
float minKeyPointMatchesRatio;
float minScaleInliersRatio;
};
class DescriptorScaleInvarianceTest : public cvtest::BaseTest
{
public:
DescriptorScaleInvarianceTest(const Ptr<FeatureDetector>& _featureDetector,
const Ptr<DescriptorExtractor>& _descriptorExtractor,
int _normType,
float _minKeyPointMatchesRatio,
float _minDescInliersRatio) :
featureDetector(_featureDetector),
descriptorExtractor(_descriptorExtractor),
normType(_normType),
minKeyPointMatchesRatio(_minKeyPointMatchesRatio),
minDescInliersRatio(_minDescInliersRatio)
{
CV_Assert(!featureDetector.empty());
CV_Assert(!descriptorExtractor.empty());
}
protected:
void run(int)
{
const string imageFilename = string(ts->get_data_path()) + IMAGE_BIKES;
// Read test data
Mat image0 = imread(imageFilename);
if(image0.empty())
{
ts->printf(cvtest::TS::LOG, "Image %s can not be read.\n", imageFilename.c_str());
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
return;
}
vector<KeyPoint> keypoints0;
featureDetector->detect(image0, keypoints0);
if(keypoints0.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
Mat descriptors0;
descriptorExtractor->compute(image0, keypoints0, descriptors0);
BFMatcher bfmatcher(normType);
for(int scale = 2; scale <= 4; scale++)
{
Mat image1;
resize(image0, image1, Size(), 1./scale, 1./scale);
vector<KeyPoint> keypoints1, osiKeypoints1; // osi - original size image
featureDetector->detect(image1, keypoints1);
if(keypoints1.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
if(keypoints1.size() > keypoints0.size() )
{
ts->printf(cvtest::TS::LOG, "Strange behavior of the detector. "
"It gives more points count in an image of the smaller size.\n"
"original size (%d, %d), keypoints count = %d\n"
"reduced size (%d, %d), keypoints count = %d\n",
image0.cols, image0.rows, keypoints0.size(),
image1.cols, image1.rows, keypoints1.size());
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return;
}
Mat descriptors1;
descriptorExtractor->compute(image1, keypoints1, descriptors1);
vector<DMatch> keyPointMatches, descMatches;
// image1 is query image (it's reduced image0)
// image0 is train image
bfmatcher.match(descriptors1, descriptors0, descMatches);
scaleKeyPoints(keypoints1, osiKeypoints1, scale);
matchKeyPoints(osiKeypoints1, Mat(), keypoints0, keyPointMatches);
const float minIntersectRatio = 0.5f;
int keyPointMatchesCount = 0;
for(size_t m = 0; m < keyPointMatches.size(); m++)
{
if(keyPointMatches[m].distance >= minIntersectRatio)
keyPointMatchesCount++;
}
int descInliersCount = 0;
for(size_t m = 0; m < descMatches.size(); m++)
{
int queryIdx = descMatches[m].queryIdx;
if(keyPointMatches[queryIdx].distance >= minIntersectRatio &&
descMatches[m].trainIdx == keyPointMatches[queryIdx].trainIdx)
descInliersCount++;
}
float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints1.size();
if(keyPointMatchesRatio < minKeyPointMatchesRatio)
{
ts->printf(cvtest::TS::LOG, "Incorrect keyPointMatchesRatio: curr = %f, min = %f.\n",
keyPointMatchesRatio, minKeyPointMatchesRatio);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return;
}
if(keyPointMatchesCount)
{
float descInliersRatio = static_cast<float>(descInliersCount) / keyPointMatchesCount;
if(descInliersRatio < minDescInliersRatio)
{
ts->printf(cvtest::TS::LOG, "Incorrect descInliersRatio: curr = %f, min = %f.\n",
descInliersRatio, minDescInliersRatio);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return;
}
}
#if SHOW_DEBUG_LOG
std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio
<< " - descInliersRatio " << static_cast<float>(descInliersCount) / keyPointMatchesCount << std::endl;
#endif
}
ts->set_failed_test_info( cvtest::TS::OK );
}
Ptr<FeatureDetector> featureDetector;
Ptr<DescriptorExtractor> descriptorExtractor;
int normType;
float minKeyPointMatchesRatio;
float minDescInliersRatio;
};
// Tests registration
// Detector's rotation invariance check
......@@ -397,7 +660,7 @@ TEST(Features2d_RotationInvariance_Descriptor_ORB, regression)
test.safe_run();
}
// TODO: uncomment test for FREAK when it will work
// TODO: Uncomment test for FREAK when it will work; add test for scale invariance for FREAK
//TEST(Features2d_RotationInvariance_Descriptor_FREAK, regression)
//{
// DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
......@@ -406,4 +669,25 @@ TEST(Features2d_RotationInvariance_Descriptor_ORB, regression)
// 0.45f,
// 0.?f);
// test.safe_run();
//}
\ No newline at end of file
//}
/* TODO: Why ORB has bad scale invariance in this tests?
// Detector's scale invariance check
TEST(Features2d_ScaleInvariance_Detector_ORB, regression)
{
DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
0.13f,
0.0f);
test.safe_run();
}
// Descriptor's scale invariance check
TEST(Features2d_ScaleInvariance_Descriptor_ORB, regression)
{
DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
Algorithm::create<DescriptorExtractor>("Feature2D.ORB"),
NORM_HAMMING,
0.13f,
0.36f);
test.safe_run();
}*/
\ No newline at end of file
modules/nonfree/test/test_rotation_invariance.cpp → modules/nonfree/test/test_rotation_and_scale_invariance.cpp
View file @ ec23d9bb
......@@ -45,8 +45,8 @@
using namespace std;
using namespace cv;
const string FEATURES2D_DIR = "features2d";
const string IMAGE_FILENAME = "tsukuba.png";
const string IMAGE_TSUKUBA = "/features2d/tsukuba.png";
const string IMAGE_BIKES = "/detectors_descriptors_evaluation/images_datasets/bikes/img1.png";
#define SHOW_DEBUG_LOG 0
......@@ -127,14 +127,17 @@ void matchKeyPoints(const vector<KeyPoint>& keypoints0, const Mat& H,
vector<Point2f> points0;
KeyPoint::convert(keypoints0, points0);
Mat points0t;
perspectiveTransform(Mat(points0), points0t, H);
if(H.empty())
points0t = Mat(points0);
else
perspectiveTransform(Mat(points0), points0t, H);
matches.clear();
vector<uchar> usedMask(keypoints1.size(), 0);
for(size_t i0 = 0; i0 < keypoints0.size(); i0++)
{
int nearestPointIndex = -1;
float maxIntersectRatio = -1.f;
float maxIntersectRatio = 0.f;
const float r0 = 0.5f * keypoints0[i0].size;
for(size_t i1 = 0; i1 < keypoints1.size(); i1++)
{
......@@ -174,7 +177,7 @@ protected:
void run(int)
{
const string imageFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
const string imageFilename = string(ts->get_data_path()) + IMAGE_TSUKUBA;
// Read test data
Mat image0 = imread(imageFilename), image1, mask1;
......@@ -187,8 +190,8 @@ protected:
vector<KeyPoint> keypoints0;
featureDetector->detect(image0, keypoints0);
CV_Assert(keypoints0.size() > 15);
if(keypoints0.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
const int maxAngle = 360, angleStep = 15;
for(int angle = 0; angle < maxAngle; angle += angleStep)
......@@ -266,6 +269,13 @@ protected:
float minAngleInliersRatio;
};
void scaleKeyPoints(const vector<KeyPoint>& src, vector<KeyPoint>& dst, float scale)
{
dst.resize(src.size());
for(size_t i = 0; i < src.size(); i++)
dst[i] = KeyPoint(src[i].pt.x * scale, src[i].pt.y * scale, src[i].size * scale);
}
class DescriptorRotationInvarianceTest : public cvtest::BaseTest
{
public:
......@@ -288,7 +298,7 @@ protected:
void run(int)
{
const string imageFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
const string imageFilename = string(ts->get_data_path()) + IMAGE_TSUKUBA;
// Read test data
Mat image0 = imread(imageFilename), image1, mask1;
......@@ -302,9 +312,10 @@ protected:
vector<KeyPoint> keypoints0;
Mat descriptors0;
featureDetector->detect(image0, keypoints0);
if(keypoints0.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
descriptorExtractor->compute(image0, keypoints0, descriptors0);
CV_Assert(keypoints0.size() > 15);
BFMatcher bfmatcher(normType);
const int maxAngle = 360, angleStep = 15;
......@@ -375,6 +386,245 @@ protected:
};
class DetectorScaleInvarianceTest : public cvtest::BaseTest
{
public:
DetectorScaleInvarianceTest(const Ptr<FeatureDetector>& _featureDetector,
float _minKeyPointMatchesRatio,
float _minScaleInliersRatio) :
featureDetector(_featureDetector),
minKeyPointMatchesRatio(_minKeyPointMatchesRatio),
minScaleInliersRatio(_minScaleInliersRatio)
{
CV_Assert(!featureDetector.empty());
}
protected:
void run(int)
{
const string imageFilename = string(ts->get_data_path()) + IMAGE_BIKES;
// Read test data
Mat image0 = imread(imageFilename);
if(image0.empty())
{
ts->printf(cvtest::TS::LOG, "Image %s can not be read.\n", imageFilename.c_str());
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
return;
}
vector<KeyPoint> keypoints0;
featureDetector->detect(image0, keypoints0);
if(keypoints0.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
for(int scale = 2; scale <= 4; scale++)
{
Mat image1;
resize(image0, image1, Size(), 1./scale, 1./scale);
vector<KeyPoint> keypoints1, osiKeypoints1; // osi - original size image
featureDetector->detect(image1, keypoints1);
if(keypoints1.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
if(keypoints1.size() > keypoints0.size())
{
ts->printf(cvtest::TS::LOG, "Strange behavior of the detector. "
"It gives more points count in an image of the smaller size.\n"
"original size (%d, %d), keypoints count = %d\n"
"reduced size (%d, %d), keypoints count = %d\n",
image0.cols, image0.rows, keypoints0.size(),
image1.cols, image1.rows, keypoints1.size());
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return;
}
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 = 0.8;//0.9f; // grad
float size0 = keypoints0[matches[m].trainIdx].size;
float size1 = osiKeypoints1[matches[m].queryIdx].size;
CV_Assert(size0 > 0 && size1 > 0);
if(std::min(size0, size1) > maxSizeDiff * std::max(size0, size1))
scaleInliersCount++;
}
float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints1.size();
if(keyPointMatchesRatio < minKeyPointMatchesRatio)
{
ts->printf(cvtest::TS::LOG, "Incorrect keyPointMatchesRatio: curr = %f, min = %f.\n",
keyPointMatchesRatio, minKeyPointMatchesRatio);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return;
}
if(keyPointMatchesCount)
{
float scaleInliersRatio = static_cast<float>(scaleInliersCount) / keyPointMatchesCount;
if(scaleInliersRatio < minScaleInliersRatio)
{
ts->printf(cvtest::TS::LOG, "Incorrect scaleInliersRatio: curr = %f, min = %f.\n",
scaleInliersRatio, minScaleInliersRatio);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return;
}
}
#if SHOW_DEBUG_LOG
std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio
<< " - scaleInliersRatio " << static_cast<float>(scaleInliersCount) / keyPointMatchesCount << std::endl;
#endif
}
ts->set_failed_test_info( cvtest::TS::OK );
}
Ptr<FeatureDetector> featureDetector;
float minKeyPointMatchesRatio;
float minScaleInliersRatio;
};
class DescriptorScaleInvarianceTest : public cvtest::BaseTest
{
public:
DescriptorScaleInvarianceTest(const Ptr<FeatureDetector>& _featureDetector,
const Ptr<DescriptorExtractor>& _descriptorExtractor,
int _normType,
float _minKeyPointMatchesRatio,
float _minDescInliersRatio) :
featureDetector(_featureDetector),
descriptorExtractor(_descriptorExtractor),
normType(_normType),
minKeyPointMatchesRatio(_minKeyPointMatchesRatio),
minDescInliersRatio(_minDescInliersRatio)
{
CV_Assert(!featureDetector.empty());
CV_Assert(!descriptorExtractor.empty());
}
protected:
void run(int)
{
const string imageFilename = string(ts->get_data_path()) + IMAGE_BIKES;
// Read test data
Mat image0 = imread(imageFilename);
if(image0.empty())
{
ts->printf(cvtest::TS::LOG, "Image %s can not be read.\n", imageFilename.c_str());
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
return;
}
vector<KeyPoint> keypoints0;
featureDetector->detect(image0, keypoints0);
if(keypoints0.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
Mat descriptors0;
descriptorExtractor->compute(image0, keypoints0, descriptors0);
BFMatcher bfmatcher(normType);
for(int scale = 2; scale <= 4; scale++)
{
Mat image1;
resize(image0, image1, Size(), 1./scale, 1./scale);
vector<KeyPoint> keypoints1, osiKeypoints1; // osi - original size image
featureDetector->detect(image1, keypoints1);
if(keypoints1.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
if(keypoints1.size() > keypoints0.size() )
{
ts->printf(cvtest::TS::LOG, "Strange behavior of the detector. "
"It gives more points count in an image of the smaller size.\n"
"original size (%d, %d), keypoints count = %d\n"
"reduced size (%d, %d), keypoints count = %d\n",
image0.cols, image0.rows, keypoints0.size(),
image1.cols, image1.rows, keypoints1.size());
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return;
}
Mat descriptors1;
descriptorExtractor->compute(image1, keypoints1, descriptors1);
vector<DMatch> keyPointMatches, descMatches;
// image1 is query image (it's reduced image0)
// image0 is train image
bfmatcher.match(descriptors1, descriptors0, descMatches);
scaleKeyPoints(keypoints1, osiKeypoints1, scale);
matchKeyPoints(osiKeypoints1, Mat(), keypoints0, keyPointMatches);
const float minIntersectRatio = 0.5f;
int keyPointMatchesCount = 0;
for(size_t m = 0; m < keyPointMatches.size(); m++)
{
if(keyPointMatches[m].distance >= minIntersectRatio)
keyPointMatchesCount++;
}
int descInliersCount = 0;
for(size_t m = 0; m < descMatches.size(); m++)
{
int queryIdx = descMatches[m].queryIdx;
if(keyPointMatches[queryIdx].distance >= minIntersectRatio &&
descMatches[m].trainIdx == keyPointMatches[queryIdx].trainIdx)
descInliersCount++;
}
float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints1.size();
if(keyPointMatchesRatio < minKeyPointMatchesRatio)
{
ts->printf(cvtest::TS::LOG, "Incorrect keyPointMatchesRatio: curr = %f, min = %f.\n",
keyPointMatchesRatio, minKeyPointMatchesRatio);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return;
}
if(keyPointMatchesCount)
{
float descInliersRatio = static_cast<float>(descInliersCount) / keyPointMatchesCount;
if(descInliersRatio < minDescInliersRatio)
{
ts->printf(cvtest::TS::LOG, "Incorrect descInliersRatio: curr = %f, min = %f.\n",
descInliersRatio, minDescInliersRatio);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return;
}
}
#if SHOW_DEBUG_LOG
std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio
<< " - descInliersRatio " << static_cast<float>(descInliersCount) / keyPointMatchesCount << std::endl;
#endif
}
ts->set_failed_test_info( cvtest::TS::OK );
}
Ptr<FeatureDetector> featureDetector;
Ptr<DescriptorExtractor> descriptorExtractor;
int normType;
float minKeyPointMatchesRatio;
float minDescInliersRatio;
};
// Tests registration
// Detector's rotation invariance check
......@@ -386,7 +636,6 @@ TEST(Features2d_RotationInvariance_Detector_SURF, regression)
test.safe_run();
}
TEST(Features2d_RotationInvariance_Detector_SIFT, regression)
{
DetectorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"),
......@@ -402,7 +651,7 @@ TEST(Features2d_RotationInvariance_Descriptor_SURF, regression)
Algorithm::create<DescriptorExtractor>("Feature2D.SURF"),
NORM_L1,
0.44f,
0.64f);
0.63f);
test.safe_run();
}
......@@ -414,4 +663,42 @@ TEST(Features2d_RotationInvariance_Descriptor_SIFT, regression)
0.64f,
0.72f);
test.safe_run();
}
// Detector's scale invariance check
TEST(Features2d_ScaleInvariance_Detector_SURF, regression)
{
DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SURF"),
0.62f,
0.68f);
test.safe_run();
}
TEST(Features2d_ScaleInvariance_Detector_SIFT, regression)
{
DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"),
0.59f,
0.94f);
test.safe_run();
}
// Descriptor's scale invariance check
TEST(Features2d_ScaleInvariance_Descriptor_SURF, regression)
{
DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SURF"),
Algorithm::create<DescriptorExtractor>("Feature2D.SURF"),
NORM_L1,
0.62f,
0.68f);
test.safe_run();
}
TEST(Features2d_ScaleInvariance_Descriptor_SIFT, regression)
{
DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"),
Algorithm::create<DescriptorExtractor>("Feature2D.SIFT"),
NORM_L1,
0.59f,
0.78f);
test.safe_run();
}
\ No newline at end of file
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