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changed tests for rotation/scale invariance of descriptors

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This commit is contained in:
Maria Dimashova 2012-07-16 13:01:55 +00:00
parent ad7a6ec41f
commit 2556bb04f0
2 changed files with 601 additions and 672 deletions
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653
modules/features2d/test/test_rotation_and_scale_invariance.cpp
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@ -53,7 +53,7 @@ const string IMAGE_BIKES = "/detectors_descriptors_evaluation/images_datasets/bi
static static
Mat generateHomography(float angle) Mat generateHomography(float angle)
{ {
// angle - rotation around Oz in degrees // angle - rotation around Oz in degrees
float angleRadian = angle * CV_PI / 180.; float angleRadian = angle * CV_PI / 180.;
Mat H = Mat::eye(3, 3, CV_32FC1); Mat H = Mat::eye(3, 3, CV_32FC1);
H.at<float>(0,0) = H.at<float>(1,1) = std::cos(angleRadian); H.at<float>(0,0) = H.at<float>(1,1) = std::cos(angleRadian);
@ -66,7 +66,7 @@ Mat generateHomography(float angle)
static static
Mat rotateImage(const Mat& srcImage, float angle, Mat& dstImage, Mat& dstMask) Mat rotateImage(const Mat& srcImage, float angle, Mat& dstImage, Mat& dstMask)
{ {
// angle - rotation around Oz in degrees // angle - rotation around Oz in degrees
float diag = std::sqrt(static_cast<float>(srcImage.cols * srcImage.cols + srcImage.rows * srcImage.rows)); float diag = std::sqrt(static_cast<float>(srcImage.cols * srcImage.cols + srcImage.rows * srcImage.rows));
Mat LUShift = Mat::eye(3, 3, CV_32FC1); // left up Mat LUShift = Mat::eye(3, 3, CV_32FC1); // left up
LUShift.at<float>(0,2) = -srcImage.cols/2; LUShift.at<float>(0,2) = -srcImage.cols/2;
@ -85,6 +85,32 @@ Mat rotateImage(const Mat& srcImage, float angle, Mat& dstImage, Mat& dstMask)
return H; return H;
} }
void rotateKeyPoints(const vector<KeyPoint>& src, const Mat& H, float angle, vector<KeyPoint>& dst)
{
// suppose that H is rotation given from rotateImage() and angle has value passed to rotateImage()
vector<Point2f> srcCenters, dstCenters;
KeyPoint::convert(src, srcCenters);
perspectiveTransform(srcCenters, dstCenters, H);
dst = src;
for(size_t i = 0; i < dst.size(); i++)
{
dst[i].pt = dstCenters[i];
float dstAngle = src[i].angle + angle;
if(dstAngle >= 360.f)
dstAngle -= 360.f;
dst[i].angle = dstAngle;
}
}
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);
}
static static
float calcCirclesIntersectArea(const Point2f& p0, float r0, const Point2f& p1, float r1) float calcCirclesIntersectArea(const Point2f& p0, float r0, const Point2f& p1, float r1)
{ {
@ -119,45 +145,45 @@ float calcIntersectRatio(const Point2f& p0, float r0, const Point2f& p1, float r
return intersectArea / unionArea; return intersectArea / unionArea;
} }
static static
void matchKeyPoints(const vector<KeyPoint>& keypoints0, const Mat& H, void matchKeyPoints(const vector<KeyPoint>& keypoints0, const Mat& H,
const vector<KeyPoint>& keypoints1, const vector<KeyPoint>& keypoints1,
vector<DMatch>& matches) vector<DMatch>& matches)
{ {
vector<Point2f> points0; vector<Point2f> points0;
KeyPoint::convert(keypoints0, points0); KeyPoint::convert(keypoints0, points0);
Mat points0t; Mat points0t;
if(H.empty()) if(H.empty())
points0t = Mat(points0); points0t = Mat(points0);
else else
perspectiveTransform(Mat(points0), points0t, H); perspectiveTransform(Mat(points0), points0t, H);
matches.clear(); matches.clear();
vector<uchar> usedMask(keypoints1.size(), 0); vector<uchar> usedMask(keypoints1.size(), 0);
for(size_t i0 = 0; i0 < keypoints0.size(); i0++) for(size_t i0 = 0; i0 < keypoints0.size(); i0++)
{ {
int nearestPointIndex = -1; int nearestPointIndex = -1;
float maxIntersectRatio = 0.f; float maxIntersectRatio = 0.f;
const float r0 = 0.5f * keypoints0[i0].size; const float r0 = 0.5f * keypoints0[i0].size;
for(size_t i1 = 0; i1 < keypoints1.size(); i1++) for(size_t i1 = 0; i1 < keypoints1.size(); i1++)
{ {
if(nearestPointIndex >= 0 && usedMask[i1]) if(nearestPointIndex >= 0 && usedMask[i1])
continue; continue;
float r1 = 0.5f * keypoints1[i1].size; float r1 = 0.5f * keypoints1[i1].size;
float intersectRatio = calcIntersectRatio(points0t.at<Point2f>(i0), r0, float intersectRatio = calcIntersectRatio(points0t.at<Point2f>(i0), r0,
keypoints1[i1].pt, r1); keypoints1[i1].pt, r1);
if(intersectRatio > maxIntersectRatio) if(intersectRatio > maxIntersectRatio)
{ {
maxIntersectRatio = intersectRatio; maxIntersectRatio = intersectRatio;
nearestPointIndex = i1; nearestPointIndex = i1;
} }
} }
matches.push_back(DMatch(i0, nearestPointIndex, maxIntersectRatio)); matches.push_back(DMatch(i0, nearestPointIndex, maxIntersectRatio));
if(nearestPointIndex >= 0) if(nearestPointIndex >= 0)
usedMask[nearestPointIndex] = 1; usedMask[nearestPointIndex] = 1;
} }
} }
class DetectorRotationInvarianceTest : public cvtest::BaseTest class DetectorRotationInvarianceTest : public cvtest::BaseTest
@ -166,134 +192,13 @@ public:
DetectorRotationInvarianceTest(const Ptr<FeatureDetector>& _featureDetector, DetectorRotationInvarianceTest(const Ptr<FeatureDetector>& _featureDetector,
float _minKeyPointMatchesRatio, float _minKeyPointMatchesRatio,
float _minAngleInliersRatio) : float _minAngleInliersRatio) :
featureDetector(_featureDetector), featureDetector(_featureDetector),
minKeyPointMatchesRatio(_minKeyPointMatchesRatio), minKeyPointMatchesRatio(_minKeyPointMatchesRatio),
minAngleInliersRatio(_minAngleInliersRatio) minAngleInliersRatio(_minAngleInliersRatio)
{ {
CV_Assert(!featureDetector.empty()); CV_Assert(!featureDetector.empty());
} }
protected:
void run(int)
{
const string imageFilename = string(ts->get_data_path()) + IMAGE_TSUKUBA;
// Read test data
Mat image0 = imread(imageFilename), image1, mask1;
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");
const int maxAngle = 360, angleStep = 15;
for(int angle = 0; angle < maxAngle; angle += angleStep)
{
Mat H = rotateImage(image0, 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;
if(angle0 == -1 || angle1 == -1)
CV_Error(CV_StsBadArg, "Given FeatureDetector is not rotation invariant, it can not be tested here.\n");
CV_Assert(angle0 >= 0.f && angle0 < 360.f);
CV_Assert(angle1 >= 0.f && 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));
CV_Assert(angleDiff >= 0.f);
bool isAngleCorrect = angleDiff < maxAngleDiff;
if(isAngleCorrect)
angleInliersCount++;
}
float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints0.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 angleInliersRatio = static_cast<float>(angleInliersCount) / keyPointMatchesCount;
if(angleInliersRatio < minAngleInliersRatio)
{
ts->printf(cvtest::TS::LOG, "Incorrect angleInliersRatio: curr = %f, min = %f.\n",
angleInliersRatio, minAngleInliersRatio);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return;
}
}
#if SHOW_DEBUG_LOG
std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio
<< " - angleInliersRatio " << static_cast<float>(angleInliersCount) / keyPointMatchesCount << std::endl;
#endif
}
ts->set_failed_test_info( cvtest::TS::OK );
}
Ptr<FeatureDetector> featureDetector;
float minKeyPointMatchesRatio;
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:
DescriptorRotationInvarianceTest(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: protected:
void run(int) void run(int)
@ -310,13 +215,9 @@ protected:
} }
vector<KeyPoint> keypoints0; vector<KeyPoint> keypoints0;
Mat descriptors0;
featureDetector->detect(image0, keypoints0); featureDetector->detect(image0, keypoints0);
if(keypoints0.size() < 15) if(keypoints0.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n"); CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
descriptorExtractor->compute(image0, keypoints0, descriptors0);
BFMatcher bfmatcher(normType);
const int maxAngle = 360, angleStep = 15; const int maxAngle = 360, angleStep = 15;
for(int angle = 0; angle < maxAngle; angle += angleStep) for(int angle = 0; angle < maxAngle; angle += angleStep)
@ -324,31 +225,42 @@ protected:
Mat H = rotateImage(image0, angle, image1, mask1); Mat H = rotateImage(image0, angle, image1, mask1);
vector<KeyPoint> keypoints1; vector<KeyPoint> keypoints1;
Mat descriptors1;
featureDetector->detect(image1, keypoints1, mask1); featureDetector->detect(image1, keypoints1, mask1);
descriptorExtractor->compute(image1, keypoints1, descriptors1);
vector<DMatch> descMatches; vector<DMatch> matches;
bfmatcher.match(descriptors0, descriptors1, descMatches); matchKeyPoints(keypoints0, H, keypoints1, matches);
vector<DMatch> keyPointMatches; int angleInliersCount = 0;
matchKeyPoints(keypoints0, H, keypoints1, keyPointMatches);
const float minIntersectRatio = 0.5f; const float minIntersectRatio = 0.5f;
int keyPointMatchesCount = 0; int keyPointMatchesCount = 0;
for(size_t m = 0; m < keyPointMatches.size(); m++) for(size_t m = 0; m < matches.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(matches[m].distance < minIntersectRatio)
if(keyPointMatches[queryIdx].distance >= minIntersectRatio && continue;
descMatches[m].trainIdx == keyPointMatches[queryIdx].trainIdx)
descInliersCount++; 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;
if(angle0 == -1 || angle1 == -1)
CV_Error(CV_StsBadArg, "Given FeatureDetector is not rotation invariant, it can not be tested here.\n");
CV_Assert(angle0 >= 0.f && angle0 < 360.f);
CV_Assert(angle1 >= 0.f && 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));
CV_Assert(angleDiff >= 0.f);
bool isAngleCorrect = angleDiff < maxAngleDiff;
if(isAngleCorrect)
angleInliersCount++;
}
float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints0.size(); float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints0.size();
if(keyPointMatchesRatio < minKeyPointMatchesRatio) if(keyPointMatchesRatio < minKeyPointMatchesRatio)
@ -359,31 +271,115 @@ protected:
return; return;
} }
if(keyPointMatchesCount) if(keyPointMatchesCount)
{ {
float descInliersRatio = static_cast<float>(descInliersCount) / keyPointMatchesCount; float angleInliersRatio = static_cast<float>(angleInliersCount) / keyPointMatchesCount;
if(descInliersRatio < minDescInliersRatio) if(angleInliersRatio < minAngleInliersRatio)
{ {
ts->printf(cvtest::TS::LOG, "Incorrect descInliersRatio: curr = %f, min = %f.\n", ts->printf(cvtest::TS::LOG, "Incorrect angleInliersRatio: curr = %f, min = %f.\n",
descInliersRatio, minDescInliersRatio); angleInliersRatio, minAngleInliersRatio);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY); ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return; return;
} }
} }
#if SHOW_DEBUG_LOG #if SHOW_DEBUG_LOG
std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio
<< " - descInliersRatio " << static_cast<float>(descInliersCount) / keyPointMatchesCount << std::endl; << " - angleInliersRatio " << static_cast<float>(angleInliersCount) / keyPointMatchesCount << std::endl;
#endif #endif
} }
ts->set_failed_test_info( cvtest::TS::OK ); ts->set_failed_test_info( cvtest::TS::OK );
} }
Ptr<FeatureDetector> featureDetector; Ptr<FeatureDetector> featureDetector;
Ptr<DescriptorExtractor> descriptorExtractor; float minKeyPointMatchesRatio;
float minAngleInliersRatio;
};
class DescriptorRotationInvarianceTest : public cvtest::BaseTest
{
public:
DescriptorRotationInvarianceTest(const Ptr<FeatureDetector>& _featureDetector,
const Ptr<DescriptorExtractor>& _descriptorExtractor,
int _normType,
float _minDescInliersRatio) :
featureDetector(_featureDetector),
descriptorExtractor(_descriptorExtractor),
normType(_normType),
minDescInliersRatio(_minDescInliersRatio)
{
CV_Assert(!featureDetector.empty());
CV_Assert(!descriptorExtractor.empty());
}
protected:
void run(int)
{
const string imageFilename = string(ts->get_data_path()) + IMAGE_TSUKUBA;
// Read test data
Mat image0 = imread(imageFilename), image1, mask1;
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;
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);
BFMatcher bfmatcher(normType);
const float minIntersectRatio = 0.5f;
const int maxAngle = 360, angleStep = 15;
for(int angle = 0; angle < maxAngle; angle += angleStep)
{
Mat H = rotateImage(image0, angle, image1, mask1);
vector<KeyPoint> keypoints1;
rotateKeyPoints(keypoints0, H, angle, keypoints1);
Mat descriptors1;
descriptorExtractor->compute(image1, keypoints1, descriptors1);
vector<DMatch> descMatches;
bfmatcher.match(descriptors0, descriptors1, descMatches);
int descInliersCount = 0;
for(size_t m = 0; m < descMatches.size(); m++)
{
const KeyPoint& transformed_p0 = keypoints1[descMatches[m].queryIdx];
const KeyPoint& p1 = keypoints1[descMatches[m].trainIdx];
if(calcIntersectRatio(transformed_p0.pt, 0.5f * transformed_p0.size,
p1.pt, 0.5f * p1.size) >= minIntersectRatio)
{
descInliersCount++;
}
}
float descInliersRatio = static_cast<float>(descInliersCount) / keypoints0.size();
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 << "descInliersRatio " << static_cast<float>(descInliersCount) / keypoints0.size() << std::endl;
#endif
}
ts->set_failed_test_info( cvtest::TS::OK );
}
Ptr<FeatureDetector> featureDetector;
Ptr<DescriptorExtractor> descriptorExtractor;
int normType; int normType;
float minKeyPointMatchesRatio; float minDescInliersRatio;
float minDescInliersRatio;
}; };
class DetectorScaleInvarianceTest : public cvtest::BaseTest class DetectorScaleInvarianceTest : public cvtest::BaseTest
@ -392,9 +388,9 @@ public:
DetectorScaleInvarianceTest(const Ptr<FeatureDetector>& _featureDetector, DetectorScaleInvarianceTest(const Ptr<FeatureDetector>& _featureDetector,
float _minKeyPointMatchesRatio, float _minKeyPointMatchesRatio,
float _minScaleInliersRatio) : float _minScaleInliersRatio) :
featureDetector(_featureDetector), featureDetector(_featureDetector),
minKeyPointMatchesRatio(_minKeyPointMatchesRatio), minKeyPointMatchesRatio(_minKeyPointMatchesRatio),
minScaleInliersRatio(_minScaleInliersRatio) minScaleInliersRatio(_minScaleInliersRatio)
{ {
CV_Assert(!featureDetector.empty()); CV_Assert(!featureDetector.empty());
} }
@ -403,7 +399,7 @@ protected:
void run(int) void run(int)
{ {
const string imageFilename = string(ts->get_data_path()) + IMAGE_BIKES; const string imageFilename = string(ts->get_data_path()) + IMAGE_BIKES;
// Read test data // Read test data
Mat image0 = imread(imageFilename); Mat image0 = imread(imageFilename);
@ -417,58 +413,59 @@ protected:
vector<KeyPoint> keypoints0; vector<KeyPoint> keypoints0;
featureDetector->detect(image0, keypoints0); featureDetector->detect(image0, keypoints0);
if(keypoints0.size() < 15) if(keypoints0.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n"); CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
for(int scale = 2; scale <= 4; scale++) for(float scaleIdx = 1; scaleIdx <= 3; scaleIdx++)
{ {
Mat image1; float scale = 1.f + scaleIdx * 0.5f;
resize(image0, image1, Size(), 1./scale, 1./scale); Mat image1;
resize(image0, image1, Size(), 1./scale, 1./scale);
vector<KeyPoint> keypoints1, osiKeypoints1; // osi - original size image vector<KeyPoint> keypoints1, osiKeypoints1; // osi - original size image
featureDetector->detect(image1, keypoints1); featureDetector->detect(image1, keypoints1);
if(keypoints1.size() < 15) if(keypoints1.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n"); CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
if(keypoints1.size() > keypoints0.size()) if(keypoints1.size() > keypoints0.size())
{ {
ts->printf(cvtest::TS::LOG, "Strange behavior of the detector. " ts->printf(cvtest::TS::LOG, "Strange behavior of the detector. "
"It gives more points count in an image of the smaller size.\n" "It gives more points count in an image of the smaller size.\n"
"original size (%d, %d), keypoints count = %d\n" "original size (%d, %d), keypoints count = %d\n"
"reduced size (%d, %d), keypoints count = %d\n", "reduced size (%d, %d), keypoints count = %d\n",
image0.cols, image0.rows, keypoints0.size(), image0.cols, image0.rows, keypoints0.size(),
image1.cols, image1.rows, keypoints1.size()); image1.cols, image1.rows, keypoints1.size());
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT); ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return; return;
} }
scaleKeyPoints(keypoints1, osiKeypoints1, scale); scaleKeyPoints(keypoints1, osiKeypoints1, scale);
vector<DMatch> matches; vector<DMatch> matches;
// image1 is query image (it's reduced image0) // image1 is query image (it's reduced image0)
// image0 is train image // image0 is train image
matchKeyPoints(osiKeypoints1, Mat(), keypoints0, matches); matchKeyPoints(osiKeypoints1, Mat(), keypoints0, matches);
const float minIntersectRatio = 0.5f; const float minIntersectRatio = 0.5f;
int keyPointMatchesCount = 0; int keyPointMatchesCount = 0;
int scaleInliersCount = 0; int scaleInliersCount = 0;
for(size_t m = 0; m < matches.size(); m++) for(size_t m = 0; m < matches.size(); m++)
{ {
if(matches[m].distance < minIntersectRatio) if(matches[m].distance < minIntersectRatio)
continue; continue;
keyPointMatchesCount++; keyPointMatchesCount++;
// Check does this inlier have consistent sizes // Check does this inlier have consistent sizes
const float maxSizeDiff = 0.8;//0.9f; // grad const float maxSizeDiff = 0.8;//0.9f; // grad
float size0 = keypoints0[matches[m].trainIdx].size; float size0 = keypoints0[matches[m].trainIdx].size;
float size1 = osiKeypoints1[matches[m].queryIdx].size; float size1 = osiKeypoints1[matches[m].queryIdx].size;
CV_Assert(size0 > 0 && size1 > 0); CV_Assert(size0 > 0 && size1 > 0);
if(std::min(size0, size1) > maxSizeDiff * std::max(size0, size1)) if(std::min(size0, size1) > maxSizeDiff * std::max(size0, size1))
scaleInliersCount++; scaleInliersCount++;
} }
float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints1.size(); float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints1.size();
if(keyPointMatchesRatio < minKeyPointMatchesRatio) if(keyPointMatchesRatio < minKeyPointMatchesRatio)
{ {
ts->printf(cvtest::TS::LOG, "Incorrect keyPointMatchesRatio: curr = %f, min = %f.\n", ts->printf(cvtest::TS::LOG, "Incorrect keyPointMatchesRatio: curr = %f, min = %f.\n",
@ -477,9 +474,9 @@ protected:
return; return;
} }
if(keyPointMatchesCount) if(keyPointMatchesCount)
{ {
float scaleInliersRatio = static_cast<float>(scaleInliersCount) / keyPointMatchesCount; float scaleInliersRatio = static_cast<float>(scaleInliersCount) / keyPointMatchesCount;
if(scaleInliersRatio < minScaleInliersRatio) if(scaleInliersRatio < minScaleInliersRatio)
{ {
ts->printf(cvtest::TS::LOG, "Incorrect scaleInliersRatio: curr = %f, min = %f.\n", ts->printf(cvtest::TS::LOG, "Incorrect scaleInliersRatio: curr = %f, min = %f.\n",
@ -490,21 +487,8 @@ protected:
} }
#if SHOW_DEBUG_LOG #if SHOW_DEBUG_LOG
std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio
<< " - scaleInliersRatio " << static_cast<float>(scaleInliersCount) / keyPointMatchesCount << std::endl; << " - scaleInliersRatio " << static_cast<float>(scaleInliersCount) / keyPointMatchesCount << std::endl;
#endif #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 ); ts->set_failed_test_info( cvtest::TS::OK );
} }
@ -518,25 +502,23 @@ class DescriptorScaleInvarianceTest : public cvtest::BaseTest
{ {
public: public:
DescriptorScaleInvarianceTest(const Ptr<FeatureDetector>& _featureDetector, DescriptorScaleInvarianceTest(const Ptr<FeatureDetector>& _featureDetector,
const Ptr<DescriptorExtractor>& _descriptorExtractor, const Ptr<DescriptorExtractor>& _descriptorExtractor,
int _normType, int _normType,
float _minKeyPointMatchesRatio,
float _minDescInliersRatio) : float _minDescInliersRatio) :
featureDetector(_featureDetector), featureDetector(_featureDetector),
descriptorExtractor(_descriptorExtractor), descriptorExtractor(_descriptorExtractor),
normType(_normType), normType(_normType),
minKeyPointMatchesRatio(_minKeyPointMatchesRatio), minDescInliersRatio(_minDescInliersRatio)
minDescInliersRatio(_minDescInliersRatio)
{ {
CV_Assert(!featureDetector.empty()); CV_Assert(!featureDetector.empty());
CV_Assert(!descriptorExtractor.empty()); CV_Assert(!descriptorExtractor.empty());
} }
protected: protected:
void run(int) void run(int)
{ {
const string imageFilename = string(ts->get_data_path()) + IMAGE_BIKES; const string imageFilename = string(ts->get_data_path()) + IMAGE_BIKES;
// Read test data // Read test data
Mat image0 = imread(imageFilename); Mat image0 = imread(imageFilename);
@ -549,145 +531,126 @@ protected:
vector<KeyPoint> keypoints0; vector<KeyPoint> keypoints0;
featureDetector->detect(image0, keypoints0); featureDetector->detect(image0, keypoints0);
if(keypoints0.size() < 15) if(keypoints0.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n"); CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
Mat descriptors0; Mat descriptors0;
descriptorExtractor->compute(image0, keypoints0, descriptors0); descriptorExtractor->compute(image0, keypoints0, descriptors0);
BFMatcher bfmatcher(normType); BFMatcher bfmatcher(normType);
for(int scale = 2; scale <= 4; scale++) for(float scaleIdx = 1; scaleIdx <= 3; scaleIdx++)
{ {
Mat image1; float scale = 1.f + scaleIdx * 0.5f;
resize(image0, image1, Size(), 1./scale, 1./scale);
vector<KeyPoint> keypoints1, osiKeypoints1; // osi - original size image Mat image1;
featureDetector->detect(image1, keypoints1); resize(image0, image1, Size(), 1./scale, 1./scale);
if(keypoints1.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n"); vector<KeyPoint> keypoints1;
if(keypoints1.size() > keypoints0.size() ) scaleKeyPoints(keypoints0, keypoints1, 1./scale);
{ Mat descriptors1;
ts->printf(cvtest::TS::LOG, "Strange behavior of the detector. " descriptorExtractor->compute(image1, keypoints1, descriptors1);
"It gives more points count in an image of the smaller size.\n"
"original size (%d, %d), keypoints count = %d\n" vector<DMatch> descMatches;
"reduced size (%d, %d), keypoints count = %d\n", bfmatcher.match(descriptors0, descriptors1, descMatches);
image0.cols, image0.rows, keypoints0.size(),
image1.cols, image1.rows, keypoints1.size()); const float minIntersectRatio = 0.5f;
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT); int descInliersCount = 0;
return; for(size_t m = 0; m < descMatches.size(); m++)
{
const KeyPoint& transformed_p0 = keypoints0[descMatches[m].queryIdx];
const KeyPoint& p1 = keypoints0[descMatches[m].trainIdx];
if(calcIntersectRatio(transformed_p0.pt, 0.5f * transformed_p0.size,
p1.pt, 0.5f * p1.size) >= minIntersectRatio)
{
descInliersCount++;
}
} }
Mat descriptors1; float descInliersRatio = static_cast<float>(descInliersCount) / keypoints0.size();
descriptorExtractor->compute(image1, keypoints1, descriptors1); if(descInliersRatio < minDescInliersRatio)
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; ts->printf(cvtest::TS::LOG, "Incorrect descInliersRatio: curr = %f, min = %f.\n",
if(keyPointMatches[queryIdx].distance >= minIntersectRatio && descInliersRatio, minDescInliersRatio);
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); ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return; 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 #if SHOW_DEBUG_LOG
std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio std::cout << "descInliersRatio " << static_cast<float>(descInliersCount) / keypoints0.size() << std::endl;
<< " - descInliersRatio " << static_cast<float>(descInliersCount) / keyPointMatchesCount << std::endl;
#endif #endif
} }
ts->set_failed_test_info( cvtest::TS::OK ); ts->set_failed_test_info( cvtest::TS::OK );
} }
Ptr<FeatureDetector> featureDetector; Ptr<FeatureDetector> featureDetector;
Ptr<DescriptorExtractor> descriptorExtractor; Ptr<DescriptorExtractor> descriptorExtractor;
int normType; int normType;
float minKeyPointMatchesRatio; float minKeyPointMatchesRatio;
float minDescInliersRatio; float minDescInliersRatio;
}; };
// Tests registration // Tests registration
// Detector's rotation invariance check /*
* Detector's rotation invariance check
*/
TEST(Features2d_RotationInvariance_Detector_ORB, regression) TEST(Features2d_RotationInvariance_Detector_ORB, regression)
{ {
DetectorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"), DetectorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
0.45f, 0.47f,
0.75f); 0.77f);
test.safe_run(); test.safe_run();
} }
// Descriptors's rotation invariance check /*
* Descriptors's rotation invariance check
*/
TEST(Features2d_RotationInvariance_Descriptor_ORB, regression) TEST(Features2d_RotationInvariance_Descriptor_ORB, regression)
{ {
DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"), DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
Algorithm::create<DescriptorExtractor>("Feature2D.ORB"), Algorithm::create<DescriptorExtractor>("Feature2D.ORB"),
NORM_HAMMING, NORM_HAMMING,
0.45f, 0.99f);
0.53f);
test.safe_run(); test.safe_run();
} }
// TODO: Uncomment test for FREAK when it will work; add test for scale invariance for FREAK
//TEST(Features2d_RotationInvariance_Descriptor_FREAK, regression) //TEST(Features2d_RotationInvariance_Descriptor_FREAK, regression)
//{ //{
// DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"), // DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
// Algorithm::create<DescriptorExtractor>("Feature2D.FREAK"), // Algorithm::create<DescriptorExtractor>("Feature2D.FREAK"),
// NORM_HAMMING(?), // NORM_HAMMING,
// 0.45f, // 0.f);
// 0.?f);
// test.safe_run(); // test.safe_run();
//} //}
/* TODO: Why ORB has bad scale invariance in this tests? /*
// Detector's scale invariance check * 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_Detector_ORB, regression)
TEST(Features2d_ScaleInvariance_Descriptor_ORB, regression) //{
{ // DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"), // 0.22f,
Algorithm::create<DescriptorExtractor>("Feature2D.ORB"), // 0.83f);
NORM_HAMMING, // test.safe_run();
0.13f, //}
0.36f);
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,
// 0.01f);
// test.safe_run();
//}
//TEST(Features2d_ScaleInvariance_Descriptor_FREAK, regression)
//{
// DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
// Algorithm::create<DescriptorExtractor>("Feature2D.FREAK"),
// NORM_HAMMING,
// 0.01f);
// test.safe_run();
//}

620
modules/nonfree/test/test_rotation_and_scale_invariance.cpp
View File

@ -53,7 +53,7 @@ const string IMAGE_BIKES = "/detectors_descriptors_evaluation/images_datasets/bi
static static
Mat generateHomography(float angle) Mat generateHomography(float angle)
{ {
// angle - rotation around Oz in degrees // angle - rotation around Oz in degrees
float angleRadian = angle * CV_PI / 180.; float angleRadian = angle * CV_PI / 180.;
Mat H = Mat::eye(3, 3, CV_32FC1); Mat H = Mat::eye(3, 3, CV_32FC1);
H.at<float>(0,0) = H.at<float>(1,1) = std::cos(angleRadian); H.at<float>(0,0) = H.at<float>(1,1) = std::cos(angleRadian);
@ -66,7 +66,7 @@ Mat generateHomography(float angle)
static static
Mat rotateImage(const Mat& srcImage, float angle, Mat& dstImage, Mat& dstMask) Mat rotateImage(const Mat& srcImage, float angle, Mat& dstImage, Mat& dstMask)
{ {
// angle - rotation around Oz in degrees // angle - rotation around Oz in degrees
float diag = std::sqrt(static_cast<float>(srcImage.cols * srcImage.cols + srcImage.rows * srcImage.rows)); float diag = std::sqrt(static_cast<float>(srcImage.cols * srcImage.cols + srcImage.rows * srcImage.rows));
Mat LUShift = Mat::eye(3, 3, CV_32FC1); // left up Mat LUShift = Mat::eye(3, 3, CV_32FC1); // left up
LUShift.at<float>(0,2) = -srcImage.cols/2; LUShift.at<float>(0,2) = -srcImage.cols/2;
@ -85,6 +85,32 @@ Mat rotateImage(const Mat& srcImage, float angle, Mat& dstImage, Mat& dstMask)
return H; return H;
} }
void rotateKeyPoints(const vector<KeyPoint>& src, const Mat& H, float angle, vector<KeyPoint>& dst)
{
// suppose that H is rotation given from rotateImage() and angle has value passed to rotateImage()
vector<Point2f> srcCenters, dstCenters;
KeyPoint::convert(src, srcCenters);
perspectiveTransform(srcCenters, dstCenters, H);
dst = src;
for(size_t i = 0; i < dst.size(); i++)
{
dst[i].pt = dstCenters[i];
float dstAngle = src[i].angle + angle;
if(dstAngle >= 360.f)
dstAngle -= 360.f;
dst[i].angle = dstAngle;
}
}
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);
}
static static
float calcCirclesIntersectArea(const Point2f& p0, float r0, const Point2f& p1, float r1) float calcCirclesIntersectArea(const Point2f& p0, float r0, const Point2f& p1, float r1)
{ {
@ -119,45 +145,45 @@ float calcIntersectRatio(const Point2f& p0, float r0, const Point2f& p1, float r
return intersectArea / unionArea; return intersectArea / unionArea;
} }
static static
void matchKeyPoints(const vector<KeyPoint>& keypoints0, const Mat& H, void matchKeyPoints(const vector<KeyPoint>& keypoints0, const Mat& H,
const vector<KeyPoint>& keypoints1, const vector<KeyPoint>& keypoints1,
vector<DMatch>& matches) vector<DMatch>& matches)
{ {
vector<Point2f> points0; vector<Point2f> points0;
KeyPoint::convert(keypoints0, points0); KeyPoint::convert(keypoints0, points0);
Mat points0t; Mat points0t;
if(H.empty()) if(H.empty())
points0t = Mat(points0); points0t = Mat(points0);
else else
perspectiveTransform(Mat(points0), points0t, H); perspectiveTransform(Mat(points0), points0t, H);
matches.clear(); matches.clear();
vector<uchar> usedMask(keypoints1.size(), 0); vector<uchar> usedMask(keypoints1.size(), 0);
for(size_t i0 = 0; i0 < keypoints0.size(); i0++) for(size_t i0 = 0; i0 < keypoints0.size(); i0++)
{ {
int nearestPointIndex = -1; int nearestPointIndex = -1;
float maxIntersectRatio = 0.f; float maxIntersectRatio = 0.f;
const float r0 = 0.5f * keypoints0[i0].size; const float r0 = 0.5f * keypoints0[i0].size;
for(size_t i1 = 0; i1 < keypoints1.size(); i1++) for(size_t i1 = 0; i1 < keypoints1.size(); i1++)
{ {
if(nearestPointIndex >= 0 && usedMask[i1]) if(nearestPointIndex >= 0 && usedMask[i1])
continue; continue;
float r1 = 0.5f * keypoints1[i1].size; float r1 = 0.5f * keypoints1[i1].size;
float intersectRatio = calcIntersectRatio(points0t.at<Point2f>(i0), r0, float intersectRatio = calcIntersectRatio(points0t.at<Point2f>(i0), r0,
keypoints1[i1].pt, r1); keypoints1[i1].pt, r1);
if(intersectRatio > maxIntersectRatio) if(intersectRatio > maxIntersectRatio)
{ {
maxIntersectRatio = intersectRatio; maxIntersectRatio = intersectRatio;
nearestPointIndex = i1; nearestPointIndex = i1;
} }
} }
matches.push_back(DMatch(i0, nearestPointIndex, maxIntersectRatio)); matches.push_back(DMatch(i0, nearestPointIndex, maxIntersectRatio));
if(nearestPointIndex >= 0) if(nearestPointIndex >= 0)
usedMask[nearestPointIndex] = 1; usedMask[nearestPointIndex] = 1;
} }
} }
class DetectorRotationInvarianceTest : public cvtest::BaseTest class DetectorRotationInvarianceTest : public cvtest::BaseTest
@ -166,134 +192,13 @@ public:
DetectorRotationInvarianceTest(const Ptr<FeatureDetector>& _featureDetector, DetectorRotationInvarianceTest(const Ptr<FeatureDetector>& _featureDetector,
float _minKeyPointMatchesRatio, float _minKeyPointMatchesRatio,
float _minAngleInliersRatio) : float _minAngleInliersRatio) :
featureDetector(_featureDetector), featureDetector(_featureDetector),
minKeyPointMatchesRatio(_minKeyPointMatchesRatio), minKeyPointMatchesRatio(_minKeyPointMatchesRatio),
minAngleInliersRatio(_minAngleInliersRatio) minAngleInliersRatio(_minAngleInliersRatio)
{ {
CV_Assert(!featureDetector.empty()); CV_Assert(!featureDetector.empty());
} }
protected:
void run(int)
{
const string imageFilename = string(ts->get_data_path()) + IMAGE_TSUKUBA;
// Read test data
Mat image0 = imread(imageFilename), image1, mask1;
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");
const int maxAngle = 360, angleStep = 15;
for(int angle = 0; angle < maxAngle; angle += angleStep)
{
Mat H = rotateImage(image0, 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;
if(angle0 == -1 || angle1 == -1)
CV_Error(CV_StsBadArg, "Given FeatureDetector is not rotation invariant, it can not be tested here.\n");
CV_Assert(angle0 >= 0.f && angle0 < 360.f);
CV_Assert(angle1 >= 0.f && 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));
CV_Assert(angleDiff >= 0.f);
bool isAngleCorrect = angleDiff < maxAngleDiff;
if(isAngleCorrect)
angleInliersCount++;
}
float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints0.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 angleInliersRatio = static_cast<float>(angleInliersCount) / keyPointMatchesCount;
if(angleInliersRatio < minAngleInliersRatio)
{
ts->printf(cvtest::TS::LOG, "Incorrect angleInliersRatio: curr = %f, min = %f.\n",
angleInliersRatio, minAngleInliersRatio);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return;
}
}
#if SHOW_DEBUG_LOG
std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio
<< " - angleInliersRatio " << static_cast<float>(angleInliersCount) / keyPointMatchesCount << std::endl;
#endif
}
ts->set_failed_test_info( cvtest::TS::OK );
}
Ptr<FeatureDetector> featureDetector;
float minKeyPointMatchesRatio;
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:
DescriptorRotationInvarianceTest(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: protected:
void run(int) void run(int)
@ -310,13 +215,9 @@ protected:
} }
vector<KeyPoint> keypoints0; vector<KeyPoint> keypoints0;
Mat descriptors0;
featureDetector->detect(image0, keypoints0); featureDetector->detect(image0, keypoints0);
if(keypoints0.size() < 15) if(keypoints0.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n"); CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
descriptorExtractor->compute(image0, keypoints0, descriptors0);
BFMatcher bfmatcher(normType);
const int maxAngle = 360, angleStep = 15; const int maxAngle = 360, angleStep = 15;
for(int angle = 0; angle < maxAngle; angle += angleStep) for(int angle = 0; angle < maxAngle; angle += angleStep)
@ -324,31 +225,42 @@ protected:
Mat H = rotateImage(image0, angle, image1, mask1); Mat H = rotateImage(image0, angle, image1, mask1);
vector<KeyPoint> keypoints1; vector<KeyPoint> keypoints1;
Mat descriptors1;
featureDetector->detect(image1, keypoints1, mask1); featureDetector->detect(image1, keypoints1, mask1);
descriptorExtractor->compute(image1, keypoints1, descriptors1);
vector<DMatch> descMatches; vector<DMatch> matches;
bfmatcher.match(descriptors0, descriptors1, descMatches); matchKeyPoints(keypoints0, H, keypoints1, matches);
vector<DMatch> keyPointMatches; int angleInliersCount = 0;
matchKeyPoints(keypoints0, H, keypoints1, keyPointMatches);
const float minIntersectRatio = 0.5f; const float minIntersectRatio = 0.5f;
int keyPointMatchesCount = 0; int keyPointMatchesCount = 0;
for(size_t m = 0; m < keyPointMatches.size(); m++) for(size_t m = 0; m < matches.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(matches[m].distance < minIntersectRatio)
if(keyPointMatches[queryIdx].distance >= minIntersectRatio && continue;
descMatches[m].trainIdx == keyPointMatches[queryIdx].trainIdx)
descInliersCount++; 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;
if(angle0 == -1 || angle1 == -1)
CV_Error(CV_StsBadArg, "Given FeatureDetector is not rotation invariant, it can not be tested here.\n");
CV_Assert(angle0 >= 0.f && angle0 < 360.f);
CV_Assert(angle1 >= 0.f && 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));
CV_Assert(angleDiff >= 0.f);
bool isAngleCorrect = angleDiff < maxAngleDiff;
if(isAngleCorrect)
angleInliersCount++;
}
float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints0.size(); float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints0.size();
if(keyPointMatchesRatio < minKeyPointMatchesRatio) if(keyPointMatchesRatio < minKeyPointMatchesRatio)
@ -359,31 +271,115 @@ protected:
return; return;
} }
if(keyPointMatchesCount) if(keyPointMatchesCount)
{ {
float descInliersRatio = static_cast<float>(descInliersCount) / keyPointMatchesCount; float angleInliersRatio = static_cast<float>(angleInliersCount) / keyPointMatchesCount;
if(descInliersRatio < minDescInliersRatio) if(angleInliersRatio < minAngleInliersRatio)
{ {
ts->printf(cvtest::TS::LOG, "Incorrect descInliersRatio: curr = %f, min = %f.\n", ts->printf(cvtest::TS::LOG, "Incorrect angleInliersRatio: curr = %f, min = %f.\n",
descInliersRatio, minDescInliersRatio); angleInliersRatio, minAngleInliersRatio);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY); ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return; return;
} }
} }
#if SHOW_DEBUG_LOG #if SHOW_DEBUG_LOG
std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio
<< " - descInliersRatio " << static_cast<float>(descInliersCount) / keyPointMatchesCount << std::endl; << " - angleInliersRatio " << static_cast<float>(angleInliersCount) / keyPointMatchesCount << std::endl;
#endif #endif
} }
ts->set_failed_test_info( cvtest::TS::OK ); ts->set_failed_test_info( cvtest::TS::OK );
} }
Ptr<FeatureDetector> featureDetector; Ptr<FeatureDetector> featureDetector;
Ptr<DescriptorExtractor> descriptorExtractor; float minKeyPointMatchesRatio;
float minAngleInliersRatio;
};
class DescriptorRotationInvarianceTest : public cvtest::BaseTest
{
public:
DescriptorRotationInvarianceTest(const Ptr<FeatureDetector>& _featureDetector,
const Ptr<DescriptorExtractor>& _descriptorExtractor,
int _normType,
float _minDescInliersRatio) :
featureDetector(_featureDetector),
descriptorExtractor(_descriptorExtractor),
normType(_normType),
minDescInliersRatio(_minDescInliersRatio)
{
CV_Assert(!featureDetector.empty());
CV_Assert(!descriptorExtractor.empty());
}
protected:
void run(int)
{
const string imageFilename = string(ts->get_data_path()) + IMAGE_TSUKUBA;
// Read test data
Mat image0 = imread(imageFilename), image1, mask1;
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;
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);
BFMatcher bfmatcher(normType);
const float minIntersectRatio = 0.5f;
const int maxAngle = 360, angleStep = 15;
for(int angle = 0; angle < maxAngle; angle += angleStep)
{
Mat H = rotateImage(image0, angle, image1, mask1);
vector<KeyPoint> keypoints1;
rotateKeyPoints(keypoints0, H, angle, keypoints1);
Mat descriptors1;
descriptorExtractor->compute(image1, keypoints1, descriptors1);
vector<DMatch> descMatches;
bfmatcher.match(descriptors0, descriptors1, descMatches);
int descInliersCount = 0;
for(size_t m = 0; m < descMatches.size(); m++)
{
const KeyPoint& transformed_p0 = keypoints1[descMatches[m].queryIdx];
const KeyPoint& p1 = keypoints1[descMatches[m].trainIdx];
if(calcIntersectRatio(transformed_p0.pt, 0.5f * transformed_p0.size,
p1.pt, 0.5f * p1.size) >= minIntersectRatio)
{
descInliersCount++;
}
}
float descInliersRatio = static_cast<float>(descInliersCount) / keypoints0.size();
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 << "descInliersRatio " << static_cast<float>(descInliersCount) / keypoints0.size() << std::endl;
#endif
}
ts->set_failed_test_info( cvtest::TS::OK );
}
Ptr<FeatureDetector> featureDetector;
Ptr<DescriptorExtractor> descriptorExtractor;
int normType; int normType;
float minKeyPointMatchesRatio; float minDescInliersRatio;
float minDescInliersRatio;
}; };
class DetectorScaleInvarianceTest : public cvtest::BaseTest class DetectorScaleInvarianceTest : public cvtest::BaseTest
@ -392,9 +388,9 @@ public:
DetectorScaleInvarianceTest(const Ptr<FeatureDetector>& _featureDetector, DetectorScaleInvarianceTest(const Ptr<FeatureDetector>& _featureDetector,
float _minKeyPointMatchesRatio, float _minKeyPointMatchesRatio,
float _minScaleInliersRatio) : float _minScaleInliersRatio) :
featureDetector(_featureDetector), featureDetector(_featureDetector),
minKeyPointMatchesRatio(_minKeyPointMatchesRatio), minKeyPointMatchesRatio(_minKeyPointMatchesRatio),
minScaleInliersRatio(_minScaleInliersRatio) minScaleInliersRatio(_minScaleInliersRatio)
{ {
CV_Assert(!featureDetector.empty()); CV_Assert(!featureDetector.empty());
} }
@ -403,7 +399,7 @@ protected:
void run(int) void run(int)
{ {
const string imageFilename = string(ts->get_data_path()) + IMAGE_BIKES; const string imageFilename = string(ts->get_data_path()) + IMAGE_BIKES;
// Read test data // Read test data
Mat image0 = imread(imageFilename); Mat image0 = imread(imageFilename);
@ -417,58 +413,59 @@ protected:
vector<KeyPoint> keypoints0; vector<KeyPoint> keypoints0;
featureDetector->detect(image0, keypoints0); featureDetector->detect(image0, keypoints0);
if(keypoints0.size() < 15) if(keypoints0.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n"); CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
for(int scale = 2; scale <= 4; scale++) for(float scaleIdx = 1; scaleIdx <= 3; scaleIdx++)
{ {
Mat image1; float scale = 1.f + scaleIdx * 0.5f;
resize(image0, image1, Size(), 1./scale, 1./scale); Mat image1;
resize(image0, image1, Size(), 1./scale, 1./scale);
vector<KeyPoint> keypoints1, osiKeypoints1; // osi - original size image vector<KeyPoint> keypoints1, osiKeypoints1; // osi - original size image
featureDetector->detect(image1, keypoints1); featureDetector->detect(image1, keypoints1);
if(keypoints1.size() < 15) if(keypoints1.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n"); CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
if(keypoints1.size() > keypoints0.size()) if(keypoints1.size() > keypoints0.size())
{ {
ts->printf(cvtest::TS::LOG, "Strange behavior of the detector. " ts->printf(cvtest::TS::LOG, "Strange behavior of the detector. "
"It gives more points count in an image of the smaller size.\n" "It gives more points count in an image of the smaller size.\n"
"original size (%d, %d), keypoints count = %d\n" "original size (%d, %d), keypoints count = %d\n"
"reduced size (%d, %d), keypoints count = %d\n", "reduced size (%d, %d), keypoints count = %d\n",
image0.cols, image0.rows, keypoints0.size(), image0.cols, image0.rows, keypoints0.size(),
image1.cols, image1.rows, keypoints1.size()); image1.cols, image1.rows, keypoints1.size());
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT); ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return; return;
} }
scaleKeyPoints(keypoints1, osiKeypoints1, scale); scaleKeyPoints(keypoints1, osiKeypoints1, scale);
vector<DMatch> matches; vector<DMatch> matches;
// image1 is query image (it's reduced image0) // image1 is query image (it's reduced image0)
// image0 is train image // image0 is train image
matchKeyPoints(osiKeypoints1, Mat(), keypoints0, matches); matchKeyPoints(osiKeypoints1, Mat(), keypoints0, matches);
const float minIntersectRatio = 0.5f; const float minIntersectRatio = 0.5f;
int keyPointMatchesCount = 0; int keyPointMatchesCount = 0;
int scaleInliersCount = 0; int scaleInliersCount = 0;
for(size_t m = 0; m < matches.size(); m++) for(size_t m = 0; m < matches.size(); m++)
{ {
if(matches[m].distance < minIntersectRatio) if(matches[m].distance < minIntersectRatio)
continue; continue;
keyPointMatchesCount++; keyPointMatchesCount++;
// Check does this inlier have consistent sizes // Check does this inlier have consistent sizes
const float maxSizeDiff = 0.8;//0.9f; // grad const float maxSizeDiff = 0.8;//0.9f; // grad
float size0 = keypoints0[matches[m].trainIdx].size; float size0 = keypoints0[matches[m].trainIdx].size;
float size1 = osiKeypoints1[matches[m].queryIdx].size; float size1 = osiKeypoints1[matches[m].queryIdx].size;
CV_Assert(size0 > 0 && size1 > 0); CV_Assert(size0 > 0 && size1 > 0);
if(std::min(size0, size1) > maxSizeDiff * std::max(size0, size1)) if(std::min(size0, size1) > maxSizeDiff * std::max(size0, size1))
scaleInliersCount++; scaleInliersCount++;
} }
float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints1.size(); float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints1.size();
if(keyPointMatchesRatio < minKeyPointMatchesRatio) if(keyPointMatchesRatio < minKeyPointMatchesRatio)
{ {
ts->printf(cvtest::TS::LOG, "Incorrect keyPointMatchesRatio: curr = %f, min = %f.\n", ts->printf(cvtest::TS::LOG, "Incorrect keyPointMatchesRatio: curr = %f, min = %f.\n",
@ -477,9 +474,9 @@ protected:
return; return;
} }
if(keyPointMatchesCount) if(keyPointMatchesCount)
{ {
float scaleInliersRatio = static_cast<float>(scaleInliersCount) / keyPointMatchesCount; float scaleInliersRatio = static_cast<float>(scaleInliersCount) / keyPointMatchesCount;
if(scaleInliersRatio < minScaleInliersRatio) if(scaleInliersRatio < minScaleInliersRatio)
{ {
ts->printf(cvtest::TS::LOG, "Incorrect scaleInliersRatio: curr = %f, min = %f.\n", ts->printf(cvtest::TS::LOG, "Incorrect scaleInliersRatio: curr = %f, min = %f.\n",
@ -490,7 +487,7 @@ protected:
} }
#if SHOW_DEBUG_LOG #if SHOW_DEBUG_LOG
std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio
<< " - scaleInliersRatio " << static_cast<float>(scaleInliersCount) / keyPointMatchesCount << std::endl; << " - scaleInliersRatio " << static_cast<float>(scaleInliersCount) / keyPointMatchesCount << std::endl;
#endif #endif
} }
ts->set_failed_test_info( cvtest::TS::OK ); ts->set_failed_test_info( cvtest::TS::OK );
@ -505,25 +502,23 @@ class DescriptorScaleInvarianceTest : public cvtest::BaseTest
{ {
public: public:
DescriptorScaleInvarianceTest(const Ptr<FeatureDetector>& _featureDetector, DescriptorScaleInvarianceTest(const Ptr<FeatureDetector>& _featureDetector,
const Ptr<DescriptorExtractor>& _descriptorExtractor, const Ptr<DescriptorExtractor>& _descriptorExtractor,
int _normType, int _normType,
float _minKeyPointMatchesRatio,
float _minDescInliersRatio) : float _minDescInliersRatio) :
featureDetector(_featureDetector), featureDetector(_featureDetector),
descriptorExtractor(_descriptorExtractor), descriptorExtractor(_descriptorExtractor),
normType(_normType), normType(_normType),
minKeyPointMatchesRatio(_minKeyPointMatchesRatio), minDescInliersRatio(_minDescInliersRatio)
minDescInliersRatio(_minDescInliersRatio)
{ {
CV_Assert(!featureDetector.empty()); CV_Assert(!featureDetector.empty());
CV_Assert(!descriptorExtractor.empty()); CV_Assert(!descriptorExtractor.empty());
} }
protected: protected:
void run(int) void run(int)
{ {
const string imageFilename = string(ts->get_data_path()) + IMAGE_BIKES; const string imageFilename = string(ts->get_data_path()) + IMAGE_BIKES;
// Read test data // Read test data
Mat image0 = imread(imageFilename); Mat image0 = imread(imageFilename);
@ -536,102 +531,71 @@ protected:
vector<KeyPoint> keypoints0; vector<KeyPoint> keypoints0;
featureDetector->detect(image0, keypoints0); featureDetector->detect(image0, keypoints0);
if(keypoints0.size() < 15) if(keypoints0.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n"); CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
Mat descriptors0; Mat descriptors0;
descriptorExtractor->compute(image0, keypoints0, descriptors0); descriptorExtractor->compute(image0, keypoints0, descriptors0);
BFMatcher bfmatcher(normType); BFMatcher bfmatcher(normType);
for(int scale = 2; scale <= 4; scale++) for(float scaleIdx = 1; scaleIdx <= 3; scaleIdx++)
{ {
Mat image1; float scale = 1.f + scaleIdx * 0.5f;
resize(image0, image1, Size(), 1./scale, 1./scale);
vector<KeyPoint> keypoints1, osiKeypoints1; // osi - original size image Mat image1;
featureDetector->detect(image1, keypoints1); resize(image0, image1, Size(), 1./scale, 1./scale);
if(keypoints1.size() < 15)
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n"); vector<KeyPoint> keypoints1;
if(keypoints1.size() > keypoints0.size() ) scaleKeyPoints(keypoints0, keypoints1, 1./scale);
{ Mat descriptors1;
ts->printf(cvtest::TS::LOG, "Strange behavior of the detector. " descriptorExtractor->compute(image1, keypoints1, descriptors1);
"It gives more points count in an image of the smaller size.\n"
"original size (%d, %d), keypoints count = %d\n" vector<DMatch> descMatches;
"reduced size (%d, %d), keypoints count = %d\n", bfmatcher.match(descriptors0, descriptors1, descMatches);
image0.cols, image0.rows, keypoints0.size(),
image1.cols, image1.rows, keypoints1.size()); const float minIntersectRatio = 0.5f;
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT); int descInliersCount = 0;
return; for(size_t m = 0; m < descMatches.size(); m++)
{
const KeyPoint& transformed_p0 = keypoints0[descMatches[m].queryIdx];
const KeyPoint& p1 = keypoints0[descMatches[m].trainIdx];
if(calcIntersectRatio(transformed_p0.pt, 0.5f * transformed_p0.size,
p1.pt, 0.5f * p1.size) >= minIntersectRatio)
{
descInliersCount++;
}
} }
Mat descriptors1; float descInliersRatio = static_cast<float>(descInliersCount) / keypoints0.size();
descriptorExtractor->compute(image1, keypoints1, descriptors1); if(descInliersRatio < minDescInliersRatio)
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; ts->printf(cvtest::TS::LOG, "Incorrect descInliersRatio: curr = %f, min = %f.\n",
if(keyPointMatches[queryIdx].distance >= minIntersectRatio && descInliersRatio, minDescInliersRatio);
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); ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return; 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 #if SHOW_DEBUG_LOG
std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio std::cout << "descInliersRatio " << static_cast<float>(descInliersCount) / keypoints0.size() << std::endl;
<< " - descInliersRatio " << static_cast<float>(descInliersCount) / keyPointMatchesCount << std::endl;
#endif #endif
} }
ts->set_failed_test_info( cvtest::TS::OK ); ts->set_failed_test_info( cvtest::TS::OK );
} }
Ptr<FeatureDetector> featureDetector; Ptr<FeatureDetector> featureDetector;
Ptr<DescriptorExtractor> descriptorExtractor; Ptr<DescriptorExtractor> descriptorExtractor;
int normType; int normType;
float minKeyPointMatchesRatio; float minKeyPointMatchesRatio;
float minDescInliersRatio; float minDescInliersRatio;
}; };
// Tests registration // Tests registration
// Detector's rotation invariance check /*
* Detector's rotation invariance check
*/
TEST(Features2d_RotationInvariance_Detector_SURF, regression) TEST(Features2d_RotationInvariance_Detector_SURF, regression)
{ {
DetectorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SURF"), DetectorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SURF"),
0.44f, 0.45f,
0.76f); 0.76f);
test.safe_run(); test.safe_run();
} }
@ -639,19 +603,20 @@ TEST(Features2d_RotationInvariance_Detector_SURF, regression)
TEST(Features2d_RotationInvariance_Detector_SIFT, regression) TEST(Features2d_RotationInvariance_Detector_SIFT, regression)
{ {
DetectorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"), DetectorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"),
0.64f, 0.75f,
0.74f); 0.76f);
test.safe_run(); test.safe_run();
} }
// Descriptors's rotation invariance check /*
* Descriptors's rotation invariance check
*/
TEST(Features2d_RotationInvariance_Descriptor_SURF, regression) TEST(Features2d_RotationInvariance_Descriptor_SURF, regression)
{ {
DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SURF"), DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SURF"),
Algorithm::create<DescriptorExtractor>("Feature2D.SURF"), Algorithm::create<DescriptorExtractor>("Feature2D.SURF"),
NORM_L1, NORM_L1,
0.44f, 0.83f);
0.63f);
test.safe_run(); test.safe_run();
} }
@ -660,45 +625,46 @@ TEST(Features2d_RotationInvariance_Descriptor_SIFT, regression)
DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"), DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"),
Algorithm::create<DescriptorExtractor>("Feature2D.SIFT"), Algorithm::create<DescriptorExtractor>("Feature2D.SIFT"),
NORM_L1, NORM_L1,
0.64f, 0.98f);
0.72f);
test.safe_run(); test.safe_run();
} }
// Detector's scale invariance check /*
* Detector's scale invariance check
*/
TEST(Features2d_ScaleInvariance_Detector_SURF, regression) TEST(Features2d_ScaleInvariance_Detector_SURF, regression)
{ {
DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SURF"), DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SURF"),
0.62f, 0.64f,
0.68f); 0.84f);
test.safe_run(); test.safe_run();
} }
TEST(Features2d_ScaleInvariance_Detector_SIFT, regression) TEST(Features2d_ScaleInvariance_Detector_SIFT, regression)
{ {
DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"), DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"),
0.59f, 0.69f,
0.94f); 0.99f);
test.safe_run(); test.safe_run();
} }
// Descriptor's scale invariance check /*
* Descriptor's scale invariance check
*/
TEST(Features2d_ScaleInvariance_Descriptor_SURF, regression) TEST(Features2d_ScaleInvariance_Descriptor_SURF, regression)
{ {
DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SURF"), DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SURF"),
Algorithm::create<DescriptorExtractor>("Feature2D.SURF"), Algorithm::create<DescriptorExtractor>("Feature2D.SURF"),
NORM_L1, NORM_L1,
0.62f, 0.61f);
0.68f);
test.safe_run(); test.safe_run();
} }
TEST(Features2d_ScaleInvariance_Descriptor_SIFT, regression) //TEST(Features2d_ScaleInvariance_Descriptor_SIFT, regression)
{ //{
DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"), // DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"),
Algorithm::create<DescriptorExtractor>("Feature2D.SIFT"), // Algorithm::create<DescriptorExtractor>("Feature2D.SIFT"),
NORM_L1, // NORM_L1,
0.59f, // 0.14f);
0.78f); // test.safe_run();
test.safe_run(); //}
}