Open Source Computer Vision Library https://opencv.org/
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// 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_invariance_utils.hpp"
#include <functional>
namespace opencv_test { namespace {
#define SHOW_DEBUG_LOG 1
// NOTE: using factory function (function<Ptr<Type>()>) instead of object instance (Ptr<Type>) as a
// test parameter, because parameters exist during whole test program run and consume a lot of memory
typedef std::function<cv::Ptr<cv::FeatureDetector>()> DetectorFactory;
typedef std::function<cv::Ptr<cv::DescriptorExtractor>()> ExtractorFactory;
typedef tuple<std::string, DetectorFactory, ExtractorFactory, float>
String_FeatureDetector_DescriptorExtractor_Float_t;
static
void SetSuitableSIFTOctave(vector<KeyPoint>& keypoints,
int firstOctave = -1, int nOctaveLayers = 3, double sigma = 1.6)
{
for (size_t i = 0; i < keypoints.size(); i++ )
{
int octv, layer;
KeyPoint& kpt = keypoints[i];
double octv_layer = std::log(kpt.size / sigma) / std::log(2.) - 1;
octv = cvFloor(octv_layer);
layer = cvRound( (octv_layer - octv) * nOctaveLayers );
if (octv < firstOctave)
{
octv = firstOctave;
layer = 0;
}
kpt.octave = (layer << 8) | (octv & 255);
}
}
static
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;
}
}
class DescriptorInvariance : public TestWithParam<String_FeatureDetector_DescriptorExtractor_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())();
descriptorExtractor = get<2>(GetParam())();
minInliersRatio = get<3>(GetParam());
}
Ptr<FeatureDetector> featureDetector;
Ptr<DescriptorExtractor> descriptorExtractor;
float minInliersRatio;
Mat image0;
};
typedef DescriptorInvariance DescriptorScaleInvariance;
typedef DescriptorInvariance DescriptorRotationInvariance;
TEST_P(DescriptorRotationInvariance, 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;
Mat descriptors0;
featureDetector->detect(image0, keypoints0, mask0);
std::cout << "Keypoints: " << keypoints0.size() << std::endl;
EXPECT_GE(keypoints0.size(), 15u);
descriptorExtractor->compute(image0, keypoints0, descriptors0);
BFMatcher bfmatcher(descriptorExtractor->defaultNorm());
const float minIntersectRatio = 0.5f;
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;
rotateKeyPoints(keypoints0, H, static_cast<float>(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();
EXPECT_GE(descInliersRatio, minInliersRatio);
#if SHOW_DEBUG_LOG
std::cout
<< "angle = " << angle
<< ", inliers = " << descInliersCount
<< ", descInliersRatio = " << static_cast<float>(descInliersCount) / keypoints0.size()
<< std::endl;
#endif
}
}
TEST_P(DescriptorScaleInvariance, scale)
{
vector<KeyPoint> keypoints0;
featureDetector->detect(image0, keypoints0);
std::cout << "Keypoints: " << keypoints0.size() << std::endl;
EXPECT_GE(keypoints0.size(), 15u);
Mat descriptors0;
descriptorExtractor->compute(image0, keypoints0, descriptors0);
BFMatcher bfmatcher(descriptorExtractor->defaultNorm());
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;
scaleKeyPoints(keypoints0, keypoints1, 1.0f/scale);
if (featureDetector->getDefaultName() == "Feature2D.SIFT")
{
SetSuitableSIFTOctave(keypoints1);
}
Mat descriptors1;
descriptorExtractor->compute(image1, keypoints1, descriptors1);
vector<DMatch> descMatches;
bfmatcher.match(descriptors0, descriptors1, descMatches);
const float minIntersectRatio = 0.5f;
int descInliersCount = 0;
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++;
}
}
float descInliersRatio = static_cast<float>(descInliersCount) / keypoints0.size();
EXPECT_GE(descInliersRatio, minInliersRatio);
#if SHOW_DEBUG_LOG
std::cout
<< "scale = " << scale
<< ", inliers = " << descInliersCount
<< ", descInliersRatio = " << static_cast<float>(descInliersCount) / keypoints0.size()
<< std::endl;
#endif
}
}
#undef SHOW_DEBUG_LOG
}} // namespace
namespace std {
using namespace opencv_test;
static inline void PrintTo(const String_FeatureDetector_DescriptorExtractor_Float_t& v, std::ostream* os)
{
*os << "(\"" << get<0>(v)
<< "\", " << get<3>(v)
<< ")";
}
} // namespace