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| #include "test_invariance_utils.hpp"
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| #include <functional>
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| namespace opencv_test { namespace {
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| #define SHOW_DEBUG_LOG 1
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| typedef std::function<cv::Ptr<cv::FeatureDetector>()> DetectorFactory;
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| typedef std::function<cv::Ptr<cv::DescriptorExtractor>()> ExtractorFactory;
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| typedef tuple<std::string, DetectorFactory, ExtractorFactory, float>
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| String_FeatureDetector_DescriptorExtractor_Float_t;
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| static
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| void SetSuitableSIFTOctave(vector<KeyPoint>& keypoints,
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| int firstOctave = -1, int nOctaveLayers = 3, double sigma = 1.6)
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| {
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| for (size_t i = 0; i < keypoints.size(); i++ )
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| {
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| int octv, layer;
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| KeyPoint& kpt = keypoints[i];
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| double octv_layer = std::log(kpt.size / sigma) / std::log(2.) - 1;
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| octv = cvFloor(octv_layer);
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| layer = cvRound( (octv_layer - octv) * nOctaveLayers );
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| if (octv < firstOctave)
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| {
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| octv = firstOctave;
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| layer = 0;
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| }
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| kpt.octave = (layer << 8) | (octv & 255);
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| }
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| }
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| static
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| void rotateKeyPoints(const vector<KeyPoint>& src, const Mat& H, float angle, vector<KeyPoint>& dst)
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| {
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| vector<Point2f> srcCenters, dstCenters;
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| KeyPoint::convert(src, srcCenters);
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| perspectiveTransform(srcCenters, dstCenters, H);
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| dst = src;
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| for(size_t i = 0; i < dst.size(); i++)
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| {
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| dst[i].pt = dstCenters[i];
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| float dstAngle = src[i].angle + angle;
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| if(dstAngle >= 360.f)
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| dstAngle -= 360.f;
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| dst[i].angle = dstAngle;
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| }
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| }
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| class DescriptorInvariance : public TestWithParam<String_FeatureDetector_DescriptorExtractor_Float_t>
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| {
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| protected:
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| virtual void SetUp() {
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| const std::string filename = cvtest::TS::ptr()->get_data_path() + get<0>(GetParam());
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| image0 = imread(filename);
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| ASSERT_FALSE(image0.empty()) << "couldn't read input image";
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| featureDetector = get<1>(GetParam())();
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| descriptorExtractor = get<2>(GetParam())();
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| minInliersRatio = get<3>(GetParam());
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| }
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| Ptr<FeatureDetector> featureDetector;
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| Ptr<DescriptorExtractor> descriptorExtractor;
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| float minInliersRatio;
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| Mat image0;
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| };
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| typedef DescriptorInvariance DescriptorScaleInvariance;
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| typedef DescriptorInvariance DescriptorRotationInvariance;
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| TEST_P(DescriptorRotationInvariance, rotation)
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| {
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| Mat image1, mask1;
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| const int borderSize = 16;
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| Mat mask0(image0.size(), CV_8UC1, Scalar(0));
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| mask0(Rect(borderSize, borderSize, mask0.cols - 2*borderSize, mask0.rows - 2*borderSize)).setTo(Scalar(255));
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| vector<KeyPoint> keypoints0;
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| Mat descriptors0;
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| featureDetector->detect(image0, keypoints0, mask0);
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| std::cout << "Keypoints: " << keypoints0.size() << std::endl;
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| EXPECT_GE(keypoints0.size(), 15u);
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| descriptorExtractor->compute(image0, keypoints0, descriptors0);
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| BFMatcher bfmatcher(descriptorExtractor->defaultNorm());
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| const float minIntersectRatio = 0.5f;
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| const int maxAngle = 360, angleStep = 15;
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| for(int angle = 0; angle < maxAngle; angle += angleStep)
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| {
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| Mat H = rotateImage(image0, mask0, static_cast<float>(angle), image1, mask1);
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| vector<KeyPoint> keypoints1;
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| rotateKeyPoints(keypoints0, H, static_cast<float>(angle), keypoints1);
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| Mat descriptors1;
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| descriptorExtractor->compute(image1, keypoints1, descriptors1);
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| vector<DMatch> descMatches;
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| bfmatcher.match(descriptors0, descriptors1, descMatches);
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| int descInliersCount = 0;
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| for(size_t m = 0; m < descMatches.size(); m++)
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| {
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| const KeyPoint& transformed_p0 = keypoints1[descMatches[m].queryIdx];
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| const KeyPoint& p1 = keypoints1[descMatches[m].trainIdx];
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| if(calcIntersectRatio(transformed_p0.pt, 0.5f * transformed_p0.size,
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| p1.pt, 0.5f * p1.size) >= minIntersectRatio)
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| {
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| descInliersCount++;
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| }
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| }
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| float descInliersRatio = static_cast<float>(descInliersCount) / keypoints0.size();
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| EXPECT_GE(descInliersRatio, minInliersRatio);
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| #if SHOW_DEBUG_LOG
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| std::cout
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| << "angle = " << angle
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| << ", inliers = " << descInliersCount
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| << ", descInliersRatio = " << static_cast<float>(descInliersCount) / keypoints0.size()
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| << std::endl;
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| #endif
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| }
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| }
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| TEST_P(DescriptorScaleInvariance, scale)
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| {
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| vector<KeyPoint> keypoints0;
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| featureDetector->detect(image0, keypoints0);
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| std::cout << "Keypoints: " << keypoints0.size() << std::endl;
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| EXPECT_GE(keypoints0.size(), 15u);
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| Mat descriptors0;
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| descriptorExtractor->compute(image0, keypoints0, descriptors0);
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| BFMatcher bfmatcher(descriptorExtractor->defaultNorm());
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| for(int scaleIdx = 1; scaleIdx <= 3; scaleIdx++)
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| {
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| float scale = 1.f + scaleIdx * 0.5f;
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| Mat image1;
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| resize(image0, image1, Size(), 1./scale, 1./scale, INTER_LINEAR_EXACT);
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| vector<KeyPoint> keypoints1;
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| scaleKeyPoints(keypoints0, keypoints1, 1.0f/scale);
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| if (featureDetector->getDefaultName() == "Feature2D.SIFT")
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| {
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| SetSuitableSIFTOctave(keypoints1);
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| }
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| Mat descriptors1;
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| descriptorExtractor->compute(image1, keypoints1, descriptors1);
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| vector<DMatch> descMatches;
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| bfmatcher.match(descriptors0, descriptors1, descMatches);
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| const float minIntersectRatio = 0.5f;
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| int descInliersCount = 0;
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| for(size_t m = 0; m < descMatches.size(); m++)
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| {
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| const KeyPoint& transformed_p0 = keypoints0[descMatches[m].queryIdx];
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| const KeyPoint& p1 = keypoints0[descMatches[m].trainIdx];
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| if(calcIntersectRatio(transformed_p0.pt, 0.5f * transformed_p0.size,
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| p1.pt, 0.5f * p1.size) >= minIntersectRatio)
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| {
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| descInliersCount++;
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| }
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| }
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| float descInliersRatio = static_cast<float>(descInliersCount) / keypoints0.size();
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| EXPECT_GE(descInliersRatio, minInliersRatio);
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| #if SHOW_DEBUG_LOG
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| std::cout
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| << "scale = " << scale
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| << ", inliers = " << descInliersCount
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| << ", descInliersRatio = " << static_cast<float>(descInliersCount) / keypoints0.size()
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| << std::endl;
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| #endif
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| }
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| }
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| #undef SHOW_DEBUG_LOG
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| }}
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| namespace std {
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| using namespace opencv_test;
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| static inline void PrintTo(const String_FeatureDetector_DescriptorExtractor_Float_t& v, std::ostream* os)
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| {
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| *os << "(\"" << get<0>(v)
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| << "\", " << get<3>(v)
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| << ")";
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| }
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| }
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