// 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" namespace opencv_test { namespace { #define SHOW_DEBUG_LOG 1 typedef tuple, Ptr, float> String_FeatureDetector_DescriptorExtractor_Float_t; static void SetSuitableSIFTOctave(vector& 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& src, const Mat& H, float angle, vector& dst) { // suppose that H is rotation given from rotateImage() and angle has value passed to rotateImage() vector 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 { 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; Ptr 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 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(angle), image1, mask1); vector keypoints1; rotateKeyPoints(keypoints0, H, static_cast(angle), keypoints1); Mat descriptors1; descriptorExtractor->compute(image1, keypoints1, descriptors1); vector 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(descInliersCount) / keypoints0.size(); EXPECT_GE(descInliersRatio, minInliersRatio); #if SHOW_DEBUG_LOG std::cout << "angle = " << angle << ", inliers = " << descInliersCount << ", descInliersRatio = " << static_cast(descInliersCount) / keypoints0.size() << std::endl; #endif } } TEST_P(DescriptorScaleInvariance, scale) { vector 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 keypoints1; scaleKeyPoints(keypoints0, keypoints1, 1.0f/scale); if (featureDetector->getDefaultName() == "Feature2D.SIFT") { SetSuitableSIFTOctave(keypoints1); } Mat descriptors1; descriptorExtractor->compute(image1, keypoints1, descriptors1); vector 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(descInliersCount) / keypoints0.size(); EXPECT_GE(descInliersRatio, minInliersRatio); #if SHOW_DEBUG_LOG std::cout << "scale = " << scale << ", inliers = " << descInliersCount << ", descInliersRatio = " << static_cast(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