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198 lines
6.6 KiB
198 lines
6.6 KiB
// This file is part of OpenCV project. |
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// It is subject to the license terms in the LICENSE file found in the top-level directory |
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// of this distribution and at http://opencv.org/license.html |
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#include "test_invariance_utils.hpp" |
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namespace opencv_test { namespace { |
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#define SHOW_DEBUG_LOG 1 |
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typedef tuple<std::string, Ptr<FeatureDetector>, Ptr<DescriptorExtractor>, 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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// suppose that H is rotation given from rotateImage() and angle has value passed to rotateImage() |
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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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// Read test data |
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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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}} // namespace |
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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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} // namespace
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