mirror of
https://github.com/opencv/opencv.git
synced 2024-11-24 19:20:28 +08:00
added tests on scale invariance of detectors and descriptors
This commit is contained in:
Maria Dimashova
parent
dc68a56bab
commit
ec23d9bb5e
@ -45,8 +45,8 @@
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using namespace std;
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using namespace cv;
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const string FEATURES2D_DIR = "features2d";
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const string IMAGE_FILENAME = "tsukuba.png";
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const string IMAGE_TSUKUBA = "/features2d/tsukuba.png";
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const string IMAGE_BIKES = "/detectors_descriptors_evaluation/images_datasets/bikes/img1.png";
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#define SHOW_DEBUG_LOG 0
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@ -127,14 +127,17 @@ void matchKeyPoints(const vector<KeyPoint>& keypoints0, const Mat& H,
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vector<Point2f> points0;
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KeyPoint::convert(keypoints0, points0);
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Mat points0t;
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perspectiveTransform(Mat(points0), points0t, H);
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if(H.empty())
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points0t = Mat(points0);
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else
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perspectiveTransform(Mat(points0), points0t, H);
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matches.clear();
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vector<uchar> usedMask(keypoints1.size(), 0);
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for(size_t i0 = 0; i0 < keypoints0.size(); i0++)
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{
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int nearestPointIndex = -1;
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float maxIntersectRatio = -1.f;
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float maxIntersectRatio = 0.f;
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const float r0 = 0.5f * keypoints0[i0].size;
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for(size_t i1 = 0; i1 < keypoints1.size(); i1++)
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{
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@ -174,7 +177,7 @@ protected:
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void run(int)
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{
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const string imageFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
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const string imageFilename = string(ts->get_data_path()) + IMAGE_TSUKUBA;
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// Read test data
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Mat image0 = imread(imageFilename), image1, mask1;
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@ -187,8 +190,8 @@ protected:
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vector<KeyPoint> keypoints0;
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featureDetector->detect(image0, keypoints0);
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CV_Assert(keypoints0.size() > 15);
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if(keypoints0.size() < 15)
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CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
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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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@ -266,6 +269,13 @@ protected:
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float minAngleInliersRatio;
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};
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void scaleKeyPoints(const vector<KeyPoint>& src, vector<KeyPoint>& dst, float scale)
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{
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dst.resize(src.size());
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for(size_t i = 0; i < src.size(); i++)
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dst[i] = KeyPoint(src[i].pt.x * scale, src[i].pt.y * scale, src[i].size * scale);
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}
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class DescriptorRotationInvarianceTest : public cvtest::BaseTest
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{
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public:
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@ -288,7 +298,7 @@ protected:
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void run(int)
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{
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const string imageFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
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const string imageFilename = string(ts->get_data_path()) + IMAGE_TSUKUBA;
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// Read test data
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Mat image0 = imread(imageFilename), image1, mask1;
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@ -302,9 +312,10 @@ protected:
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vector<KeyPoint> keypoints0;
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Mat descriptors0;
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featureDetector->detect(image0, keypoints0);
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if(keypoints0.size() < 15)
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CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
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descriptorExtractor->compute(image0, keypoints0, descriptors0);
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CV_Assert(keypoints0.size() > 15);
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BFMatcher bfmatcher(normType);
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const int maxAngle = 360, angleStep = 15;
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@ -375,6 +386,258 @@ protected:
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};
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class DetectorScaleInvarianceTest : public cvtest::BaseTest
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{
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public:
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DetectorScaleInvarianceTest(const Ptr<FeatureDetector>& _featureDetector,
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float _minKeyPointMatchesRatio,
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float _minScaleInliersRatio) :
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featureDetector(_featureDetector),
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minKeyPointMatchesRatio(_minKeyPointMatchesRatio),
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minScaleInliersRatio(_minScaleInliersRatio)
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{
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CV_Assert(!featureDetector.empty());
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}
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protected:
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void run(int)
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{
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const string imageFilename = string(ts->get_data_path()) + IMAGE_BIKES;
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// Read test data
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Mat image0 = imread(imageFilename);
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if(image0.empty())
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{
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ts->printf(cvtest::TS::LOG, "Image %s can not be read.\n", imageFilename.c_str());
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ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
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return;
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}
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vector<KeyPoint> keypoints0;
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featureDetector->detect(image0, keypoints0);
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if(keypoints0.size() < 15)
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CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
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for(int scale = 2; scale <= 4; scale++)
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{
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Mat image1;
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resize(image0, image1, Size(), 1./scale, 1./scale);
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vector<KeyPoint> keypoints1, osiKeypoints1; // osi - original size image
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featureDetector->detect(image1, keypoints1);
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if(keypoints1.size() < 15)
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CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
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if(keypoints1.size() > keypoints0.size())
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{
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ts->printf(cvtest::TS::LOG, "Strange behavior of the detector. "
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"It gives more points count in an image of the smaller size.\n"
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"original size (%d, %d), keypoints count = %d\n"
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"reduced size (%d, %d), keypoints count = %d\n",
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image0.cols, image0.rows, keypoints0.size(),
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image1.cols, image1.rows, keypoints1.size());
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ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
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return;
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}
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scaleKeyPoints(keypoints1, osiKeypoints1, scale);
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vector<DMatch> matches;
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// image1 is query image (it's reduced image0)
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// image0 is train image
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matchKeyPoints(osiKeypoints1, Mat(), keypoints0, matches);
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const float minIntersectRatio = 0.5f;
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int keyPointMatchesCount = 0;
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int scaleInliersCount = 0;
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for(size_t m = 0; m < matches.size(); m++)
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{
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if(matches[m].distance < minIntersectRatio)
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continue;
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keyPointMatchesCount++;
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// Check does this inlier have consistent sizes
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const float maxSizeDiff = 0.8;//0.9f; // grad
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float size0 = keypoints0[matches[m].trainIdx].size;
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float size1 = osiKeypoints1[matches[m].queryIdx].size;
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CV_Assert(size0 > 0 && size1 > 0);
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if(std::min(size0, size1) > maxSizeDiff * std::max(size0, size1))
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scaleInliersCount++;
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}
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float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints1.size();
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if(keyPointMatchesRatio < minKeyPointMatchesRatio)
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{
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ts->printf(cvtest::TS::LOG, "Incorrect keyPointMatchesRatio: curr = %f, min = %f.\n",
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keyPointMatchesRatio, minKeyPointMatchesRatio);
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ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
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return;
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}
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if(keyPointMatchesCount)
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{
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float scaleInliersRatio = static_cast<float>(scaleInliersCount) / keyPointMatchesCount;
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if(scaleInliersRatio < minScaleInliersRatio)
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{
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ts->printf(cvtest::TS::LOG, "Incorrect scaleInliersRatio: curr = %f, min = %f.\n",
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scaleInliersRatio, minScaleInliersRatio);
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ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
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return;
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}
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}
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#if SHOW_DEBUG_LOG
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std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio
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<< " - scaleInliersRatio " << static_cast<float>(scaleInliersCount) / keyPointMatchesCount << std::endl;
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#endif
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/*vector<DMatch> filteredMatches;
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for(size_t i = 0; i < matches.size(); i++)
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{
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if(matches[i].distance >= minIntersectRatio)
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filteredMatches.push_back(matches[i]);
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}
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Mat out;
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namedWindow("out", CV_WINDOW_NORMAL);
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drawMatches(image1, keypoints1, image0, keypoints0, filteredMatches, out,
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Scalar::all(-1), Scalar(-1), vector<char>(), DrawMatchesFlags::DEFAULT + DrawMatchesFlags::DRAW_RICH_KEYPOINTS);
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imshow("out", out);
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waitKey();*/
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}
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ts->set_failed_test_info( cvtest::TS::OK );
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}
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Ptr<FeatureDetector> featureDetector;
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float minKeyPointMatchesRatio;
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float minScaleInliersRatio;
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};
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class DescriptorScaleInvarianceTest : public cvtest::BaseTest
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{
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public:
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DescriptorScaleInvarianceTest(const Ptr<FeatureDetector>& _featureDetector,
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const Ptr<DescriptorExtractor>& _descriptorExtractor,
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int _normType,
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float _minKeyPointMatchesRatio,
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float _minDescInliersRatio) :
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featureDetector(_featureDetector),
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descriptorExtractor(_descriptorExtractor),
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normType(_normType),
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minKeyPointMatchesRatio(_minKeyPointMatchesRatio),
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minDescInliersRatio(_minDescInliersRatio)
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{
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CV_Assert(!featureDetector.empty());
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CV_Assert(!descriptorExtractor.empty());
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}
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protected:
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void run(int)
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{
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const string imageFilename = string(ts->get_data_path()) + IMAGE_BIKES;
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// Read test data
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Mat image0 = imread(imageFilename);
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if(image0.empty())
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{
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ts->printf(cvtest::TS::LOG, "Image %s can not be read.\n", imageFilename.c_str());
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ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
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return;
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}
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vector<KeyPoint> keypoints0;
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featureDetector->detect(image0, keypoints0);
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if(keypoints0.size() < 15)
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CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
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Mat descriptors0;
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descriptorExtractor->compute(image0, keypoints0, descriptors0);
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BFMatcher bfmatcher(normType);
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for(int scale = 2; scale <= 4; scale++)
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{
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Mat image1;
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resize(image0, image1, Size(), 1./scale, 1./scale);
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vector<KeyPoint> keypoints1, osiKeypoints1; // osi - original size image
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featureDetector->detect(image1, keypoints1);
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if(keypoints1.size() < 15)
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CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
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if(keypoints1.size() > keypoints0.size() )
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{
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ts->printf(cvtest::TS::LOG, "Strange behavior of the detector. "
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"It gives more points count in an image of the smaller size.\n"
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"original size (%d, %d), keypoints count = %d\n"
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"reduced size (%d, %d), keypoints count = %d\n",
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image0.cols, image0.rows, keypoints0.size(),
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image1.cols, image1.rows, keypoints1.size());
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ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
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return;
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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> keyPointMatches, descMatches;
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// image1 is query image (it's reduced image0)
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// image0 is train image
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bfmatcher.match(descriptors1, descriptors0, descMatches);
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scaleKeyPoints(keypoints1, osiKeypoints1, scale);
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matchKeyPoints(osiKeypoints1, Mat(), keypoints0, keyPointMatches);
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const float minIntersectRatio = 0.5f;
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int keyPointMatchesCount = 0;
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for(size_t m = 0; m < keyPointMatches.size(); m++)
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{
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if(keyPointMatches[m].distance >= minIntersectRatio)
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keyPointMatchesCount++;
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}
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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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int queryIdx = descMatches[m].queryIdx;
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if(keyPointMatches[queryIdx].distance >= minIntersectRatio &&
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descMatches[m].trainIdx == keyPointMatches[queryIdx].trainIdx)
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descInliersCount++;
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}
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float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints1.size();
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if(keyPointMatchesRatio < minKeyPointMatchesRatio)
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{
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ts->printf(cvtest::TS::LOG, "Incorrect keyPointMatchesRatio: curr = %f, min = %f.\n",
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keyPointMatchesRatio, minKeyPointMatchesRatio);
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ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
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return;
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}
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if(keyPointMatchesCount)
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{
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float descInliersRatio = static_cast<float>(descInliersCount) / keyPointMatchesCount;
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if(descInliersRatio < minDescInliersRatio)
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{
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ts->printf(cvtest::TS::LOG, "Incorrect descInliersRatio: curr = %f, min = %f.\n",
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descInliersRatio, minDescInliersRatio);
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ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
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return;
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}
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}
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#if SHOW_DEBUG_LOG
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std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio
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<< " - descInliersRatio " << static_cast<float>(descInliersCount) / keyPointMatchesCount << std::endl;
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#endif
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}
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ts->set_failed_test_info( cvtest::TS::OK );
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}
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Ptr<FeatureDetector> featureDetector;
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Ptr<DescriptorExtractor> descriptorExtractor;
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int normType;
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float minKeyPointMatchesRatio;
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float minDescInliersRatio;
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};
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// Tests registration
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// Detector's rotation invariance check
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@ -397,7 +660,7 @@ TEST(Features2d_RotationInvariance_Descriptor_ORB, regression)
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test.safe_run();
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}
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// TODO: uncomment test for FREAK when it will work
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// TODO: Uncomment test for FREAK when it will work; add test for scale invariance for FREAK
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//TEST(Features2d_RotationInvariance_Descriptor_FREAK, regression)
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//{
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// DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
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@ -406,4 +669,25 @@ TEST(Features2d_RotationInvariance_Descriptor_ORB, regression)
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// 0.45f,
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// 0.?f);
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// test.safe_run();
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//}
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//}
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/* TODO: Why ORB has bad scale invariance in this tests?
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// Detector's scale invariance check
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TEST(Features2d_ScaleInvariance_Detector_ORB, regression)
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{
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DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
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0.13f,
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0.0f);
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test.safe_run();
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}
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// Descriptor's scale invariance check
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TEST(Features2d_ScaleInvariance_Descriptor_ORB, regression)
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{
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DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
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Algorithm::create<DescriptorExtractor>("Feature2D.ORB"),
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NORM_HAMMING,
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0.13f,
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0.36f);
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test.safe_run();
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}*/
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@ -45,8 +45,8 @@
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using namespace std;
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using namespace cv;
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const string FEATURES2D_DIR = "features2d";
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const string IMAGE_FILENAME = "tsukuba.png";
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const string IMAGE_TSUKUBA = "/features2d/tsukuba.png";
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const string IMAGE_BIKES = "/detectors_descriptors_evaluation/images_datasets/bikes/img1.png";
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#define SHOW_DEBUG_LOG 0
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@ -127,14 +127,17 @@ void matchKeyPoints(const vector<KeyPoint>& keypoints0, const Mat& H,
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vector<Point2f> points0;
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KeyPoint::convert(keypoints0, points0);
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Mat points0t;
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perspectiveTransform(Mat(points0), points0t, H);
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if(H.empty())
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points0t = Mat(points0);
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else
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perspectiveTransform(Mat(points0), points0t, H);
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matches.clear();
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vector<uchar> usedMask(keypoints1.size(), 0);
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for(size_t i0 = 0; i0 < keypoints0.size(); i0++)
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{
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int nearestPointIndex = -1;
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float maxIntersectRatio = -1.f;
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float maxIntersectRatio = 0.f;
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const float r0 = 0.5f * keypoints0[i0].size;
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for(size_t i1 = 0; i1 < keypoints1.size(); i1++)
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{
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@ -174,7 +177,7 @@ protected:
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void run(int)
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{
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const string imageFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
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const string imageFilename = string(ts->get_data_path()) + IMAGE_TSUKUBA;
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// Read test data
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Mat image0 = imread(imageFilename), image1, mask1;
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@ -187,8 +190,8 @@ protected:
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vector<KeyPoint> keypoints0;
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featureDetector->detect(image0, keypoints0);
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CV_Assert(keypoints0.size() > 15);
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if(keypoints0.size() < 15)
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CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
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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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@ -266,6 +269,13 @@ protected:
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float minAngleInliersRatio;
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};
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void scaleKeyPoints(const vector<KeyPoint>& src, vector<KeyPoint>& dst, float scale)
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{
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dst.resize(src.size());
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for(size_t i = 0; i < src.size(); i++)
|
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dst[i] = KeyPoint(src[i].pt.x * scale, src[i].pt.y * scale, src[i].size * scale);
|
||||
}
|
||||
|
||||
class DescriptorRotationInvarianceTest : public cvtest::BaseTest
|
||||
{
|
||||
public:
|
||||
@ -288,7 +298,7 @@ protected:
|
||||
|
||||
void run(int)
|
||||
{
|
||||
const string imageFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
|
||||
const string imageFilename = string(ts->get_data_path()) + IMAGE_TSUKUBA;
|
||||
|
||||
// Read test data
|
||||
Mat image0 = imread(imageFilename), image1, mask1;
|
||||
@ -302,9 +312,10 @@ protected:
|
||||
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);
|
||||
|
||||
CV_Assert(keypoints0.size() > 15);
|
||||
BFMatcher bfmatcher(normType);
|
||||
|
||||
const int maxAngle = 360, angleStep = 15;
|
||||
@ -375,6 +386,245 @@ protected:
|
||||
|
||||
};
|
||||
|
||||
class DetectorScaleInvarianceTest : public cvtest::BaseTest
|
||||
{
|
||||
public:
|
||||
DetectorScaleInvarianceTest(const Ptr<FeatureDetector>& _featureDetector,
|
||||
float _minKeyPointMatchesRatio,
|
||||
float _minScaleInliersRatio) :
|
||||
featureDetector(_featureDetector),
|
||||
minKeyPointMatchesRatio(_minKeyPointMatchesRatio),
|
||||
minScaleInliersRatio(_minScaleInliersRatio)
|
||||
{
|
||||
CV_Assert(!featureDetector.empty());
|
||||
}
|
||||
|
||||
protected:
|
||||
|
||||
void run(int)
|
||||
{
|
||||
const string imageFilename = string(ts->get_data_path()) + IMAGE_BIKES;
|
||||
|
||||
// Read test data
|
||||
Mat image0 = imread(imageFilename);
|
||||
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");
|
||||
|
||||
for(int scale = 2; scale <= 4; scale++)
|
||||
{
|
||||
Mat image1;
|
||||
resize(image0, image1, Size(), 1./scale, 1./scale);
|
||||
|
||||
vector<KeyPoint> keypoints1, osiKeypoints1; // osi - original size image
|
||||
featureDetector->detect(image1, keypoints1);
|
||||
if(keypoints1.size() < 15)
|
||||
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
|
||||
|
||||
if(keypoints1.size() > keypoints0.size())
|
||||
{
|
||||
ts->printf(cvtest::TS::LOG, "Strange behavior of the detector. "
|
||||
"It gives more points count in an image of the smaller size.\n"
|
||||
"original size (%d, %d), keypoints count = %d\n"
|
||||
"reduced size (%d, %d), keypoints count = %d\n",
|
||||
image0.cols, image0.rows, keypoints0.size(),
|
||||
image1.cols, image1.rows, keypoints1.size());
|
||||
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
|
||||
return;
|
||||
}
|
||||
|
||||
scaleKeyPoints(keypoints1, osiKeypoints1, scale);
|
||||
|
||||
vector<DMatch> matches;
|
||||
// image1 is query image (it's reduced image0)
|
||||
// image0 is train image
|
||||
matchKeyPoints(osiKeypoints1, Mat(), keypoints0, matches);
|
||||
|
||||
const float minIntersectRatio = 0.5f;
|
||||
int keyPointMatchesCount = 0;
|
||||
int scaleInliersCount = 0;
|
||||
|
||||
for(size_t m = 0; m < matches.size(); m++)
|
||||
{
|
||||
if(matches[m].distance < minIntersectRatio)
|
||||
continue;
|
||||
|
||||
keyPointMatchesCount++;
|
||||
|
||||
// Check does this inlier have consistent sizes
|
||||
const float maxSizeDiff = 0.8;//0.9f; // grad
|
||||
float size0 = keypoints0[matches[m].trainIdx].size;
|
||||
float size1 = osiKeypoints1[matches[m].queryIdx].size;
|
||||
CV_Assert(size0 > 0 && size1 > 0);
|
||||
if(std::min(size0, size1) > maxSizeDiff * std::max(size0, size1))
|
||||
scaleInliersCount++;
|
||||
}
|
||||
|
||||
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);
|
||||
return;
|
||||
}
|
||||
|
||||
if(keyPointMatchesCount)
|
||||
{
|
||||
float scaleInliersRatio = static_cast<float>(scaleInliersCount) / keyPointMatchesCount;
|
||||
if(scaleInliersRatio < minScaleInliersRatio)
|
||||
{
|
||||
ts->printf(cvtest::TS::LOG, "Incorrect scaleInliersRatio: curr = %f, min = %f.\n",
|
||||
scaleInliersRatio, minScaleInliersRatio);
|
||||
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
|
||||
return;
|
||||
}
|
||||
}
|
||||
#if SHOW_DEBUG_LOG
|
||||
std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio
|
||||
<< " - scaleInliersRatio " << static_cast<float>(scaleInliersCount) / keyPointMatchesCount << std::endl;
|
||||
#endif
|
||||
}
|
||||
ts->set_failed_test_info( cvtest::TS::OK );
|
||||
}
|
||||
|
||||
Ptr<FeatureDetector> featureDetector;
|
||||
float minKeyPointMatchesRatio;
|
||||
float minScaleInliersRatio;
|
||||
};
|
||||
|
||||
class DescriptorScaleInvarianceTest : public cvtest::BaseTest
|
||||
{
|
||||
public:
|
||||
DescriptorScaleInvarianceTest(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:
|
||||
|
||||
void run(int)
|
||||
{
|
||||
const string imageFilename = string(ts->get_data_path()) + IMAGE_BIKES;
|
||||
|
||||
// Read test data
|
||||
Mat image0 = imread(imageFilename);
|
||||
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");
|
||||
Mat descriptors0;
|
||||
descriptorExtractor->compute(image0, keypoints0, descriptors0);
|
||||
|
||||
BFMatcher bfmatcher(normType);
|
||||
for(int scale = 2; scale <= 4; scale++)
|
||||
{
|
||||
Mat image1;
|
||||
resize(image0, image1, Size(), 1./scale, 1./scale);
|
||||
|
||||
vector<KeyPoint> keypoints1, osiKeypoints1; // osi - original size image
|
||||
featureDetector->detect(image1, keypoints1);
|
||||
if(keypoints1.size() < 15)
|
||||
CV_Error(CV_StsAssert, "Detector gives too few points in a test image\n");
|
||||
if(keypoints1.size() > keypoints0.size() )
|
||||
{
|
||||
ts->printf(cvtest::TS::LOG, "Strange behavior of the detector. "
|
||||
"It gives more points count in an image of the smaller size.\n"
|
||||
"original size (%d, %d), keypoints count = %d\n"
|
||||
"reduced size (%d, %d), keypoints count = %d\n",
|
||||
image0.cols, image0.rows, keypoints0.size(),
|
||||
image1.cols, image1.rows, keypoints1.size());
|
||||
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
|
||||
return;
|
||||
}
|
||||
|
||||
Mat descriptors1;
|
||||
descriptorExtractor->compute(image1, keypoints1, descriptors1);
|
||||
|
||||
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;
|
||||
if(keyPointMatches[queryIdx].distance >= minIntersectRatio &&
|
||||
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);
|
||||
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
|
||||
std::cout << "keyPointMatchesRatio - " << keyPointMatchesRatio
|
||||
<< " - descInliersRatio " << static_cast<float>(descInliersCount) / keyPointMatchesCount << std::endl;
|
||||
#endif
|
||||
}
|
||||
ts->set_failed_test_info( cvtest::TS::OK );
|
||||
}
|
||||
|
||||
Ptr<FeatureDetector> featureDetector;
|
||||
Ptr<DescriptorExtractor> descriptorExtractor;
|
||||
int normType;
|
||||
float minKeyPointMatchesRatio;
|
||||
float minDescInliersRatio;
|
||||
};
|
||||
|
||||
// Tests registration
|
||||
|
||||
// Detector's rotation invariance check
|
||||
@ -386,7 +636,6 @@ TEST(Features2d_RotationInvariance_Detector_SURF, regression)
|
||||
test.safe_run();
|
||||
}
|
||||
|
||||
|
||||
TEST(Features2d_RotationInvariance_Detector_SIFT, regression)
|
||||
{
|
||||
DetectorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"),
|
||||
@ -402,7 +651,7 @@ TEST(Features2d_RotationInvariance_Descriptor_SURF, regression)
|
||||
Algorithm::create<DescriptorExtractor>("Feature2D.SURF"),
|
||||
NORM_L1,
|
||||
0.44f,
|
||||
0.64f);
|
||||
0.63f);
|
||||
test.safe_run();
|
||||
}
|
||||
|
||||
@ -414,4 +663,42 @@ TEST(Features2d_RotationInvariance_Descriptor_SIFT, regression)
|
||||
0.64f,
|
||||
0.72f);
|
||||
test.safe_run();
|
||||
}
|
||||
|
||||
// Detector's scale invariance check
|
||||
TEST(Features2d_ScaleInvariance_Detector_SURF, regression)
|
||||
{
|
||||
DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SURF"),
|
||||
0.62f,
|
||||
0.68f);
|
||||
test.safe_run();
|
||||
}
|
||||
|
||||
TEST(Features2d_ScaleInvariance_Detector_SIFT, regression)
|
||||
{
|
||||
DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"),
|
||||
0.59f,
|
||||
0.94f);
|
||||
test.safe_run();
|
||||
}
|
||||
|
||||
// Descriptor's scale invariance check
|
||||
TEST(Features2d_ScaleInvariance_Descriptor_SURF, regression)
|
||||
{
|
||||
DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SURF"),
|
||||
Algorithm::create<DescriptorExtractor>("Feature2D.SURF"),
|
||||
NORM_L1,
|
||||
0.62f,
|
||||
0.68f);
|
||||
test.safe_run();
|
||||
}
|
||||
|
||||
TEST(Features2d_ScaleInvariance_Descriptor_SIFT, regression)
|
||||
{
|
||||
DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"),
|
||||
Algorithm::create<DescriptorExtractor>("Feature2D.SIFT"),
|
||||
NORM_L1,
|
||||
0.59f,
|
||||
0.78f);
|
||||
test.safe_run();
|
||||
}
|
||||
Loading…
Reference in New Issue
Block a user