changed tests for rotation/scale invariance of descriptors
This commit is contained in:
Maria Dimashova
parent
ad7a6ec41f
commit
2556bb04f0
@ -85,6 +85,32 @@ Mat rotateImage(const Mat& srcImage, float angle, Mat& dstImage, Mat& dstMask)
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return H;
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}
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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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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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static
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float calcCirclesIntersectArea(const Point2f& p0, float r0, const Point2f& p1, float r1)
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{
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@ -269,25 +295,16 @@ 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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DescriptorRotationInvarianceTest(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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@ -318,50 +335,33 @@ protected:
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BFMatcher bfmatcher(normType);
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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, angle, image1, mask1);
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vector<KeyPoint> keypoints1;
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rotateKeyPoints(keypoints0, H, angle, keypoints1);
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Mat descriptors1;
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featureDetector->detect(image1, keypoints1, mask1);
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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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vector<DMatch> keyPointMatches;
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matchKeyPoints(keypoints0, H, keypoints1, 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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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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float keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints0.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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float descInliersRatio = static_cast<float>(descInliersCount) / keypoints0.size();
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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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@ -369,10 +369,8 @@ protected:
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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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std::cout << "descInliersRatio " << static_cast<float>(descInliersCount) / keypoints0.size() << 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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@ -381,9 +379,7 @@ protected:
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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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class DetectorScaleInvarianceTest : public cvtest::BaseTest
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@ -419,8 +415,9 @@ protected:
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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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for(float 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);
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@ -492,19 +489,6 @@ protected:
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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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@ -520,12 +504,10 @@ 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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@ -555,66 +537,35 @@ protected:
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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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for(float 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);
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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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vector<KeyPoint> keypoints1;
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scaleKeyPoints(keypoints0, keypoints1, 1./scale);
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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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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 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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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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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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float descInliersRatio = static_cast<float>(descInliersCount) / keypoints0.size();
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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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@ -622,10 +573,8 @@ protected:
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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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std::cout << "descInliersRatio " << static_cast<float>(descInliersCount) / keypoints0.size() << 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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@ -640,54 +589,68 @@ protected:
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// Tests registration
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// Detector's rotation invariance check
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/*
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* Detector's rotation invariance check
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*/
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TEST(Features2d_RotationInvariance_Detector_ORB, regression)
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{
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DetectorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
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0.45f,
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0.75f);
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0.47f,
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0.77f);
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test.safe_run();
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}
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// Descriptors's rotation invariance check
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/*
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* Descriptors's rotation invariance check
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*/
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TEST(Features2d_RotationInvariance_Descriptor_ORB, regression)
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{
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DescriptorRotationInvarianceTest 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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0.45f,
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0.53f);
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0.99f);
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test.safe_run();
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}
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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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// Algorithm::create<DescriptorExtractor>("Feature2D.FREAK"),
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// NORM_HAMMING(?),
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// 0.45f,
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// 0.?f);
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// NORM_HAMMING,
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// 0.f);
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// test.safe_run();
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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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/*
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* Detector's scale invariance check
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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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//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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// 0.22f,
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// 0.83f);
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// test.safe_run();
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//}
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/*
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* Descriptor's scale invariance check
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*/
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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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// 0.01f);
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// test.safe_run();
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//}
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//TEST(Features2d_ScaleInvariance_Descriptor_FREAK, regression)
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//{
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// DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
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// Algorithm::create<DescriptorExtractor>("Feature2D.FREAK"),
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// NORM_HAMMING,
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// 0.01f);
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// test.safe_run();
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//}
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@ -85,6 +85,32 @@ Mat rotateImage(const Mat& srcImage, float angle, Mat& dstImage, Mat& dstMask)
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return H;
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}
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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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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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static
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float calcCirclesIntersectArea(const Point2f& p0, float r0, const Point2f& p1, float r1)
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{
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@ -269,25 +295,16 @@ 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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DescriptorRotationInvarianceTest(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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@ -318,50 +335,33 @@ protected:
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||||
|
||||
BFMatcher bfmatcher(normType);
|
||||
|
||||
const float minIntersectRatio = 0.5f;
|
||||
const int maxAngle = 360, angleStep = 15;
|
||||
for(int angle = 0; angle < maxAngle; angle += angleStep)
|
||||
{
|
||||
Mat H = rotateImage(image0, angle, image1, mask1);
|
||||
|
||||
vector<KeyPoint> keypoints1;
|
||||
rotateKeyPoints(keypoints0, H, angle, keypoints1);
|
||||
Mat descriptors1;
|
||||
featureDetector->detect(image1, keypoints1, mask1);
|
||||
descriptorExtractor->compute(image1, keypoints1, descriptors1);
|
||||
|
||||
vector<DMatch> descMatches;
|
||||
bfmatcher.match(descriptors0, descriptors1, descMatches);
|
||||
|
||||
vector<DMatch> keyPointMatches;
|
||||
matchKeyPoints(keypoints0, H, keypoints1, 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)
|
||||
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 keyPointMatchesRatio = static_cast<float>(keyPointMatchesCount) / keypoints0.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;
|
||||
float descInliersRatio = static_cast<float>(descInliersCount) / keypoints0.size();
|
||||
if(descInliersRatio < minDescInliersRatio)
|
||||
{
|
||||
ts->printf(cvtest::TS::LOG, "Incorrect descInliersRatio: curr = %f, min = %f.\n",
|
||||
@ -369,10 +369,8 @@ protected:
|
||||
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;
|
||||
std::cout << "descInliersRatio " << static_cast<float>(descInliersCount) / keypoints0.size() << std::endl;
|
||||
#endif
|
||||
}
|
||||
ts->set_failed_test_info( cvtest::TS::OK );
|
||||
@ -381,9 +379,7 @@ protected:
|
||||
Ptr<FeatureDetector> featureDetector;
|
||||
Ptr<DescriptorExtractor> descriptorExtractor;
|
||||
int normType;
|
||||
float minKeyPointMatchesRatio;
|
||||
float minDescInliersRatio;
|
||||
|
||||
};
|
||||
|
||||
class DetectorScaleInvarianceTest : public cvtest::BaseTest
|
||||
@ -419,8 +415,9 @@ protected:
|
||||
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++)
|
||||
for(float scaleIdx = 1; scaleIdx <= 3; scaleIdx++)
|
||||
{
|
||||
float scale = 1.f + scaleIdx * 0.5f;
|
||||
Mat image1;
|
||||
resize(image0, image1, Size(), 1./scale, 1./scale);
|
||||
|
||||
@ -507,12 +504,10 @@ 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());
|
||||
@ -542,66 +537,35 @@ protected:
|
||||
descriptorExtractor->compute(image0, keypoints0, descriptors0);
|
||||
|
||||
BFMatcher bfmatcher(normType);
|
||||
for(int scale = 2; scale <= 4; scale++)
|
||||
for(float scaleIdx = 1; scaleIdx <= 3; scaleIdx++)
|
||||
{
|
||||
float scale = 1.f + scaleIdx * 0.5f;
|
||||
|
||||
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;
|
||||
}
|
||||
|
||||
vector<KeyPoint> keypoints1;
|
||||
scaleKeyPoints(keypoints0, keypoints1, 1./scale);
|
||||
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);
|
||||
vector<DMatch> descMatches;
|
||||
bfmatcher.match(descriptors0, descriptors1, descMatches);
|
||||
|
||||
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)
|
||||
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 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;
|
||||
float descInliersRatio = static_cast<float>(descInliersCount) / keypoints0.size();
|
||||
if(descInliersRatio < minDescInliersRatio)
|
||||
{
|
||||
ts->printf(cvtest::TS::LOG, "Incorrect descInliersRatio: curr = %f, min = %f.\n",
|
||||
@ -609,10 +573,8 @@ protected:
|
||||
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;
|
||||
std::cout << "descInliersRatio " << static_cast<float>(descInliersCount) / keypoints0.size() << std::endl;
|
||||
#endif
|
||||
}
|
||||
ts->set_failed_test_info( cvtest::TS::OK );
|
||||
@ -627,11 +589,13 @@ protected:
|
||||
|
||||
// Tests registration
|
||||
|
||||
// Detector's rotation invariance check
|
||||
/*
|
||||
* Detector's rotation invariance check
|
||||
*/
|
||||
TEST(Features2d_RotationInvariance_Detector_SURF, regression)
|
||||
{
|
||||
DetectorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SURF"),
|
||||
0.44f,
|
||||
0.45f,
|
||||
0.76f);
|
||||
test.safe_run();
|
||||
}
|
||||
@ -639,19 +603,20 @@ TEST(Features2d_RotationInvariance_Detector_SURF, regression)
|
||||
TEST(Features2d_RotationInvariance_Detector_SIFT, regression)
|
||||
{
|
||||
DetectorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"),
|
||||
0.64f,
|
||||
0.74f);
|
||||
0.75f,
|
||||
0.76f);
|
||||
test.safe_run();
|
||||
}
|
||||
|
||||
// Descriptors's rotation invariance check
|
||||
/*
|
||||
* Descriptors's rotation invariance check
|
||||
*/
|
||||
TEST(Features2d_RotationInvariance_Descriptor_SURF, regression)
|
||||
{
|
||||
DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SURF"),
|
||||
Algorithm::create<DescriptorExtractor>("Feature2D.SURF"),
|
||||
NORM_L1,
|
||||
0.44f,
|
||||
0.63f);
|
||||
0.83f);
|
||||
test.safe_run();
|
||||
}
|
||||
|
||||
@ -660,45 +625,46 @@ TEST(Features2d_RotationInvariance_Descriptor_SIFT, regression)
|
||||
DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"),
|
||||
Algorithm::create<DescriptorExtractor>("Feature2D.SIFT"),
|
||||
NORM_L1,
|
||||
0.64f,
|
||||
0.72f);
|
||||
0.98f);
|
||||
test.safe_run();
|
||||
}
|
||||
|
||||
// Detector's scale invariance check
|
||||
/*
|
||||
* Detector's scale invariance check
|
||||
*/
|
||||
TEST(Features2d_ScaleInvariance_Detector_SURF, regression)
|
||||
{
|
||||
DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SURF"),
|
||||
0.62f,
|
||||
0.68f);
|
||||
0.64f,
|
||||
0.84f);
|
||||
test.safe_run();
|
||||
}
|
||||
|
||||
TEST(Features2d_ScaleInvariance_Detector_SIFT, regression)
|
||||
{
|
||||
DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"),
|
||||
0.59f,
|
||||
0.94f);
|
||||
0.69f,
|
||||
0.99f);
|
||||
test.safe_run();
|
||||
}
|
||||
|
||||
// Descriptor's scale invariance check
|
||||
/*
|
||||
* 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);
|
||||
0.61f);
|
||||
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();
|
||||
}
|
||||
//TEST(Features2d_ScaleInvariance_Descriptor_SIFT, regression)
|
||||
//{
|
||||
// DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"),
|
||||
// Algorithm::create<DescriptorExtractor>("Feature2D.SIFT"),
|
||||
// NORM_L1,
|
||||
// 0.14f);
|
||||
// test.safe_run();
|
||||
//}
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user