Merge pull request #2449 from saskatchewancatch:issue-16736 (f3982616) · Commits · SUMMER2020 / students / proj-2020194

modules/xfeatures2d/include/opencv2/xfeatures2d.hpp

+33 −0

Original line number	Diff line number	Diff line
		@@ -65,6 +65,39 @@ namespace cv
		namespace xfeatures2d
		{


		/** @brief Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform
		(SIFT) algorithm by D. Lowe @cite Lowe04 .
		*/
		class CV_EXPORTS_W SIFT : public Feature2D
		{
		public:
		/**
		@param nfeatures The number of best features to retain. The features are ranked by their scores
		(measured in SIFT algorithm as the local contrast)

		@param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
		number of octaves is computed automatically from the image resolution.

		@param contrastThreshold The contrast threshold used to filter out weak features in semi-uniform
		(low-contrast) regions. The larger the threshold, the less features are produced by the detector.

		@param edgeThreshold The threshold used to filter out edge-like features. Note that the its meaning
		is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
		filtered out (more features are retained).

		@param sigma The sigma of the Gaussian applied to the input image at the octave \#0. If your image
		is captured with a weak camera with soft lenses, you might want to reduce the number.
		*/
		CV_WRAP static Ptr<SIFT> create(int nfeatures = 0, int nOctaveLayers = 3,
		double contrastThreshold = 0.04, double edgeThreshold = 10,
		double sigma = 1.6);
		};

		typedef SIFT SiftFeatureDetector;
		typedef SIFT SiftDescriptorExtractor;


		//! @addtogroup xfeatures2d_experiment
		//! @{

modules/xfeatures2d/include/opencv2/xfeatures2d/nonfree.hpp

+0 −34

Original line number	Diff line number	Diff line
		@@ -50,40 +50,6 @@ namespace cv
		namespace xfeatures2d
		{

		//! @addtogroup xfeatures2d_nonfree
		//! @{

		/** @brief Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform
		(SIFT) algorithm by D. Lowe @cite Lowe04 .
		*/
		class CV_EXPORTS_W SIFT : public Feature2D
		{
		public:
		/**
		@param nfeatures The number of best features to retain. The features are ranked by their scores
		(measured in SIFT algorithm as the local contrast)

		@param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
		number of octaves is computed automatically from the image resolution.

		@param contrastThreshold The contrast threshold used to filter out weak features in semi-uniform
		(low-contrast) regions. The larger the threshold, the less features are produced by the detector.

		@param edgeThreshold The threshold used to filter out edge-like features. Note that the its meaning
		is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
		filtered out (more features are retained).

		@param sigma The sigma of the Gaussian applied to the input image at the octave \#0. If your image
		is captured with a weak camera with soft lenses, you might want to reduce the number.
		*/
		CV_WRAP static Ptr<SIFT> create( int nfeatures = 0, int nOctaveLayers = 3,
		double contrastThreshold = 0.04, double edgeThreshold = 10,
		double sigma = 1.6);
		};

		typedef SIFT SiftFeatureDetector;
		typedef SIFT SiftDescriptorExtractor;

		/** @brief Class for extracting Speeded Up Robust Features from an image @cite Bay06 .

		The algorithm parameters:

modules/xfeatures2d/src/sift.cpp

+0 −11

Original line number	Diff line number	Diff line
		@@ -114,8 +114,6 @@ namespace cv
		namespace xfeatures2d
		{

		#ifdef OPENCV_ENABLE_NONFREE

		/*!
		SIFT implementation.

		@@ -1202,14 +1200,5 @@ void SIFT_Impl::detectAndCompute(InputArray _image, InputArray _mask,
		}
		}

		#else // ! #ifdef OPENCV_ENABLE_NONFREE
		Ptr<SIFT> SIFT::create( int, int, double, double, double )
		{
		CV_Error(Error::StsNotImplemented,
		"This algorithm is patented and is excluded in this configuration; "
		"Set OPENCV_ENABLE_NONFREE CMake option and rebuild the library");
		}
		#endif

		}
		}

modules/xfeatures2d/test/test_features2d.cpp

+5 −4

Original line number	Diff line number	Diff line
		@@ -987,13 +987,13 @@ void CV_DescriptorMatcherTest::run( int )
		* Detectors
		*/

		#ifdef OPENCV_ENABLE_NONFREE
		TEST( Features2d_Detector_SIFT, regression )
		{
		CV_FeatureDetectorTest test( "detector-sift", SIFT::create() );
		test.safe_run();
		}

		#ifdef OPENCV_ENABLE_NONFREE
		TEST( Features2d_Detector_SURF, regression )
		{
		CV_FeatureDetectorTest test( "detector-surf", SURF::create() );
		@@ -1028,7 +1028,6 @@ TEST( Features2d_Detector_Harris_Laplace_Affine, regression )
		/*
		* Descriptors
		*/
		#ifdef OPENCV_ENABLE_NONFREE
		TEST( Features2d_DescriptorExtractor_SIFT, regression )
		{
		CV_DescriptorExtractorTest<L1<float> > test( "descriptor-sift", 1.0f,
		@@ -1036,6 +1035,7 @@ TEST( Features2d_DescriptorExtractor_SIFT, regression )
		test.safe_run();
		}

		#ifdef OPENCV_ENABLE_NONFREE
		TEST( Features2d_DescriptorExtractor_SURF, regression )
		{
		#ifdef HAVE_OPENCL
		@@ -1334,8 +1334,9 @@ protected:
		Ptr<Feature2D> f2d;
		};

		#ifdef OPENCV_ENABLE_NONFREE
		TEST(Features2d_SIFTHomographyTest, regression) { CV_DetectPlanarTest test("SIFT", 80, SIFT::create()); test.safe_run(); }

		#ifdef OPENCV_ENABLE_NONFREE
		TEST(Features2d_SURFHomographyTest, regression) { CV_DetectPlanarTest test("SURF", 80, SURF::create()); test.safe_run(); }
		#endif

		@@ -1400,13 +1401,13 @@ protected:
		Ptr<FeatureDetector> featureDetector_;
		};

		#ifdef OPENCV_ENABLE_NONFREE
		TEST(Features2d_SIFT_using_mask, regression)
		{
		FeatureDetectorUsingMaskTest test(SIFT::create());
		test.safe_run();
		}

		#ifdef OPENCV_ENABLE_NONFREE
		TEST(DISABLED_Features2d_SURF_using_mask, regression)
		{
		FeatureDetectorUsingMaskTest test(SURF::create());