third_party/opencv
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

[move sift.cpp] refactored xfeatures2d in the same style as features2d

Browse Source 
original commit: 0cfd795303
This commit is contained in:
Vadim Pisarevsky 2014-10-16 16:33:21 +04:00
parent d92bee821d
commit e3654d5416
1 changed files with 56 additions and 26 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

82
modules/features2d/src/sift.cpp
View File

@ -76,6 +76,53 @@
namespace cv
{
/*!
SIFT implementation.
The class implements SIFT algorithm by D. Lowe.
*/
class SIFT_Impl : public SIFT
{
public:
explicit SIFT_Impl( int nfeatures = 0, int nOctaveLayers = 3,
double contrastThreshold = 0.04, double edgeThreshold = 10,
double sigma = 1.6);
//! returns the descriptor size in floats (128)
int descriptorSize() const;
//! returns the descriptor type
int descriptorType() const;
//! returns the default norm type
int defaultNorm() const;
//! finds the keypoints and computes descriptors for them using SIFT algorithm.
//! Optionally it can compute descriptors for the user-provided keypoints
void detectAndCompute(InputArray img, InputArray mask,
std::vector<KeyPoint>& keypoints,
OutputArray descriptors,
bool useProvidedKeypoints = false);
void buildGaussianPyramid( const Mat& base, std::vector<Mat>& pyr, int nOctaves ) const;
void buildDoGPyramid( const std::vector<Mat>& pyr, std::vector<Mat>& dogpyr ) const;
void findScaleSpaceExtrema( const std::vector<Mat>& gauss_pyr, const std::vector<Mat>& dog_pyr,
std::vector<KeyPoint>& keypoints ) const;
protected:
CV_PROP_RW int nfeatures;
CV_PROP_RW int nOctaveLayers;
CV_PROP_RW double contrastThreshold;
CV_PROP_RW double edgeThreshold;
CV_PROP_RW double sigma;
};
Ptr<SIFT> SIFT::create( int _nfeatures, int _nOctaveLayers,
double _contrastThreshold, double _edgeThreshold, double _sigma )
{
return makePtr<SIFT_Impl>(_nfeatures, _nOctaveLayers, _contrastThreshold, _edgeThreshold, _sigma);
}
/******************************* Defs and macros *****************************/
// default width of descriptor histogram array
@ -161,7 +208,7 @@ static Mat createInitialImage( const Mat& img, bool doubleImageSize, float sigma
}
void SIFT::buildGaussianPyramid( const Mat& base, std::vector<Mat>& pyr, int nOctaves ) const
void SIFT_Impl::buildGaussianPyramid( const Mat& base, std::vector<Mat>& pyr, int nOctaves ) const
{
std::vector<double> sig(nOctaveLayers + 3);
pyr.resize(nOctaves*(nOctaveLayers + 3));
@ -201,7 +248,7 @@ void SIFT::buildGaussianPyramid( const Mat& base, std::vector<Mat>& pyr, int nOc
}
void SIFT::buildDoGPyramid( const std::vector<Mat>& gpyr, std::vector<Mat>& dogpyr ) const
void SIFT_Impl::buildDoGPyramid( const std::vector<Mat>& gpyr, std::vector<Mat>& dogpyr ) const
{
int nOctaves = (int)gpyr.size()/(nOctaveLayers + 3);
dogpyr.resize( nOctaves*(nOctaveLayers + 2) );
@ -399,7 +446,7 @@ static bool adjustLocalExtrema( const std::vector<Mat>& dog_pyr, KeyPoint& kpt,
//
// Detects features at extrema in DoG scale space. Bad features are discarded
// based on contrast and ratio of principal curvatures.
void SIFT::findScaleSpaceExtrema( const std::vector<Mat>& gauss_pyr, const std::vector<Mat>& dog_pyr,
void SIFT_Impl::findScaleSpaceExtrema( const std::vector<Mat>& gauss_pyr, const std::vector<Mat>& dog_pyr,
std::vector<KeyPoint>& keypoints ) const
{
int nOctaves = (int)gauss_pyr.size()/(nOctaveLayers + 3);
@ -652,40 +699,33 @@ static void calcDescriptors(const std::vector<Mat>& gpyr, const std::vector<KeyP
//////////////////////////////////////////////////////////////////////////////////////////
SIFT::SIFT( int _nfeatures, int _nOctaveLayers,
SIFT_Impl::SIFT_Impl( int _nfeatures, int _nOctaveLayers,
double _contrastThreshold, double _edgeThreshold, double _sigma )
: nfeatures(_nfeatures), nOctaveLayers(_nOctaveLayers),
contrastThreshold(_contrastThreshold), edgeThreshold(_edgeThreshold), sigma(_sigma)
{
}
int SIFT::descriptorSize() const
int SIFT_Impl::descriptorSize() const
{
return SIFT_DESCR_WIDTH*SIFT_DESCR_WIDTH*SIFT_DESCR_HIST_BINS;
}
int SIFT::descriptorType() const
int SIFT_Impl::descriptorType() const
{
return CV_32F;
}
int SIFT::defaultNorm() const
int SIFT_Impl::defaultNorm() const
{
return NORM_L2;
}
void SIFT::operator()(InputArray _image, InputArray _mask,
std::vector<KeyPoint>& keypoints) const
{
(*this)(_image, _mask, keypoints, noArray());
}
void SIFT::operator()(InputArray _image, InputArray _mask,
void SIFT_Impl::detectAndCompute(InputArray _image, InputArray _mask,
std::vector<KeyPoint>& keypoints,
OutputArray _descriptors,
bool useProvidedKeypoints) const
bool useProvidedKeypoints)
{
int firstOctave = -1, actualNOctaves = 0, actualNLayers = 0;
Mat image = _image.getMat(), mask = _mask.getMat();
@ -770,14 +810,4 @@ void SIFT::operator()(InputArray _image, InputArray _mask,
}
}
void SIFT::detectImpl( InputArray image, std::vector<KeyPoint>& keypoints, InputArray mask) const
{
(*this)(image.getMat(), mask.getMat(), keypoints, noArray());
}
void SIFT::computeImpl( InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors) const
{
(*this)(image, Mat(), keypoints, descriptors, true);
}
}