Open Source Computer Vision Library https://opencv.org/
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/*
OpenCV wrapper of reference implementation of
[1] KAZE Features. Pablo F. Alcantarilla, Adrien Bartoli and Andrew J. Davison.
In European Conference on Computer Vision (ECCV), Fiorenze, Italy, October 2012
http://www.robesafe.com/personal/pablo.alcantarilla/papers/Alcantarilla12eccv.pdf
@author Eugene Khvedchenya <ekhvedchenya@gmail.com>
*/
#include "precomp.hpp"
#include "kaze/KAZEFeatures.h"
namespace cv
{
class KAZE_Impl : public KAZE
{
public:
KAZE_Impl(bool _extended, bool _upright, float _threshold, int _octaves,
int _sublevels, int _diffusivity)
: extended(_extended)
, upright(_upright)
, threshold(_threshold)
, octaves(_octaves)
, sublevels(_sublevels)
, diffusivity(_diffusivity)
{
}
virtual ~KAZE_Impl() {}
void setExtended(bool extended_) { extended = extended_; }
bool getExtended() const { return extended; }
void setUpright(bool upright_) { upright = upright_; }
bool getUpright() const { return upright; }
void setThreshold(double threshold_) { threshold = threshold_; }
double getThreshold() const { return threshold; }
void setNOctaves(int octaves_) { octaves = octaves_; }
int getNOctaves() const { return octaves; }
void setNOctaveLayers(int octaveLayers_) { sublevels = octaveLayers_; }
int getNOctaveLayers() const { return sublevels; }
void setDiffusivity(int diff_) { diffusivity = diff_; }
int getDiffusivity() const { return diffusivity; }
// returns the descriptor size in bytes
int descriptorSize() const
{
return extended ? 128 : 64;
}
// returns the descriptor type
int descriptorType() const
{
return CV_32F;
}
// returns the default norm type
int defaultNorm() const
{
return NORM_L2;
}
void detectAndCompute(InputArray image, InputArray mask,
std::vector<KeyPoint>& keypoints,
OutputArray descriptors,
bool useProvidedKeypoints)
{
cv::Mat img = image.getMat();
if (img.type() != CV_8UC1)
cvtColor(image, img, COLOR_BGR2GRAY);
Mat img1_32;
img.convertTo(img1_32, CV_32F, 1.0 / 255.0, 0);
KAZEOptions options;
options.img_width = img.cols;
options.img_height = img.rows;
options.extended = extended;
options.upright = upright;
options.dthreshold = threshold;
options.omax = octaves;
options.nsublevels = sublevels;
options.diffusivity = diffusivity;
KAZEFeatures impl(options);
impl.Create_Nonlinear_Scale_Space(img1_32);
if (!useProvidedKeypoints)
{
impl.Feature_Detection(keypoints);
}
if (!mask.empty())
{
cv::KeyPointsFilter::runByPixelsMask(keypoints, mask.getMat());
}
if( descriptors.needed() )
{
Mat& desc = descriptors.getMatRef();
impl.Feature_Description(keypoints, desc);
CV_Assert((!desc.rows || desc.cols == descriptorSize()));
CV_Assert((!desc.rows || (desc.type() == descriptorType())));
}
}
void write(FileStorage& fs) const
{
fs << "extended" << (int)extended;
fs << "upright" << (int)upright;
fs << "threshold" << threshold;
fs << "octaves" << octaves;
fs << "sublevels" << sublevels;
fs << "diffusivity" << diffusivity;
}
void read(const FileNode& fn)
{
extended = (int)fn["extended"] != 0;
upright = (int)fn["upright"] != 0;
threshold = (float)fn["threshold"];
octaves = (int)fn["octaves"];
sublevels = (int)fn["sublevels"];
diffusivity = (int)fn["diffusivity"];
}
bool extended;
bool upright;
float threshold;
int octaves;
int sublevels;
int diffusivity;
};
Ptr<KAZE> KAZE::create(bool extended, bool upright,
float threshold,
int octaves, int sublevels,
int diffusivity)
{
return makePtr<KAZE_Impl>(extended, upright, threshold, octaves, sublevels, diffusivity);
}
}