Repository for OpenCV's extra modules
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///////////// see LICENSE.txt in the OpenCV root directory //////////////
#ifndef __OPENCV_XFEATURES2D_SURF_HPP__
#define __OPENCV_XFEATURES2D_SURF_HPP__
namespace cv
{
namespace xfeatures2d
{
//! Speeded up robust features, port from CUDA module.
////////////////////////////////// SURF //////////////////////////////////////////
/*!
SURF implementation.
The class implements SURF algorithm by H. Bay et al.
*/
class SURF_Impl : public SURF
{
public:
//! the full constructor taking all the necessary parameters
explicit CV_WRAP SURF_Impl(double hessianThreshold,
int nOctaves = 4, int nOctaveLayers = 2,
bool extended = true, bool upright = false);
//! returns the descriptor size in float's (64 or 128)
CV_WRAP int descriptorSize() const;
//! returns the descriptor type
CV_WRAP int descriptorType() const;
//! returns the descriptor type
CV_WRAP int defaultNorm() const;
void set(int, double);
double get(int) const;
//! finds the keypoints and computes their descriptors.
// Optionally it can compute descriptors for the user-provided keypoints
void detectAndCompute(InputArray img, InputArray mask,
CV_OUT std::vector<KeyPoint>& keypoints,
OutputArray descriptors,
bool useProvidedKeypoints = false);
void setHessianThreshold(double hessianThreshold_) { hessianThreshold = hessianThreshold_; }
double getHessianThreshold() const { return hessianThreshold; }
void setNOctaves(int nOctaves_) { nOctaves = nOctaves_; }
int getNOctaves() const { return nOctaves; }
void setNOctaveLayers(int nOctaveLayers_) { nOctaveLayers = nOctaveLayers_; }
int getNOctaveLayers() const { return nOctaveLayers; }
void setExtended(bool extended_) { extended = extended_; }
bool getExtended() const { return extended; }
void setUpright(bool upright_) { upright = upright_; }
bool getUpright() const { return upright; }
double hessianThreshold;
int nOctaves;
int nOctaveLayers;
bool extended;
bool upright;
};
#ifdef HAVE_OPENCL
class SURF_OCL
{
public:
enum KeypointLayout
{
X_ROW = 0,
Y_ROW,
LAPLACIAN_ROW,
OCTAVE_ROW,
SIZE_ROW,
ANGLE_ROW,
HESSIAN_ROW,
ROWS_COUNT
};
//! the full constructor taking all the necessary parameters
SURF_OCL();
bool init(const SURF_Impl* params);
//! returns the descriptor size in float's (64 or 128)
int descriptorSize() const { return params->extended ? 128 : 64; }
void uploadKeypoints(const std::vector<KeyPoint> &keypoints, UMat &keypointsGPU);
void downloadKeypoints(const UMat &keypointsGPU, std::vector<KeyPoint> &keypoints);
//! finds the keypoints using fast hessian detector used in SURF
//! supports CV_8UC1 images
//! keypoints will have nFeature cols and 6 rows
//! keypoints.ptr<float>(X_ROW)[i] will contain x coordinate of i'th feature
//! keypoints.ptr<float>(Y_ROW)[i] will contain y coordinate of i'th feature
//! keypoints.ptr<float>(LAPLACIAN_ROW)[i] will contain laplacian sign of i'th feature
//! keypoints.ptr<float>(OCTAVE_ROW)[i] will contain octave of i'th feature
//! keypoints.ptr<float>(SIZE_ROW)[i] will contain size of i'th feature
//! keypoints.ptr<float>(ANGLE_ROW)[i] will contain orientation of i'th feature
//! keypoints.ptr<float>(HESSIAN_ROW)[i] will contain response of i'th feature
bool detect(InputArray img, InputArray mask, UMat& keypoints);
//! finds the keypoints and computes their descriptors.
//! Optionally it can compute descriptors for the user-provided keypoints and recompute keypoints direction
bool detectAndCompute(InputArray img, InputArray mask, UMat& keypoints,
OutputArray descriptors, bool useProvidedKeypoints = false);
protected:
bool setImage(InputArray img, InputArray mask);
// kernel callers declarations
bool calcLayerDetAndTrace(int octave, int layer_rows);
bool findMaximaInLayer(int counterOffset, int octave, int layer_rows, int layer_cols);
bool interpolateKeypoint(int maxCounter, UMat &keypoints, int octave, int layer_rows, int maxFeatures);
bool calcOrientation(UMat &keypoints);
bool setUpRight(UMat &keypoints);
bool computeDescriptors(const UMat &keypoints, OutputArray descriptors);
bool detectKeypoints(UMat &keypoints);
const SURF_Impl* params;
//! max keypoints = min(keypointsRatio * img.size().area(), 65535)
UMat sum, intBuffer;
UMat det, trace;
UMat maxPosBuffer;
int img_cols, img_rows;
int maxCandidates;
int maxFeatures;
UMat img, counters;
// texture buffers
ocl::Image2D imgTex, sumTex;
bool haveImageSupport;
String kerOpts;
int status;
};
#endif // HAVE_OPENCL
/*
template<typename _Tp> void copyVectorToUMat(const std::vector<_Tp>& v, UMat& um)
{
if(v.empty())
um.release();
else
Mat(1, (int)(v.size()*sizeof(v[0])), CV_8U, (void*)&v[0]).copyTo(um);
}
template<typename _Tp> void copyUMatToVector(const UMat& um, std::vector<_Tp>& v)
{
if(um.empty())
v.clear();
else
{
size_t sz = um.total()*um.elemSize();
CV_Assert(um.isContinuous() && (sz % sizeof(_Tp) == 0));
v.resize(sz/sizeof(_Tp));
Mat m(um.size(), um.type(), &v[0]);
um.copyTo(m);
}
}*/
}
}
#endif