HxNvr/resources/libraries/opencv/include/opencv2/xfeatures2d/cuda.hpp

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#ifndef __OPENCV_XFEATURES2D_CUDA_HPP__
#define __OPENCV_XFEATURES2D_CUDA_HPP__
#include "opencv2/core/cuda.hpp"
namespace cv { namespace cuda {
//! @addtogroup xfeatures2d_nonfree
//! @{
/** @brief Class used for extracting Speeded Up Robust Features (SURF) from an image. :
The class SURF_CUDA implements Speeded Up Robust Features descriptor. There is a fast multi-scale
Hessian keypoint detector that can be used to find the keypoints (which is the default option). But
the descriptors can also be computed for the user-specified keypoints. Only 8-bit grayscale images
are supported.
The class SURF_CUDA can store results in the GPU and CPU memory. It provides functions to convert
results between CPU and GPU version ( uploadKeypoints, downloadKeypoints, downloadDescriptors ). The
format of CPU results is the same as SURF results. GPU results are stored in GpuMat. The keypoints
matrix is \f$\texttt{nFeatures} \times 7\f$ matrix with the CV_32FC1 type.
- keypoints.ptr\<float\>(X_ROW)[i] contains x coordinate of the i-th feature.
- keypoints.ptr\<float\>(Y_ROW)[i] contains y coordinate of the i-th feature.
- keypoints.ptr\<float\>(LAPLACIAN_ROW)[i] contains the laplacian sign of the i-th feature.
- keypoints.ptr\<float\>(OCTAVE_ROW)[i] contains the octave of the i-th feature.
- keypoints.ptr\<float\>(SIZE_ROW)[i] contains the size of the i-th feature.
- keypoints.ptr\<float\>(ANGLE_ROW)[i] contain orientation of the i-th feature.
- keypoints.ptr\<float\>(HESSIAN_ROW)[i] contains the response of the i-th feature.
The descriptors matrix is \f$\texttt{nFeatures} \times \texttt{descriptorSize}\f$ matrix with the
CV_32FC1 type.
The class SURF_CUDA uses some buffers and provides access to it. All buffers can be safely released
between function calls.
@sa SURF
@note
- An example for using the SURF keypoint matcher on GPU can be found at
opencv_source_code/samples/gpu/surf_keypoint_matcher.cpp
*/
class CV_EXPORTS SURF_CUDA
{
public:
enum KeypointLayout
{
X_ROW = 0,
Y_ROW,
LAPLACIAN_ROW,
OCTAVE_ROW,
SIZE_ROW,
ANGLE_ROW,
HESSIAN_ROW,
ROWS_COUNT
};
//! the default constructor
SURF_CUDA();
//! the full constructor taking all the necessary parameters
explicit SURF_CUDA(double _hessianThreshold, int _nOctaves=4,
int _nOctaveLayers=2, bool _extended=false, float _keypointsRatio=0.01f, bool _upright = false);
//! returns the descriptor size in float's (64 or 128)
int descriptorSize() const;
//! returns the default norm type
int defaultNorm() const;
//! upload host keypoints to device memory
void uploadKeypoints(const std::vector<KeyPoint>& keypoints, GpuMat& keypointsGPU);
//! download keypoints from device to host memory
void downloadKeypoints(const GpuMat& keypointsGPU, std::vector<KeyPoint>& keypoints);
//! download descriptors from device to host memory
void downloadDescriptors(const GpuMat& descriptorsGPU, std::vector<float>& descriptors);
//! 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
void operator()(const GpuMat& img, const GpuMat& mask, GpuMat& keypoints);
//! finds the keypoints and computes their descriptors.
//! Optionally it can compute descriptors for the user-provided keypoints and recompute keypoints direction
void operator()(const GpuMat& img, const GpuMat& mask, GpuMat& keypoints, GpuMat& descriptors,
bool useProvidedKeypoints = false);
void operator()(const GpuMat& img, const GpuMat& mask, std::vector<KeyPoint>& keypoints);
void operator()(const GpuMat& img, const GpuMat& mask, std::vector<KeyPoint>& keypoints, GpuMat& descriptors,
bool useProvidedKeypoints = false);
void operator()(const GpuMat& img, const GpuMat& mask, std::vector<KeyPoint>& keypoints, std::vector<float>& descriptors,
bool useProvidedKeypoints = false);
void releaseMemory();
// SURF parameters
double hessianThreshold;
int nOctaves;
int nOctaveLayers;
bool extended;
bool upright;
//! max keypoints = min(keypointsRatio * img.size().area(), 65535)
float keypointsRatio;
GpuMat sum, mask1, maskSum;
GpuMat det, trace;
GpuMat maxPosBuffer;
};
//! @}
}} // namespace cv { namespace cuda {
#endif // __OPENCV_XFEATURES2D_CUDA_HPP__