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compilation with no cuda re factored

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This commit is contained in:
Anatoly Baksheev
2010-07-19 09:31:12 +00:00
parent 20e2dc84b0
commit 07825bad1e
15 changed files with 555 additions and 587 deletions
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5
modules/gpu/include/opencv2/gpu/devmem2d.hpp
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@@ -48,12 +48,13 @@ namespace cv
namespace gpu
{
// Simple lightweight structure that encapsulates image ptr on device, its pitch and its sizes.
// It is intended to pass to nvcc-compiled code.
// It is intended to pass to nvcc-compiled code. GpuMat depends on headers that nvcc can't compile
template<typename T = unsigned char>
struct DevMem2D_
{
enum { elem_size = sizeof(T) };
typedef T elem_t;
enum { elem_size = sizeof(elem_t) };
int cols;
int rows;

135
modules/gpu/include/opencv2/gpu/gpu.hpp
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@@ -52,15 +52,20 @@ namespace cv
{
//////////////////////////////// Initialization ////////////////////////
//! This is the only function that do not throw exceptions if the library is compiled without Cuda.
CV_EXPORTS int getCudaEnabledDeviceCount();
//! Functions below throw cv::Expception if the library is compiled without Cuda.
CV_EXPORTS string getDeviceName(int device);
CV_EXPORTS void setDevice(int device);
CV_EXPORTS int getDevice();
CV_EXPORTS void getComputeCapability(int device, int* major, int* minor);
CV_EXPORTS int getNumberOfSMs(int device);
//////////////////////////////// GpuMat ////////////////////////////////
//! Smart pointer for GPU memory with reference counting. Its interface is mostly similar with cv::Mat.
class CV_EXPORTS GpuMat
{
public:
@@ -85,7 +90,7 @@ namespace cv
GpuMat(const GpuMat& m, const Rect& roi);
//! builds GpuMat from Mat. Perfom blocking upload to device.
GpuMat (const Mat& m);
explicit GpuMat (const Mat& m);
//! destructor - calls release()
~GpuMat();
@@ -211,44 +216,109 @@ namespace cv
uchar* dataend;
};
//////////////////////////////// CudaStream ////////////////////////////////
//////////////////////////////// MatPL ////////////////////////////////
// MatPL is limited cv::Mat with page locked memory allocation.
// Page locked memory is only needed for async and faster coping to GPU.
// It is convertable to cv::Mat header without reference counting
// so you can use it with other opencv functions.
class CV_EXPORTS MatPL
{
public:
class CudaStream
//Not supported. Now behaviour is like ALLOC_DEFAULT.
//enum { ALLOC_DEFAULT = 0, ALLOC_PORTABLE = 1, ALLOC_WRITE_COMBINED = 4 }
MatPL();
MatPL(const MatPL& m);
MatPL(int _rows, int _cols, int _type);
MatPL(Size _size, int _type);
//! creates from cv::Mat with coping data
explicit MatPL(const Mat& m);
~MatPL();
MatPL& operator = (const MatPL& m);
//! returns deep copy of the matrix, i.e. the data is copied
MatPL clone() const;
//! allocates new matrix data unless the matrix already has specified size and type.
void create(int _rows, int _cols, int _type);
void create(Size _size, int _type);
//! decrements reference counter and released memory if needed.
void release();
//! returns matrix header with disabled reference counting for MatPL data.
Mat createMatHeader() const;
operator Mat() const;
// Please see cv::Mat for descriptions
bool isContinuous() const;
size_t elemSize() const;
size_t elemSize1() const;
int type() const;
int depth() const;
int channels() const;
size_t step1() const;
Size size() const;
bool empty() const;
// Please see cv::Mat for descriptions
int flags;
int rows, cols;
size_t step;
uchar* data;
int* refcount;
uchar* datastart;
uchar* dataend;
};
//////////////////////////////// CudaStream ////////////////////////////////
// Encapculates Cuda Stream. Provides interface for async coping.
// Passed to each function that supports async kernel execution.
// Reference counting is enabled
class CV_EXPORTS CudaStream
{
public:
static CudaStream empty();
CudaStream();
~CudaStream();
CudaStream(const CudaStream&);
CudaStream& operator=(const CudaStream&);
bool queryIfComplete();
void waitForCompletion();
void waitForCompletion();
//calls cudaMemcpyAsync
//! downloads asynchronously.
// Warning! cv::Mat must point to page locked memory (i.e. to MatPL data or to its subMat)
void enqueueDownload(const GpuMat& src, MatPL& dst);
void enqueueDownload(const GpuMat& src, Mat& dst);
//! uploads asynchronously.
// Warning! cv::Mat must point to page locked memory (i.e. to MatPL data or to its ROI)
void enqueueUpload(const MatPL& src, GpuMat& dst);
void enqueueUpload(const Mat& src, GpuMat& dst);
void enqueueCopy(const GpuMat& src, GpuMat& dst);
// calls cudaMemset2D asynchronous for single channel. Invoke kernel for some multichannel.
void enqueueMemSet(const GpuMat& src, Scalar val);
// invoke kernel asynchronous because of mask
void enqueueMemSet(const GpuMat& src, Scalar val);
void enqueueMemSet(const GpuMat& src, Scalar val, const GpuMat& mask);
// converts matrix type, ex from float to uchar depending on type
void enqueueConvert(const GpuMat& src, GpuMat& dst, int type);
struct Impl;
const Impl& getImpl() const;
void enqueueConvert(const GpuMat& src, GpuMat& dst, int type, double a = 1, double b = 0);
private:
Impl *impl;
CudaStream(const CudaStream&);
CudaStream& operator=(const CudaStream&);
void create();
void release();
struct Impl;
Impl *impl;
friend struct StreamAccessor;
};
//////////////////////////////// StereoBM_GPU ////////////////////////////////
@@ -265,17 +335,22 @@ namespace cv
StereoBM_GPU(int preset, int ndisparities=0);
//! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair
//! Output disparity has CV_8U type.
void operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity) const;
void operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity);
//! Acync version
void operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity, const CudaStream& stream);
//! Some heuristics that tries to estmate
// if current GPU will be faster then CPU in this algorithm.
// It queries current active device.
static bool checkIfGpuCallReasonable();
private:
mutable GpuMat minSSD;
GpuMat minSSD;
int preset;
int ndisp;
};
}
}
#include "opencv2/gpu/gpumat.hpp"
#include "opencv2/gpu/matrix_operations.hpp"
#endif /* __OPENCV_GPU_HPP__ */

265
modules/gpu/include/opencv2/gpu/matpl.hpp
View File

@@ -1,265 +0,0 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other GpuMaterials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_GPU_MATPL_HPP__
#define __OPENCV_GPU_MATPL_HPP__
#include "opencv2/core/core.hpp"
namespace cv
{
namespace gpu
{
//////////////////////////////// MatPL ////////////////////////////////
//class CV_EXPORTS MatPL : private Mat
//{
//public:
// MatPL() {}
// MatPL(int _rows, int _cols, int _type) : Mat(_rows, _cols, _type) {}
// MatPL(Size _size, int _type) : Mat(_size, _type) {}
//
// Mat(int _rows, int _cols, int _type, const Scalar& _s) : Mat
// MatPL(Size _size, int _type, const Scalar& _s);
// //! copy constructor
// MatPL(const Mat& m);
// //! constructor for matrix headers pointing to user-allocated data
// MatPL(int _rows, int _cols, int _type, void* _data, size_t _step=AUTO_STEP);
// MatPL(Size _size, int _type, void* _data, size_t _step=AUTO_STEP);
// //! creates a matrix header for a part of the bigger matrix
// MatPL(const Mat& m, const Range& rowRange, const Range& colRange);
// MatPL(const Mat& m, const Rect& roi);
// //! converts old-style CvMat to the new matrix; the data is not copied by default
// Mat(const CvMat* m, bool copyData=false);
// MatPL converts old-style IplImage to the new matrix; the data is not copied by default
// MatPL(const IplImage* img, bool copyData=false);
// //! builds matrix from std::vector with or without copying the data
// template<typename _Tp> explicit Mat(const vector<_Tp>& vec, bool copyData=false);
// //! builds matrix from cv::Vec; the data is copied by default
// template<typename _Tp, int n> explicit Mat(const Vec<_Tp, n>& vec,
// bool copyData=true);
// //! builds matrix from cv::Matx; the data is copied by default
// template<typename _Tp, int m, int n> explicit Mat(const Matx<_Tp, m, n>& mtx,
// bool copyData=true);
// //! builds matrix from a 2D point
// template<typename _Tp> explicit Mat(const Point_<_Tp>& pt);
// //! builds matrix from a 3D point
// template<typename _Tp> explicit Mat(const Point3_<_Tp>& pt);
// //! builds matrix from comma initializer
// template<typename _Tp> explicit Mat(const MatCommaInitializer_<_Tp>& commaInitializer);
// //! helper constructor to compile matrix expressions
// Mat(const MatExpr_Base& expr);
// //! destructor - calls release()
// ~Mat();
// //! assignment operators
// Mat& operator = (const Mat& m);
// Mat& operator = (const MatExpr_Base& expr);
// operator MatExpr_<Mat, Mat>() const;
// //! returns a new matrix header for the specified row
// Mat row(int y) const;
// //! returns a new matrix header for the specified column
// Mat col(int x) const;
// //! ... for the specified row span
// Mat rowRange(int startrow, int endrow) const;
// Mat rowRange(const Range& r) const;
// //! ... for the specified column span
// Mat colRange(int startcol, int endcol) const;
// Mat colRange(const Range& r) const;
// //! ... for the specified diagonal
// // (d=0 - the main diagonal,
// // >0 - a diagonal from the lower half,
// // <0 - a diagonal from the upper half)
// Mat diag(int d=0) const;
// //! constructs a square diagonal matrix which main diagonal is vector "d"
// static Mat diag(const Mat& d);
// //! returns deep copy of the matrix, i.e. the data is copied
// Mat clone() const;
// //! copies the matrix content to "m".
// // It calls m.create(this->size(), this->type()).
// void copyTo( Mat& m ) const;
// //! copies those matrix elements to "m" that are marked with non-zero mask elements.
// void copyTo( Mat& m, const Mat& mask ) const;
// //! converts matrix to another datatype with optional scalng. See cvConvertScale.
// void convertTo( Mat& m, int rtype, double alpha=1, double beta=0 ) const;
// void assignTo( Mat& m, int type=-1 ) const;
// //! sets every matrix element to s
// Mat& operator = (const Scalar& s);
// //! sets some of the matrix elements to s, according to the mask
// Mat& setTo(const Scalar& s, const Mat& mask=Mat());
// //! creates alternative matrix header for the same data, with different
// // number of channels and/or different number of rows. see cvReshape.
// Mat reshape(int _cn, int _rows=0) const;
// //! matrix transposition by means of matrix expressions
// MatExpr_<MatExpr_Op2_<Mat, double, Mat, MatOp_T_<Mat> >, Mat>
// t() const;
// //! matrix inversion by means of matrix expressions
// MatExpr_<MatExpr_Op2_<Mat, int, Mat, MatOp_Inv_<Mat> >, Mat>
// inv(int method=DECOMP_LU) const;
// MatExpr_<MatExpr_Op4_<Mat, Mat, double, char, Mat, MatOp_MulDiv_<Mat> >, Mat>
// //! per-element matrix multiplication by means of matrix expressions
// mul(const Mat& m, double scale=1) const;
// MatExpr_<MatExpr_Op4_<Mat, Mat, double, char, Mat, MatOp_MulDiv_<Mat> >, Mat>
// mul(const MatExpr_<MatExpr_Op2_<Mat, double, Mat, MatOp_Scale_<Mat> >, Mat>& m, double scale=1) const;
// MatExpr_<MatExpr_Op4_<Mat, Mat, double, char, Mat, MatOp_MulDiv_<Mat> >, Mat>
// mul(const MatExpr_<MatExpr_Op2_<Mat, double, Mat, MatOp_DivRS_<Mat> >, Mat>& m, double scale=1) const;
// //! computes cross-product of 2 3D vectors
// Mat cross(const Mat& m) const;
// //! computes dot-product
// double dot(const Mat& m) const;
// //! Matlab-style matrix initialization
// static MatExpr_Initializer zeros(int rows, int cols, int type);
// static MatExpr_Initializer zeros(Size size, int type);
// static MatExpr_Initializer ones(int rows, int cols, int type);
// static MatExpr_Initializer ones(Size size, int type);
// static MatExpr_Initializer eye(int rows, int cols, int type);
// static MatExpr_Initializer eye(Size size, int type);
// //! allocates new matrix data unless the matrix already has specified size and type.
// // previous data is unreferenced if needed.
// void create(int _rows, int _cols, int _type);
// void create(Size _size, int _type);
// //! increases the reference counter; use with care to avoid memleaks
// void addref();
// //! decreases reference counter;
// // deallocate the data when reference counter reaches 0.
// void release();
// //! locates matrix header within a parent matrix. See below
// void locateROI( Size& wholeSize, Point& ofs ) const;
// //! moves/resizes the current matrix ROI inside the parent matrix.
// Mat& adjustROI( int dtop, int dbottom, int dleft, int dright );
// //! extracts a rectangular sub-matrix
// // (this is a generalized form of row, rowRange etc.)
// Mat operator()( Range rowRange, Range colRange ) const;
// Mat operator()( const Rect& roi ) const;
// //! converts header to CvMat; no data is copied
// operator CvMat() const;
// //! converts header to IplImage; no data is copied
// operator IplImage() const;
// //! returns true iff the matrix data is continuous
// // (i.e. when there are no gaps between successive rows).
// // similar to CV_IS_MAT_CONT(cvmat->type)
// bool isContinuous() const;
// //! returns element size in bytes,
// // similar to CV_ELEM_SIZE(cvmat->type)
// size_t elemSize() const;
// //! returns the size of element channel in bytes.
// size_t elemSize1() const;
// //! returns element type, similar to CV_MAT_TYPE(cvmat->type)
// int type() const;
// //! returns element type, similar to CV_MAT_DEPTH(cvmat->type)
// int depth() const;
// //! returns element type, similar to CV_MAT_CN(cvmat->type)
// int channels() const;
// //! returns step/elemSize1()
// size_t step1() const;
// //! returns matrix size:
// // width == number of columns, height == number of rows
// Size size() const;
// //! returns true if matrix data is NULL
// bool empty() const;
// //! returns pointer to y-th row
// uchar* ptr(int y=0);
// const uchar* ptr(int y=0) const;
// //! template version of the above method
// template<typename _Tp> _Tp* ptr(int y=0);
// template<typename _Tp> const _Tp* ptr(int y=0) const;
// //! template methods for read-write or read-only element access.
// // note that _Tp must match the actual matrix type -
// // the functions do not do any on-fly type conversion
// template<typename _Tp> _Tp& at(int y, int x);
// template<typename _Tp> _Tp& at(Point pt);
// template<typename _Tp> const _Tp& at(int y, int x) const;
// template<typename _Tp> const _Tp& at(Point pt) const;
// template<typename _Tp> _Tp& at(int i);
// template<typename _Tp> const _Tp& at(int i) const;
// //! template methods for iteration over matrix elements.
// // the iterators take care of skipping gaps in the end of rows (if any)
// template<typename _Tp> MatIterator_<_Tp> begin();
// template<typename _Tp> MatIterator_<_Tp> end();
// template<typename _Tp> MatConstIterator_<_Tp> begin() const;
// template<typename _Tp> MatConstIterator_<_Tp> end() const;
// enum { MAGIC_VAL=0x42FF0000, AUTO_STEP=0, CONTINUOUS_FLAG=CV_MAT_CONT_FLAG };
// /*! includes several bit-fields:
// - the magic signature
// - continuity flag
// - depth
// - number of channels
// */
// int flags;
// //! the number of rows and columns
// int rows, cols;
// //! a distance between successive rows in bytes; includes the gap if any
// size_t step;
// //! pointer to the data
// uchar* data;
// //! pointer to the reference counter;
// // when matrix points to user-allocated data, the pointer is NULL
// int* refcount;
// //! helper fields used in locateROI and adjustROI
// uchar* datastart;
// uchar* dataend;
//};
}
}
#endif /* __OPENCV_GPU_MATPL_HPP__ */

98
modules/gpu/include/opencv2/gpu/gpumat.hpp → modules/gpu/include/opencv2/gpu/matrix_operations.hpp
View File

@@ -43,27 +43,25 @@
#ifndef __OPENCV_GPU_MATRIX_OPERATIONS_HPP__
#define __OPENCV_GPU_MATRIX_OPERATIONS_HPP__
namespace cv
{
namespace gpu
{
////////////////////////////////////////////////////////////////////////
//////////////////////////////// GpuMat ////////////////////////////////
////////////////////////////////////////////////////////////////////////
inline GpuMat::GpuMat()
: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) {}
inline GpuMat::GpuMat() : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) {}
inline GpuMat::GpuMat(int _rows, int _cols, int _type)
: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
inline GpuMat::GpuMat(int _rows, int _cols, int _type) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
{
if( _rows > 0 && _cols > 0 )
create( _rows, _cols, _type );
}
inline GpuMat::GpuMat(Size _size, int _type)
: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
inline GpuMat::GpuMat(Size _size, int _type) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
{
if( _size.height > 0 && _size.width > 0 )
create( _size.height, _size.width, _type );
@@ -249,12 +247,9 @@ inline void GpuMat::assignTo( GpuMat& m, int type ) const
//CPP GpuMat& GpuMat::operator = (const Scalar& s);
//CPP GpuMat& GpuMat::setTo(const Scalar& s, const GpuMat& mask=GpuMat());
//CPP GpuMat GpuMat::reshape(int _cn, int _rows=0) const;
//CPP void GpuMat::create(int _rows, int _cols, int _type);
inline void GpuMat::create(Size _size, int _type) { create(_size.height, _size.width, _type); }
//CPP void GpuMat::create(int _rows, int _cols, int _type);
//CPP void GpuMat::release();
inline void GpuMat::swap(GpuMat& b)
@@ -343,6 +338,87 @@ template<typename _Tp> inline const _Tp* GpuMat::ptr(int y) const
static inline void swap( GpuMat& a, GpuMat& b ) { a.swap(b); }
///////////////////////////////////////////////////////////////////////
//////////////////////////////// MatPL ////////////////////////////////
///////////////////////////////////////////////////////////////////////
MatPL::MatPL() : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) {}
MatPL::MatPL(int _rows, int _cols, int _type) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
{
if( _rows > 0 && _cols > 0 )
create( _rows, _cols, _type );
}
MatPL::MatPL(Size _size, int _type) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
{
if( _size.height > 0 && _size.width > 0 )
create( _size.height, _size.width, _type );
}
MatPL::MatPL(const MatPL& m) : flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data), refcount(m.refcount), datastart(0), dataend(0)
{
if( refcount )
CV_XADD(refcount, 1);
}
MatPL::MatPL(const Mat& m) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
{
if( m.rows > 0 && m.cols > 0 )
create( m.size(), m.type() );
Mat tmp = createMatHeader();
m.copyTo(tmp);
}
MatPL::~MatPL()
{
release();
}
MatPL& MatPL::operator = (const MatPL& m)
{
if( this != &m )
{
if( m.refcount )
CV_XADD(m.refcount, 1);
release();
flags = m.flags;
rows = m.rows; cols = m.cols;
step = m.step; data = m.data;
datastart = m.datastart;
dataend = m.dataend;
refcount = m.refcount;
}
return *this;
}
MatPL MatPL::clone() const
{
MatPL m(size(), type());
Mat to = m;
Mat from = *this;
from.copyTo(to);
return m;
}
inline void MatPL::create(Size _size, int _type) { create(_size.height, _size.width, _type); }
//CCP void MatPL::create(int _rows, int _cols, int _type);
//CPP void MatPL::release();
inline Mat MatPL::createMatHeader() const { return Mat(size(), type(), data); }
inline MatPL::operator Mat() const { return createMatHeader(); }
inline bool MatPL::isContinuous() const { return (flags & Mat::CONTINUOUS_FLAG) != 0; }
inline size_t MatPL::elemSize() const { return CV_ELEM_SIZE(flags); }
inline size_t MatPL::elemSize1() const { return CV_ELEM_SIZE1(flags); }
inline int MatPL::type() const { return CV_MAT_TYPE(flags); }
inline int MatPL::depth() const { return CV_MAT_DEPTH(flags); }
inline int MatPL::channels() const { return CV_MAT_CN(flags); }
inline size_t MatPL::step1() const { return step/elemSize1(); }
inline Size MatPL::size() const { return Size(cols, rows); }
inline bool MatPL::empty() const { return data == 0; }
} /* end of namespace gpu */
} /* end of namespace cv */

64
modules/gpu/include/opencv2/gpu/stream_accessor.hpp Normal file
View File

@@ -0,0 +1,64 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other GpuMaterials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_GPU_STREAM_ACCESSOR_HPP__
#define __OPENCV_GPU_STREAM_ACCESSOR_HPP__
#include "opencv2/gpu/gpu.hpp"
#include "cuda_runtime_api.h"
namespace cv
{
namespace gpu
{
// This is only header file that depends on Cuda. All other headers are independent.
// So if you use OpenCV binaries you do noot need to install Cuda Toolkit.
// But of you wanna use GPU by yourself, may get cuda stream instance using the class below.
// In this case you have to install Cuda Toolkit.
struct StreamAccessor
{
CV_EXPORTS static cudaStream_t getStream(const CudaStream& stream);
};
}
}
#endif /* __OPENCV_GPU_STREAM_ACCESSOR_HPP__ */