generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

moved GpuMat and DevMem2D to core module, some code refactoring

Browse Source
This commit is contained in:
Vladislav Vinogradov
2011-11-09 13:13:52 +00:00
parent 8a148e39f0
commit fcfa72081e
95 changed files with 18889 additions and 18485 deletions
Download Patch File Download Diff File Expand all files Collapse all files

8
modules/core/include/opencv2/core/core.hpp
View File

@@ -90,6 +90,10 @@ class Mat;
class SparseMat;
typedef Mat MatND;
namespace gpu {
class GpuMat;
}
class CV_EXPORTS MatExpr;
class CV_EXPORTS MatOp_Base;
class CV_EXPORTS MatArg;
@@ -1627,6 +1631,10 @@ public:
template<typename _Tp> explicit Mat(const Point3_<_Tp>& pt, bool copyData=true);
//! builds matrix from comma initializer
template<typename _Tp> explicit Mat(const MatCommaInitializer_<_Tp>& commaInitializer);
//! download data from GpuMat
explicit Mat(const gpu::GpuMat& m);
//! destructor - calls release()
~Mat();
//! assignment operators

157
modules/core/include/opencv2/core/devmem2d.hpp Normal file
View File

@@ -0,0 +1,157 @@
/*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_CORE_DevMem2D_HPP__
#define __OPENCV_CORE_DevMem2D_HPP__
#ifdef __CUDACC__
#define __CV_GPU_HOST_DEVICE__ __host__ __device__ __forceinline__
#else
#define __CV_GPU_HOST_DEVICE__
#endif
namespace cv
{
namespace gpu
{
// Simple lightweight structures that encapsulates information about an image on device.
// It is intended to pass to nvcc-compiled code. GpuMat depends on headers that nvcc can't compile
template <bool expr> struct StaticAssert;
template <> struct StaticAssert<true> {static __CV_GPU_HOST_DEVICE__ void check(){}};
template<typename T> struct DevPtr
{
typedef T elem_type;
typedef int index_type;
enum { elem_size = sizeof(elem_type) };
T* data;
__CV_GPU_HOST_DEVICE__ DevPtr() : data(0) {}
__CV_GPU_HOST_DEVICE__ DevPtr(T* data_) : data(data_) {}
__CV_GPU_HOST_DEVICE__ size_t elemSize() const { return elem_size; }
__CV_GPU_HOST_DEVICE__ operator T*() { return data; }
__CV_GPU_HOST_DEVICE__ operator const T*() const { return data; }
};
template<typename T> struct PtrSz : public DevPtr<T>
{
__CV_GPU_HOST_DEVICE__ PtrSz() : size(0) {}
__CV_GPU_HOST_DEVICE__ PtrSz(T* data_, size_t size_) : DevPtr<T>(data_), size(size_) {}
size_t size;
};
template<typename T> struct PtrStep : public DevPtr<T>
{
__CV_GPU_HOST_DEVICE__ PtrStep() : step(0) {}
__CV_GPU_HOST_DEVICE__ PtrStep(T* data_, size_t step_) : DevPtr<T>(data_), step(step_) {}
/** \brief stride between two consecutive rows in bytes. Step is stored always and everywhere in bytes!!! */
size_t step;
__CV_GPU_HOST_DEVICE__ T* ptr(int y = 0) { return ( T*)( ( char*)DevPtr<T>::data + y * step); }
__CV_GPU_HOST_DEVICE__ const T* ptr(int y = 0) const { return (const T*)( (const char*)DevPtr<T>::data + y * step); }
__CV_GPU_HOST_DEVICE__ T& operator ()(int y, int x) { return ptr(y)[x]; }
__CV_GPU_HOST_DEVICE__ const T& operator ()(int y, int x) const { return ptr(y)[x]; }
};
template <typename T> struct PtrStepSz : public PtrStep<T>
{
__CV_GPU_HOST_DEVICE__ PtrStepSz() : cols(0), rows(0) {}
__CV_GPU_HOST_DEVICE__ PtrStepSz(int rows_, int cols_, T* data_, size_t step_)
: PtrStep<T>(data_, step_), cols(cols_), rows(rows_) {}
int cols;
int rows;
};
template <typename T> struct DevMem2D_ : public PtrStepSz<T>
{
DevMem2D_() {}
DevMem2D_(int rows_, int cols_, T* data_, size_t step_) : PtrStepSz<T>(rows_, cols_, data_, step_) {}
template <typename U>
explicit DevMem2D_(const DevMem2D_<U>& d) : PtrStepSz<T>(d.rows, d.cols, (T*)d.data, d.step) {}
};
template<typename T> struct PtrElemStep_ : public PtrStep<T>
{
PtrElemStep_(const DevMem2D_<T>& mem) : PtrStep<T>(mem.data, mem.step)
{
StaticAssert<256 % sizeof(T) == 0>::check();
PtrStep<T>::step /= PtrStep<T>::elem_size;
}
__CV_GPU_HOST_DEVICE__ T* ptr(int y = 0) { return PtrStep<T>::data + y * PtrStep<T>::step; }
__CV_GPU_HOST_DEVICE__ const T* ptr(int y = 0) const { return PtrStep<T>::data + y * PtrStep<T>::step; }
__CV_GPU_HOST_DEVICE__ T& operator ()(int y, int x) { return ptr(y)[x]; }
__CV_GPU_HOST_DEVICE__ const T& operator ()(int y, int x) const { return ptr(y)[x]; }
};
template<typename T> struct PtrStep_ : public PtrStep<T>
{
PtrStep_() {}
PtrStep_(const DevMem2D_<T>& mem) : PtrStep<T>(mem.data, mem.step) {}
};
typedef DevMem2D_<unsigned char> DevMem2Db;
typedef DevMem2Db DevMem2D;
typedef DevMem2D_<float> DevMem2Df;
typedef DevMem2D_<int> DevMem2Di;
typedef PtrStep<unsigned char> PtrStepb;
typedef PtrStep<float> PtrStepf;
typedef PtrStep<int> PtrStepi;
typedef PtrElemStep_<unsigned char> PtrElemStep;
typedef PtrElemStep_<float> PtrElemStepf;
typedef PtrElemStep_<int> PtrElemStepi;
}
}
#endif /* __OPENCV_GPU_DevMem2D_HPP__ */

471
modules/core/include/opencv2/core/gpumat.hpp Normal file
View File

@@ -0,0 +1,471 @@
/*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_GPUMAT_HPP__
#define __OPENCV_GPUMAT_HPP__
#include "opencv2/core/core.hpp"
#include "opencv2/core/devmem2d.hpp"
namespace cv { namespace gpu
{
//! Smart pointer for GPU memory with reference counting. Its interface is mostly similar with cv::Mat.
class CV_EXPORTS GpuMat
{
public:
//! default constructor
GpuMat();
//! constructs GpuMatrix of the specified size and type (_type is CV_8UC1, CV_64FC3, CV_32SC(12) etc.)
GpuMat(int rows, int cols, int type);
GpuMat(Size size, int type);
//! constucts GpuMatrix and fills it with the specified value _s.
GpuMat(int rows, int cols, int type, Scalar s);
GpuMat(Size size, int type, Scalar s);
//! copy constructor
GpuMat(const GpuMat& m);
//! constructor for GpuMatrix headers pointing to user-allocated data
GpuMat(int rows, int cols, int type, void* data, size_t step = Mat::AUTO_STEP);
GpuMat(Size size, int type, void* data, size_t step = Mat::AUTO_STEP);
//! creates a matrix header for a part of the bigger matrix
GpuMat(const GpuMat& m, Range rowRange, Range colRange);
GpuMat(const GpuMat& m, Rect roi);
//! builds GpuMat from Mat. Perfom blocking upload to device.
explicit GpuMat(const Mat& m);
//! destructor - calls release()
~GpuMat();
//! assignment operators
GpuMat& operator = (const GpuMat& m);
//! pefroms blocking upload data to GpuMat.
void upload(const Mat& m);
//! downloads data from device to host memory. Blocking calls.
void download(Mat& m) const;
//! returns a new GpuMatrix header for the specified row
GpuMat row(int y) const;
//! returns a new GpuMatrix header for the specified column
GpuMat col(int x) const;
//! ... for the specified row span
GpuMat rowRange(int startrow, int endrow) const;
GpuMat rowRange(Range r) const;
//! ... for the specified column span
GpuMat colRange(int startcol, int endcol) const;
GpuMat colRange(Range r) const;
//! returns deep copy of the GpuMatrix, i.e. the data is copied
GpuMat clone() const;
//! copies the GpuMatrix content to "m".
// It calls m.create(this->size(), this->type()).
void copyTo(GpuMat& m) const;
//! copies those GpuMatrix elements to "m" that are marked with non-zero mask elements.
void copyTo(GpuMat& m, const GpuMat& mask) const;
//! converts GpuMatrix to another datatype with optional scalng. See cvConvertScale.
void convertTo(GpuMat& m, int rtype, double alpha = 1, double beta = 0) const;
void assignTo(GpuMat& m, int type=-1) const;
//! sets every GpuMatrix element to s
GpuMat& operator = (Scalar s);
//! sets some of the GpuMatrix elements to s, according to the mask
GpuMat& setTo(Scalar s, const GpuMat& mask = GpuMat());
//! creates alternative GpuMatrix header for the same data, with different
// number of channels and/or different number of rows. see cvReshape.
GpuMat reshape(int cn, int rows = 0) const;
//! allocates new GpuMatrix data unless the GpuMatrix 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);
//! decreases reference counter;
// deallocate the data when reference counter reaches 0.
void release();
//! swaps with other smart pointer
void swap(GpuMat& mat);
//! locates GpuMatrix header within a parent GpuMatrix. See below
void locateROI(Size& wholeSize, Point& ofs) const;
//! moves/resizes the current GpuMatrix ROI inside the parent GpuMatrix.
GpuMat& adjustROI(int dtop, int dbottom, int dleft, int dright);
//! extracts a rectangular sub-GpuMatrix
// (this is a generalized form of row, rowRange etc.)
GpuMat operator()(Range rowRange, Range colRange) const;
GpuMat operator()(Rect roi) const;
//! returns true iff the GpuMatrix data is continuous
// (i.e. when there are no gaps between successive rows).
// similar to CV_IS_GpuMat_CONT(cvGpuMat->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 GpuMatrix size:
// width == number of columns, height == number of rows
Size size() const;
//! returns true if GpuMatrix 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 <typename _Tp> operator DevMem2D_<_Tp>() const;
template <typename _Tp> operator PtrStep_<_Tp>() const;
/*! 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 GpuMatrix points to user-allocated data, the pointer is NULL
int* refcount;
//! helper fields used in locateROI and adjustROI
uchar* datastart;
uchar* dataend;
};
//! Creates continuous GPU matrix
CV_EXPORTS void createContinuous(int rows, int cols, int type, GpuMat& m);
CV_EXPORTS GpuMat createContinuous(int rows, int cols, int type);
CV_EXPORTS void createContinuous(Size size, int type, GpuMat& m);
CV_EXPORTS GpuMat createContinuous(Size size, int type);
//! Ensures that size of the given matrix is not less than (rows, cols) size
//! and matrix type is match specified one too
CV_EXPORTS void ensureSizeIsEnough(int rows, int cols, int type, GpuMat& m);
CV_EXPORTS void ensureSizeIsEnough(Size size, int type, GpuMat& m);
class CV_EXPORTS GpuFuncTable
{
public:
virtual ~GpuFuncTable() {}
virtual void copy(const Mat& src, GpuMat& dst) const = 0;
virtual void copy(const GpuMat& src, Mat& dst) const = 0;
virtual void copy(const GpuMat& src, GpuMat& dst) const = 0;
virtual void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask) const = 0;
virtual void convert(const GpuMat& src, GpuMat& dst) const = 0;
virtual void convert(const GpuMat& src, GpuMat& dst, double alpha, double beta) const = 0;
virtual void setTo(GpuMat& m, Scalar s, const GpuMat& mask) const = 0;
virtual void mallocPitch(void** devPtr, size_t* step, size_t width, size_t height) const = 0;
virtual void free(void* devPtr) const = 0;
};
CV_EXPORTS void setGpuFuncTable(const GpuFuncTable* funcTbl);
////////////////////////////////////////////////////////////////////////
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)
{
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)
{
if (size_.height > 0 && size_.width > 0)
create(size_.height, size_.width, type_);
}
inline GpuMat::GpuMat(int rows_, int cols_, int type_, Scalar s_)
: 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_);
setTo(s_);
}
}
inline GpuMat::GpuMat(Size size_, int type_, Scalar s_)
: 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_);
setTo(s_);
}
}
inline GpuMat::~GpuMat()
{
release();
}
inline GpuMat GpuMat::clone() const
{
GpuMat m;
copyTo(m);
return m;
}
inline void GpuMat::assignTo(GpuMat& m, int type) const
{
if (type < 0)
m = *this;
else
convertTo(m, type);
}
inline size_t GpuMat::step1() const
{
return step / elemSize1();
}
inline bool GpuMat::empty() const
{
return data == 0;
}
template<typename _Tp> inline _Tp* GpuMat::ptr(int y)
{
return (_Tp*)ptr(y);
}
template<typename _Tp> inline const _Tp* GpuMat::ptr(int y) const
{
return (const _Tp*)ptr(y);
}
inline void swap(GpuMat& a, GpuMat& b)
{
a.swap(b);
}
inline GpuMat GpuMat::row(int y) const
{
return GpuMat(*this, Range(y, y+1), Range::all());
}
inline GpuMat GpuMat::col(int x) const
{
return GpuMat(*this, Range::all(), Range(x, x+1));
}
inline GpuMat GpuMat::rowRange(int startrow, int endrow) const
{
return GpuMat(*this, Range(startrow, endrow), Range::all());
}
inline GpuMat GpuMat::rowRange(Range r) const
{
return GpuMat(*this, r, Range::all());
}
inline GpuMat GpuMat::colRange(int startcol, int endcol) const
{
return GpuMat(*this, Range::all(), Range(startcol, endcol));
}
inline GpuMat GpuMat::colRange(Range r) const
{
return GpuMat(*this, Range::all(), r);
}
inline void GpuMat::create(Size size_, int type_)
{
create(size_.height, size_.width, type_);
}
inline GpuMat GpuMat::operator()(Range rowRange, Range colRange) const
{
return GpuMat(*this, rowRange, colRange);
}
inline GpuMat GpuMat::operator()(Rect roi) const
{
return GpuMat(*this, roi);
}
inline bool GpuMat::isContinuous() const
{
return (flags & Mat::CONTINUOUS_FLAG) != 0;
}
inline size_t GpuMat::elemSize() const
{
return CV_ELEM_SIZE(flags);
}
inline size_t GpuMat::elemSize1() const
{
return CV_ELEM_SIZE1(flags);
}
inline int GpuMat::type() const
{
return CV_MAT_TYPE(flags);
}
inline int GpuMat::depth() const
{
return CV_MAT_DEPTH(flags);
}
inline int GpuMat::channels() const
{
return CV_MAT_CN(flags);
}
inline Size GpuMat::size() const
{
return Size(cols, rows);
}
inline uchar* GpuMat::ptr(int y)
{
CV_DbgAssert((unsigned)y < (unsigned)rows);
return data + step * y;
}
inline const uchar* GpuMat::ptr(int y) const
{
CV_DbgAssert((unsigned)y < (unsigned)rows);
return data + step * y;
}
inline GpuMat& GpuMat::operator = (Scalar s)
{
setTo(s);
return *this;
}
template <class T> inline GpuMat::operator DevMem2D_<T>() const
{
return DevMem2D_<T>(rows, cols, (T*)data, step);
}
template <class T> inline GpuMat::operator PtrStep_<T>() const
{
return PtrStep_<T>(static_cast< DevMem2D_<T> >(*this));
}
inline GpuMat createContinuous(int rows, int cols, int type)
{
GpuMat m;
createContinuous(rows, cols, type, m);
return m;
}
inline void createContinuous(Size size, int type, GpuMat& m)
{
createContinuous(size.height, size.width, type, m);
}
inline GpuMat createContinuous(Size size, int type)
{
GpuMat m;
createContinuous(size, type, m);
return m;
}
inline void ensureSizeIsEnough(Size size, int type, GpuMat& m)
{
ensureSizeIsEnough(size.height, size.width, type, m);
}
inline void createContinuous(int rows, int cols, int type, GpuMat& m)
{
int area = rows * cols;
if (!m.isContinuous() || m.type() != type || m.size().area() != area)
m.create(1, area, type);
m = m.reshape(0, rows);
}
inline void ensureSizeIsEnough(int rows, int cols, int type, GpuMat& m)
{
if (m.type() == type && m.rows >= rows && m.cols >= cols)
m = m(Rect(0, 0, cols, rows));
else
m.create(rows, cols, type);
}
}}
#endif // __OPENCV_GPUMAT_HPP__