opencv/modules/core/src/gpumat.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//
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// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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// Redistribution and use in source and binary forms, with or without modification,
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//
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// this list of conditions and the following disclaimer.
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#include "precomp.hpp"
#include "opencv2/core/gpumat.hpp"
#include <iostream>
#ifdef HAVE_CUDA
#include <cuda_runtime.h>
#include <npp.h>
#endif
#ifdef HAVE_OPENGL
#include <GL/gl.h>
#ifdef HAVE_CUDA
#include <cuda_gl_interop.h>
#endif
#endif
using namespace std;
using namespace cv;
using namespace cv::gpu;
////////////////////////////////////////////////////////////////////////
// GpuMat
cv::gpu::GpuMat::GpuMat(const GpuMat& m)
: flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data), refcount(m.refcount), datastart(m.datastart), dataend(m.dataend)
{
if (refcount)
CV_XADD(refcount, 1);
}
cv::gpu::GpuMat::GpuMat(int rows_, int cols_, int type_, void* data_, size_t step_) :
flags(Mat::MAGIC_VAL + (type_ & TYPE_MASK)), rows(rows_), cols(cols_),
step(step_), data((uchar*)data_), refcount(0),
datastart((uchar*)data_), dataend((uchar*)data_)
{
size_t minstep = cols * elemSize();
if (step == Mat::AUTO_STEP)
{
step = minstep;
flags |= Mat::CONTINUOUS_FLAG;
}
else
{
if (rows == 1)
step = minstep;
CV_DbgAssert(step >= minstep);
flags |= step == minstep ? Mat::CONTINUOUS_FLAG : 0;
}
dataend += step * (rows - 1) + minstep;
}
cv::gpu::GpuMat::GpuMat(Size size_, int type_, void* data_, size_t step_) :
flags(Mat::MAGIC_VAL + (type_ & TYPE_MASK)), rows(size_.height), cols(size_.width),
step(step_), data((uchar*)data_), refcount(0),
datastart((uchar*)data_), dataend((uchar*)data_)
{
size_t minstep = cols * elemSize();
if (step == Mat::AUTO_STEP)
{
step = minstep;
flags |= Mat::CONTINUOUS_FLAG;
}
else
{
if (rows == 1)
step = minstep;
CV_DbgAssert(step >= minstep);
flags |= step == minstep ? Mat::CONTINUOUS_FLAG : 0;
}
dataend += step * (rows - 1) + minstep;
}
cv::gpu::GpuMat::GpuMat(const GpuMat& m, Range rowRange, Range colRange)
{
flags = m.flags;
step = m.step; refcount = m.refcount;
data = m.data; datastart = m.datastart; dataend = m.dataend;
if (rowRange == Range::all())
rows = m.rows;
else
{
CV_Assert(0 <= rowRange.start && rowRange.start <= rowRange.end && rowRange.end <= m.rows);
rows = rowRange.size();
data += step*rowRange.start;
}
if (colRange == Range::all())
cols = m.cols;
else
{
CV_Assert(0 <= colRange.start && colRange.start <= colRange.end && colRange.end <= m.cols);
cols = colRange.size();
data += colRange.start*elemSize();
flags &= cols < m.cols ? ~Mat::CONTINUOUS_FLAG : -1;
}
if (rows == 1)
flags |= Mat::CONTINUOUS_FLAG;
if (refcount)
CV_XADD(refcount, 1);
if (rows <= 0 || cols <= 0)
rows = cols = 0;
}
cv::gpu::GpuMat::GpuMat(const GpuMat& m, Rect roi) :
flags(m.flags), rows(roi.height), cols(roi.width),
step(m.step), data(m.data + roi.y*step), refcount(m.refcount),
datastart(m.datastart), dataend(m.dataend)
{
flags &= roi.width < m.cols ? ~Mat::CONTINUOUS_FLAG : -1;
data += roi.x * elemSize();
CV_Assert(0 <= roi.x && 0 <= roi.width && roi.x + roi.width <= m.cols && 0 <= roi.y && 0 <= roi.height && roi.y + roi.height <= m.rows);
if (refcount)
CV_XADD(refcount, 1);
if (rows <= 0 || cols <= 0)
rows = cols = 0;
}
cv::gpu::GpuMat::GpuMat(const Mat& m) :
flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
{
upload(m);
}
GpuMat& cv::gpu::GpuMat::operator = (const GpuMat& m)
{
if (this != &m)
{
GpuMat temp(m);
swap(temp);
}
return *this;
}
void cv::gpu::GpuMat::swap(GpuMat& b)
{
std::swap(flags, b.flags);
std::swap(rows, b.rows);
std::swap(cols, b.cols);
std::swap(step, b.step);
std::swap(data, b.data);
std::swap(datastart, b.datastart);
std::swap(dataend, b.dataend);
std::swap(refcount, b.refcount);
}
void cv::gpu::GpuMat::locateROI(Size& wholeSize, Point& ofs) const
{
size_t esz = elemSize();
ptrdiff_t delta1 = data - datastart;
ptrdiff_t delta2 = dataend - datastart;
CV_DbgAssert(step > 0);
if (delta1 == 0)
ofs.x = ofs.y = 0;
else
{
ofs.y = static_cast<int>(delta1 / step);
ofs.x = static_cast<int>((delta1 - step * ofs.y) / esz);
CV_DbgAssert(data == datastart + ofs.y * step + ofs.x * esz);
}
size_t minstep = (ofs.x + cols) * esz;
wholeSize.height = std::max(static_cast<int>((delta2 - minstep) / step + 1), ofs.y + rows);
wholeSize.width = std::max(static_cast<int>((delta2 - step * (wholeSize.height - 1)) / esz), ofs.x + cols);
}
GpuMat& cv::gpu::GpuMat::adjustROI(int dtop, int dbottom, int dleft, int dright)
{
Size wholeSize;
Point ofs;
locateROI(wholeSize, ofs);
size_t esz = elemSize();
int row1 = std::max(ofs.y - dtop, 0);
int row2 = std::min(ofs.y + rows + dbottom, wholeSize.height);
int col1 = std::max(ofs.x - dleft, 0);
int col2 = std::min(ofs.x + cols + dright, wholeSize.width);
data += (row1 - ofs.y) * step + (col1 - ofs.x) * esz;
rows = row2 - row1;
cols = col2 - col1;
if (esz * cols == step || rows == 1)
flags |= Mat::CONTINUOUS_FLAG;
else
flags &= ~Mat::CONTINUOUS_FLAG;
return *this;
}
GpuMat cv::gpu::GpuMat::reshape(int new_cn, int new_rows) const
{
GpuMat hdr = *this;
int cn = channels();
if (new_cn == 0)
new_cn = cn;
int total_width = cols * cn;
if ((new_cn > total_width || total_width % new_cn != 0) && new_rows == 0)
new_rows = rows * total_width / new_cn;
if (new_rows != 0 && new_rows != rows)
{
int total_size = total_width * rows;
if (!isContinuous())
CV_Error(CV_BadStep, "The matrix is not continuous, thus its number of rows can not be changed");
if ((unsigned)new_rows > (unsigned)total_size)
CV_Error(CV_StsOutOfRange, "Bad new number of rows");
total_width = total_size / new_rows;
if (total_width * new_rows != total_size)
CV_Error(CV_StsBadArg, "The total number of matrix elements is not divisible by the new number of rows");
hdr.rows = new_rows;
hdr.step = total_width * elemSize1();
}
int new_width = total_width / new_cn;
if (new_width * new_cn != total_width)
CV_Error(CV_BadNumChannels, "The total width is not divisible by the new number of channels");
hdr.cols = new_width;
hdr.flags = (hdr.flags & ~CV_MAT_CN_MASK) | ((new_cn - 1) << CV_CN_SHIFT);
return hdr;
}
cv::Mat::Mat(const GpuMat& m) : flags(0), dims(0), rows(0), cols(0), data(0), refcount(0), datastart(0), dataend(0), datalimit(0), allocator(0), size(&rows)
{
m.download(*this);
}
namespace
{
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;
};
}
#ifndef HAVE_CUDA
namespace
{
void throw_nogpu()
{
CV_Error(CV_GpuNotSupported, "The library is compiled without GPU support");
}
class EmptyFuncTable : public GpuFuncTable
{
public:
void copy(const Mat&, GpuMat&) const { throw_nogpu(); }
void copy(const GpuMat&, Mat&) const { throw_nogpu(); }
void copy(const GpuMat&, GpuMat&) const { throw_nogpu(); }
void copyWithMask(const GpuMat&, GpuMat&, const GpuMat&) const { throw_nogpu(); }
void convert(const GpuMat&, GpuMat&) const { throw_nogpu(); }
void convert(const GpuMat&, GpuMat&, double, double) const { throw_nogpu(); }
void setTo(GpuMat&, Scalar, const GpuMat&) const { throw_nogpu(); }
void mallocPitch(void**, size_t*, size_t, size_t) const { throw_nogpu(); }
void free(void*) const {}
};
const GpuFuncTable* gpuFuncTable()
{
static EmptyFuncTable empty;
return &empty;
}
}
#else // HAVE_CUDA
namespace cv { namespace gpu { namespace device
{
void copy_to_with_mask(DevMem2Db src, DevMem2Db dst, int depth, DevMem2Db mask, int channels, cudaStream_t stream);
template <typename T>
void set_to_gpu(DevMem2Db mat, const T* scalar, int channels, cudaStream_t stream);
template <typename T>
void set_to_gpu(DevMem2Db mat, const T* scalar, DevMem2Db mask, int channels, cudaStream_t stream);
void convert_gpu(DevMem2Db src, int sdepth, DevMem2Db dst, int ddepth, double alpha, double beta, cudaStream_t stream);
}}}
namespace
{
#if defined(__GNUC__)
#define cudaSafeCall(expr) ___cudaSafeCall(expr, __FILE__, __LINE__, __func__)
#define nppSafeCall(expr) ___nppSafeCall(expr, __FILE__, __LINE__, __func__)
#else /* defined(__CUDACC__) || defined(__MSVC__) */
#define cudaSafeCall(expr) ___cudaSafeCall(expr, __FILE__, __LINE__)
#define nppSafeCall(expr) ___nppSafeCall(expr, __FILE__, __LINE__)
#endif
inline void ___cudaSafeCall(cudaError_t err, const char *file, const int line, const char *func = "")
{
if (cudaSuccess != err)
cv::gpu::error(cudaGetErrorString(err), file, line, func);
}
inline void ___nppSafeCall(int err, const char *file, const int line, const char *func = "")
{
if (err < 0)
{
std::ostringstream msg;
msg << "NPP API Call Error: " << err;
cv::gpu::error(msg.str().c_str(), file, line, func);
}
}
}
namespace
{
template <typename T> void kernelSetCaller(GpuMat& src, Scalar s, cudaStream_t stream)
{
Scalar_<T> sf = s;
::cv::gpu::device::set_to_gpu(src, sf.val, src.channels(), stream);
}
template <typename T> void kernelSetCaller(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream)
{
Scalar_<T> sf = s;
::cv::gpu::device::set_to_gpu(src, sf.val, mask, src.channels(), stream);
}
}
namespace cv { namespace gpu
{
CV_EXPORTS void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t stream = 0)
{
::cv::gpu::device::copy_to_with_mask(src, dst, src.depth(), mask, src.channels(), stream);
}
CV_EXPORTS void convertTo(const GpuMat& src, GpuMat& dst)
{
::cv::gpu::device::convert_gpu(src.reshape(1), src.depth(), dst.reshape(1), dst.depth(), 1.0, 0.0, 0);
}
CV_EXPORTS void convertTo(const GpuMat& src, GpuMat& dst, double alpha, double beta, cudaStream_t stream = 0)
{
::cv::gpu::device::convert_gpu(src.reshape(1), src.depth(), dst.reshape(1), dst.depth(), alpha, beta, stream);
}
CV_EXPORTS void setTo(GpuMat& src, Scalar s, cudaStream_t stream)
{
typedef void (*caller_t)(GpuMat& src, Scalar s, cudaStream_t stream);
static const caller_t callers[] =
{
kernelSetCaller<uchar>, kernelSetCaller<schar>, kernelSetCaller<ushort>, kernelSetCaller<short>, kernelSetCaller<int>,
kernelSetCaller<float>, kernelSetCaller<double>
};
callers[src.depth()](src, s, stream);
}
CV_EXPORTS void setTo(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream)
{
typedef void (*caller_t)(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream);
static const caller_t callers[] =
{
kernelSetCaller<uchar>, kernelSetCaller<schar>, kernelSetCaller<ushort>, kernelSetCaller<short>, kernelSetCaller<int>,
kernelSetCaller<float>, kernelSetCaller<double>
};
callers[src.depth()](src, s, mask, stream);
}
CV_EXPORTS void setTo(GpuMat& src, Scalar s)
{
setTo(src, s, 0);
}
CV_EXPORTS void setTo(GpuMat& src, Scalar s, const GpuMat& mask)
{
setTo(src, s, mask, 0);
}
}}
namespace
{
//////////////////////////////////////////////////////////////////////////
// Convert
template<int n> struct NPPTypeTraits;
template<> struct NPPTypeTraits<CV_8U> { typedef Npp8u npp_type; };
template<> struct NPPTypeTraits<CV_16U> { typedef Npp16u npp_type; };
template<> struct NPPTypeTraits<CV_16S> { typedef Npp16s npp_type; };
template<> struct NPPTypeTraits<CV_32S> { typedef Npp32s npp_type; };
template<> struct NPPTypeTraits<CV_32F> { typedef Npp32f npp_type; };
template<int SDEPTH, int DDEPTH> struct NppConvertFunc
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
typedef NppStatus (*func_ptr)(const src_t* pSrc, int nSrcStep, dst_t* pDst, int nDstStep, NppiSize oSizeROI);
};
template<int DDEPTH> struct NppConvertFunc<CV_32F, DDEPTH>
{
typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
typedef NppStatus (*func_ptr)(const Npp32f* pSrc, int nSrcStep, dst_t* pDst, int nDstStep, NppiSize oSizeROI, NppRoundMode eRoundMode);
};
template<int SDEPTH, int DDEPTH, typename NppConvertFunc<SDEPTH, DDEPTH>::func_ptr func> struct NppCvt
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
static void cvt(const GpuMat& src, GpuMat& dst)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
nppSafeCall( func(src.ptr<src_t>(), static_cast<int>(src.step), dst.ptr<dst_t>(), static_cast<int>(dst.step), sz) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<int DDEPTH, typename NppConvertFunc<CV_32F, DDEPTH>::func_ptr func> struct NppCvt<CV_32F, DDEPTH, func>
{
typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
static void cvt(const GpuMat& src, GpuMat& dst)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
nppSafeCall( func(src.ptr<Npp32f>(), static_cast<int>(src.step), dst.ptr<dst_t>(), static_cast<int>(dst.step), sz, NPP_RND_NEAR) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
//////////////////////////////////////////////////////////////////////////
// Set
template<int SDEPTH, int SCN> struct NppSetFunc
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef NppStatus (*func_ptr)(const src_t values[], src_t* pSrc, int nSrcStep, NppiSize oSizeROI);
};
template<int SDEPTH> struct NppSetFunc<SDEPTH, 1>
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef NppStatus (*func_ptr)(src_t val, src_t* pSrc, int nSrcStep, NppiSize oSizeROI);
};
template<int SDEPTH, int SCN, typename NppSetFunc<SDEPTH, SCN>::func_ptr func> struct NppSet
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
static void set(GpuMat& src, Scalar s)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
Scalar_<src_t> nppS = s;
nppSafeCall( func(nppS.val, src.ptr<src_t>(), static_cast<int>(src.step), sz) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<int SDEPTH, typename NppSetFunc<SDEPTH, 1>::func_ptr func> struct NppSet<SDEPTH, 1, func>
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
static void set(GpuMat& src, Scalar s)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
Scalar_<src_t> nppS = s;
nppSafeCall( func(nppS[0], src.ptr<src_t>(), static_cast<int>(src.step), sz) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<int SDEPTH, int SCN> struct NppSetMaskFunc
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef NppStatus (*func_ptr)(const src_t values[], src_t* pSrc, int nSrcStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep);
};
template<int SDEPTH> struct NppSetMaskFunc<SDEPTH, 1>
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef NppStatus (*func_ptr)(src_t val, src_t* pSrc, int nSrcStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep);
};
template<int SDEPTH, int SCN, typename NppSetMaskFunc<SDEPTH, SCN>::func_ptr func> struct NppSetMask
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
static void set(GpuMat& src, Scalar s, const GpuMat& mask)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
Scalar_<src_t> nppS = s;
nppSafeCall( func(nppS.val, src.ptr<src_t>(), static_cast<int>(src.step), sz, mask.ptr<Npp8u>(), static_cast<int>(mask.step)) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<int SDEPTH, typename NppSetMaskFunc<SDEPTH, 1>::func_ptr func> struct NppSetMask<SDEPTH, 1, func>
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
static void set(GpuMat& src, Scalar s, const GpuMat& mask)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
Scalar_<src_t> nppS = s;
nppSafeCall( func(nppS[0], src.ptr<src_t>(), static_cast<int>(src.step), sz, mask.ptr<Npp8u>(), static_cast<int>(mask.step)) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
class CudaFuncTable : public GpuFuncTable
{
public:
void copy(const Mat& src, GpuMat& dst) const
{
cudaSafeCall( cudaMemcpy2D(dst.data, dst.step, src.data, src.step, src.cols * src.elemSize(), src.rows, cudaMemcpyHostToDevice) );
}
void copy(const GpuMat& src, Mat& dst) const
{
cudaSafeCall( cudaMemcpy2D(dst.data, dst.step, src.data, src.step, src.cols * src.elemSize(), src.rows, cudaMemcpyDeviceToHost) );
}
void copy(const GpuMat& src, GpuMat& dst) const
{
cudaSafeCall( cudaMemcpy2D(dst.data, dst.step, src.data, src.step, src.cols * src.elemSize(), src.rows, cudaMemcpyDeviceToDevice) );
}
void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask) const
{
::cv::gpu::copyWithMask(src, dst, mask);
}
void convert(const GpuMat& src, GpuMat& dst) const
{
typedef void (*caller_t)(const GpuMat& src, GpuMat& dst);
static const caller_t callers[7][7][7] =
{
{
/* 8U -> 8U */ {0, 0, 0, 0},
/* 8U -> 8S */ {::cv::gpu::convertTo, ::cv::gpu::convertTo, ::cv::gpu::convertTo, ::cv::gpu::convertTo},
/* 8U -> 16U */ {NppCvt<CV_8U, CV_16U, nppiConvert_8u16u_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,NppCvt<CV_8U, CV_16U, nppiConvert_8u16u_C4R>::cvt},
/* 8U -> 16S */ {NppCvt<CV_8U, CV_16S, nppiConvert_8u16s_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,NppCvt<CV_8U, CV_16S, nppiConvert_8u16s_C4R>::cvt},
/* 8U -> 32S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 8U -> 32F */ {NppCvt<CV_8U, CV_32F, nppiConvert_8u32f_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 8U -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}
},
{
/* 8S -> 8U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 8S -> 8S */ {0,0,0,0},
/* 8S -> 16U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 8S -> 16S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 8S -> 32S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 8S -> 32F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 8S -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}
},
{
/* 16U -> 8U */ {NppCvt<CV_16U, CV_8U, nppiConvert_16u8u_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,NppCvt<CV_16U, CV_8U, nppiConvert_16u8u_C4R>::cvt},
/* 16U -> 8S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 16U -> 16U */ {0,0,0,0},
/* 16U -> 16S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 16U -> 32S */ {NppCvt<CV_16U, CV_32S, nppiConvert_16u32s_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 16U -> 32F */ {NppCvt<CV_16U, CV_32F, nppiConvert_16u32f_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 16U -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}
},
{
/* 16S -> 8U */ {NppCvt<CV_16S, CV_8U, nppiConvert_16s8u_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,NppCvt<CV_16S, CV_8U, nppiConvert_16s8u_C4R>::cvt},
/* 16S -> 8S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 16S -> 16U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 16S -> 16S */ {0,0,0,0},
/* 16S -> 32S */ {NppCvt<CV_16S, CV_32S, nppiConvert_16s32s_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 16S -> 32F */ {NppCvt<CV_16S, CV_32F, nppiConvert_16s32f_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 16S -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}
},
{
/* 32S -> 8U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 32S -> 8S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 32S -> 16U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 32S -> 16S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 32S -> 32S */ {0,0,0,0},
/* 32S -> 32F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 32S -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}
},
{
/* 32F -> 8U */ {NppCvt<CV_32F, CV_8U, nppiConvert_32f8u_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 32F -> 8S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 32F -> 16U */ {NppCvt<CV_32F, CV_16U, nppiConvert_32f16u_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 32F -> 16S */ {NppCvt<CV_32F, CV_16S, nppiConvert_32f16s_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 32F -> 32S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 32F -> 32F */ {0,0,0,0},
/* 32F -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}
},
{
/* 64F -> 8U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 64F -> 8S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 64F -> 16U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 64F -> 16S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 64F -> 32S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 64F -> 32F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
/* 64F -> 64F */ {0,0,0,0}
}
};
caller_t func = callers[src.depth()][dst.depth()][src.channels() - 1];
CV_DbgAssert(func != 0);
func(src, dst);
}
void convert(const GpuMat& src, GpuMat& dst, double alpha, double beta) const
{
::cv::gpu::convertTo(src, dst, alpha, beta);
}
void setTo(GpuMat& m, Scalar s, const GpuMat& mask) const
{
NppiSize sz;
sz.width = m.cols;
sz.height = m.rows;
if (mask.empty())
{
if (s[0] == 0.0 && s[1] == 0.0 && s[2] == 0.0 && s[3] == 0.0)
{
cudaSafeCall( cudaMemset2D(m.data, m.step, 0, m.cols * m.elemSize(), m.rows) );
return;
}
if (m.depth() == CV_8U)
{
int cn = m.channels();
if (cn == 1 || (cn == 2 && s[0] == s[1]) || (cn == 3 && s[0] == s[1] && s[0] == s[2]) || (cn == 4 && s[0] == s[1] && s[0] == s[2] && s[0] == s[3]))
{
int val = saturate_cast<uchar>(s[0]);
cudaSafeCall( cudaMemset2D(m.data, m.step, val, m.cols * m.elemSize(), m.rows) );
return;
}
}
typedef void (*caller_t)(GpuMat& src, Scalar s);
static const caller_t callers[7][4] =
{
{NppSet<CV_8U, 1, nppiSet_8u_C1R>::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSet<CV_8U, 4, nppiSet_8u_C4R>::set},
{::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo},
{NppSet<CV_16U, 1, nppiSet_16u_C1R>::set, NppSet<CV_16U, 2, nppiSet_16u_C2R>::set, ::cv::gpu::setTo, NppSet<CV_16U, 4, nppiSet_16u_C4R>::set},
{NppSet<CV_16S, 1, nppiSet_16s_C1R>::set, NppSet<CV_16S, 2, nppiSet_16s_C2R>::set, ::cv::gpu::setTo, NppSet<CV_16S, 4, nppiSet_16s_C4R>::set},
{NppSet<CV_32S, 1, nppiSet_32s_C1R>::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSet<CV_32S, 4, nppiSet_32s_C4R>::set},
{NppSet<CV_32F, 1, nppiSet_32f_C1R>::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSet<CV_32F, 4, nppiSet_32f_C4R>::set},
{::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo}
};
callers[m.depth()][m.channels() - 1](m, s);
}
else
{
typedef void (*caller_t)(GpuMat& src, Scalar s, const GpuMat& mask);
static const caller_t callers[7][4] =
{
{NppSetMask<CV_8U, 1, nppiSet_8u_C1MR>::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSetMask<CV_8U, 4, nppiSet_8u_C4MR>::set},
{::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo},
{NppSetMask<CV_16U, 1, nppiSet_16u_C1MR>::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSetMask<CV_16U, 4, nppiSet_16u_C4MR>::set},
{NppSetMask<CV_16S, 1, nppiSet_16s_C1MR>::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSetMask<CV_16S, 4, nppiSet_16s_C4MR>::set},
{NppSetMask<CV_32S, 1, nppiSet_32s_C1MR>::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSetMask<CV_32S, 4, nppiSet_32s_C4MR>::set},
{NppSetMask<CV_32F, 1, nppiSet_32f_C1MR>::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSetMask<CV_32F, 4, nppiSet_32f_C4MR>::set},
{::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo}
};
callers[m.depth()][m.channels() - 1](m, s, mask);
}
}
void mallocPitch(void** devPtr, size_t* step, size_t width, size_t height) const
{
cudaSafeCall( cudaMallocPitch(devPtr, step, width, height) );
}
void free(void* devPtr) const
{
cudaFree(devPtr);
}
};
const GpuFuncTable* gpuFuncTable()
{
static CudaFuncTable funcTable;
return &funcTable;
}
}
#endif // HAVE_CUDA
void cv::gpu::GpuMat::upload(const Mat& m)
{
CV_DbgAssert(!m.empty());
create(m.size(), m.type());
gpuFuncTable()->copy(m, *this);
}
void cv::gpu::GpuMat::download(Mat& m) const
{
CV_DbgAssert(!empty());
m.create(size(), type());
gpuFuncTable()->copy(*this, m);
}
void cv::gpu::GpuMat::copyTo(GpuMat& m) const
{
CV_DbgAssert(!empty());
m.create(size(), type());
gpuFuncTable()->copy(*this, m);
}
void cv::gpu::GpuMat::copyTo(GpuMat& mat, const GpuMat& mask) const
{
if (mask.empty())
copyTo(mat);
else
{
mat.create(size(), type());
gpuFuncTable()->copyWithMask(*this, mat, mask);
}
}
void cv::gpu::GpuMat::convertTo(GpuMat& dst, int rtype, double alpha, double beta) const
{
bool noScale = fabs(alpha - 1) < numeric_limits<double>::epsilon() && fabs(beta) < numeric_limits<double>::epsilon();
if (rtype < 0)
rtype = type();
else
rtype = CV_MAKETYPE(CV_MAT_DEPTH(rtype), channels());
int sdepth = depth();
int ddepth = CV_MAT_DEPTH(rtype);
if (sdepth == ddepth && noScale)
{
copyTo(dst);
return;
}
GpuMat temp;
const GpuMat* psrc = this;
if (sdepth != ddepth && psrc == &dst)
{
temp = *this;
psrc = &temp;
}
dst.create(size(), rtype);
if (noScale)
gpuFuncTable()->convert(*psrc, dst);
else
gpuFuncTable()->convert(*psrc, dst, alpha, beta);
}
GpuMat& cv::gpu::GpuMat::setTo(Scalar s, const GpuMat& mask)
{
CV_Assert(mask.empty() || mask.type() == CV_8UC1);
CV_DbgAssert(!empty());
gpuFuncTable()->setTo(*this, s, mask);
return *this;
}
void cv::gpu::GpuMat::create(int _rows, int _cols, int _type)
{
_type &= TYPE_MASK;
if (rows == _rows && cols == _cols && type() == _type && data)
return;
if (data)
release();
CV_DbgAssert(_rows >= 0 && _cols >= 0);
if (_rows > 0 && _cols > 0)
{
flags = Mat::MAGIC_VAL + _type;
rows = _rows;
cols = _cols;
size_t esz = elemSize();
void* devPtr;
gpuFuncTable()->mallocPitch(&devPtr, &step, esz * cols, rows);
// Single row must be continuous
if (rows == 1)
step = esz * cols;
if (esz * cols == step)
flags |= Mat::CONTINUOUS_FLAG;
int64 _nettosize = static_cast<int64>(step) * rows;
size_t nettosize = static_cast<size_t>(_nettosize);
datastart = data = static_cast<uchar*>(devPtr);
dataend = data + nettosize;
refcount = static_cast<int*>(fastMalloc(sizeof(*refcount)));
*refcount = 1;
}
}
void cv::gpu::GpuMat::release()
{
if (refcount && CV_XADD(refcount, -1) == 1)
{
fastFree(refcount);
gpuFuncTable()->free(datastart);
}
data = datastart = dataend = 0;
step = rows = cols = 0;
refcount = 0;
}
////////////////////////////////////////////////////////////////////////
// OpenGL
namespace
{
void throw_nogl()
{
#ifndef HAVE_OPENGL
CV_Error(CV_OpenGlNotSupported, "The library is compiled without OpenGL support");
#else
CV_Error(CV_OpenGlNotSupported, "OpenGL context doesn't exist");
#endif
}
class EmptyGlFuncTab : public GlFuncTab
{
public:
void genBuffers(int, unsigned int*) const { throw_nogl(); }
void deleteBuffers(int, const unsigned int*) const { throw_nogl(); }
void bufferData(unsigned int, ptrdiff_t, const void*, unsigned int) const { throw_nogl(); }
void bufferSubData(unsigned int, ptrdiff_t, ptrdiff_t, const void*) const { throw_nogl(); }
void bindBuffer(unsigned int, unsigned int) const { throw_nogl(); }
void* mapBuffer(unsigned int, unsigned int) const { throw_nogl(); return 0; }
void unmapBuffer(unsigned int) const { throw_nogl(); }
bool isGlContextInitialized() const { return false; }
};
const GlFuncTab* g_glFuncTab = 0;
const GlFuncTab* glFuncTab()
{
static EmptyGlFuncTab empty;
return g_glFuncTab ? g_glFuncTab : &empty;
}
}
void cv::gpu::setGlFuncTab(const GlFuncTab* tab)
{
g_glFuncTab = tab;
}
#ifdef HAVE_OPENGL
#ifndef GL_DYNAMIC_DRAW
#define GL_DYNAMIC_DRAW 0x88E8
#endif
#ifndef GL_READ_WRITE
#define GL_READ_WRITE 0x88BA
#endif
#ifndef GL_BGR
#define GL_BGR 0x80E0
#endif
#ifndef GL_BGRA
#define GL_BGRA 0x80E1
#endif
namespace
{
const GLenum gl_types[] = {GL_UNSIGNED_BYTE, GL_BYTE, GL_UNSIGNED_SHORT, GL_SHORT, GL_INT, GL_FLOAT, GL_DOUBLE};
#ifdef HAVE_CUDA
bool g_isCudaGlDeviceInitialized = false;
#endif
}
#endif // HAVE_OPENGL
void cv::gpu::setGlDevice(int device)
{
#ifndef HAVE_CUDA
throw_nogpu();
#else
#ifndef HAVE_OPENGL
throw_nogl();
#else
if (!glFuncTab()->isGlContextInitialized())
throw_nogl();
cudaSafeCall( cudaGLSetGLDevice(device) );
g_isCudaGlDeviceInitialized = true;
#endif
#endif
}
////////////////////////////////////////////////////////////////////////
// CudaGlInterop
#if defined HAVE_CUDA && defined HAVE_OPENGL
namespace
{
class CudaGlInterop
{
public:
CudaGlInterop() : resource_(0)
{
}
~CudaGlInterop()
{
if (resource_)
{
cudaGraphicsUnregisterResource(resource_);
resource_ = 0;
}
}
void registerBuffer(unsigned int buffer)
{
if (!g_isCudaGlDeviceInitialized)
cvError(CV_GpuApiCallError, "registerBuffer", "cuda GL device wasn't initialized, call setGlDevice", __FILE__, __LINE__);
cudaGraphicsResource_t resource;
cudaSafeCall( cudaGraphicsGLRegisterBuffer(&resource, buffer, cudaGraphicsMapFlagsNone) );
resource_ = resource;
}
void copyFrom(const GpuMat& mat, cudaStream_t stream = 0)
{
CV_Assert(resource_ != 0);
cudaSafeCall( cudaGraphicsMapResources(1, &resource_, stream) );
void* dst_ptr;
size_t num_bytes;
cudaSafeCall( cudaGraphicsResourceGetMappedPointer(&dst_ptr, &num_bytes, resource_) );
const void* src_ptr = mat.ptr();
size_t widthBytes = mat.cols * mat.elemSize();
CV_Assert(widthBytes * mat.rows <= num_bytes);
if (stream == 0)
cudaSafeCall( cudaMemcpy2D(dst_ptr, widthBytes, src_ptr, mat.step, widthBytes, mat.rows, cudaMemcpyDeviceToDevice) );
else
cudaSafeCall( cudaMemcpy2DAsync(dst_ptr, widthBytes, src_ptr, mat.step, widthBytes, mat.rows, cudaMemcpyDeviceToDevice, stream) );
cudaGraphicsUnmapResources(1, &resource_, stream);
}
GpuMat map(int rows, int cols, int type, cudaStream_t stream = 0)
{
CV_Assert(resource_ != 0);
cudaSafeCall( cudaGraphicsMapResources(1, &resource_, stream) );
void* ptr;
size_t num_bytes;
cudaSafeCall( cudaGraphicsResourceGetMappedPointer(&ptr, &num_bytes, resource_) );
CV_Assert( static_cast<size_t>(cols) * CV_ELEM_SIZE(type) * rows <= num_bytes );
return GpuMat(rows, cols, type, ptr);
}
void unmap(cudaStream_t stream = 0)
{
cudaGraphicsUnmapResources(1, &resource_, stream);
}
private:
cudaGraphicsResource_t resource_;
};
}
#endif // HAVE_CUDA && HAVE_OPENGL
////////////////////////////////////////////////////////////////////////
// GlBuffer
#ifndef HAVE_OPENGL
class cv::gpu::GlBuffer::Impl
{
};
#else
class cv::gpu::GlBuffer::Impl
{
public:
explicit Impl(unsigned int target) : rows_(0), cols_(0), type_(0), target_(target), buffer_(0)
{
}
Impl(int rows, int cols, int type, unsigned int target);
Impl(const Mat& m, unsigned int target);
~Impl();
void copyFrom(const Mat& m);
#ifdef HAVE_CUDA
void copyFrom(const GpuMat& mat, cudaStream_t stream = 0);
#endif
void bind() const;
void unbind() const;
Mat mapHost();
void unmapHost();
#ifdef HAVE_CUDA
GpuMat mapDevice(cudaStream_t stream = 0);
void unmapDevice(cudaStream_t stream = 0);
#endif
int rows() const { return rows_; }
int cols() const { return cols_; }
int type() const { return type_; }
int target() const { return target_; }
private:
int rows_;
int cols_;
int type_;
unsigned int target_;
unsigned int buffer_;
#ifdef HAVE_CUDA
CudaGlInterop cudaGlInterop_;
#endif
};
cv::gpu::GlBuffer::Impl::Impl(int rows, int cols, int type, unsigned int target) : rows_(0), cols_(0), type_(0), target_(target), buffer_(0)
{
if (!glFuncTab()->isGlContextInitialized())
throw_nogl();
CV_DbgAssert(rows > 0 && cols > 0);
CV_DbgAssert(CV_MAT_DEPTH(type) >= 0 && CV_MAT_DEPTH(type) <= CV_64F);
unsigned int buffer;
glFuncTab()->genBuffers(1, &buffer);
CV_CheckGlError();
size_t size = rows * cols * CV_ELEM_SIZE(type);
glFuncTab()->bindBuffer(target_, buffer);
CV_CheckGlError();
glFuncTab()->bufferData(target_, size, 0, GL_DYNAMIC_DRAW);
CV_CheckGlError();
glFuncTab()->bindBuffer(target_, 0);
#ifdef HAVE_CUDA
if (g_isCudaGlDeviceInitialized)
cudaGlInterop_.registerBuffer(buffer);
#endif
rows_ = rows;
cols_ = cols;
type_ = type;
buffer_ = buffer;
}
cv::gpu::GlBuffer::Impl::Impl(const Mat& m, unsigned int target) : rows_(0), cols_(0), type_(0), target_(target), buffer_(0)
{
if (!glFuncTab()->isGlContextInitialized())
throw_nogl();
CV_DbgAssert(m.rows > 0 && m.cols > 0);
CV_DbgAssert(m.depth() >= 0 && m.depth() <= CV_64F);
CV_Assert(m.isContinuous());
unsigned int buffer;
glFuncTab()->genBuffers(1, &buffer);
CV_CheckGlError();
size_t size = m.rows * m.cols * m.elemSize();
glFuncTab()->bindBuffer(target_, buffer);
CV_CheckGlError();
glFuncTab()->bufferData(target_, size, m.data, GL_DYNAMIC_DRAW);
CV_CheckGlError();
glFuncTab()->bindBuffer(target_, 0);
#ifdef HAVE_CUDA
if (g_isCudaGlDeviceInitialized)
cudaGlInterop_.registerBuffer(buffer);
#endif
rows_ = m.rows;
cols_ = m.cols;
type_ = m.type();
buffer_ = buffer;
}
cv::gpu::GlBuffer::Impl::~Impl()
{
try
{
if (buffer_)
glFuncTab()->deleteBuffers(1, &buffer_);
}
#ifdef _DEBUG
catch(const exception& e)
{
cerr << e.what() << endl;
}
#endif
catch(...)
{
}
}
void cv::gpu::GlBuffer::Impl::copyFrom(const Mat& m)
{
CV_Assert(buffer_ != 0);
CV_DbgAssert(rows_ == m.rows && cols_ == m.cols && type_ == m.type());
CV_Assert(m.isContinuous());
bind();
size_t size = m.rows * m.cols * m.elemSize();
glFuncTab()->bufferSubData(target_, 0, size, m.data);
CV_CheckGlError();
unbind();
}
#ifdef HAVE_CUDA
void cv::gpu::GlBuffer::Impl::copyFrom(const GpuMat& mat, cudaStream_t stream)
{
if (!g_isCudaGlDeviceInitialized)
cvError(CV_GpuApiCallError, "copyFrom", "cuda GL device wasn't initialized, call setGlDevice", __FILE__, __LINE__);
CV_Assert(buffer_ != 0);
CV_DbgAssert(rows_ == mat.rows && cols_ == mat.cols && type_ == mat.type());
cudaGlInterop_.copyFrom(mat, stream);
}
#endif // HAVE_CUDA
void cv::gpu::GlBuffer::Impl::bind() const
{
CV_Assert(buffer_ != 0);
glFuncTab()->bindBuffer(target_, buffer_);
CV_CheckGlError();
}
void cv::gpu::GlBuffer::Impl::unbind() const
{
glFuncTab()->bindBuffer(target_, 0);
}
Mat cv::gpu::GlBuffer::Impl::mapHost()
{
void* ptr = glFuncTab()->mapBuffer(target_, GL_READ_WRITE);
CV_CheckGlError();
return Mat(rows_, cols_, type_, ptr);
}
void cv::gpu::GlBuffer::Impl::unmapHost()
{
glFuncTab()->unmapBuffer(target_);
}
#ifdef HAVE_CUDA
GpuMat cv::gpu::GlBuffer::Impl::mapDevice(cudaStream_t stream)
{
if (!g_isCudaGlDeviceInitialized)
cvError(CV_GpuApiCallError, "copyFrom", "cuda GL device wasn't initialized, call setGlDevice", __FILE__, __LINE__);
CV_Assert(buffer_ != 0);
return cudaGlInterop_.map(rows_, cols_, type_, stream);
}
void cv::gpu::GlBuffer::Impl::unmapDevice(cudaStream_t stream)
{
if (!g_isCudaGlDeviceInitialized)
cvError(CV_GpuApiCallError, "copyFrom", "cuda GL device wasn't initialized, call setGlDevice", __FILE__, __LINE__);
cudaGlInterop_.unmap(stream);
}
#endif // HAVE_CUDA
#endif // HAVE_OPENGL
cv::gpu::GlBuffer::GlBuffer(Usage usage)
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
impl_ = new Impl(usage);
#endif
}
cv::gpu::GlBuffer::GlBuffer(int rows, int cols, int type, Usage usage)
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
impl_ = new Impl(rows, cols, type, usage);
#endif
}
cv::gpu::GlBuffer::GlBuffer(Size size, int type, Usage usage)
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
impl_ = new Impl(size.height, size.width, type, usage);
#endif
}
cv::gpu::GlBuffer::GlBuffer(const Mat& mat, Usage usage)
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
impl_ = new Impl(mat, usage);
#endif
}
cv::gpu::GlBuffer::GlBuffer(const GpuMat& d_mat, Usage usage)
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
#ifndef HAVE_CUDA
throw_nogpu();
#else
impl_ = new Impl(d_mat.rows, d_mat.cols, d_mat.type(), usage);
impl_->copyFrom(d_mat);
#endif
#endif
}
cv::gpu::GlBuffer::~GlBuffer()
{
}
void cv::gpu::GlBuffer::create(int rows_, int cols_, int type_, Usage usage_)
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
if (rows_ != rows() || cols_ != cols() || type_ != type() || usage_ != usage())
impl_ = new Impl(rows_, cols_, type_, usage_);
#endif
}
void cv::gpu::GlBuffer::release()
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
impl_ = new Impl(usage());
#endif
}
void cv::gpu::GlBuffer::copyFrom(const Mat& mat)
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
create(mat.rows, mat.cols, mat.type());
impl_->copyFrom(mat);
#endif
}
void cv::gpu::GlBuffer::copyFrom(const GpuMat& d_mat)
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
#ifndef HAVE_CUDA
throw_nogpu();
#else
create(d_mat.rows, d_mat.cols, d_mat.type());
impl_->copyFrom(d_mat);
#endif
#endif
}
void cv::gpu::GlBuffer::bind() const
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
impl_->bind();
#endif
}
void cv::gpu::GlBuffer::unbind() const
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
impl_->unbind();
#endif
}
Mat cv::gpu::GlBuffer::mapHost()
{
#ifndef HAVE_OPENGL
throw_nogl();
return Mat();
#else
return impl_->mapHost();
#endif
}
void cv::gpu::GlBuffer::unmapHost()
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
impl_->unmapHost();
#endif
}
GpuMat cv::gpu::GlBuffer::mapDevice()
{
#ifndef HAVE_OPENGL
throw_nogl();
return GpuMat();
#else
#ifndef HAVE_CUDA
throw_nogpu();
return GpuMat();
#else
return impl_->mapDevice();
#endif
#endif
}
void cv::gpu::GlBuffer::unmapDevice()
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
#ifndef HAVE_CUDA
throw_nogpu();
#else
impl_->unmapDevice();
#endif
#endif
}
int cv::gpu::GlBuffer::rows() const
{
#ifndef HAVE_OPENGL
return 0;
#else
return impl_->rows();
#endif
}
int cv::gpu::GlBuffer::cols() const
{
#ifndef HAVE_OPENGL
return 0;
#else
return impl_->cols();
#endif
}
Size cv::gpu::GlBuffer::size() const
{
return Size(cols(), rows());
}
bool cv::gpu::GlBuffer::empty() const
{
return rows() == 0 || cols() == 0;
}
int cv::gpu::GlBuffer::type() const
{
#ifndef HAVE_OPENGL
return 0;
#else
return impl_->type();
#endif
}
int cv::gpu::GlBuffer::depth() const
{
return CV_MAT_DEPTH(type());
}
int cv::gpu::GlBuffer::channels() const
{
return CV_MAT_CN(type());
}
int cv::gpu::GlBuffer::elemSize() const
{
return CV_ELEM_SIZE(type());
}
int cv::gpu::GlBuffer::elemSize1() const
{
return CV_ELEM_SIZE1(type());
}
GlBuffer::Usage cv::gpu::GlBuffer::usage() const
{
#ifndef HAVE_OPENGL
return ARRAY_BUFFER;
#else
return static_cast<Usage>(impl_->target());
#endif
}
//////////////////////////////////////////////////////////////////////////////////////////
// GlTexture
#ifndef HAVE_OPENGL
class cv::gpu::GlTexture::Impl
{
};
#else
class cv::gpu::GlTexture::Impl
{
public:
Impl();
Impl(int rows, int cols, int type);
Impl(const Mat& mat, bool bgra);
Impl(const GlBuffer& buf, bool bgra);
~Impl();
void copyFrom(const Mat& mat, bool bgra);
void copyFrom(const GlBuffer& buf, bool bgra);
void bind() const;
void unbind() const;
int rows() const { return rows_; }
int cols() const { return cols_; }
int type() const { return type_; }
private:
int rows_;
int cols_;
int type_;
unsigned int tex_;
};
cv::gpu::GlTexture::Impl::Impl() : rows_(0), cols_(0), type_(0), tex_(0)
{
}
cv::gpu::GlTexture::Impl::Impl(int rows, int cols, int type) : rows_(0), cols_(0), type_(0), tex_(0)
{
if (!glFuncTab()->isGlContextInitialized())
throw_nogl();
int depth = CV_MAT_DEPTH(type);
int cn = CV_MAT_CN(type);
CV_DbgAssert(rows > 0 && cols > 0);
CV_Assert(cn == 1 || cn == 3 || cn == 4);
CV_Assert(depth >= 0 && depth <= CV_32F);
GLuint tex;
glGenTextures(1, &tex);
CV_CheckGlError();
glBindTexture(GL_TEXTURE_2D, tex);
CV_CheckGlError();
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_S, GL_REPEAT);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_T, GL_REPEAT);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_LINEAR);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_LINEAR);
CV_CheckGlError();
GLenum format = cn == 1 ? GL_LUMINANCE : cn == 3 ? GL_BGR : GL_BGRA;
glPixelStorei(GL_UNPACK_ALIGNMENT, 1);
CV_CheckGlError();
glTexImage2D(GL_TEXTURE_2D, 0, cn, cols, rows, 0, format, gl_types[depth], 0);
CV_CheckGlError();
rows_ = rows;
cols_ = cols;
type_ = type;
tex_ = tex;
}
cv::gpu::GlTexture::Impl::Impl(const Mat& mat, bool bgra) : rows_(0), cols_(0), type_(0), tex_(0)
{
if (!glFuncTab()->isGlContextInitialized())
throw_nogl();
int depth = mat.depth();
int cn = mat.channels();
CV_DbgAssert(mat.rows > 0 && mat.cols > 0);
CV_Assert(cn == 1 || cn == 3 || cn == 4);
CV_Assert(depth >= 0 && depth <= CV_32F);
CV_Assert(mat.isContinuous());
GLuint tex;
glGenTextures(1, &tex);
CV_CheckGlError();
glBindTexture(GL_TEXTURE_2D, tex);
CV_CheckGlError();
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_S, GL_REPEAT);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_T, GL_REPEAT);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_LINEAR);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_LINEAR);
CV_CheckGlError();
GLenum format = cn == 1 ? GL_LUMINANCE : (cn == 3 ? (bgra ? GL_BGR : GL_RGB) : (bgra ? GL_BGRA : GL_RGBA));
glPixelStorei(GL_UNPACK_ALIGNMENT, 1);
CV_CheckGlError();
glTexImage2D(GL_TEXTURE_2D, 0, cn, mat.cols, mat.rows, 0, format, gl_types[depth], mat.data);
CV_CheckGlError();
rows_ = mat.rows;
cols_ = mat.cols;
type_ = mat.type();
tex_ = tex;
}
cv::gpu::GlTexture::Impl::Impl(const GlBuffer& buf, bool bgra) : rows_(0), cols_(0), type_(0), tex_(0)
{
if (!glFuncTab()->isGlContextInitialized())
throw_nogl();
int depth = buf.depth();
int cn = buf.channels();
CV_DbgAssert(buf.rows() > 0 && buf.cols() > 0);
CV_Assert(cn == 1 || cn == 3 || cn == 4);
CV_Assert(depth >= 0 && depth <= CV_32F);
CV_Assert(buf.usage() == GlBuffer::TEXTURE_BUFFER);
GLuint tex;
glGenTextures(1, &tex);
CV_CheckGlError();
glBindTexture(GL_TEXTURE_2D, tex);
CV_CheckGlError();
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_S, GL_REPEAT);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_T, GL_REPEAT);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_LINEAR);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_LINEAR);
CV_CheckGlError();
GLenum format = cn == 1 ? GL_LUMINANCE : (cn == 3 ? (bgra ? GL_BGR : GL_RGB) : (bgra ? GL_BGRA : GL_RGBA));
buf.bind();
glPixelStorei(GL_UNPACK_ALIGNMENT, 1);
CV_CheckGlError();
glTexImage2D(GL_TEXTURE_2D, 0, cn, buf.cols(), buf.rows(), 0, format, gl_types[depth], 0);
CV_CheckGlError();
buf.unbind();
rows_ = buf.rows();
cols_ = buf.cols();
type_ = buf.type();
tex_ = tex;
}
cv::gpu::GlTexture::Impl::~Impl()
{
if (tex_)
glDeleteTextures(1, &tex_);
}
void cv::gpu::GlTexture::Impl::copyFrom(const Mat& mat, bool bgra)
{
CV_Assert(tex_ != 0);
CV_DbgAssert(mat.cols == cols_ && mat.rows == rows_ && mat.type() == type_);
glPixelStorei(GL_UNPACK_ALIGNMENT, 1);
CV_CheckGlError();
int cn = mat.channels();
GLenum format = cn == 1 ? GL_LUMINANCE : (cn == 3 ? (bgra ? GL_BGR : GL_RGB) : (bgra ? GL_BGRA : GL_RGBA));
glTexSubImage2D(GL_TEXTURE_2D, 0, 0, 0, cols_, rows_, format, gl_types[mat.depth()], mat.data);
CV_CheckGlError();
}
void cv::gpu::GlTexture::Impl::copyFrom(const GlBuffer& buf, bool bgra)
{
CV_Assert(tex_ != 0);
CV_DbgAssert(buf.cols() == cols_ && buf.rows() == rows_ && buf.type() == type_);
CV_Assert(buf.usage() == GlBuffer::TEXTURE_BUFFER);
buf.bind();
glPixelStorei(GL_UNPACK_ALIGNMENT, 1);
CV_CheckGlError();
int cn = buf.channels();
GLenum format = cn == 1 ? GL_LUMINANCE : (cn == 3 ? (bgra ? GL_BGR : GL_RGB) : (bgra ? GL_BGRA : GL_RGBA));
glTexSubImage2D(GL_TEXTURE_2D, 0, 0, 0, cols_, rows_, format, gl_types[buf.depth()], 0);
CV_CheckGlError();
buf.unbind();
}
void cv::gpu::GlTexture::Impl::bind() const
{
CV_Assert(tex_ != 0);
glEnable(GL_TEXTURE_2D);
CV_CheckGlError();
glBindTexture(GL_TEXTURE_2D, tex_);
CV_CheckGlError();
}
void cv::gpu::GlTexture::Impl::unbind() const
{
glBindTexture(GL_TEXTURE_2D, 0);
glDisable(GL_TEXTURE_2D);
}
#endif // HAVE_OPENGL
cv::gpu::GlTexture::GlTexture()
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
impl_ = new Impl;
#endif
}
cv::gpu::GlTexture::GlTexture(int rows, int cols, int type)
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
impl_ = new Impl(rows, cols, type);
#endif
}
cv::gpu::GlTexture::GlTexture(Size size, int type)
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
impl_ = new Impl(size.height, size.width, type);
#endif
}
cv::gpu::GlTexture::GlTexture(const Mat& mat, bool bgra)
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
impl_ = new Impl(mat, bgra);
#endif
}
cv::gpu::GlTexture::GlTexture(const GlBuffer& buf, bool bgra)
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
impl_ = new Impl(buf, bgra);
#endif
}
cv::gpu::GlTexture::~GlTexture()
{
}
void cv::gpu::GlTexture::create(int rows_, int cols_, int type_)
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
if (rows_ != rows() || cols_ != cols() || type_ != type())
impl_ = new Impl(rows_, cols_, type_);
#endif
}
void cv::gpu::GlTexture::release()
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
impl_ = new Impl;
#endif
}
void cv::gpu::GlTexture::copyFrom(const Mat& mat, bool bgra)
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
create(mat.rows, mat.cols, mat.type());
impl_->copyFrom(mat, bgra);
#endif
}
void cv::gpu::GlTexture::copyFrom(const GlBuffer& buf, bool bgra)
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
create(buf.rows(), buf.cols(), buf.type());
impl_->copyFrom(buf, bgra);
#endif
}
void cv::gpu::GlTexture::bind() const
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
impl_->bind();
#endif
}
void cv::gpu::GlTexture::unbind() const
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
impl_->unbind();
#endif
}
int cv::gpu::GlTexture::rows() const
{
#ifndef HAVE_OPENGL
return 0;
#else
return impl_->rows();
#endif
}
int cv::gpu::GlTexture::cols() const
{
#ifndef HAVE_OPENGL
return 0;
#else
return impl_->cols();
#endif
}
Size cv::gpu::GlTexture::size() const
{
return Size(cols(), rows());
}
bool cv::gpu::GlTexture::empty() const
{
return rows() == 0 || cols() == 0;
}
int cv::gpu::GlTexture::type() const
{
#ifndef HAVE_OPENGL
return 0;
#else
return impl_->type();
#endif
}
int cv::gpu::GlTexture::depth() const
{
return CV_MAT_DEPTH(type());
}
int cv::gpu::GlTexture::channels() const
{
return CV_MAT_CN(type());
}
int cv::gpu::GlTexture::elemSize() const
{
return CV_ELEM_SIZE(type());
}
int cv::gpu::GlTexture::elemSize1() const
{
return CV_ELEM_SIZE1(type());
}
////////////////////////////////////////////////////////////////////////
// Rendering
void cv::gpu::render(const GlTexture& tex)
{
#ifndef HAVE_OPENGL
throw_nogl();
#else
if (!tex.empty())
{
tex.bind();
glDisable(GL_DEPTH_TEST);
glMatrixMode(GL_PROJECTION);
glLoadIdentity();
glOrtho(0, 1, 1, 0, -1, 1);
glMatrixMode(GL_MODELVIEW);
glLoadIdentity();
glTexEnvi(GL_TEXTURE_ENV, GL_TEXTURE_ENV_MODE, GL_REPLACE);
glBegin(GL_QUADS);
glVertex2d(0.0, 0.0);
glTexCoord2d(1.0, 0.0);
glVertex2d(1.0, 0.0);
glTexCoord2d(1.0, 1.0);
glVertex2d(1.0, 1.0);
glTexCoord2d(0.0, 1.0);
glVertex2d(0.0, 1.0);
glTexCoord2d(0.0, 0.0);
glEnd();
CV_CheckGlError();
tex.unbind();
}
#endif
}
////////////////////////////////////////////////////////////////////////
// Error handling
void cv::gpu::error(const char *error_string, const char *file, const int line, const char *func)
{
int code = CV_GpuApiCallError;
if (uncaught_exception())
{
const char* errorStr = cvErrorStr(code);
const char* function = func ? func : "unknown function";
cerr << "OpenCV Error: " << errorStr << "(" << error_string << ") in " << function << ", file " << file << ", line " << line;
cerr.flush();
}
else
cv::error( cv::Exception(code, error_string, func, file, line) );
}
bool cv::gpu::checkGlError(const char* file, const int line, const char* func)
{
#ifndef HAVE_OPENGL
return true;
#else
GLenum err = glGetError();
if (err != GL_NO_ERROR)
{
const char* msg;
switch (err)
{
case GL_INVALID_ENUM:
msg = "An unacceptable value is specified for an enumerated argument";
break;
case GL_INVALID_VALUE:
msg = "A numeric argument is out of range";
break;
case GL_INVALID_OPERATION:
msg = "The specified operation is not allowed in the current state";
break;
case GL_STACK_OVERFLOW:
msg = "This command would cause a stack overflow";
break;
case GL_STACK_UNDERFLOW:
msg = "This command would cause a stack underflow";
break;
case GL_OUT_OF_MEMORY:
msg = "There is not enough memory left to execute the command";
break;
default:
msg = "Unknown error";
};
cvError(CV_OpenGlApiCallError, func, msg, file, line);
return false;
}
return true;
#endif
}