opencv/modules/gpu/src/matrix_operations.cpp

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#include "precomp.hpp"

using namespace cv;
using namespace cv::gpu;

cv::gpu::CudaMem::CudaMem()
    : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(0)
{
}

cv::gpu::CudaMem::CudaMem(int _rows, int _cols, int _type, int _alloc_type)
    : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(0)
{
    if( _rows > 0 && _cols > 0 )
        create( _rows, _cols, _type, _alloc_type);
}

cv::gpu::CudaMem::CudaMem(Size _size, int _type, int _alloc_type)
    : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(0)
{
    if( _size.height > 0 && _size.width > 0 )
        create( _size.height, _size.width, _type, _alloc_type);
}

cv::gpu::CudaMem::CudaMem(const CudaMem& 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), alloc_type(m.alloc_type)
{
    if( refcount )
        CV_XADD(refcount, 1);
}

cv::gpu::CudaMem::CudaMem(const Mat& m, int _alloc_type)
    : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(0)
{
    if( m.rows > 0 && m.cols > 0 )
        create( m.size(), m.type(), _alloc_type);

    Mat tmp = createMatHeader();
    m.copyTo(tmp);
}

cv::gpu::CudaMem::~CudaMem()
{
    release();
}

CudaMem& cv::gpu::CudaMem::operator = (const CudaMem& 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;
        alloc_type = m.alloc_type;
    }
    return *this;
}

CudaMem cv::gpu::CudaMem::clone() const
{
    CudaMem m(size(), type(), alloc_type);
    Mat to = m;
    Mat from = *this;
    from.copyTo(to);
    return m;
}

void cv::gpu::CudaMem::create(Size _size, int _type, int _alloc_type)
{
    create(_size.height, _size.width, _type, _alloc_type);
}

Mat cv::gpu::CudaMem::createMatHeader() const
{
    return Mat(size(), type(), data, step);
}

cv::gpu::CudaMem::operator Mat() const
{
    return createMatHeader();
}

cv::gpu::CudaMem::operator GpuMat() const
{
    return createGpuMatHeader();
}

bool cv::gpu::CudaMem::isContinuous() const
{
    return (flags & Mat::CONTINUOUS_FLAG) != 0;
}

size_t cv::gpu::CudaMem::elemSize() const
{
    return CV_ELEM_SIZE(flags);
}

size_t cv::gpu::CudaMem::elemSize1() const
{
    return CV_ELEM_SIZE1(flags);
}

int cv::gpu::CudaMem::type() const
{
    return CV_MAT_TYPE(flags);
}

int cv::gpu::CudaMem::depth() const
{
    return CV_MAT_DEPTH(flags);
}

int cv::gpu::CudaMem::channels() const
{
    return CV_MAT_CN(flags);
}

size_t cv::gpu::CudaMem::step1() const
{
    return step/elemSize1();
}

Size cv::gpu::CudaMem::size() const
{
    return Size(cols, rows);
}

bool cv::gpu::CudaMem::empty() const
{
    return data == 0;
}

#if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)

void cv::gpu::registerPageLocked(Mat&) { throw_nogpu(); }
void cv::gpu::unregisterPageLocked(Mat&) { throw_nogpu(); }
void cv::gpu::CudaMem::create(int /*_rows*/, int /*_cols*/, int /*_type*/, int /*type_alloc*/) { throw_nogpu(); }
bool cv::gpu::CudaMem::canMapHostMemory() { throw_nogpu(); return false; }
void cv::gpu::CudaMem::release() { throw_nogpu(); }
GpuMat cv::gpu::CudaMem::createGpuMatHeader () const { throw_nogpu(); return GpuMat(); }

#else /* !defined (HAVE_CUDA) */

void cv::gpu::registerPageLocked(Mat& m)
{
    cudaSafeCall( cudaHostRegister(m.ptr(), m.step * m.rows, cudaHostRegisterPortable) );
}

void cv::gpu::unregisterPageLocked(Mat& m)
{
    cudaSafeCall( cudaHostUnregister(m.ptr()) );
}

bool cv::gpu::CudaMem::canMapHostMemory()
{
    cudaDeviceProp prop;
    cudaSafeCall( cudaGetDeviceProperties(&prop, getDevice()) );
    return (prop.canMapHostMemory != 0) ? true : false;
}

namespace
{
    size_t alignUpStep(size_t what, size_t alignment)
    {
        size_t alignMask = alignment-1;
        size_t inverseAlignMask = ~alignMask;
        size_t res = (what + alignMask) & inverseAlignMask;
        return res;
    }
}

void cv::gpu::CudaMem::create(int _rows, int _cols, int _type, int _alloc_type)
{
    if (_alloc_type == ALLOC_ZEROCOPY && !canMapHostMemory())
            cv::gpu::error("ZeroCopy is not supported by current device", __FILE__, __LINE__);

    _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 + Mat::CONTINUOUS_FLAG + _type;
        rows = _rows;
        cols = _cols;
        step = elemSize()*cols;
        if (_alloc_type == ALLOC_ZEROCOPY)
        {
            cudaDeviceProp prop;
            cudaSafeCall( cudaGetDeviceProperties(&prop, getDevice()) );
            step = alignUpStep(step, prop.textureAlignment);
        }
        int64 _nettosize = (int64)step*rows;
        size_t nettosize = (size_t)_nettosize;
        if( _nettosize != (int64)nettosize )
            CV_Error(CV_StsNoMem, "Too big buffer is allocated");
        size_t datasize = alignSize(nettosize, (int)sizeof(*refcount));

        //datastart = data = (uchar*)fastMalloc(datasize + sizeof(*refcount));
        alloc_type = _alloc_type;
        void *ptr;

        switch (alloc_type)
        {
            case ALLOC_PAGE_LOCKED:    cudaSafeCall( cudaHostAlloc( &ptr, datasize, cudaHostAllocDefault) ); break;
            case ALLOC_ZEROCOPY:       cudaSafeCall( cudaHostAlloc( &ptr, datasize, cudaHostAllocMapped) );  break;
            case ALLOC_WRITE_COMBINED: cudaSafeCall( cudaHostAlloc( &ptr, datasize, cudaHostAllocWriteCombined) ); break;
            default: cv::gpu::error("Invalid alloc type", __FILE__, __LINE__);
        }

        datastart = data =  (uchar*)ptr;
        dataend = data + nettosize;

        refcount = (int*)cv::fastMalloc(sizeof(*refcount));
        *refcount = 1;
    }
}

GpuMat cv::gpu::CudaMem::createGpuMatHeader () const
{
    GpuMat res;
    if (alloc_type == ALLOC_ZEROCOPY)
    {
        void *pdev;
        cudaSafeCall( cudaHostGetDevicePointer( &pdev, data, 0 ) );
        res = GpuMat(rows, cols, type(), pdev, step);
    }
    else
        cv::gpu::error("Zero-copy is not supported or memory was allocated without zero-copy flag", __FILE__, __LINE__);

    return res;
}

void cv::gpu::CudaMem::release()
{
    if( refcount && CV_XADD(refcount, -1) == 1 )
    {
        cudaSafeCall( cudaFreeHost(datastart ) );
        fastFree(refcount);
    }
    data = datastart = dataend = 0;
    step = rows = cols = 0;
    refcount = 0;
}

#endif /* !defined (HAVE_CUDA) */