opencv/modules/gpu/src/gpumat.cpp

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/*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.
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// 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.
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// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
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// (including, but not limited to, procurement of substitute goods or services;
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//M*/
#include "precomp.hpp"
using namespace cv;
using namespace cv::gpu;
//////////////////////////////// GpuMat ////////////////////////////////
void GpuMat::upload(const Mat& m)
{
CV_DbgAssert(!m.empty());
create(m.size(), m.type());
cudaSafeCall( cudaMemcpy2D(data, step, m.data, m.step, cols * elemSize(), rows, cudaMemcpyHostToDevice) );
}
void GpuMat::download(cv::Mat& m) const
{
CV_DbgAssert(!this->empty());
m.create(size(), type());
cudaSafeCall( cudaMemcpy2D(m.data, m.step, data, step, cols * elemSize(), rows, cudaMemcpyDeviceToHost) );
}
void GpuMat::copyTo( GpuMat& m ) const
{
CV_DbgAssert(!this->empty());
m.create(size(), type());
cudaSafeCall( cudaMemcpy2D(m.data, m.step, data, step, cols * elemSize(), rows, cudaMemcpyDeviceToDevice) );
cudaSafeCall( cudaThreadSynchronize() );
}
void GpuMat::copyTo( GpuMat& /*m*/, const GpuMat&/* mask */) const
{
CV_Assert(!"Not implemented");
}
void GpuMat::convertTo( GpuMat& /*m*/, int /*rtype*/, double /*alpha*/, double /*beta*/ ) const
{
CV_Assert(!"Not implemented");
}
GpuMat& GpuMat::operator = (const Scalar& s)
{
cv::gpu::impl::set_to_without_mask(*this, s.val, this->depth(), this->channels());
return *this;
}
GpuMat& GpuMat::setTo(const Scalar& s, const GpuMat& mask)
{
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CV_Assert(mask.type() == CV_32F);
CV_DbgAssert(!this->empty());
this->channels();
this->depth();
if (mask.empty())
{
cv::gpu::impl::set_to_without_mask(*this, s.val, this->depth(), this->channels());
}
else
{
cv::gpu::impl::set_to_with_mask(*this, s.val, mask, this->depth(), this->channels());
}
return *this;
}
GpuMat 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;
}
void 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 *dev_ptr;
cudaSafeCall( cudaMallocPitch(&dev_ptr, &step, esz * cols, rows) );
if (esz * cols == step)
flags |= Mat::CONTINUOUS_FLAG;
int64 _nettosize = (int64)step*rows;
size_t nettosize = (size_t)_nettosize;
datastart = data = (uchar*)dev_ptr;
dataend = data + nettosize;
refcount = (int*)fastMalloc(sizeof(*refcount));
*refcount = 1;
}
}
void GpuMat::release()
{
if( refcount && CV_XADD(refcount, -1) == 1 )
{
fastFree(refcount);
cudaSafeCall( cudaFree(datastart) );
}
data = datastart = dataend = 0;
step = rows = cols = 0;
refcount = 0;
}