opencv/modules/gpu/test/nvidia/TestTranspose.cpp
2013-03-22 14:03:15 +04:00

184 lines
6.1 KiB
C++

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#if !defined CUDA_DISABLER
#include <math.h>
#include "TestTranspose.h"
template <class T>
TestTranspose<T>::TestTranspose(std::string testName_, NCVTestSourceProvider<T> &src_,
Ncv32u width_, Ncv32u height_)
:
NCVTestProvider(testName_),
src(src_),
width(width_),
height(height_)
{
}
template <class T>
bool TestTranspose<T>::toString(std::ofstream &strOut)
{
strOut << "sizeof(T)=" << sizeof(T) << std::endl;
strOut << "width=" << width << std::endl;
return true;
}
template <class T>
bool TestTranspose<T>::init()
{
return true;
}
template <class T>
bool TestTranspose<T>::process()
{
NCVStatus ncvStat;
bool rcode = false;
NcvSize32u srcSize(this->width, this->height);
NCVMatrixAlloc<T> d_img(*this->allocatorGPU.get(), this->width, this->height);
ncvAssertReturn(d_img.isMemAllocated(), false);
NCVMatrixAlloc<T> h_img(*this->allocatorCPU.get(), this->width, this->height);
ncvAssertReturn(h_img.isMemAllocated(), false);
NCVMatrixAlloc<T> d_dst(*this->allocatorGPU.get(), this->height, this->width);
ncvAssertReturn(d_dst.isMemAllocated(), false);
NCVMatrixAlloc<T> h_dst(*this->allocatorCPU.get(), this->height, this->width);
ncvAssertReturn(h_dst.isMemAllocated(), false);
NCVMatrixAlloc<T> h_dst_d(*this->allocatorCPU.get(), this->height, this->width);
ncvAssertReturn(h_dst_d.isMemAllocated(), false);
NCV_SET_SKIP_COND(this->allocatorGPU.get()->isCounting());
NCV_SKIP_COND_BEGIN
ncvAssertReturn(this->src.fill(h_img), false);
NCV_SKIP_COND_END
ncvStat = h_img.copySolid(d_img, 0);
ncvAssertReturn(ncvStat == NPPST_SUCCESS, false);
NCV_SKIP_COND_BEGIN
if (sizeof(T) == sizeof(Ncv32u))
{
ncvStat = nppiStTranspose_32u_C1R((Ncv32u *)d_img.ptr(), d_img.pitch(),
(Ncv32u *)d_dst.ptr(), d_dst.pitch(),
NcvSize32u(this->width, this->height));
}
else if (sizeof(T) == sizeof(Ncv64u))
{
ncvStat = nppiStTranspose_64u_C1R((Ncv64u *)d_img.ptr(), d_img.pitch(),
(Ncv64u *)d_dst.ptr(), d_dst.pitch(),
NcvSize32u(this->width, this->height));
}
else
{
ncvAssertPrintReturn(false, "Incorrect transpose test instance", false);
}
ncvAssertReturn(ncvStat == NPPST_SUCCESS, false);
NCV_SKIP_COND_END
ncvStat = d_dst.copySolid(h_dst_d, 0);
ncvAssertReturn(ncvStat == NPPST_SUCCESS, false);
NCV_SKIP_COND_BEGIN
if (sizeof(T) == sizeof(Ncv32u))
{
ncvStat = nppiStTranspose_32u_C1R_host((Ncv32u *)h_img.ptr(), h_img.pitch(),
(Ncv32u *)h_dst.ptr(), h_dst.pitch(),
NcvSize32u(this->width, this->height));
}
else if (sizeof(T) == sizeof(Ncv64u))
{
ncvStat = nppiStTranspose_64u_C1R_host((Ncv64u *)h_img.ptr(), h_img.pitch(),
(Ncv64u *)h_dst.ptr(), h_dst.pitch(),
NcvSize32u(this->width, this->height));
}
else
{
ncvAssertPrintReturn(false, "Incorrect downsample test instance", false);
}
ncvAssertReturn(ncvStat == NPPST_SUCCESS, false);
NCV_SKIP_COND_END
//bit-to-bit check
bool bLoopVirgin = true;
NCV_SKIP_COND_BEGIN
//const Ncv64f relEPS = 0.005;
for (Ncv32u i=0; bLoopVirgin && i < this->width; i++)
{
for (Ncv32u j=0; bLoopVirgin && j < this->height; j++)
{
if (h_dst.ptr()[h_dst.stride()*i+j] != h_dst_d.ptr()[h_dst_d.stride()*i+j])
{
bLoopVirgin = false;
}
}
}
NCV_SKIP_COND_END
if (bLoopVirgin)
{
rcode = true;
}
return rcode;
}
template <class T>
bool TestTranspose<T>::deinit()
{
return true;
}
template class TestTranspose<Ncv32u>;
template class TestTranspose<Ncv64u>;
#endif /* CUDA_DISABLER */