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Commit 5522f43b authored by Vladislav Vinogradov's avatar Vladislav Vinogradov
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used new device layer for cv::gpu::threshold

parent e83be009
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Showing with 79 additions and 114 deletions
modules/cudaarithm/src/cuda/threshold.cu
View file @ 5522f43b
......@@ -40,75 +40,109 @@
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/opencv_modules.hpp"
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#ifndef HAVE_OPENCV_CUDEV
#include "arithm_func_traits.hpp"
#error "opencv_cudev is required"
using namespace cv::cuda;
using namespace cv::cuda::device;
#else
namespace cv { namespace cuda { namespace device
#include "opencv2/cudaarithm.hpp"
#include "opencv2/cudev.hpp"
#include "opencv2/core/private.cuda.hpp"
using namespace cv::cudev;
namespace
{
template <typename T> struct TransformFunctorTraits< thresh_binary_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
template <typename ScalarDepth> struct TransformPolicy : DefaultTransformPolicy
{
};
template <typename T> struct TransformFunctorTraits< thresh_binary_inv_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
template <> struct TransformPolicy<double> : DefaultTransformPolicy
{
enum {
shift = 1
};
template <typename T> struct TransformFunctorTraits< thresh_trunc_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
template <typename T> struct TransformFunctorTraits< thresh_to_zero_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
template <typename T>
void thresholdImpl(const GpuMat& src, GpuMat& dst, double thresh, double maxVal, int type, Stream& stream)
{
};
const T thresh_ = static_cast<T>(thresh);
const T maxVal_ = static_cast<T>(maxVal);
template <typename T> struct TransformFunctorTraits< thresh_to_zero_inv_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
switch (type)
{
case 0:
gridTransformUnary_< TransformPolicy<T> >(globPtr<T>(src), globPtr<T>(dst), thresh_binary_func(thresh_, maxVal_), stream);
break;
case 1:
gridTransformUnary_< TransformPolicy<T> >(globPtr<T>(src), globPtr<T>(dst), thresh_binary_inv_func(thresh_, maxVal_), stream);
break;
case 2:
gridTransformUnary_< TransformPolicy<T> >(globPtr<T>(src), globPtr<T>(dst), thresh_trunc_func(thresh_), stream);
break;
case 3:
gridTransformUnary_< TransformPolicy<T> >(globPtr<T>(src), globPtr<T>(dst), thresh_to_zero_func(thresh_), stream);
break;
case 4:
gridTransformUnary_< TransformPolicy<T> >(globPtr<T>(src), globPtr<T>(dst), thresh_to_zero_inv_func(thresh_), stream);
break;
};
}}}
}
}
namespace arithm
double cv::cuda::threshold(InputArray _src, OutputArray _dst, double thresh, double maxVal, int type, Stream& stream)
{
template <template <typename> class Op, typename T>
void threshold_caller(PtrStepSz<T> src, PtrStepSz<T> dst, T thresh, T maxVal, cudaStream_t stream)
{
Op<T> op(thresh, maxVal);
device::transform(src, dst, op, WithOutMask(), stream);
}
GpuMat src = _src.getGpuMat();
template <typename T>
void threshold(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream)
const int depth = src.depth();
CV_DbgAssert( src.channels() == 1 && depth <= CV_64F );
CV_DbgAssert( type <= 4 /*THRESH_TOZERO_INV*/ );
_dst.create(src.size(), src.type());
GpuMat dst = _dst.getGpuMat();
if (depth == CV_32F && type == 2 /*THRESH_TRUNC*/)
{
typedef void (*caller_t)(PtrStepSz<T> src, PtrStepSz<T> dst, T thresh, T maxVal, cudaStream_t stream);
NppStreamHandler h(StreamAccessor::getStream(stream));
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
nppSafeCall( nppiThreshold_32f_C1R(src.ptr<Npp32f>(), static_cast<int>(src.step),
dst.ptr<Npp32f>(), static_cast<int>(dst.step), sz, static_cast<Npp32f>(thresh), NPP_CMP_GREATER) );
static const caller_t callers[] =
if (!stream)
CV_CUDEV_SAFE_CALL( cudaDeviceSynchronize() );
}
else
{
typedef void (*func_t)(const GpuMat& src, GpuMat& dst, double thresh, double maxVal, int type, Stream& stream);
static const func_t funcs[] =
{
threshold_caller<thresh_binary_func, T>,
threshold_caller<thresh_binary_inv_func, T>,
threshold_caller<thresh_trunc_func, T>,
threshold_caller<thresh_to_zero_func, T>,
threshold_caller<thresh_to_zero_inv_func, T>
thresholdImpl<uchar>,
thresholdImpl<schar>,
thresholdImpl<ushort>,
thresholdImpl<short>,
thresholdImpl<int>,
thresholdImpl<float>,
thresholdImpl<double>
};
callers[type]((PtrStepSz<T>) src, (PtrStepSz<T>) dst, static_cast<T>(thresh), static_cast<T>(maxVal), stream);
if (depth != CV_32F && depth != CV_64F)
{
thresh = cvFloor(thresh);
maxVal = cvRound(maxVal);
}
funcs[depth](src, dst, thresh, maxVal, type, stream);
}
template void threshold<uchar>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
template void threshold<schar>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
template void threshold<ushort>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
template void threshold<short>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
template void threshold<int>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
template void threshold<float>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
template void threshold<double>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
return thresh;
}
#endif // CUDA_DISABLER
#endif
modules/cudaarithm/src/element_operations.cpp
View file @ 5522f43b
......@@ -449,75 +449,6 @@ void cv::cuda::max(InputArray src1, InputArray src2, OutputArray dst, Stream& st
arithm_op(src1, src2, dst, noArray(), 1.0, -1, stream, minMaxMat, minMaxScalar, MAX_OP);
}
////////////////////////////////////////////////////////////////////////
// threshold
namespace arithm
{
template <typename T>
void threshold(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
}
double cv::cuda::threshold(InputArray _src, OutputArray _dst, double thresh, double maxVal, int type, Stream& _stream)
{
GpuMat src = _src.getGpuMat();
const int depth = src.depth();
CV_Assert( src.channels() == 1 && depth <= CV_64F );
CV_Assert( type <= 4/*THRESH_TOZERO_INV*/ );
if (depth == CV_64F)
{
if (!deviceSupports(NATIVE_DOUBLE))
CV_Error(cv::Error::StsUnsupportedFormat, "The device doesn't support double");
}
_dst.create(src.size(), src.type());
GpuMat dst = _dst.getGpuMat();
cudaStream_t stream = StreamAccessor::getStream(_stream);
if (src.type() == CV_32FC1 && type == 2/*THRESH_TRUNC*/)
{
NppStreamHandler h(stream);
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
nppSafeCall( nppiThreshold_32f_C1R(src.ptr<Npp32f>(), static_cast<int>(src.step),
dst.ptr<Npp32f>(), static_cast<int>(dst.step), sz, static_cast<Npp32f>(thresh), NPP_CMP_GREATER) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
else
{
typedef void (*func_t)(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
static const func_t funcs[] =
{
arithm::threshold<unsigned char>,
arithm::threshold<signed char>,
arithm::threshold<unsigned short>,
arithm::threshold<short>,
arithm::threshold<int>,
arithm::threshold<float>,
arithm::threshold<double>
};
if (depth != CV_32F && depth != CV_64F)
{
thresh = cvFloor(thresh);
maxVal = cvRound(maxVal);
}
funcs[depth](src, dst, thresh, maxVal, type, stream);
}
return thresh;
}
////////////////////////////////////////////////////////////////////////
// NPP magnitide
......
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