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used new device layer for cv::gpu::absdiff

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pull/1540/head
Vladislav Vinogradov 12 years ago
parent 574ff47146
commit 7628e57fc6
3 changed files with 146 additions and 189 deletions
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  1. 159
      modules/cudaarithm/src/cuda/absdiff_mat.cu
  2. 76
      modules/cudaarithm/src/cuda/absdiff_scalar.cu
  3. 100
      modules/cudaarithm/src/element_operations.cpp

159
modules/cudaarithm/src/cuda/absdiff_mat.cu
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@ -40,43 +40,22 @@
//
//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 arithm
{
struct VAbsDiff4 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vabsdiff4(a, b);
}
__host__ __device__ __forceinline__ VAbsDiff4() {}
__host__ __device__ __forceinline__ VAbsDiff4(const VAbsDiff4&) {}
};
#include "opencv2/cudev.hpp"
struct VAbsDiff2 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vabsdiff2(a, b);
}
using namespace cv::cudev;
__host__ __device__ __forceinline__ VAbsDiff2() {}
__host__ __device__ __forceinline__ VAbsDiff2(const VAbsDiff2&) {}
};
void absDiffMat(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat&, double, Stream& stream, int);
namespace
{
__device__ __forceinline__ int _abs(int a)
{
return ::abs(a);
@ -90,58 +69,120 @@ namespace arithm
return ::fabs(a);
}
template <typename T> struct AbsDiffMat : binary_function<T, T, T>
template <typename T> struct AbsDiffOp1 : binary_function<T, T, T>
{
__device__ __forceinline__ T operator ()(T a, T b) const
{
return saturate_cast<T>(_abs(a - b));
}
__host__ __device__ __forceinline__ AbsDiffMat() {}
__host__ __device__ __forceinline__ AbsDiffMat(const AbsDiffMat&) {}
};
}
namespace cv { namespace cuda { namespace device
{
template <> struct TransformFunctorTraits< arithm::VAbsDiff4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
template <typename ScalarDepth> struct TransformPolicy : DefaultTransformPolicy
{
};
template <> struct TransformFunctorTraits< arithm::VAbsDiff2 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
template <> struct TransformPolicy<double> : DefaultTransformPolicy
{
enum {
shift = 1
};
};
template <typename T> struct TransformFunctorTraits< arithm::AbsDiffMat<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
template <typename T>
void absDiffMat_v1(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)
{
gridTransformBinary_< TransformPolicy<T> >(globPtr<T>(src1), globPtr<T>(src2), globPtr<T>(dst), AbsDiffOp1<T>(), stream);
}
struct AbsDiffOp2 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vabsdiff2(a, b);
}
};
}}}
namespace arithm
{
void absDiffMat_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
void absDiffMat_v2(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)
{
device::transform(src1, src2, dst, VAbsDiff4(), WithOutMask(), stream);
const int vcols = src1.cols >> 1;
GlobPtrSz<uint> src1_ = globPtr((uint*) src1.data, src1.step, src1.rows, vcols);
GlobPtrSz<uint> src2_ = globPtr((uint*) src2.data, src2.step, src1.rows, vcols);
GlobPtrSz<uint> dst_ = globPtr((uint*) dst.data, dst.step, src1.rows, vcols);
gridTransformBinary(src1_, src2_, dst_, AbsDiffOp2(), stream);
}
void absDiffMat_v2(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
struct AbsDiffOp4 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vabsdiff4(a, b);
}
};
void absDiffMat_v4(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)
{
device::transform(src1, src2, dst, VAbsDiff2(), WithOutMask(), stream);
const int vcols = src1.cols >> 2;
GlobPtrSz<uint> src1_ = globPtr((uint*) src1.data, src1.step, src1.rows, vcols);
GlobPtrSz<uint> src2_ = globPtr((uint*) src2.data, src2.step, src1.rows, vcols);
GlobPtrSz<uint> dst_ = globPtr((uint*) dst.data, dst.step, src1.rows, vcols);
gridTransformBinary(src1_, src2_, dst_, AbsDiffOp4(), stream);
}
}
template <typename T>
void absDiffMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
void absDiffMat(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat&, double, Stream& stream, int)
{
typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream);
static const func_t funcs[] =
{
absDiffMat_v1<uchar>,
absDiffMat_v1<schar>,
absDiffMat_v1<ushort>,
absDiffMat_v1<short>,
absDiffMat_v1<int>,
absDiffMat_v1<float>,
absDiffMat_v1<double>
};
const int depth = src1.depth();
CV_DbgAssert( depth < 7 );
GpuMat src1_ = src1.reshape(1);
GpuMat src2_ = src2.reshape(1);
GpuMat dst_ = dst.reshape(1);
if (depth == CV_8U || depth == CV_16U)
{
device::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, AbsDiffMat<T>(), WithOutMask(), stream);
const intptr_t src1ptr = reinterpret_cast<intptr_t>(src1_.data);
const intptr_t src2ptr = reinterpret_cast<intptr_t>(src2_.data);
const intptr_t dstptr = reinterpret_cast<intptr_t>(dst_.data);
const bool isAllAligned = (src1ptr & 31) == 0 && (src2ptr & 31) == 0 && (dstptr & 31) == 0;
if (isAllAligned)
{
if (depth == CV_8U && (src1_.cols & 3) == 0)
{
absDiffMat_v4(src1_, src2_, dst_, stream);
return;
}
else if (depth == CV_16U && (src1_.cols & 1) == 0)
{
absDiffMat_v2(src1_, src2_, dst_, stream);
return;
}
}
}
template void absDiffMat<uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffMat<schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffMat<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffMat<short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffMat<int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffMat<float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffMat<double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
const func_t func = funcs[depth];
if (!func)
CV_Error(cv::Error::StsUnsupportedFormat, "Unsupported combination of source and destination types");
func(src1_, src2_, dst_, stream);
}
#endif // CUDA_DISABLER
#endif

76
modules/cudaarithm/src/cuda/absdiff_scalar.cu
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@ -40,59 +40,71 @@
//
//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 arithm
#include "opencv2/cudev.hpp"
using namespace cv::cudev;
void absDiffScalar(const GpuMat& src, cv::Scalar val, bool, GpuMat& dst, const GpuMat&, double, Stream& stream, int);
namespace
{
template <typename T, typename S> struct AbsDiffScalar : unary_function<T, T>
template <typename T, typename S> struct AbsDiffScalarOp : unary_function<T, T>
{
S val;
__host__ explicit AbsDiffScalar(S val_) : val(val_) {}
__device__ __forceinline__ T operator ()(T a) const
{
abs_func<S> f;
return saturate_cast<T>(f(a - val));
}
};
}
namespace cv { namespace cuda { namespace device
{
template <typename T, typename S> struct TransformFunctorTraits< arithm::AbsDiffScalar<T, S> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
template <typename ScalarDepth> struct TransformPolicy : DefaultTransformPolicy
{
};
template <> struct TransformPolicy<double> : DefaultTransformPolicy
{
enum {
shift = 1
};
};
}}}
namespace arithm
template <typename SrcType, typename ScalarDepth>
void absDiffScalarImpl(const GpuMat& src, double value, GpuMat& dst, Stream& stream)
{
AbsDiffScalarOp<SrcType, ScalarDepth> op;
op.val = static_cast<ScalarDepth>(value);
gridTransformUnary_< TransformPolicy<ScalarDepth> >(globPtr<SrcType>(src), globPtr<SrcType>(dst), op, stream);
}
}
void absDiffScalar(const GpuMat& src, cv::Scalar val, bool, GpuMat& dst, const GpuMat&, double, Stream& stream, int)
{
template <typename T, typename S>
void absDiffScalar(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream)
typedef void (*func_t)(const GpuMat& src, double val, GpuMat& dst, Stream& stream);
static const func_t funcs[] =
{
AbsDiffScalar<T, S> op(static_cast<S>(val));
absDiffScalarImpl<uchar, float>,
absDiffScalarImpl<schar, float>,
absDiffScalarImpl<ushort, float>,
absDiffScalarImpl<short, float>,
absDiffScalarImpl<int, float>,
absDiffScalarImpl<float, float>,
absDiffScalarImpl<double, double>
};
device::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) dst, op, WithOutMask(), stream);
}
const int depth = src.depth();
CV_DbgAssert( depth < 7 );
template void absDiffScalar<uchar, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffScalar<schar, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffScalar<ushort, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffScalar<short, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffScalar<int, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffScalar<float, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffScalar<double, double>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
funcs[depth](src, val[0], dst, stream);
}
#endif // CUDA_DISABLER
#endif

100
modules/cudaarithm/src/element_operations.cpp
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@ -442,105 +442,9 @@ void cv::cuda::divide(InputArray _src1, InputArray _src2, OutputArray _dst, doub
//////////////////////////////////////////////////////////////////////////////
// absdiff
namespace arithm
{
void absDiffMat_v4(PtrStepSz<unsigned int> src1, PtrStepSz<unsigned int> src2, PtrStepSz<unsigned int> dst, cudaStream_t stream);
void absDiffMat_v2(PtrStepSz<unsigned int> src1, PtrStepSz<unsigned int> src2, PtrStepSz<unsigned int> dst, cudaStream_t stream);
template <typename T>
void absDiffMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
}
static void absDiffMat(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat&, double, Stream& _stream, int)
{
typedef void (*func_t)(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
static const func_t funcs[] =
{
arithm::absDiffMat<unsigned char>,
arithm::absDiffMat<signed char>,
arithm::absDiffMat<unsigned short>,
arithm::absDiffMat<short>,
arithm::absDiffMat<int>,
arithm::absDiffMat<float>,
arithm::absDiffMat<double>
};
const int depth = src1.depth();
const int cn = src1.channels();
cudaStream_t stream = StreamAccessor::getStream(_stream);
PtrStepSzb src1_(src1.rows, src1.cols * cn, src1.data, src1.step);
PtrStepSzb src2_(src1.rows, src1.cols * cn, src2.data, src2.step);
PtrStepSzb dst_(src1.rows, src1.cols * cn, dst.data, dst.step);
if (depth == CV_8U || depth == CV_16U)
{
const intptr_t src1ptr = reinterpret_cast<intptr_t>(src1_.data);
const intptr_t src2ptr = reinterpret_cast<intptr_t>(src2_.data);
const intptr_t dstptr = reinterpret_cast<intptr_t>(dst_.data);
const bool isAllAligned = (src1ptr & 31) == 0 && (src2ptr & 31) == 0 && (dstptr & 31) == 0;
if (isAllAligned)
{
if (depth == CV_8U && (src1_.cols & 3) == 0)
{
const int vcols = src1_.cols >> 2;
arithm::absDiffMat_v4(PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) src1_.data, src1_.step),
PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) src2_.data, src2_.step),
PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) dst_.data, dst_.step),
stream);
return;
}
else if (depth == CV_16U && (src1_.cols & 1) == 0)
{
const int vcols = src1_.cols >> 1;
arithm::absDiffMat_v2(PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) src1_.data, src1_.step),
PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) src2_.data, src2_.step),
PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) dst_.data, dst_.step),
stream);
void absDiffMat(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat&, double, Stream& stream, int);
return;
}
}
}
const func_t func = funcs[depth];
if (!func)
CV_Error(cv::Error::StsUnsupportedFormat, "Unsupported combination of source and destination types");
func(src1_, src2_, dst_, stream);
}
namespace arithm
{
template <typename T, typename S>
void absDiffScalar(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
}
static void absDiffScalar(const GpuMat& src, Scalar val, bool, GpuMat& dst, const GpuMat&, double, Stream& stream, int)
{
typedef void (*func_t)(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
static const func_t funcs[] =
{
arithm::absDiffScalar<unsigned char, float>,
arithm::absDiffScalar<signed char, float>,
arithm::absDiffScalar<unsigned short, float>,
arithm::absDiffScalar<short, float>,
arithm::absDiffScalar<int, float>,
arithm::absDiffScalar<float, float>,
arithm::absDiffScalar<double, double>
};
const int depth = src.depth();
funcs[depth](src, val[0], dst, StreamAccessor::getStream(stream));
}
void absDiffScalar(const GpuMat& src, cv::Scalar val, bool, GpuMat& dst, const GpuMat&, double, Stream& stream, int);
void cv::cuda::absdiff(InputArray src1, InputArray src2, OutputArray dst, Stream& stream)
{

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