opencv/modules/gpu/src/element_operations.cpp
Vladislav Vinogradov 2582464e51 fixed several problems with CUDA 5.0
* gpu::LUT, uses device memory instead of host memory
* gpu::multiply, round mod for CV_8U depth
2012-05-28 12:09:40 +00:00

2720 lines
134 KiB
C++

/*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.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// 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.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other GpuMaterials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
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// This software is provided by the copyright holders and contributors "as is" and
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//M*/
#include "precomp.hpp"
using namespace cv;
using namespace cv::gpu;
#if !defined (HAVE_CUDA)
void cv::gpu::add(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, int, Stream&) { throw_nogpu(); }
void cv::gpu::add(const GpuMat&, const Scalar&, GpuMat&, const GpuMat&, int, Stream&) { throw_nogpu(); }
void cv::gpu::subtract(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, int, Stream&) { throw_nogpu(); }
void cv::gpu::subtract(const GpuMat&, const Scalar&, GpuMat&, const GpuMat&, int, Stream&) { throw_nogpu(); }
void cv::gpu::multiply(const GpuMat&, const GpuMat&, GpuMat&, double, int, Stream&) { throw_nogpu(); }
void cv::gpu::multiply(const GpuMat&, const Scalar&, GpuMat&, double, int, Stream&) { throw_nogpu(); }
void cv::gpu::divide(const GpuMat&, const GpuMat&, GpuMat&, double, int, Stream&) { throw_nogpu(); }
void cv::gpu::divide(const GpuMat&, const Scalar&, GpuMat&, double, int, Stream&) { throw_nogpu(); }
void cv::gpu::divide(double, const GpuMat&, GpuMat&, int, Stream&) { throw_nogpu(); }
void cv::gpu::absdiff(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::absdiff(const GpuMat&, const Scalar&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::abs(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::sqr(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::sqrt(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::exp(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::log(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::compare(const GpuMat&, const GpuMat&, GpuMat&, int, Stream&) { throw_nogpu(); }
void cv::gpu::compare(const GpuMat&, Scalar, GpuMat&, int, Stream&) { throw_nogpu(); }
void cv::gpu::bitwise_not(const GpuMat&, GpuMat&, const GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::bitwise_or(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::bitwise_or(const GpuMat&, const Scalar&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::bitwise_and(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::bitwise_and(const GpuMat&, const Scalar&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::bitwise_xor(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::bitwise_xor(const GpuMat&, const Scalar&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::rshift(const GpuMat&, Scalar_<int>, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::lshift(const GpuMat&, Scalar_<int>, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::min(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::min(const GpuMat&, double, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::max(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::max(const GpuMat&, double, GpuMat&, Stream&) { throw_nogpu(); }
double cv::gpu::threshold(const GpuMat&, GpuMat&, double, double, int, Stream&) {throw_nogpu(); return 0.0;}
void cv::gpu::pow(const GpuMat&, double, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::alphaComp(const GpuMat&, const GpuMat&, GpuMat&, int, Stream&) { throw_nogpu(); }
void cv::gpu::addWeighted(const GpuMat&, double, const GpuMat&, double, double, GpuMat&, int, Stream&) { throw_nogpu(); }
#else
////////////////////////////////////////////////////////////////////////
// Basic arithmetical operations (add subtract multiply divide)
namespace
{
template<int DEPTH> struct NppTypeTraits;
template<> struct NppTypeTraits<CV_8U> { typedef Npp8u npp_t; };
template<> struct NppTypeTraits<CV_8S> { typedef Npp8s npp_t; };
template<> struct NppTypeTraits<CV_16U> { typedef Npp16u npp_t; };
template<> struct NppTypeTraits<CV_16S> { typedef Npp16s npp_t; typedef Npp16sc npp_complex_type; };
template<> struct NppTypeTraits<CV_32S> { typedef Npp32s npp_t; typedef Npp32sc npp_complex_type; };
template<> struct NppTypeTraits<CV_32F> { typedef Npp32f npp_t; typedef Npp32fc npp_complex_type; };
template<> struct NppTypeTraits<CV_64F> { typedef Npp64f npp_t; typedef Npp64fc npp_complex_type; };
template <int DEPTH> struct NppArithmFunc
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef NppStatus (*func_t)(const npp_t* pSrc1, int nSrc1Step, const npp_t* pSrc2, int nSrc2Step, npp_t* pDst, int nDstStep, NppiSize oSizeROI, int nScaleFactor);
};
template <> struct NppArithmFunc<CV_32F>
{
typedef NppTypeTraits<CV_32F>::npp_t npp_t;
typedef NppStatus (*func_t)(const Npp32f* pSrc1, int nSrc1Step, const Npp32f* pSrc2, int nSrc2Step, Npp32f* pDst, int nDstStep, NppiSize oSizeROI);
};
template <int DEPTH, typename NppArithmFunc<DEPTH>::func_t func> struct NppArithm
{
typedef typename NppArithmFunc<DEPTH>::npp_t npp_t;
static void call(const DevMem2Db src1, const PtrStepb src2, PtrStepb dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize sz;
sz.width = src1.cols;
sz.height = src1.rows;
nppSafeCall( func((const npp_t*)src1.data, static_cast<int>(src1.step), (const npp_t*)src2.data, static_cast<int>(src2.step),
(npp_t*)dst.data, static_cast<int>(dst.step), sz, 0) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template <typename NppArithmFunc<CV_32F>::func_t func> struct NppArithm<CV_32F, func>
{
typedef typename NppArithmFunc<CV_32F>::npp_t npp_t;
static void call(const DevMem2Db src1, const PtrStepb src2, PtrStepb dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize sz;
sz.width = src1.cols;
sz.height = src1.rows;
nppSafeCall( func((const npp_t*)src1.data, static_cast<int>(src1.step), (const npp_t*)src2.data, static_cast<int>(src2.step),
(npp_t*)dst.data, static_cast<int>(dst.step), sz) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<int DEPTH, int cn> struct NppArithmScalarFunc
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef NppStatus (*func_ptr)(const npp_t* pSrc1, int nSrc1Step, const npp_t* pConstants,
npp_t* pDst, int nDstStep, NppiSize oSizeROI, int nScaleFactor);
};
template<int DEPTH> struct NppArithmScalarFunc<DEPTH, 1>
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef NppStatus (*func_ptr)(const npp_t* pSrc1, int nSrc1Step, const npp_t pConstants,
npp_t* pDst, int nDstStep, NppiSize oSizeROI, int nScaleFactor);
};
template<int DEPTH> struct NppArithmScalarFunc<DEPTH, 2>
{
typedef typename NppTypeTraits<DEPTH>::npp_complex_type npp_complex_type;
typedef NppStatus (*func_ptr)(const npp_complex_type* pSrc1, int nSrc1Step, const npp_complex_type pConstants,
npp_complex_type* pDst, int nDstStep, NppiSize oSizeROI, int nScaleFactor);
};
template<int cn> struct NppArithmScalarFunc<CV_32F, cn>
{
typedef NppStatus (*func_ptr)(const Npp32f* pSrc1, int nSrc1Step, const Npp32f* pConstants, Npp32f* pDst, int nDstStep, NppiSize oSizeROI);
};
template<> struct NppArithmScalarFunc<CV_32F, 1>
{
typedef NppStatus (*func_ptr)(const Npp32f* pSrc1, int nSrc1Step, const Npp32f pConstants, Npp32f* pDst, int nDstStep, NppiSize oSizeROI);
};
template<> struct NppArithmScalarFunc<CV_32F, 2>
{
typedef NppStatus (*func_ptr)(const Npp32fc* pSrc1, int nSrc1Step, const Npp32fc pConstants, Npp32fc* pDst, int nDstStep, NppiSize oSizeROI);
};
template<int DEPTH, int cn, typename NppArithmScalarFunc<DEPTH, cn>::func_ptr func> struct NppArithmScalar
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
static void call(const DevMem2Db src, Scalar sc, PtrStepb dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
const npp_t pConstants[] = { saturate_cast<npp_t>(sc.val[0]), saturate_cast<npp_t>(sc.val[1]), saturate_cast<npp_t>(sc.val[2]), saturate_cast<npp_t>(sc.val[3]) };
nppSafeCall( func((const npp_t*)src.data, static_cast<int>(src.step), pConstants, (npp_t*)dst.data, static_cast<int>(dst.step), sz, 0) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<int DEPTH, typename NppArithmScalarFunc<DEPTH, 1>::func_ptr func> struct NppArithmScalar<DEPTH, 1, func>
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
static void call(const DevMem2Db src, Scalar sc, PtrStepb dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
nppSafeCall( func((const npp_t*)src.data, static_cast<int>(src.step), saturate_cast<npp_t>(sc.val[0]), (npp_t*)dst.data, static_cast<int>(dst.step), sz, 0) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<int DEPTH, typename NppArithmScalarFunc<DEPTH, 2>::func_ptr func> struct NppArithmScalar<DEPTH, 2, func>
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef typename NppTypeTraits<DEPTH>::npp_complex_type npp_complex_type;
static void call(const DevMem2Db src, Scalar sc, PtrStepb dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
npp_complex_type nConstant;
nConstant.re = saturate_cast<npp_t>(sc.val[0]);
nConstant.im = saturate_cast<npp_t>(sc.val[1]);
nppSafeCall( func((const npp_complex_type*)src.data, static_cast<int>(src.step), nConstant,
(npp_complex_type*)dst.data, static_cast<int>(dst.step), sz, 0) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<int cn, typename NppArithmScalarFunc<CV_32F, cn>::func_ptr func> struct NppArithmScalar<CV_32F, cn, func>
{
typedef typename NppTypeTraits<CV_32F>::npp_t npp_t;
static void call(const DevMem2Db src, Scalar sc, PtrStepb dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
const Npp32f pConstants[] = { saturate_cast<Npp32f>(sc.val[0]), saturate_cast<Npp32f>(sc.val[1]), saturate_cast<Npp32f>(sc.val[2]), saturate_cast<Npp32f>(sc.val[3]) };
nppSafeCall( func((const npp_t*)src.data, static_cast<int>(src.step), pConstants, (npp_t*)dst.data, static_cast<int>(dst.step), sz) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<typename NppArithmScalarFunc<CV_32F, 1>::func_ptr func> struct NppArithmScalar<CV_32F, 1, func>
{
typedef typename NppTypeTraits<CV_32F>::npp_t npp_t;
static void call(const DevMem2Db src, Scalar sc, PtrStepb dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
nppSafeCall( func((const npp_t*)src.data, static_cast<int>(src.step), saturate_cast<Npp32f>(sc.val[0]), (npp_t*)dst.data, static_cast<int>(dst.step), sz) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<typename NppArithmScalarFunc<CV_32F, 2>::func_ptr func> struct NppArithmScalar<CV_32F, 2, func>
{
typedef typename NppTypeTraits<CV_32F>::npp_t npp_t;
typedef typename NppTypeTraits<CV_32F>::npp_complex_type npp_complex_type;
static void call(const DevMem2Db src, Scalar sc, PtrStepb dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
Npp32fc nConstant;
nConstant.re = saturate_cast<Npp32f>(sc.val[0]);
nConstant.im = saturate_cast<Npp32f>(sc.val[1]);
nppSafeCall( func((const npp_complex_type*)src.data, static_cast<int>(src.step), nConstant, (npp_complex_type*)dst.data, static_cast<int>(dst.step), sz) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
}
////////////////////////////////////////////////////////////////////////
// add
namespace cv { namespace gpu { namespace device
{
template <typename T, typename D>
void add_gpu(const DevMem2Db& src1, const DevMem2Db& src2, const DevMem2Db& dst, const PtrStepb& mask, cudaStream_t stream);
template <typename T, typename D>
void add_gpu(const DevMem2Db& src1, double val, const DevMem2Db& dst, const PtrStepb& mask, cudaStream_t stream);
}}}
void cv::gpu::add(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, int dtype, Stream& s)
{
using namespace cv::gpu::device;
typedef void (*func_t)(const DevMem2Db& src1, const DevMem2Db& src2, const DevMem2Db& dst, const PtrStepb& mask, cudaStream_t stream);
static const func_t funcs[7][7] =
{
{add_gpu<unsigned char, unsigned char> , 0 /*add_gpu<unsigned char, signed char>*/ , add_gpu<unsigned char, unsigned short> , add_gpu<unsigned char, short> , add_gpu<unsigned char, int> , add_gpu<unsigned char, float> , add_gpu<unsigned char, double> },
{0 /*add_gpu<signed char, unsigned char>*/ , 0 /*add_gpu<signed char, signed char>*/ , 0 /*add_gpu<signed char, unsigned short>*/, 0 /*add_gpu<signed char, short>*/ , 0 /*add_gpu<signed char, int>*/, 0 /*add_gpu<signed char, float>*/, 0 /*add_gpu<signed char, double>*/},
{0 /*add_gpu<unsigned short, unsigned char>*/, 0 /*add_gpu<unsigned short, signed char>*/, add_gpu<unsigned short, unsigned short> , 0 /*add_gpu<unsigned short, short>*/, add_gpu<unsigned short, int> , add_gpu<unsigned short, float> , add_gpu<unsigned short, double> },
{0 /*add_gpu<short, unsigned char>*/ , 0 /*add_gpu<short, signed char>*/ , 0 /*add_gpu<short, unsigned short>*/ , add_gpu<short, short> , add_gpu<short, int> , add_gpu<short, float> , add_gpu<short, double> },
{0 /*add_gpu<int, unsigned char>*/ , 0 /*add_gpu<int, signed char>*/ , 0 /*add_gpu<int, unsigned short>*/ , 0 /*add_gpu<int, short>*/ , add_gpu<int, int> , add_gpu<int, float> , add_gpu<int, double> },
{0 /*add_gpu<float, unsigned char>*/ , 0 /*add_gpu<float, signed char>*/ , 0 /*add_gpu<float, unsigned short>*/ , 0 /*add_gpu<float, short>*/ , 0 /*add_gpu<float, int>*/ , add_gpu<float, float> , add_gpu<float, double> },
{0 /*add_gpu<double, unsigned char>*/ , 0 /*add_gpu<double, signed char>*/ , 0 /*add_gpu<double, unsigned short>*/ , 0 /*add_gpu<double, short>*/ , 0 /*add_gpu<double, int>*/ , 0 /*add_gpu<double, float>*/ , add_gpu<double, double> }
};
typedef void (*npp_func_t)(const DevMem2Db src1, const PtrStepb src2, PtrStepb dst, cudaStream_t stream);
static const npp_func_t npp_funcs[] =
{
NppArithm<CV_8U , nppiAdd_8u_C1RSfs >::call,
0,
NppArithm<CV_16U, nppiAdd_16u_C1RSfs>::call,
NppArithm<CV_16S, nppiAdd_16s_C1RSfs>::call,
NppArithm<CV_32S, nppiAdd_32s_C1RSfs>::call,
NppArithm<CV_32F, nppiAdd_32f_C1R >::call
};
if (dtype < 0)
dtype = src1.depth();
CV_Assert(src1.depth() <= CV_64F && CV_MAT_DEPTH(dtype) <= CV_64F);
CV_Assert(src1.type() == src2.type() && src1.size() == src2.size());
CV_Assert(mask.empty() || (src1.channels() == 1 && mask.size() == src1.size() && mask.type() == CV_8U));
if (src1.depth() == CV_64F || CV_MAT_DEPTH(dtype) == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src1.size(), CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), src1.channels()));
cudaStream_t stream = StreamAccessor::getStream(s);
if (mask.empty() && dst.type() == src1.type() && src1.depth() <= CV_32F)
{
npp_funcs[src1.depth()](src1.reshape(1), src2.reshape(1), dst.reshape(1), stream);
return;
}
const func_t func = funcs[src1.depth()][dst.depth()];
if (!func)
CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of source and destination types");
func(src1.reshape(1), src2.reshape(1), dst.reshape(1), mask, stream);
}
void cv::gpu::add(const GpuMat& src, const Scalar& sc, GpuMat& dst, const GpuMat& mask, int dtype, Stream& s)
{
using namespace cv::gpu::device;
typedef void (*func_t)(const DevMem2Db& src1, double val, const DevMem2Db& dst, const PtrStepb& mask, cudaStream_t stream);
static const func_t funcs[7][7] =
{
{add_gpu<unsigned char, unsigned char> , 0 /*add_gpu<unsigned char, signed char>*/ , add_gpu<unsigned char, unsigned short> , add_gpu<unsigned char, short> , add_gpu<unsigned char, int> , add_gpu<unsigned char, float> , add_gpu<unsigned char, double> },
{0 /*add_gpu<signed char, unsigned char>*/ , 0 /*add_gpu<signed char, signed char>*/ , 0 /*add_gpu<signed char, unsigned short>*/, 0 /*add_gpu<signed char, short>*/ , 0 /*add_gpu<signed char, int>*/, 0 /*add_gpu<signed char, float>*/, 0 /*add_gpu<signed char, double>*/},
{0 /*add_gpu<unsigned short, unsigned char>*/, 0 /*add_gpu<unsigned short, signed char>*/, add_gpu<unsigned short, unsigned short> , 0 /*add_gpu<unsigned short, short>*/, add_gpu<unsigned short, int> , add_gpu<unsigned short, float> , add_gpu<unsigned short, double> },
{0 /*add_gpu<short, unsigned char>*/ , 0 /*add_gpu<short, signed char>*/ , 0 /*add_gpu<short, unsigned short>*/ , add_gpu<short, short> , add_gpu<short, int> , add_gpu<short, float> , add_gpu<short, double> },
{0 /*add_gpu<int, unsigned char>*/ , 0 /*add_gpu<int, signed char>*/ , 0 /*add_gpu<int, unsigned short>*/ , 0 /*add_gpu<int, short>*/ , add_gpu<int, int> , add_gpu<int, float> , add_gpu<int, double> },
{0 /*add_gpu<float, unsigned char>*/ , 0 /*add_gpu<float, signed char>*/ , 0 /*add_gpu<float, unsigned short>*/ , 0 /*add_gpu<float, short>*/ , 0 /*add_gpu<float, int>*/ , add_gpu<float, float> , add_gpu<float, double> },
{0 /*add_gpu<double, unsigned char>*/ , 0 /*add_gpu<double, signed char>*/ , 0 /*add_gpu<double, unsigned short>*/ , 0 /*add_gpu<double, short>*/ , 0 /*add_gpu<double, int>*/ , 0 /*add_gpu<double, float>*/ , add_gpu<double, double> }
};
typedef void (*npp_func_t)(const DevMem2Db src, Scalar sc, PtrStepb dst, cudaStream_t stream);
static const npp_func_t npp_funcs[7][4] =
{
{NppArithmScalar<CV_8U , 1, nppiAddC_8u_C1RSfs >::call, 0 , NppArithmScalar<CV_8U , 3, nppiAddC_8u_C3RSfs >::call, NppArithmScalar<CV_8U , 4, nppiAddC_8u_C4RSfs >::call},
{0 , 0 , 0 , 0 },
{NppArithmScalar<CV_16U, 1, nppiAddC_16u_C1RSfs>::call, 0 , NppArithmScalar<CV_16U, 3, nppiAddC_16u_C3RSfs>::call, NppArithmScalar<CV_16U, 4, nppiAddC_16u_C4RSfs>::call},
{NppArithmScalar<CV_16S, 1, nppiAddC_16s_C1RSfs>::call, NppArithmScalar<CV_16S, 2, nppiAddC_16sc_C1RSfs>::call, NppArithmScalar<CV_16S, 3, nppiAddC_16s_C3RSfs>::call, NppArithmScalar<CV_16S, 4, nppiAddC_16s_C4RSfs>::call},
{NppArithmScalar<CV_32S, 1, nppiAddC_32s_C1RSfs>::call, NppArithmScalar<CV_32S, 2, nppiAddC_32sc_C1RSfs>::call, NppArithmScalar<CV_32S, 3, nppiAddC_32s_C3RSfs>::call, 0 },
{NppArithmScalar<CV_32F, 1, nppiAddC_32f_C1R >::call, NppArithmScalar<CV_32F, 2, nppiAddC_32fc_C1R >::call, NppArithmScalar<CV_32F, 3, nppiAddC_32f_C3R >::call, NppArithmScalar<CV_32F, 4, nppiAddC_32f_C4R >::call},
{0 , 0 , 0 , 0 }
};
if (dtype < 0)
dtype = src.depth();
CV_Assert(src.depth() <= CV_64F && CV_MAT_DEPTH(dtype) <= CV_64F);
CV_Assert(src.channels() <= 4);
CV_Assert(mask.empty() || (src.channels() == 1 && mask.size() == src.size() && mask.type() == CV_8U));
if (src.depth() == CV_64F || CV_MAT_DEPTH(dtype) == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src.size(), CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), src.channels()));
cudaStream_t stream = StreamAccessor::getStream(s);
if (mask.empty() && dst.type() == src.type())
{
const npp_func_t npp_func = npp_funcs[src.depth()][src.channels() - 1];
if (npp_func)
{
npp_func(src, sc, dst, stream);
return;
}
}
CV_Assert(src.channels() == 1);
const func_t func = funcs[src.depth()][dst.depth()];
if (!func)
CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of source and destination types");
func(src, sc.val[0], dst, mask, stream);
}
////////////////////////////////////////////////////////////////////////
// subtract
namespace cv { namespace gpu { namespace device
{
template <typename T, typename D>
void subtract_gpu(const DevMem2Db& src1, const DevMem2Db& src2, const DevMem2Db& dst, const PtrStepb& mask, cudaStream_t stream);
template <typename T, typename D>
void subtract_gpu(const DevMem2Db& src1, double val, const DevMem2Db& dst, const PtrStepb& mask, cudaStream_t stream);
}}}
void cv::gpu::subtract(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, int dtype, Stream& s)
{
using namespace cv::gpu::device;
typedef void (*func_t)(const DevMem2Db& src1, const DevMem2Db& src2, const DevMem2Db& dst, const PtrStepb& mask, cudaStream_t stream);
static const func_t funcs[7][7] =
{
{subtract_gpu<unsigned char, unsigned char> , 0 /*subtract_gpu<unsigned char, signed char>*/ , subtract_gpu<unsigned char, unsigned short> , subtract_gpu<unsigned char, short> , subtract_gpu<unsigned char, int> , subtract_gpu<unsigned char, float> , subtract_gpu<unsigned char, double> },
{0 /*subtract_gpu<signed char, unsigned char>*/ , 0 /*subtract_gpu<signed char, signed char>*/ , 0 /*subtract_gpu<signed char, unsigned short>*/, 0 /*subtract_gpu<signed char, short>*/ , 0 /*subtract_gpu<signed char, int>*/, 0 /*subtract_gpu<signed char, float>*/, 0 /*subtract_gpu<signed char, double>*/},
{0 /*subtract_gpu<unsigned short, unsigned char>*/, 0 /*subtract_gpu<unsigned short, signed char>*/, subtract_gpu<unsigned short, unsigned short> , 0 /*subtract_gpu<unsigned short, short>*/, subtract_gpu<unsigned short, int> , subtract_gpu<unsigned short, float> , subtract_gpu<unsigned short, double> },
{0 /*subtract_gpu<short, unsigned char>*/ , 0 /*subtract_gpu<short, signed char>*/ , 0 /*subtract_gpu<short, unsigned short>*/ , subtract_gpu<short, short> , subtract_gpu<short, int> , subtract_gpu<short, float> , subtract_gpu<short, double> },
{0 /*subtract_gpu<int, unsigned char>*/ , 0 /*subtract_gpu<int, signed char>*/ , 0 /*subtract_gpu<int, unsigned short>*/ , 0 /*subtract_gpu<int, short>*/ , subtract_gpu<int, int> , subtract_gpu<int, float> , subtract_gpu<int, double> },
{0 /*subtract_gpu<float, unsigned char>*/ , 0 /*subtract_gpu<float, signed char>*/ , 0 /*subtract_gpu<float, unsigned short>*/ , 0 /*subtract_gpu<float, short>*/ , 0 /*subtract_gpu<float, int>*/ , subtract_gpu<float, float> , subtract_gpu<float, double> },
{0 /*subtract_gpu<double, unsigned char>*/ , 0 /*subtract_gpu<double, signed char>*/ , 0 /*subtract_gpu<double, unsigned short>*/ , 0 /*subtract_gpu<double, short>*/ , 0 /*subtract_gpu<double, int>*/ , 0 /*subtract_gpu<double, float>*/ , subtract_gpu<double, double> }
};
typedef void (*npp_func_t)(const DevMem2Db src1, const PtrStepb src2, PtrStepb dst, cudaStream_t stream);
static const npp_func_t npp_funcs[6] =
{
NppArithm<CV_8U , nppiSub_8u_C1RSfs>::call,
0,
NppArithm<CV_16U, nppiSub_16u_C1RSfs>::call,
NppArithm<CV_16S, nppiSub_16s_C1RSfs>::call,
NppArithm<CV_32S, nppiSub_32s_C1RSfs>::call,
NppArithm<CV_32F, nppiSub_32f_C1R >::call
};
if (dtype < 0)
dtype = src1.depth();
CV_Assert(src1.depth() <= CV_64F && CV_MAT_DEPTH(dtype) <= CV_64F);
CV_Assert(src1.type() == src2.type() && src1.size() == src2.size());
CV_Assert(mask.empty() || (src1.channels() == 1 && mask.size() == src1.size() && mask.type() == CV_8U));
if (src1.depth() == CV_64F || CV_MAT_DEPTH(dtype) == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src1.size(), CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), src1.channels()));
cudaStream_t stream = StreamAccessor::getStream(s);
if (mask.empty() && dst.type() == src1.type() && src1.depth() <= CV_32F)
{
npp_funcs[src1.depth()](src2.reshape(1), src1.reshape(1), dst.reshape(1), stream);
return;
}
const func_t func = funcs[src1.depth()][dst.depth()];
if (!func)
CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of source and destination types");
func(src1.reshape(1), src2.reshape(1), dst.reshape(1), mask, stream);
}
void cv::gpu::subtract(const GpuMat& src, const Scalar& sc, GpuMat& dst, const GpuMat& mask, int dtype, Stream& s)
{
using namespace cv::gpu::device;
typedef void (*func_t)(const DevMem2Db& src1, double val, const DevMem2Db& dst, const PtrStepb& mask, cudaStream_t stream);
static const func_t funcs[7][7] =
{
{subtract_gpu<unsigned char, unsigned char> , 0 /*subtract_gpu<unsigned char, signed char>*/ , subtract_gpu<unsigned char, unsigned short> , subtract_gpu<unsigned char, short> , subtract_gpu<unsigned char, int> , subtract_gpu<unsigned char, float> , subtract_gpu<unsigned char, double> },
{0 /*subtract_gpu<signed char, unsigned char>*/ , 0 /*subtract_gpu<signed char, signed char>*/ , 0 /*subtract_gpu<signed char, unsigned short>*/, 0 /*subtract_gpu<signed char, short>*/ , 0 /*subtract_gpu<signed char, int>*/, 0 /*subtract_gpu<signed char, float>*/, 0 /*subtract_gpu<signed char, double>*/},
{0 /*subtract_gpu<unsigned short, unsigned char>*/, 0 /*subtract_gpu<unsigned short, signed char>*/, subtract_gpu<unsigned short, unsigned short> , 0 /*subtract_gpu<unsigned short, short>*/, subtract_gpu<unsigned short, int> , subtract_gpu<unsigned short, float> , subtract_gpu<unsigned short, double> },
{0 /*subtract_gpu<short, unsigned char>*/ , 0 /*subtract_gpu<short, signed char>*/ , 0 /*subtract_gpu<short, unsigned short>*/ , subtract_gpu<short, short> , subtract_gpu<short, int> , subtract_gpu<short, float> , subtract_gpu<short, double> },
{0 /*subtract_gpu<int, unsigned char>*/ , 0 /*subtract_gpu<int, signed char>*/ , 0 /*subtract_gpu<int, unsigned short>*/ , 0 /*subtract_gpu<int, short>*/ , subtract_gpu<int, int> , subtract_gpu<int, float> , subtract_gpu<int, double> },
{0 /*subtract_gpu<float, unsigned char>*/ , 0 /*subtract_gpu<float, signed char>*/ , 0 /*subtract_gpu<float, unsigned short>*/ , 0 /*subtract_gpu<float, short>*/ , 0 /*subtract_gpu<float, int>*/ , subtract_gpu<float, float> , subtract_gpu<float, double> },
{0 /*subtract_gpu<double, unsigned char>*/ , 0 /*subtract_gpu<double, signed char>*/ , 0 /*subtract_gpu<double, unsigned short>*/ , 0 /*subtract_gpu<double, short>*/ , 0 /*subtract_gpu<double, int>*/ , 0 /*subtract_gpu<double, float>*/ , subtract_gpu<double, double> }
};
typedef void (*npp_func_t)(const DevMem2Db src, Scalar sc, PtrStepb dst, cudaStream_t stream);
static const npp_func_t npp_funcs[7][4] =
{
{NppArithmScalar<CV_8U , 1, nppiSubC_8u_C1RSfs >::call, 0 , NppArithmScalar<CV_8U , 3, nppiSubC_8u_C3RSfs >::call, NppArithmScalar<CV_8U , 4, nppiSubC_8u_C4RSfs >::call},
{0 , 0 , 0 , 0 },
{NppArithmScalar<CV_16U, 1, nppiSubC_16u_C1RSfs>::call, 0 , NppArithmScalar<CV_16U, 3, nppiSubC_16u_C3RSfs>::call, NppArithmScalar<CV_16U, 4, nppiSubC_16u_C4RSfs>::call},
{NppArithmScalar<CV_16S, 1, nppiSubC_16s_C1RSfs>::call, NppArithmScalar<CV_16S, 2, nppiSubC_16sc_C1RSfs>::call, NppArithmScalar<CV_16S, 3, nppiSubC_16s_C3RSfs>::call, NppArithmScalar<CV_16S, 4, nppiSubC_16s_C4RSfs>::call},
{NppArithmScalar<CV_32S, 1, nppiSubC_32s_C1RSfs>::call, NppArithmScalar<CV_32S, 2, nppiSubC_32sc_C1RSfs>::call, NppArithmScalar<CV_32S, 3, nppiSubC_32s_C3RSfs>::call, 0 },
{NppArithmScalar<CV_32F, 1, nppiSubC_32f_C1R >::call, NppArithmScalar<CV_32F, 2, nppiSubC_32fc_C1R >::call, NppArithmScalar<CV_32F, 3, nppiSubC_32f_C3R >::call, NppArithmScalar<CV_32F, 4, nppiSubC_32f_C4R >::call},
{0 , 0 , 0 , 0 }
};
if (dtype < 0)
dtype = src.depth();
CV_Assert(src.depth() <= CV_64F && CV_MAT_DEPTH(dtype) <= CV_64F);
CV_Assert(src.channels() <= 4);
CV_Assert(mask.empty() || (src.channels() == 1 && mask.size() == src.size() && mask.type() == CV_8U));
if (src.depth() == CV_64F || CV_MAT_DEPTH(dtype) == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src.size(), CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), src.channels()));
cudaStream_t stream = StreamAccessor::getStream(s);
if (mask.empty() && dst.type() == src.type())
{
const npp_func_t npp_func = npp_funcs[src.depth()][src.channels() - 1];
if (npp_func)
{
npp_func(src, sc, dst, stream);
return;
}
}
CV_Assert(src.channels() == 1);
const func_t func = funcs[src.depth()][dst.depth()];
if (!func)
CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of source and destination types");
func(src, sc.val[0], dst, mask, stream);
}
////////////////////////////////////////////////////////////////////////
// multiply
namespace cv { namespace gpu { namespace device
{
void multiply_gpu(const DevMem2D_<uchar4>& src1, const DevMem2Df& src2, const DevMem2D_<uchar4>& dst, cudaStream_t stream);
void multiply_gpu(const DevMem2D_<short4>& src1, const DevMem2Df& src2, const DevMem2D_<short4>& dst, cudaStream_t stream);
template <typename T, typename D>
void multiply_gpu(const DevMem2Db& src1, const DevMem2Db& src2, const DevMem2Db& dst, double scale, cudaStream_t stream);
template <typename T, typename D>
void multiply_gpu(const DevMem2Db& src1, double val, const DevMem2Db& dst, double scale, cudaStream_t stream);
}}}
void cv::gpu::multiply(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, double scale, int dtype, Stream& s)
{
using namespace cv::gpu::device;
cudaStream_t stream = StreamAccessor::getStream(s);
if (src1.type() == CV_8UC4 && src2.type() == CV_32FC1)
{
CV_Assert(src1.size() == src2.size());
dst.create(src1.size(), src1.type());
multiply_gpu(static_cast<DevMem2D_<uchar4> >(src1), static_cast<DevMem2Df>(src2), static_cast<DevMem2D_<uchar4> >(dst), stream);
}
else if (src1.type() == CV_16SC4 && src2.type() == CV_32FC1)
{
CV_Assert(src1.size() == src2.size());
dst.create(src1.size(), src1.type());
multiply_gpu(static_cast<DevMem2D_<short4> >(src1), static_cast<DevMem2Df>(src2), static_cast<DevMem2D_<short4> >(dst), stream);
}
else
{
typedef void (*func_t)(const DevMem2Db& src1, const DevMem2Db& src2, const DevMem2Db& dst, double scale, cudaStream_t stream);
static const func_t funcs[7][7] =
{
{multiply_gpu<unsigned char, unsigned char> , 0 /*multiply_gpu<unsigned char, signed char>*/ , multiply_gpu<unsigned char, unsigned short> , multiply_gpu<unsigned char, short> , multiply_gpu<unsigned char, int> , multiply_gpu<unsigned char, float> , multiply_gpu<unsigned char, double> },
{0 /*multiply_gpu<signed char, unsigned char>*/ , 0 /*multiply_gpu<signed char, signed char>*/ , 0 /*multiply_gpu<signed char, unsigned short>*/, 0 /*multiply_gpu<signed char, short>*/ , 0 /*multiply_gpu<signed char, int>*/, 0 /*multiply_gpu<signed char, float>*/, 0 /*multiply_gpu<signed char, double>*/},
{0 /*multiply_gpu<unsigned short, unsigned char>*/, 0 /*multiply_gpu<unsigned short, signed char>*/, multiply_gpu<unsigned short, unsigned short> , 0 /*multiply_gpu<unsigned short, short>*/, multiply_gpu<unsigned short, int> , multiply_gpu<unsigned short, float> , multiply_gpu<unsigned short, double> },
{0 /*multiply_gpu<short, unsigned char>*/ , 0 /*multiply_gpu<short, signed char>*/ , 0 /*multiply_gpu<short, unsigned short>*/ , multiply_gpu<short, short> , multiply_gpu<short, int> , multiply_gpu<short, float> , multiply_gpu<short, double> },
{0 /*multiply_gpu<int, unsigned char>*/ , 0 /*multiply_gpu<int, signed char>*/ , 0 /*multiply_gpu<int, unsigned short>*/ , 0 /*multiply_gpu<int, short>*/ , multiply_gpu<int, int> , multiply_gpu<int, float> , multiply_gpu<int, double> },
{0 /*multiply_gpu<float, unsigned char>*/ , 0 /*multiply_gpu<float, signed char>*/ , 0 /*multiply_gpu<float, unsigned short>*/ , 0 /*multiply_gpu<float, short>*/ , 0 /*multiply_gpu<float, int>*/ , multiply_gpu<float, float> , multiply_gpu<float, double> },
{0 /*multiply_gpu<double, unsigned char>*/ , 0 /*multiply_gpu<double, signed char>*/ , 0 /*multiply_gpu<double, unsigned short>*/ , 0 /*multiply_gpu<double, short>*/ , 0 /*multiply_gpu<double, int>*/ , 0 /*multiply_gpu<double, float>*/ , multiply_gpu<double, double> }
};
typedef void (*npp_func_t)(const DevMem2Db src1, const PtrStepb src2, PtrStepb dst, cudaStream_t stream);
static const npp_func_t npp_funcs[] =
{
NppArithm<CV_8U , nppiMul_8u_C1RSfs >::call,
0,
NppArithm<CV_16U, nppiMul_16u_C1RSfs>::call,
NppArithm<CV_16S, nppiMul_16s_C1RSfs>::call,
NppArithm<CV_32S, nppiMul_32s_C1RSfs>::call,
NppArithm<CV_32F, nppiMul_32f_C1R >::call
};
if (dtype < 0)
dtype = src1.depth();
CV_Assert(src1.depth() <= CV_64F && CV_MAT_DEPTH(dtype) <= CV_64F);
CV_Assert(src1.type() == src2.type() && src1.size() == src2.size());
if (src1.depth() == CV_64F || CV_MAT_DEPTH(dtype) == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src1.size(), CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), src1.channels()));
#if (CUDA_VERSION <= 4020)
if (scale == 1 && dst.type() == src1.type() && src1.depth() <= CV_32F)
#else
if (scale == 1 && dst.type() == src1.type() && src1.depth() <= CV_32F && src1.depth() > CV_8U)
#endif
{
npp_funcs[src1.depth()](src1.reshape(1), src2.reshape(1), dst.reshape(1), stream);
return;
}
const func_t func = funcs[src1.depth()][dst.depth()];
if (!func)
CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of source and destination types");
func(src1.reshape(1), src2.reshape(1), dst.reshape(1), scale, stream);
}
}
namespace
{
inline bool isIntScalar(Scalar sc)
{
return sc.val[0] == static_cast<int>(sc.val[0]) && sc.val[1] == static_cast<int>(sc.val[1]) && sc.val[2] == static_cast<int>(sc.val[2]) && sc.val[3] == static_cast<int>(sc.val[3]);
}
}
void cv::gpu::multiply(const GpuMat& src, const Scalar& sc, GpuMat& dst, double scale, int dtype, Stream& s)
{
using namespace cv::gpu::device;
typedef void (*func_t)(const DevMem2Db& src1, double val, const DevMem2Db& dst, double scale, cudaStream_t stream);
static const func_t funcs[7][7] =
{
{multiply_gpu<unsigned char, unsigned char> , 0 /*multiply_gpu<unsigned char, signed char>*/ , multiply_gpu<unsigned char, unsigned short> , multiply_gpu<unsigned char, short> , multiply_gpu<unsigned char, int> , multiply_gpu<unsigned char, float> , multiply_gpu<unsigned char, double> },
{0 /*multiply_gpu<signed char, unsigned char>*/ , 0 /*multiply_gpu<signed char, signed char>*/ , 0 /*multiply_gpu<signed char, unsigned short>*/, 0 /*multiply_gpu<signed char, short>*/ , 0 /*multiply_gpu<signed char, int>*/, 0 /*multiply_gpu<signed char, float>*/, 0 /*multiply_gpu<signed char, double>*/},
{0 /*multiply_gpu<unsigned short, unsigned char>*/, 0 /*multiply_gpu<unsigned short, signed char>*/, multiply_gpu<unsigned short, unsigned short> , 0 /*multiply_gpu<unsigned short, short>*/, multiply_gpu<unsigned short, int> , multiply_gpu<unsigned short, float> , multiply_gpu<unsigned short, double> },
{0 /*multiply_gpu<short, unsigned char>*/ , 0 /*multiply_gpu<short, signed char>*/ , 0 /*multiply_gpu<short, unsigned short>*/ , multiply_gpu<short, short> , multiply_gpu<short, int> , multiply_gpu<short, float> , multiply_gpu<short, double> },
{0 /*multiply_gpu<int, unsigned char>*/ , 0 /*multiply_gpu<int, signed char>*/ , 0 /*multiply_gpu<int, unsigned short>*/ , 0 /*multiply_gpu<int, short>*/ , multiply_gpu<int, int> , multiply_gpu<int, float> , multiply_gpu<int, double> },
{0 /*multiply_gpu<float, unsigned char>*/ , 0 /*multiply_gpu<float, signed char>*/ , 0 /*multiply_gpu<float, unsigned short>*/ , 0 /*multiply_gpu<float, short>*/ , 0 /*multiply_gpu<float, int>*/ , multiply_gpu<float, float> , multiply_gpu<float, double> },
{0 /*multiply_gpu<double, unsigned char>*/ , 0 /*multiply_gpu<double, signed char>*/ , 0 /*multiply_gpu<double, unsigned short>*/ , 0 /*multiply_gpu<double, short>*/ , 0 /*multiply_gpu<double, int>*/ , 0 /*multiply_gpu<double, float>*/ , multiply_gpu<double, double> }
};
typedef void (*npp_func_t)(const DevMem2Db src, Scalar sc, PtrStepb dst, cudaStream_t stream);
static const npp_func_t npp_funcs[7][4] =
{
{NppArithmScalar<CV_8U , 1, nppiMulC_8u_C1RSfs >::call, 0, NppArithmScalar<CV_8U , 3, nppiMulC_8u_C3RSfs >::call, NppArithmScalar<CV_8U , 4, nppiMulC_8u_C4RSfs >::call},
{0 , 0, 0 , 0 },
{NppArithmScalar<CV_16U, 1, nppiMulC_16u_C1RSfs>::call, 0, NppArithmScalar<CV_16U, 3, nppiMulC_16u_C3RSfs>::call, NppArithmScalar<CV_16U, 4, nppiMulC_16u_C4RSfs>::call},
{NppArithmScalar<CV_16S, 1, nppiMulC_16s_C1RSfs>::call, 0, NppArithmScalar<CV_16S, 3, nppiMulC_16s_C3RSfs>::call, NppArithmScalar<CV_16S, 4, nppiMulC_16s_C4RSfs>::call},
{NppArithmScalar<CV_32S, 1, nppiMulC_32s_C1RSfs>::call, 0, NppArithmScalar<CV_32S, 3, nppiMulC_32s_C3RSfs>::call, 0 },
{NppArithmScalar<CV_32F, 1, nppiMulC_32f_C1R >::call, 0, NppArithmScalar<CV_32F, 3, nppiMulC_32f_C3R >::call, NppArithmScalar<CV_32F, 4, nppiMulC_32f_C4R >::call},
{0 , 0, 0 , 0 }
};
if (dtype < 0)
dtype = src.depth();
CV_Assert(src.depth() <= CV_64F && CV_MAT_DEPTH(dtype) <= CV_64F);
CV_Assert(src.channels() <= 4);
if (src.depth() == CV_64F || CV_MAT_DEPTH(dtype) == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src.size(), CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), src.channels()));
cudaStream_t stream = StreamAccessor::getStream(s);
if (dst.type() == src.type() && scale == 1 && (src.depth() == CV_32F || isIntScalar(sc)))
{
const npp_func_t npp_func = npp_funcs[src.depth()][src.channels() - 1];
if (npp_func)
{
npp_func(src, sc, dst, stream);
return;
}
}
CV_Assert(src.channels() == 1);
const func_t func = funcs[src.depth()][dst.depth()];
if (!func)
CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of source and destination types");
func(src, sc.val[0], dst, scale, stream);
}
////////////////////////////////////////////////////////////////////////
// divide
namespace cv { namespace gpu { namespace device
{
void divide_gpu(const DevMem2D_<uchar4>& src1, const DevMem2Df& src2, const DevMem2D_<uchar4>& dst, cudaStream_t stream);
void divide_gpu(const DevMem2D_<short4>& src1, const DevMem2Df& src2, const DevMem2D_<short4>& dst, cudaStream_t stream);
template <typename T, typename D>
void divide_gpu(const DevMem2Db& src1, const DevMem2Db& src2, const DevMem2Db& dst, double scale, cudaStream_t stream);
template <typename T, typename D>
void divide_gpu(const DevMem2Db& src1, double val, const DevMem2Db& dst, double scale, cudaStream_t stream);
template <typename T, typename D>
void divide_gpu(double scalar, const DevMem2Db& src2, const DevMem2Db& dst, cudaStream_t stream);
}}}
void cv::gpu::divide(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, double scale, int dtype, Stream& s)
{
using namespace cv::gpu::device;
cudaStream_t stream = StreamAccessor::getStream(s);
if (src1.type() == CV_8UC4 && src2.type() == CV_32FC1)
{
CV_Assert(src1.size() == src2.size());
dst.create(src1.size(), src1.type());
divide_gpu(static_cast<DevMem2D_<uchar4> >(src1), static_cast<DevMem2Df>(src2), static_cast<DevMem2D_<uchar4> >(dst), stream);
}
else if (src1.type() == CV_16SC4 && src2.type() == CV_32FC1)
{
CV_Assert(src1.size() == src2.size());
dst.create(src1.size(), src1.type());
divide_gpu(static_cast<DevMem2D_<short4> >(src1), static_cast<DevMem2Df>(src2), static_cast<DevMem2D_<short4> >(dst), stream);
}
else
{
typedef void (*func_t)(const DevMem2Db& src1, const DevMem2Db& src2, const DevMem2Db& dst, double scale, cudaStream_t stream);
static const func_t funcs[7][7] =
{
{divide_gpu<unsigned char, unsigned char> , 0 /*divide_gpu<unsigned char, signed char>*/ , divide_gpu<unsigned char, unsigned short> , divide_gpu<unsigned char, short> , divide_gpu<unsigned char, int> , divide_gpu<unsigned char, float> , divide_gpu<unsigned char, double> },
{0 /*divide_gpu<signed char, unsigned char>*/ , 0 /*divide_gpu<signed char, signed char>*/ , 0 /*divide_gpu<signed char, unsigned short>*/, 0 /*divide_gpu<signed char, short>*/ , 0 /*divide_gpu<signed char, int>*/, 0 /*divide_gpu<signed char, float>*/, 0 /*divide_gpu<signed char, double>*/},
{0 /*divide_gpu<unsigned short, unsigned char>*/, 0 /*divide_gpu<unsigned short, signed char>*/, divide_gpu<unsigned short, unsigned short> , 0 /*divide_gpu<unsigned short, short>*/, divide_gpu<unsigned short, int> , divide_gpu<unsigned short, float> , divide_gpu<unsigned short, double> },
{0 /*divide_gpu<short, unsigned char>*/ , 0 /*divide_gpu<short, signed char>*/ , 0 /*divide_gpu<short, unsigned short>*/ , divide_gpu<short, short> , divide_gpu<short, int> , divide_gpu<short, float> , divide_gpu<short, double> },
{0 /*divide_gpu<int, unsigned char>*/ , 0 /*divide_gpu<int, signed char>*/ , 0 /*divide_gpu<int, unsigned short>*/ , 0 /*divide_gpu<int, short>*/ , divide_gpu<int, int> , divide_gpu<int, float> , divide_gpu<int, double> },
{0 /*divide_gpu<float, unsigned char>*/ , 0 /*divide_gpu<float, signed char>*/ , 0 /*divide_gpu<float, unsigned short>*/ , 0 /*divide_gpu<float, short>*/ , 0 /*divide_gpu<float, int>*/ , divide_gpu<float, float> , divide_gpu<float, double> },
{0 /*divide_gpu<double, unsigned char>*/ , 0 /*divide_gpu<double, signed char>*/ , 0 /*divide_gpu<double, unsigned short>*/ , 0 /*divide_gpu<double, short>*/ , 0 /*divide_gpu<double, int>*/ , 0 /*divide_gpu<double, float>*/ , divide_gpu<double, double> }
};
typedef void (*npp_func_t)(const DevMem2Db src1, const PtrStepb src2, PtrStepb dst, cudaStream_t stream);
static const npp_func_t npp_funcs[6] =
{
NppArithm<CV_8U , nppiDiv_8u_C1RSfs >::call,
0,
NppArithm<CV_16U, nppiDiv_16u_C1RSfs>::call,
NppArithm<CV_16S, nppiDiv_16s_C1RSfs>::call,
NppArithm<CV_32S, nppiDiv_32s_C1RSfs>::call,
NppArithm<CV_32F, nppiDiv_32f_C1R >::call
};
if (dtype < 0)
dtype = src1.depth();
CV_Assert(src1.depth() <= CV_64F && CV_MAT_DEPTH(dtype) <= CV_64F);
CV_Assert(src1.type() == src2.type() && src1.size() == src2.size());
if (src1.depth() == CV_64F || CV_MAT_DEPTH(dtype) == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src1.size(), CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), src1.channels()));
if (scale == 1 && dst.type() == src1.type() && src1.depth() <= CV_32F)
{
npp_funcs[src1.depth()](src2.reshape(1), src1.reshape(1), dst.reshape(1), stream);
return;
}
const func_t func = funcs[src1.depth()][dst.depth()];
if (!func)
CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of source and destination types");
func(src1.reshape(1), src2.reshape(1), dst.reshape(1), scale, stream);
}
}
void cv::gpu::divide(const GpuMat& src, const Scalar& sc, GpuMat& dst, double scale, int dtype, Stream& s)
{
using namespace cv::gpu::device;
typedef void (*func_t)(const DevMem2Db& src1, double val, const DevMem2Db& dst, double scale, cudaStream_t stream);
static const func_t funcs[7][7] =
{
{divide_gpu<unsigned char, unsigned char> , 0 /*divide_gpu<unsigned char, signed char>*/ , divide_gpu<unsigned char, unsigned short> , divide_gpu<unsigned char, short> , divide_gpu<unsigned char, int> , divide_gpu<unsigned char, float> , divide_gpu<unsigned char, double> },
{0 /*divide_gpu<signed char, unsigned char>*/ , 0 /*divide_gpu<signed char, signed char>*/ , 0 /*divide_gpu<signed char, unsigned short>*/, 0 /*divide_gpu<signed char, short>*/ , 0 /*divide_gpu<signed char, int>*/, 0 /*divide_gpu<signed char, float>*/, 0 /*divide_gpu<signed char, double>*/},
{0 /*divide_gpu<unsigned short, unsigned char>*/, 0 /*divide_gpu<unsigned short, signed char>*/, divide_gpu<unsigned short, unsigned short> , 0 /*divide_gpu<unsigned short, short>*/, divide_gpu<unsigned short, int> , divide_gpu<unsigned short, float> , divide_gpu<unsigned short, double> },
{0 /*divide_gpu<short, unsigned char>*/ , 0 /*divide_gpu<short, signed char>*/ , 0 /*divide_gpu<short, unsigned short>*/ , divide_gpu<short, short> , divide_gpu<short, int> , divide_gpu<short, float> , divide_gpu<short, double> },
{0 /*divide_gpu<int, unsigned char>*/ , 0 /*divide_gpu<int, signed char>*/ , 0 /*divide_gpu<int, unsigned short>*/ , 0 /*divide_gpu<int, short>*/ , divide_gpu<int, int> , divide_gpu<int, float> , divide_gpu<int, double> },
{0 /*divide_gpu<float, unsigned char>*/ , 0 /*divide_gpu<float, signed char>*/ , 0 /*divide_gpu<float, unsigned short>*/ , 0 /*divide_gpu<float, short>*/ , 0 /*divide_gpu<float, int>*/ , divide_gpu<float, float> , divide_gpu<float, double> },
{0 /*divide_gpu<double, unsigned char>*/ , 0 /*divide_gpu<double, signed char>*/ , 0 /*divide_gpu<double, unsigned short>*/ , 0 /*divide_gpu<double, short>*/ , 0 /*divide_gpu<double, int>*/ , 0 /*divide_gpu<double, float>*/ , divide_gpu<double, double> }
};
typedef void (*npp_func_t)(const DevMem2Db src, Scalar sc, PtrStepb dst, cudaStream_t stream);
static const npp_func_t npp_funcs[7][4] =
{
{NppArithmScalar<CV_8U , 1, nppiDivC_8u_C1RSfs >::call, 0, NppArithmScalar<CV_8U , 3, nppiDivC_8u_C3RSfs >::call, NppArithmScalar<CV_8U , 4, nppiDivC_8u_C4RSfs >::call},
{0 , 0, 0 , 0 },
{NppArithmScalar<CV_16U, 1, nppiDivC_16u_C1RSfs>::call, 0, NppArithmScalar<CV_16U, 3, nppiDivC_16u_C3RSfs>::call, NppArithmScalar<CV_16U, 4, nppiDivC_16u_C4RSfs>::call},
{NppArithmScalar<CV_16S, 1, nppiDivC_16s_C1RSfs>::call, 0, NppArithmScalar<CV_16S, 3, nppiDivC_16s_C3RSfs>::call, NppArithmScalar<CV_16S, 4, nppiDivC_16s_C4RSfs>::call},
{NppArithmScalar<CV_32S, 1, nppiDivC_32s_C1RSfs>::call, 0, NppArithmScalar<CV_32S, 3, nppiDivC_32s_C3RSfs>::call, 0 },
{NppArithmScalar<CV_32F, 1, nppiDivC_32f_C1R >::call, 0, NppArithmScalar<CV_32F, 3, nppiDivC_32f_C3R >::call, NppArithmScalar<CV_32F, 4, nppiDivC_32f_C4R >::call},
{0 , 0, 0 , 0 }
};
if (dtype < 0)
dtype = src.depth();
CV_Assert(src.depth() <= CV_64F && CV_MAT_DEPTH(dtype) <= CV_64F);
CV_Assert(src.channels() <= 4);
if (src.depth() == CV_64F || CV_MAT_DEPTH(dtype) == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src.size(), CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), src.channels()));
cudaStream_t stream = StreamAccessor::getStream(s);
if (dst.type() == src.type() && scale == 1 && (src.depth() == CV_32F || isIntScalar(sc)))
{
const npp_func_t npp_func = npp_funcs[src.depth()][src.channels() - 1];
if (npp_func)
{
npp_func(src, sc, dst, stream);
return;
}
}
CV_Assert(src.channels() == 1);
const func_t func = funcs[src.depth()][dst.depth()];
if (!func)
CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of source and destination types");
func(src, sc.val[0], dst, scale, stream);
}
void cv::gpu::divide(double scale, const GpuMat& src, GpuMat& dst, int dtype, Stream& s)
{
using namespace cv::gpu::device;
typedef void (*func_t)(double scalar, const DevMem2Db& src2, const DevMem2Db& dst, cudaStream_t stream);
static const func_t funcs[7][7] =
{
{divide_gpu<unsigned char, unsigned char> , 0 /*divide_gpu<unsigned char, signed char>*/ , divide_gpu<unsigned char, unsigned short> , divide_gpu<unsigned char, short> , divide_gpu<unsigned char, int> , divide_gpu<unsigned char, float> , divide_gpu<unsigned char, double> },
{0 /*divide_gpu<signed char, unsigned char>*/ , 0 /*divide_gpu<signed char, signed char>*/ , 0 /*divide_gpu<signed char, unsigned short>*/, 0 /*divide_gpu<signed char, short>*/ , 0 /*divide_gpu<signed char, int>*/, 0 /*divide_gpu<signed char, float>*/, 0 /*divide_gpu<signed char, double>*/},
{0 /*divide_gpu<unsigned short, unsigned char>*/, 0 /*divide_gpu<unsigned short, signed char>*/, divide_gpu<unsigned short, unsigned short> , 0 /*divide_gpu<unsigned short, short>*/, divide_gpu<unsigned short, int> , divide_gpu<unsigned short, float> , divide_gpu<unsigned short, double> },
{0 /*divide_gpu<short, unsigned char>*/ , 0 /*divide_gpu<short, signed char>*/ , 0 /*divide_gpu<short, unsigned short>*/ , divide_gpu<short, short> , divide_gpu<short, int> , divide_gpu<short, float> , divide_gpu<short, double> },
{0 /*divide_gpu<int, unsigned char>*/ , 0 /*divide_gpu<int, signed char>*/ , 0 /*divide_gpu<int, unsigned short>*/ , 0 /*divide_gpu<int, short>*/ , divide_gpu<int, int> , divide_gpu<int, float> , divide_gpu<int, double> },
{0 /*divide_gpu<float, unsigned char>*/ , 0 /*divide_gpu<float, signed char>*/ , 0 /*divide_gpu<float, unsigned short>*/ , 0 /*divide_gpu<float, short>*/ , 0 /*divide_gpu<float, int>*/ , divide_gpu<float, float> , divide_gpu<float, double> },
{0 /*divide_gpu<double, unsigned char>*/ , 0 /*divide_gpu<double, signed char>*/ , 0 /*divide_gpu<double, unsigned short>*/ , 0 /*divide_gpu<double, short>*/ , 0 /*divide_gpu<double, int>*/ , 0 /*divide_gpu<double, float>*/ , divide_gpu<double, double> }
};
if (dtype < 0)
dtype = src.depth();
CV_Assert(src.depth() <= CV_64F && CV_MAT_DEPTH(dtype) <= CV_64F);
CV_Assert(src.channels() == 1);
if (src.depth() == CV_64F || CV_MAT_DEPTH(dtype) == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src.size(), CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), src.channels()));
cudaStream_t stream = StreamAccessor::getStream(s);
const func_t func = funcs[src.depth()][dst.depth()];
if (!func)
CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of source and destination types");
func(scale, src, dst, stream);
}
//////////////////////////////////////////////////////////////////////////////
// absdiff
namespace cv { namespace gpu { namespace device
{
template <typename T>
void absdiff_gpu(const DevMem2Db src1, const DevMem2Db src2, DevMem2Db dst, cudaStream_t stream);
template <typename T>
void absdiff_gpu(const DevMem2Db src1, double val, DevMem2Db dst, cudaStream_t stream);
}}}
namespace
{
template <int DEPTH> struct NppAbsDiffFunc
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef NppStatus (*func_t)(const npp_t* src1, int src1_step, const npp_t* src2, int src2_step, npp_t* dst, int dst_step, NppiSize sz);
};
template <int DEPTH, typename NppAbsDiffFunc<DEPTH>::func_t func> struct NppAbsDiff
{
typedef typename NppAbsDiffFunc<DEPTH>::npp_t npp_t;
static void call(const DevMem2Db src1, const DevMem2Db src2, DevMem2Db dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize sz;
sz.width = src1.cols;
sz.height = src1.rows;
nppSafeCall( func((const npp_t*)src1.data, static_cast<int>(src1.step), (const npp_t*)src2.data, static_cast<int>(src2.step),
(npp_t*)dst.data, static_cast<int>(dst.step), sz) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template <int DEPTH> struct NppAbsDiffCFunc
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef npp_t scalar_t;
typedef NppStatus (*func_t)(const npp_t* pSrc1, int nSrc1Step, npp_t* pDst, int nDstStep, NppiSize oSizeROI, npp_t nConstant);
};
template <> struct NppAbsDiffCFunc<CV_16U>
{
typedef NppTypeTraits<CV_16U>::npp_t npp_t;
typedef Npp32u scalar_t;
#if (CUDA_VERSION <= 4020)
typedef NppStatus (*func_t)(const Npp16u* pSrc1, int nSrc1Step, Npp16u* pDst, int nDstStep, NppiSize oSizeROI, Npp32u nConstant);
#else
typedef NppStatus (*func_t)(const Npp16u * pSrc1, int nSrc1Step, Npp16u * pDst, int nDstStep, NppiSize oSizeROI, Npp16u nConstant);
#endif
};
template <int DEPTH, typename NppAbsDiffCFunc<DEPTH>::func_t func> struct NppAbsDiffC
{
typedef typename NppAbsDiffCFunc<DEPTH>::npp_t npp_t;
typedef typename NppAbsDiffCFunc<DEPTH>::scalar_t scalar_t;
static void call(const DevMem2Db src1, double val, DevMem2Db dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize sz;
sz.width = src1.cols;
sz.height = src1.rows;
nppSafeCall( func((const npp_t*)src1.data, static_cast<int>(src1.step),
(npp_t*)dst.data, static_cast<int>(dst.step), sz, static_cast<scalar_t>(val)) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
}
void cv::gpu::absdiff(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)
{
using namespace cv::gpu::device;
typedef void (*func_t)(const DevMem2Db src1, const DevMem2Db src2, DevMem2Db dst, cudaStream_t stream);
static const func_t funcs[] =
{
NppAbsDiff<CV_8U, nppiAbsDiff_8u_C1R>::call,
absdiff_gpu<signed char>,
NppAbsDiff<CV_16U, nppiAbsDiff_16u_C1R>::call,
absdiff_gpu<short>,
absdiff_gpu<int>,
NppAbsDiff<CV_32F, nppiAbsDiff_32f_C1R>::call,
absdiff_gpu<double>
};
CV_Assert(src1.depth() <= CV_64F);
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
if (src1.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src1.size(), src1.type());
funcs[src1.depth()](src1.reshape(1), src2.reshape(1), dst.reshape(1), StreamAccessor::getStream(stream));
}
void cv::gpu::absdiff(const GpuMat& src1, const Scalar& src2, GpuMat& dst, Stream& stream)
{
using namespace cv::gpu::device;
typedef void (*func_t)(const DevMem2Db src1, double val, DevMem2Db dst, cudaStream_t stream);
static const func_t funcs[] =
{
NppAbsDiffC<CV_8U, nppiAbsDiffC_8u_C1R>::call,
absdiff_gpu<signed char>,
NppAbsDiffC<CV_16U, nppiAbsDiffC_16u_C1R>::call,
absdiff_gpu<short>,
absdiff_gpu<int>,
NppAbsDiffC<CV_32F, nppiAbsDiffC_32f_C1R>::call,
absdiff_gpu<double>
};
CV_Assert(src1.depth() <= CV_64F);
CV_Assert(src1.channels() == 1);
if (src1.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src1.size(), src1.type());
funcs[src1.depth()](src1, src2.val[0], dst, StreamAccessor::getStream(stream));
}
//////////////////////////////////////////////////////////////////////////////
// abs
void cv::gpu::abs(const GpuMat& src, GpuMat& dst, Stream& s)
{
CV_Assert(src.depth() == CV_16S || src.depth() == CV_32F);
dst.create(src.size(), src.type());
cudaStream_t stream = StreamAccessor::getStream(s);
NppStreamHandler h(stream);
NppiSize oSizeROI;
oSizeROI.width = src.cols * src.channels();
oSizeROI.height = src.rows;
bool aligned = isAligned(src.data, 16) && isAligned(dst.data, 16);
if (src.depth() == CV_16S)
{
if (aligned && oSizeROI.width % 4 == 0)
{
oSizeROI.width /= 4;
nppSafeCall( nppiAbs_16s_C4R(src.ptr<Npp16s>(), static_cast<int>(src.step), dst.ptr<Npp16s>(), static_cast<int>(dst.step), oSizeROI) );
}
else
{
nppSafeCall( nppiAbs_16s_C1R(src.ptr<Npp16s>(), static_cast<int>(src.step), dst.ptr<Npp16s>(), static_cast<int>(dst.step), oSizeROI) );
}
}
else
{
if (aligned && oSizeROI.width % 4 == 0)
{
oSizeROI.width /= 4;
nppSafeCall( nppiAbs_32f_C4R(src.ptr<Npp32f>(), static_cast<int>(src.step), dst.ptr<Npp32f>(), static_cast<int>(dst.step), oSizeROI) );
}
else
{
nppSafeCall( nppiAbs_32f_C1R(src.ptr<Npp32f>(), static_cast<int>(src.step), dst.ptr<Npp32f>(), static_cast<int>(dst.step), oSizeROI) );
}
}
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
//////////////////////////////////////////////////////////////////////////////
// sqr
namespace
{
template <int DEPTH> struct NppSqrFunc
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef NppStatus (*func_t)(const npp_t* pSrc, int nSrcStep, npp_t* pDst, int nDstStep, NppiSize oSizeROI, int nScaleFactor);
};
template <> struct NppSqrFunc<CV_32F>
{
typedef NppTypeTraits<CV_32F>::npp_t npp_t;
typedef NppStatus (*func_t)(const npp_t* pSrc, int nSrcStep, npp_t* pDst, int nDstStep, NppiSize oSizeROI);
};
template <int DEPTH, typename NppSqrFunc<DEPTH>::func_t func, typename NppSqrFunc<DEPTH>::func_t func_c4> struct NppSqr
{
typedef typename NppSqrFunc<DEPTH>::npp_t npp_t;
static void call(const GpuMat& src, GpuMat& dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize oSizeROI;
oSizeROI.width = src.cols * src.channels();
oSizeROI.height = src.rows;
bool aligned = isAligned(src.data, 16) && isAligned(dst.data, 16);
if (aligned && oSizeROI.width % 4 == 0)
{
oSizeROI.width /= 4;
nppSafeCall( func_c4(src.ptr<npp_t>(), static_cast<int>(src.step), dst.ptr<npp_t>(), static_cast<int>(dst.step), oSizeROI, 0) );
}
else
{
nppSafeCall( func(src.ptr<npp_t>(), static_cast<int>(src.step), dst.ptr<npp_t>(), static_cast<int>(dst.step), oSizeROI, 0) );
}
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template <typename NppSqrFunc<CV_32F>::func_t func, typename NppSqrFunc<CV_32F>::func_t func_c4> struct NppSqr<CV_32F, func, func_c4>
{
typedef NppSqrFunc<CV_32F>::npp_t npp_t;
static void call(const GpuMat& src, GpuMat& dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize oSizeROI;
oSizeROI.width = src.cols * src.channels();
oSizeROI.height = src.rows;
bool aligned = isAligned(src.data, 16) && isAligned(dst.data, 16);
if (aligned && oSizeROI.width % 4 == 0)
{
oSizeROI.width /= 4;
nppSafeCall( func_c4(src.ptr<npp_t>(), static_cast<int>(src.step), dst.ptr<npp_t>(), static_cast<int>(dst.step), oSizeROI) );
}
else
{
nppSafeCall( func(src.ptr<npp_t>(), static_cast<int>(src.step), dst.ptr<npp_t>(), static_cast<int>(dst.step), oSizeROI) );
}
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
}
void cv::gpu::sqr(const GpuMat& src, GpuMat& dst, Stream& stream)
{
typedef void (*func_t)(const GpuMat& src, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[] =
{
NppSqr<CV_8U, nppiSqr_8u_C1RSfs, nppiSqr_8u_C4RSfs>::call,
0,
NppSqr<CV_16U, nppiSqr_16u_C1RSfs, nppiSqr_16u_C4RSfs>::call,
NppSqr<CV_16S, nppiSqr_16s_C1RSfs, nppiSqr_16s_C4RSfs>::call,
0,
NppSqr<CV_32F, nppiSqr_32f_C1R, nppiSqr_32f_C4R>::call
};
CV_Assert(src.depth() == CV_8U || src.depth() == CV_16U || src.depth() == CV_16S || src.depth() == CV_32F);
dst.create(src.size(), src.type());
funcs[src.depth()](src, dst, StreamAccessor::getStream(stream));
}
//////////////////////////////////////////////////////////////////////////////
// sqrt
namespace
{
template <int DEPTH> struct NppOneSourceFunc
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef NppStatus (*func_t)(const npp_t* pSrc, int nSrcStep, npp_t* pDst, int nDstStep, NppiSize oSizeROI, int nScaleFactor);
};
template <> struct NppOneSourceFunc<CV_32F>
{
typedef NppTypeTraits<CV_32F>::npp_t npp_t;
typedef NppStatus (*func_t)(const npp_t* pSrc, int nSrcStep, npp_t* pDst, int nDstStep, NppiSize oSizeROI);
};
template <int DEPTH, typename NppOneSourceFunc<DEPTH>::func_t func> struct NppOneSource
{
typedef typename NppOneSourceFunc<DEPTH>::npp_t npp_t;
static void call(const GpuMat& src, GpuMat& dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize oSizeROI;
oSizeROI.width = src.cols * src.channels();
oSizeROI.height = src.rows;
nppSafeCall( func(src.ptr<npp_t>(), static_cast<int>(src.step), dst.ptr<npp_t>(), static_cast<int>(dst.step), oSizeROI, 0) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template <typename NppOneSourceFunc<CV_32F>::func_t func> struct NppOneSource<CV_32F, func>
{
typedef NppOneSourceFunc<CV_32F>::npp_t npp_t;
static void call(const GpuMat& src, GpuMat& dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize oSizeROI;
oSizeROI.width = src.cols * src.channels();
oSizeROI.height = src.rows;
nppSafeCall( func(src.ptr<npp_t>(), static_cast<int>(src.step), dst.ptr<npp_t>(), static_cast<int>(dst.step), oSizeROI) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
}
void cv::gpu::sqrt(const GpuMat& src, GpuMat& dst, Stream& stream)
{
typedef void (*func_t)(const GpuMat& src, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[] =
{
NppOneSource<CV_8U, nppiSqrt_8u_C1RSfs>::call,
0,
NppOneSource<CV_16U, nppiSqrt_16u_C1RSfs>::call,
NppOneSource<CV_16S, nppiSqrt_16s_C1RSfs>::call,
0,
NppOneSource<CV_32F, nppiSqrt_32f_C1R>::call
};
CV_Assert(src.depth() == CV_8U || src.depth() == CV_16U || src.depth() == CV_16S || src.depth() == CV_32F);
dst.create(src.size(), src.type());
funcs[src.depth()](src, dst, StreamAccessor::getStream(stream));
}
////////////////////////////////////////////////////////////////////////
// log
void cv::gpu::log(const GpuMat& src, GpuMat& dst, Stream& stream)
{
typedef void (*func_t)(const GpuMat& src, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[] =
{
NppOneSource<CV_8U, nppiLn_8u_C1RSfs>::call,
0,
NppOneSource<CV_16U, nppiLn_16u_C1RSfs>::call,
NppOneSource<CV_16S, nppiLn_16s_C1RSfs>::call,
0,
NppOneSource<CV_32F, nppiLn_32f_C1R>::call
};
CV_Assert(src.depth() == CV_8U || src.depth() == CV_16U || src.depth() == CV_16S || src.depth() == CV_32F);
dst.create(src.size(), src.type());
funcs[src.depth()](src, dst, StreamAccessor::getStream(stream));
}
////////////////////////////////////////////////////////////////////////
// exp
void cv::gpu::exp(const GpuMat& src, GpuMat& dst, Stream& stream)
{
typedef void (*func_t)(const GpuMat& src, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[] =
{
NppOneSource<CV_8U, nppiExp_8u_C1RSfs>::call,
0,
NppOneSource<CV_16U, nppiExp_16u_C1RSfs>::call,
NppOneSource<CV_16S, nppiExp_16s_C1RSfs>::call,
0,
NppOneSource<CV_32F, nppiExp_32f_C1R>::call
};
CV_Assert(src.depth() == CV_8U || src.depth() == CV_16U || src.depth() == CV_16S || src.depth() == CV_32F);
dst.create(src.size(), src.type());
funcs[src.depth()](src, dst, StreamAccessor::getStream(stream));
}
//////////////////////////////////////////////////////////////////////////////
// Comparison of two matrixes
namespace cv { namespace gpu { namespace device
{
template <typename T> void compare_eq(DevMem2Db src1, DevMem2Db src2, DevMem2Db dst, cudaStream_t stream);
template <typename T> void compare_ne(DevMem2Db src1, DevMem2Db src2, DevMem2Db dst, cudaStream_t stream);
template <typename T> void compare_lt(DevMem2Db src1, DevMem2Db src2, DevMem2Db dst, cudaStream_t stream);
template <typename T> void compare_le(DevMem2Db src1, DevMem2Db src2, DevMem2Db dst, cudaStream_t stream);
template <typename T> void compare_eq(DevMem2Db src, int cn, double val[4], DevMem2Db dst, cudaStream_t stream);
template <typename T> void compare_ne(DevMem2Db src, int cn, double val[4], DevMem2Db dst, cudaStream_t stream);
template <typename T> void compare_lt(DevMem2Db src, int cn, double val[4], DevMem2Db dst, cudaStream_t stream);
template <typename T> void compare_le(DevMem2Db src, int cn, double val[4], DevMem2Db dst, cudaStream_t stream);
template <typename T> void compare_gt(DevMem2Db src, int cn, double val[4], DevMem2Db dst, cudaStream_t stream);
template <typename T> void compare_ge(DevMem2Db src, int cn, double val[4], DevMem2Db dst, cudaStream_t stream);
}}}
void cv::gpu::compare(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, int cmpop, Stream& stream)
{
using namespace cv::gpu::device;
typedef void (*func_t)(DevMem2Db src1, DevMem2Db src2, DevMem2Db dst, cudaStream_t stream);
static const func_t funcs[7][4] =
{
{compare_eq<unsigned char> , compare_ne<unsigned char> , compare_lt<unsigned char> , compare_le<unsigned char> },
{compare_eq<signed char> , compare_ne<signed char> , compare_lt<signed char> , compare_le<signed char> },
{compare_eq<unsigned short>, compare_ne<unsigned short>, compare_lt<unsigned short>, compare_le<unsigned short>},
{compare_eq<short> , compare_ne<short> , compare_lt<short> , compare_le<short> },
{compare_eq<int> , compare_ne<int> , compare_lt<int> , compare_le<int> },
{compare_eq<float> , compare_ne<float> , compare_lt<float> , compare_le<float> },
{compare_eq<double> , compare_ne<double> , compare_lt<double> , compare_le<double> }
};
CV_Assert(src1.depth() <= CV_64F);
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
CV_Assert(cmpop >= CMP_EQ && cmpop <= CMP_NE);
if (src1.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
static const int codes[] =
{
0, 2, 3, 2, 3, 1
};
const GpuMat* psrc1[] =
{
&src1, &src2, &src2, &src1, &src1, &src1
};
const GpuMat* psrc2[] =
{
&src2, &src1, &src1, &src2, &src2, &src2
};
dst.create(src1.size(), CV_MAKE_TYPE(CV_8U, src1.channels()));
funcs[src1.depth()][codes[cmpop]](psrc1[cmpop]->reshape(1), psrc2[cmpop]->reshape(1), dst.reshape(1), StreamAccessor::getStream(stream));
}
namespace
{
template <typename T>
void castScalar(Scalar& sc)
{
sc.val[0] = saturate_cast<T>(sc.val[0]);
sc.val[1] = saturate_cast<T>(sc.val[1]);
sc.val[2] = saturate_cast<T>(sc.val[2]);
sc.val[3] = saturate_cast<T>(sc.val[3]);
}
}
void cv::gpu::compare(const GpuMat& src, Scalar sc, GpuMat& dst, int cmpop, Stream& stream)
{
using namespace cv::gpu::device;
typedef void (*func_t)(DevMem2Db src, int cn, double val[4], DevMem2Db dst, cudaStream_t stream);
static const func_t funcs[7][6] =
{
{compare_eq<unsigned char> , compare_gt<unsigned char> , compare_ge<unsigned char> , compare_lt<unsigned char> , compare_le<unsigned char> , compare_ne<unsigned char> },
{compare_eq<signed char> , compare_gt<signed char> , compare_ge<signed char> , compare_lt<signed char> , compare_le<signed char> , compare_ne<signed char> },
{compare_eq<unsigned short>, compare_gt<unsigned short>, compare_ge<unsigned short>, compare_lt<unsigned short>, compare_le<unsigned short>, compare_ne<unsigned short>},
{compare_eq<short> , compare_gt<short> , compare_ge<short> , compare_lt<short> , compare_le<short> , compare_ne<short> },
{compare_eq<int> , compare_gt<int> , compare_ge<int> , compare_lt<int> , compare_le<int> , compare_ne<int> },
{compare_eq<float> , compare_gt<float> , compare_ge<float> , compare_lt<float> , compare_le<float> , compare_ne<float> },
{compare_eq<double> , compare_gt<double> , compare_ge<double> , compare_lt<double> , compare_le<double> , compare_ne<double> }
};
typedef void (*cast_func_t)(Scalar& sc);
static const cast_func_t cast_func[] =
{
castScalar<unsigned char>, castScalar<signed char>, castScalar<unsigned short>, castScalar<short>, castScalar<int>, castScalar<float>, castScalar<double>
};
CV_Assert(src.depth() <= CV_64F);
CV_Assert(src.channels() <= 4);
CV_Assert(cmpop >= CMP_EQ && cmpop <= CMP_NE);
if (src.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src.size(), CV_MAKE_TYPE(CV_8U, src.channels()));
cast_func[src.depth()](sc);
funcs[src.depth()][cmpop](src, src.channels(), sc.val, dst, StreamAccessor::getStream(stream));
}
//////////////////////////////////////////////////////////////////////////////
// Unary bitwise logical operations
namespace cv { namespace gpu { namespace device
{
void bitwiseNotCaller(int rows, int cols, size_t elem_size1, int cn, const PtrStepb src, PtrStepb dst, cudaStream_t stream);
template <typename T>
void bitwiseMaskNotCaller(int rows, int cols, int cn, const PtrStepb src, const PtrStepb mask, PtrStepb dst, cudaStream_t stream);
}}}
namespace
{
void bitwiseNotCaller(const GpuMat& src, GpuMat& dst, cudaStream_t stream)
{
dst.create(src.size(), src.type());
cv::gpu::device::bitwiseNotCaller(src.rows, src.cols, src.elemSize1(), dst.channels(), src, dst, stream);
}
void bitwiseNotCaller(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
{
using namespace cv::gpu::device;
typedef void (*func_t)(int, int, int, const PtrStepb, const PtrStepb, PtrStepb, cudaStream_t);
static func_t funcs[] =
{
bitwiseMaskNotCaller<unsigned char>, bitwiseMaskNotCaller<unsigned char>,
bitwiseMaskNotCaller<unsigned short>, bitwiseMaskNotCaller<unsigned short>,
bitwiseMaskNotCaller<unsigned int>, bitwiseMaskNotCaller<unsigned int>,
bitwiseMaskNotCaller<unsigned int>
};
CV_Assert(src.depth() <= CV_64F);
CV_Assert(mask.type() == CV_8U && mask.size() == src.size());
dst.create(src.size(), src.type());
const func_t func = funcs[src.depth()];
int cn = src.depth() != CV_64F ? src.channels() : src.channels() * (sizeof(double) / sizeof(unsigned int));
func(src.rows, src.cols, cn, src, mask, dst, stream);
}
}
void cv::gpu::bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask, Stream& stream)
{
if (mask.empty())
bitwiseNotCaller(src, dst, StreamAccessor::getStream(stream));
else
bitwiseNotCaller(src, dst, mask, StreamAccessor::getStream(stream));
}
//////////////////////////////////////////////////////////////////////////////
// Binary bitwise logical operations
namespace cv { namespace gpu { namespace device
{
void bitwiseOrCaller(int rows, int cols, size_t elem_size1, int cn, const PtrStepb src1, const PtrStepb src2, PtrStepb dst, cudaStream_t stream);
template <typename T>
void bitwiseMaskOrCaller(int rows, int cols, int cn, const PtrStepb src1, const PtrStepb src2, const PtrStepb mask, PtrStepb dst, cudaStream_t stream);
void bitwiseAndCaller(int rows, int cols, size_t elem_size1, int cn, const PtrStepb src1, const PtrStepb src2, PtrStepb dst, cudaStream_t stream);
template <typename T>
void bitwiseMaskAndCaller(int rows, int cols, int cn, const PtrStepb src1, const PtrStepb src2, const PtrStepb mask, PtrStepb dst, cudaStream_t stream);
void bitwiseXorCaller(int rows, int cols, size_t elem_size1, int cn, const PtrStepb src1, const PtrStepb src2, PtrStepb dst, cudaStream_t stream);
template <typename T>
void bitwiseMaskXorCaller(int rows, int cols, int cn, const PtrStepb src1, const PtrStepb src2, const PtrStepb mask, PtrStepb dst, cudaStream_t stream);
}}}
namespace
{
void bitwiseOrCaller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream)
{
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
dst.create(src1.size(), src1.type());
cv::gpu::device::bitwiseOrCaller(dst.rows, dst.cols, dst.elemSize1(), dst.channels(), src1, src2, dst, stream);
}
void bitwiseOrCaller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
{
using namespace cv::gpu::device;
typedef void (*func_t)(int, int, int, const PtrStepb, const PtrStepb, const PtrStepb, PtrStepb, cudaStream_t);
static func_t funcs[] =
{
bitwiseMaskOrCaller<unsigned char>, bitwiseMaskOrCaller<unsigned char>,
bitwiseMaskOrCaller<unsigned short>, bitwiseMaskOrCaller<unsigned short>,
bitwiseMaskOrCaller<unsigned int>, bitwiseMaskOrCaller<unsigned int>,
bitwiseMaskOrCaller<unsigned int>
};
CV_Assert(src1.depth() <= CV_64F);
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
CV_Assert(mask.type() == CV_8U && mask.size() == src1.size());
dst.create(src1.size(), src1.type());
const func_t func = funcs[src1.depth()];
int cn = dst.depth() != CV_64F ? dst.channels() : dst.channels() * (sizeof(double) / sizeof(unsigned int));
func(dst.rows, dst.cols, cn, src1, src2, mask, dst, stream);
}
void bitwiseAndCaller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream)
{
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
dst.create(src1.size(), src1.type());
cv::gpu::device::bitwiseAndCaller(dst.rows, dst.cols, dst.elemSize1(), dst.channels(), src1, src2, dst, stream);
}
void bitwiseAndCaller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
{
using namespace cv::gpu::device;
typedef void (*func_t)(int, int, int, const PtrStepb, const PtrStepb, const PtrStepb, PtrStepb, cudaStream_t);
static func_t funcs[] =
{
bitwiseMaskAndCaller<unsigned char>, bitwiseMaskAndCaller<unsigned char>,
bitwiseMaskAndCaller<unsigned short>, bitwiseMaskAndCaller<unsigned short>,
bitwiseMaskAndCaller<unsigned int>, bitwiseMaskAndCaller<unsigned int>,
bitwiseMaskAndCaller<unsigned int>
};
CV_Assert(src1.depth() <= CV_64F);
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
CV_Assert(mask.type() == CV_8U && mask.size() == src1.size());
dst.create(src1.size(), src1.type());
const func_t func = funcs[src1.depth()];
int cn = dst.depth() != CV_64F ? dst.channels() : dst.channels() * (sizeof(double) / sizeof(unsigned int));
func(dst.rows, dst.cols, cn, src1, src2, mask, dst, stream);
}
void bitwiseXorCaller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream)
{
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
dst.create(src1.size(), src1.type());
cv::gpu::device::bitwiseXorCaller(dst.rows, dst.cols, dst.elemSize1(), dst.channels(), src1, src2, dst, stream);
}
void bitwiseXorCaller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
{
using namespace cv::gpu::device;
typedef void (*func_t)(int, int, int, const PtrStepb, const PtrStepb, const PtrStepb, PtrStepb, cudaStream_t);
static func_t funcs[] =
{
bitwiseMaskXorCaller<unsigned char>, bitwiseMaskXorCaller<unsigned char>,
bitwiseMaskXorCaller<unsigned short>, bitwiseMaskXorCaller<unsigned short>,
bitwiseMaskXorCaller<unsigned int>, bitwiseMaskXorCaller<unsigned int>,
bitwiseMaskXorCaller<unsigned int>
};
CV_Assert(src1.depth() <= CV_64F);
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
CV_Assert(mask.type() == CV_8U && mask.size() == src1.size());
dst.create(src1.size(), src1.type());
const func_t func = funcs[src1.depth()];
int cn = dst.depth() != CV_64F ? dst.channels() : dst.channels() * (sizeof(double) / sizeof(unsigned int));
func(dst.rows, dst.cols, cn, src1, src2, mask, dst, stream);
}
}
void cv::gpu::bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, Stream& stream)
{
if (mask.empty())
bitwiseOrCaller(src1, src2, dst, StreamAccessor::getStream(stream));
else
bitwiseOrCaller(src1, src2, dst, mask, StreamAccessor::getStream(stream));
}
void cv::gpu::bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, Stream& stream)
{
if (mask.empty())
bitwiseAndCaller(src1, src2, dst, StreamAccessor::getStream(stream));
else
bitwiseAndCaller(src1, src2, dst, mask, StreamAccessor::getStream(stream));
}
void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, Stream& stream)
{
if (mask.empty())
bitwiseXorCaller(src1, src2, dst, StreamAccessor::getStream(stream));
else
bitwiseXorCaller(src1, src2, dst, mask, StreamAccessor::getStream(stream));
}
namespace
{
template <int DEPTH, int cn> struct NppBitwiseCFunc
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef NppStatus (*func_t)(const npp_t* pSrc1, int nSrc1Step, const npp_t* pConstants, npp_t* pDst, int nDstStep, NppiSize oSizeROI);
};
template <int DEPTH> struct NppBitwiseCFunc<DEPTH, 1>
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef NppStatus (*func_t)(const npp_t* pSrc1, int nSrc1Step, const npp_t pConstant, npp_t* pDst, int nDstStep, NppiSize oSizeROI);
};
template <int DEPTH, int cn, typename NppBitwiseCFunc<DEPTH, cn>::func_t func> struct NppBitwiseC
{
typedef typename NppBitwiseCFunc<DEPTH, cn>::npp_t npp_t;
static void call(const GpuMat& src, Scalar sc, GpuMat& dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize oSizeROI;
oSizeROI.width = src.cols;
oSizeROI.height = src.rows;
const npp_t pConstants[] = {static_cast<npp_t>(sc.val[0]), static_cast<npp_t>(sc.val[1]), static_cast<npp_t>(sc.val[2]), static_cast<npp_t>(sc.val[3])};
nppSafeCall( func(src.ptr<npp_t>(), static_cast<int>(src.step), pConstants, dst.ptr<npp_t>(), static_cast<int>(dst.step), oSizeROI) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template <int DEPTH, typename NppBitwiseCFunc<DEPTH, 1>::func_t func> struct NppBitwiseC<DEPTH, 1, func>
{
typedef typename NppBitwiseCFunc<DEPTH, 1>::npp_t npp_t;
static void call(const GpuMat& src, Scalar sc, GpuMat& dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize oSizeROI;
oSizeROI.width = src.cols;
oSizeROI.height = src.rows;
nppSafeCall( func(src.ptr<npp_t>(), static_cast<int>(src.step), static_cast<npp_t>(sc.val[0]), dst.ptr<npp_t>(), static_cast<int>(dst.step), oSizeROI) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
}
void cv::gpu::bitwise_or(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream)
{
typedef void (*func_t)(const GpuMat& src, Scalar sc, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[5][4] =
{
{NppBitwiseC<CV_8U , 1, nppiOrC_8u_C1R >::call, 0, NppBitwiseC<CV_8U , 3, nppiOrC_8u_C3R >::call, NppBitwiseC<CV_8U , 4, nppiOrC_8u_C4R >::call},
{0,0,0,0},
{NppBitwiseC<CV_16U, 1, nppiOrC_16u_C1R>::call, 0, NppBitwiseC<CV_16U, 3, nppiOrC_16u_C3R>::call, NppBitwiseC<CV_16U, 4, nppiOrC_16u_C4R>::call},
{0,0,0,0},
{NppBitwiseC<CV_32S, 1, nppiOrC_32s_C1R>::call, 0, NppBitwiseC<CV_32S, 3, nppiOrC_32s_C3R>::call, NppBitwiseC<CV_32S, 4, nppiOrC_32s_C4R>::call}
};
CV_Assert(src.depth() == CV_8U || src.depth() == CV_16U || src.depth() == CV_32S);
CV_Assert(src.channels() == 1 || src.channels() == 3 || src.channels() == 4);
dst.create(src.size(), src.type());
funcs[src.depth()][src.channels() - 1](src, sc, dst, StreamAccessor::getStream(stream));
}
void cv::gpu::bitwise_and(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream)
{
typedef void (*func_t)(const GpuMat& src, Scalar sc, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[5][4] =
{
{NppBitwiseC<CV_8U , 1, nppiAndC_8u_C1R >::call, 0, NppBitwiseC<CV_8U , 3, nppiAndC_8u_C3R >::call, NppBitwiseC<CV_8U , 4, nppiAndC_8u_C4R >::call},
{0,0,0,0},
{NppBitwiseC<CV_16U, 1, nppiAndC_16u_C1R>::call, 0, NppBitwiseC<CV_16U, 3, nppiAndC_16u_C3R>::call, NppBitwiseC<CV_16U, 4, nppiAndC_16u_C4R>::call},
{0,0,0,0},
{NppBitwiseC<CV_32S, 1, nppiAndC_32s_C1R>::call, 0, NppBitwiseC<CV_32S, 3, nppiAndC_32s_C3R>::call, NppBitwiseC<CV_32S, 4, nppiAndC_32s_C4R>::call}
};
CV_Assert(src.depth() == CV_8U || src.depth() == CV_16U || src.depth() == CV_32S);
CV_Assert(src.channels() == 1 || src.channels() == 3 || src.channels() == 4);
dst.create(src.size(), src.type());
funcs[src.depth()][src.channels() - 1](src, sc, dst, StreamAccessor::getStream(stream));
}
void cv::gpu::bitwise_xor(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream)
{
typedef void (*func_t)(const GpuMat& src, Scalar sc, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[5][4] =
{
{NppBitwiseC<CV_8U , 1, nppiXorC_8u_C1R >::call, 0, NppBitwiseC<CV_8U , 3, nppiXorC_8u_C3R >::call, NppBitwiseC<CV_8U , 4, nppiXorC_8u_C4R >::call},
{0,0,0,0},
{NppBitwiseC<CV_16U, 1, nppiXorC_16u_C1R>::call, 0, NppBitwiseC<CV_16U, 3, nppiXorC_16u_C3R>::call, NppBitwiseC<CV_16U, 4, nppiXorC_16u_C4R>::call},
{0,0,0,0},
{NppBitwiseC<CV_32S, 1, nppiXorC_32s_C1R>::call, 0, NppBitwiseC<CV_32S, 3, nppiXorC_32s_C3R>::call, NppBitwiseC<CV_32S, 4, nppiXorC_32s_C4R>::call}
};
CV_Assert(src.depth() == CV_8U || src.depth() == CV_16U || src.depth() == CV_32S);
CV_Assert(src.channels() == 1 || src.channels() == 3 || src.channels() == 4);
dst.create(src.size(), src.type());
funcs[src.depth()][src.channels() - 1](src, sc, dst, StreamAccessor::getStream(stream));
}
//////////////////////////////////////////////////////////////////////////////
// shift
namespace
{
template <int DEPTH, int cn> struct NppShiftFunc
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef NppStatus (*func_t)(const npp_t* pSrc1, int nSrc1Step, const Npp32u* pConstants, npp_t* pDst, int nDstStep, NppiSize oSizeROI);
};
template <int DEPTH> struct NppShiftFunc<DEPTH, 1>
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef NppStatus (*func_t)(const npp_t* pSrc1, int nSrc1Step, const Npp32u pConstants, npp_t* pDst, int nDstStep, NppiSize oSizeROI);
};
template <int DEPTH, int cn, typename NppShiftFunc<DEPTH, cn>::func_t func> struct NppShift
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
static void call(const GpuMat& src, Scalar_<Npp32u> sc, GpuMat& dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize oSizeROI;
oSizeROI.width = src.cols;
oSizeROI.height = src.rows;
nppSafeCall( func(src.ptr<npp_t>(), static_cast<int>(src.step), sc.val, dst.ptr<npp_t>(), static_cast<int>(dst.step), oSizeROI) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template <int DEPTH, typename NppShiftFunc<DEPTH, 1>::func_t func> struct NppShift<DEPTH, 1, func>
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
static void call(const GpuMat& src, Scalar_<Npp32u> sc, GpuMat& dst, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize oSizeROI;
oSizeROI.width = src.cols;
oSizeROI.height = src.rows;
nppSafeCall( func(src.ptr<npp_t>(), static_cast<int>(src.step), sc.val[0], dst.ptr<npp_t>(), static_cast<int>(dst.step), oSizeROI) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
}
void cv::gpu::rshift(const GpuMat& src, Scalar_<int> sc, GpuMat& dst, Stream& stream)
{
typedef void (*func_t)(const GpuMat& src, Scalar_<Npp32u> sc, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[5][4] =
{
{NppShift<CV_8U , 1, nppiRShiftC_8u_C1R >::call, 0, NppShift<CV_8U , 3, nppiRShiftC_8u_C3R >::call, NppShift<CV_8U , 4, nppiRShiftC_8u_C4R>::call },
{NppShift<CV_8S , 1, nppiRShiftC_8s_C1R >::call, 0, NppShift<CV_8S , 3, nppiRShiftC_8s_C3R >::call, NppShift<CV_8S , 4, nppiRShiftC_8s_C4R>::call },
{NppShift<CV_16U, 1, nppiRShiftC_16u_C1R>::call, 0, NppShift<CV_16U, 3, nppiRShiftC_16u_C3R>::call, NppShift<CV_16U, 4, nppiRShiftC_16u_C4R>::call},
{NppShift<CV_16S, 1, nppiRShiftC_16s_C1R>::call, 0, NppShift<CV_16S, 3, nppiRShiftC_16s_C3R>::call, NppShift<CV_16S, 4, nppiRShiftC_16s_C4R>::call},
{NppShift<CV_32S, 1, nppiRShiftC_32s_C1R>::call, 0, NppShift<CV_32S, 3, nppiRShiftC_32s_C3R>::call, NppShift<CV_32S, 4, nppiRShiftC_32s_C4R>::call},
};
CV_Assert(src.depth() < CV_32F);
CV_Assert(src.channels() == 1 || src.channels() == 3 || src.channels() == 4);
dst.create(src.size(), src.type());
funcs[src.depth()][src.channels() - 1](src, sc, dst, StreamAccessor::getStream(stream));
}
void cv::gpu::lshift(const GpuMat& src, Scalar_<int> sc, GpuMat& dst, Stream& stream)
{
typedef void (*func_t)(const GpuMat& src, Scalar_<Npp32u> sc, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[5][4] =
{
{NppShift<CV_8U , 1, nppiLShiftC_8u_C1R>::call , 0, NppShift<CV_8U , 3, nppiLShiftC_8u_C3R>::call , NppShift<CV_8U , 4, nppiLShiftC_8u_C4R>::call },
{0 , 0, 0 , 0 },
{NppShift<CV_16U, 1, nppiLShiftC_16u_C1R>::call, 0, NppShift<CV_16U, 3, nppiLShiftC_16u_C3R>::call, NppShift<CV_16U, 4, nppiLShiftC_16u_C4R>::call},
{0 , 0, 0 , 0 },
{NppShift<CV_32S, 1, nppiLShiftC_32s_C1R>::call, 0, NppShift<CV_32S, 3, nppiLShiftC_32s_C3R>::call, NppShift<CV_32S, 4, nppiLShiftC_32s_C4R>::call},
};
CV_Assert(src.depth() == CV_8U || src.depth() == CV_16U || src.depth() == CV_32S);
CV_Assert(src.channels() == 1 || src.channels() == 3 || src.channels() == 4);
dst.create(src.size(), src.type());
funcs[src.depth()][src.channels() - 1](src, sc, dst, StreamAccessor::getStream(stream));
}
//////////////////////////////////////////////////////////////////////////////
// Minimum and maximum operations
namespace cv { namespace gpu { namespace device
{
template <typename T> void min_gpu(const DevMem2Db src1, const DevMem2Db src2, DevMem2Db dst, cudaStream_t stream);
template <typename T> void max_gpu(const DevMem2Db src1, const DevMem2Db src2, DevMem2Db dst, cudaStream_t stream);
template <typename T> void min_gpu(const DevMem2Db src, T val, DevMem2Db dst, cudaStream_t stream);
template <typename T> void max_gpu(const DevMem2Db src, T val, DevMem2Db dst, cudaStream_t stream);
}}}
void cv::gpu::min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)
{
using namespace cv::gpu::device;
typedef void (*func_t)(const DevMem2Db src1, const DevMem2Db src2, DevMem2Db dst, cudaStream_t stream);
static const func_t funcs[] =
{
min_gpu<unsigned char>,
min_gpu<signed char>,
min_gpu<unsigned short>,
min_gpu<short>,
min_gpu<int>,
min_gpu<float>,
min_gpu<double>
};
CV_Assert(src1.depth() <= CV_64F);
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
if (src1.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src1.size(), src1.type());
funcs[src1.depth()](src1.reshape(1), src2.reshape(1), dst.reshape(1), StreamAccessor::getStream(stream));
}
void cv::gpu::max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)
{
using namespace cv::gpu::device;
typedef void (*func_t)(const DevMem2Db src1, const DevMem2Db src2, DevMem2Db dst, cudaStream_t stream);
static const func_t funcs[] =
{
max_gpu<unsigned char>,
max_gpu<signed char>,
max_gpu<unsigned short>,
max_gpu<short>,
max_gpu<int>,
max_gpu<float>,
max_gpu<double>
};
CV_Assert(src1.depth() <= CV_64F);
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
if (src1.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src1.size(), src1.type());
funcs[src1.depth()](src1.reshape(1), src2.reshape(1), dst.reshape(1), StreamAccessor::getStream(stream));
}
namespace
{
template <typename T> void minScalar(const DevMem2Db src, double val, DevMem2Db dst, cudaStream_t stream)
{
cv::gpu::device::min_gpu(src, saturate_cast<T>(val), dst, stream);
}
template <typename T> void maxScalar(const DevMem2Db src, double val, DevMem2Db dst, cudaStream_t stream)
{
cv::gpu::device::max_gpu(src, saturate_cast<T>(val), dst, stream);
}
}
void cv::gpu::min(const GpuMat& src, double val, GpuMat& dst, Stream& stream)
{
typedef void (*func_t)(const DevMem2Db src1, double src2, DevMem2Db dst, cudaStream_t stream);
static const func_t funcs[] =
{
minScalar<unsigned char>,
minScalar<signed char>,
minScalar<unsigned short>,
minScalar<short>,
minScalar<int>,
minScalar<float>,
minScalar<double>
};
CV_Assert(src.depth() <= CV_64F);
CV_Assert(src.channels() == 1);
if (src.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src.size(), src.type());
funcs[src.depth()](src, val, dst, StreamAccessor::getStream(stream));
}
void cv::gpu::max(const GpuMat& src, double val, GpuMat& dst, Stream& stream)
{
typedef void (*func_t)(const DevMem2Db src1, double src2, DevMem2Db dst, cudaStream_t stream);
static const func_t funcs[] =
{
maxScalar<unsigned char>,
maxScalar<signed char>,
maxScalar<unsigned short>,
maxScalar<short>,
maxScalar<int>,
maxScalar<float>,
maxScalar<double>
};
CV_Assert(src.depth() <= CV_64F);
CV_Assert(src.channels() == 1);
if (src.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src.size(), src.type());
funcs[src.depth()](src, val, dst, StreamAccessor::getStream(stream));
}
////////////////////////////////////////////////////////////////////////
// threshold
namespace cv { namespace gpu { namespace device
{
template <typename T>
void threshold_gpu(const DevMem2Db& src, const DevMem2Db& dst, T thresh, T maxVal, int type, cudaStream_t stream);
}}}
namespace
{
template <typename T> void threshold_caller(const GpuMat& src, GpuMat& dst, double thresh, double maxVal, int type, cudaStream_t stream)
{
cv::gpu::device::threshold_gpu<T>(src, dst, saturate_cast<T>(thresh), saturate_cast<T>(maxVal), type, stream);
}
}
double cv::gpu::threshold(const GpuMat& src, GpuMat& dst, double thresh, double maxVal, int type, Stream& s)
{
CV_Assert(src.channels() == 1 && src.depth() <= CV_64F);
CV_Assert(type <= THRESH_TOZERO_INV);
if (src.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src.size(), src.type());
cudaStream_t stream = StreamAccessor::getStream(s);
if (src.type() == CV_32FC1 && type == 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)(const GpuMat& src, GpuMat& dst, double thresh, double maxVal, int type, cudaStream_t stream);
static const func_t funcs[] =
{
threshold_caller<unsigned char>, threshold_caller<signed char>,
threshold_caller<unsigned short>, threshold_caller<short>,
threshold_caller<int>, threshold_caller<float>, threshold_caller<double>
};
if (src.depth() != CV_32F && src.depth() != CV_64F)
{
thresh = cvFloor(thresh);
maxVal = cvRound(maxVal);
}
funcs[src.depth()](src, dst, thresh, maxVal, type, stream);
}
return thresh;
}
////////////////////////////////////////////////////////////////////////
// pow
namespace cv { namespace gpu { namespace device
{
template<typename T> void pow_caller(DevMem2Db src, double power, DevMem2Db dst, cudaStream_t stream);
}}}
void cv::gpu::pow(const GpuMat& src, double power, GpuMat& dst, Stream& stream)
{
using namespace cv::gpu::device;
typedef void (*func_t)(DevMem2Db src, double power, DevMem2Db dst, cudaStream_t stream);
static const func_t funcs[] =
{
pow_caller<unsigned char>, pow_caller<signed char>,
pow_caller<unsigned short>, pow_caller<short>,
pow_caller<int>, pow_caller<float>, pow_caller<double>
};
CV_Assert(src.depth() <= CV_64F);
if (src.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src.size(), src.type());
funcs[src.depth()](src.reshape(1), power, dst.reshape(1), StreamAccessor::getStream(stream));
}
////////////////////////////////////////////////////////////////////////
// alphaComp
namespace
{
template <int DEPTH> struct NppAlphaCompFunc
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef NppStatus (*func_t)(const npp_t* pSrc1, int nSrc1Step, const npp_t* pSrc2, int nSrc2Step, npp_t* pDst, int nDstStep, NppiSize oSizeROI, NppiAlphaOp eAlphaOp);
};
template <int DEPTH, typename NppAlphaCompFunc<DEPTH>::func_t func> struct NppAlphaComp
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
static void call(const GpuMat& img1, const GpuMat& img2, GpuMat& dst, NppiAlphaOp eAlphaOp, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize oSizeROI;
oSizeROI.width = img1.cols;
oSizeROI.height = img2.rows;
nppSafeCall( func(img1.ptr<npp_t>(), static_cast<int>(img1.step), img2.ptr<npp_t>(), static_cast<int>(img2.step),
dst.ptr<npp_t>(), static_cast<int>(dst.step), oSizeROI, eAlphaOp) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
}
void cv::gpu::alphaComp(const GpuMat& img1, const GpuMat& img2, GpuMat& dst, int alpha_op, Stream& stream)
{
static const NppiAlphaOp npp_alpha_ops[] = {
NPPI_OP_ALPHA_OVER,
NPPI_OP_ALPHA_IN,
NPPI_OP_ALPHA_OUT,
NPPI_OP_ALPHA_ATOP,
NPPI_OP_ALPHA_XOR,
NPPI_OP_ALPHA_PLUS,
NPPI_OP_ALPHA_OVER_PREMUL,
NPPI_OP_ALPHA_IN_PREMUL,
NPPI_OP_ALPHA_OUT_PREMUL,
NPPI_OP_ALPHA_ATOP_PREMUL,
NPPI_OP_ALPHA_XOR_PREMUL,
NPPI_OP_ALPHA_PLUS_PREMUL,
NPPI_OP_ALPHA_PREMUL
};
typedef void (*func_t)(const GpuMat& img1, const GpuMat& img2, GpuMat& dst, NppiAlphaOp eAlphaOp, cudaStream_t stream);
static const func_t funcs[] =
{
NppAlphaComp<CV_8U, nppiAlphaComp_8u_AC4R>::call,
0,
NppAlphaComp<CV_16U, nppiAlphaComp_16u_AC4R>::call,
0,
NppAlphaComp<CV_32S, nppiAlphaComp_32s_AC4R>::call,
NppAlphaComp<CV_32F, nppiAlphaComp_32f_AC4R>::call
};
CV_Assert(img1.type() == CV_8UC4 || img1.type() == CV_16UC4 || img1.type() == CV_32SC4 || img1.type() == CV_32FC4);
CV_Assert(img1.size() == img2.size() && img1.type() == img2.type());
dst.create(img1.size(), img1.type());
const func_t func = funcs[img1.depth()];
func(img1, img2, dst, npp_alpha_ops[alpha_op], StreamAccessor::getStream(stream));
}
////////////////////////////////////////////////////////////////////////
// addWeighted
namespace cv { namespace gpu { namespace device
{
template <typename T1, typename T2, typename D>
void addWeighted_gpu(const DevMem2Db& src1, double alpha, const DevMem2Db& src2, double beta, double gamma, const DevMem2Db& dst, cudaStream_t stream);
}}}
void cv::gpu::addWeighted(const GpuMat& src1, double alpha, const GpuMat& src2, double beta, double gamma, GpuMat& dst, int dtype, Stream& stream)
{
using namespace cv::gpu::device;
typedef void (*func_t)(const DevMem2Db& src1, double alpha, const DevMem2Db& src2, double beta, double gamma, const DevMem2Db& dst, cudaStream_t stream);
static const func_t funcs[7][7][7] =
{
{
{
addWeighted_gpu<unsigned char, unsigned char, unsigned char >,
addWeighted_gpu<unsigned char, unsigned char, signed char >,
addWeighted_gpu<unsigned char, unsigned char, unsigned short>,
addWeighted_gpu<unsigned char, unsigned char, short >,
addWeighted_gpu<unsigned char, unsigned char, int >,
addWeighted_gpu<unsigned char, unsigned char, float >,
addWeighted_gpu<unsigned char, unsigned char, double>
},
{
addWeighted_gpu<unsigned char, signed char, unsigned char >,
addWeighted_gpu<unsigned char, signed char, signed char >,
addWeighted_gpu<unsigned char, signed char, unsigned short>,
addWeighted_gpu<unsigned char, signed char, short >,
addWeighted_gpu<unsigned char, signed char, int >,
addWeighted_gpu<unsigned char, signed char, float >,
addWeighted_gpu<unsigned char, signed char, double>
},
{
addWeighted_gpu<unsigned char, unsigned short, unsigned char >,
addWeighted_gpu<unsigned char, unsigned short, signed char >,
addWeighted_gpu<unsigned char, unsigned short, unsigned short>,
addWeighted_gpu<unsigned char, unsigned short, short >,
addWeighted_gpu<unsigned char, unsigned short, int >,
addWeighted_gpu<unsigned char, unsigned short, float >,
addWeighted_gpu<unsigned char, unsigned short, double>
},
{
addWeighted_gpu<unsigned char, short, unsigned char >,
addWeighted_gpu<unsigned char, short, signed char >,
addWeighted_gpu<unsigned char, short, unsigned short>,
addWeighted_gpu<unsigned char, short, short >,
addWeighted_gpu<unsigned char, short, int >,
addWeighted_gpu<unsigned char, short, float >,
addWeighted_gpu<unsigned char, short, double>
},
{
addWeighted_gpu<unsigned char, int, unsigned char >,
addWeighted_gpu<unsigned char, int, signed char >,
addWeighted_gpu<unsigned char, int, unsigned short>,
addWeighted_gpu<unsigned char, int, short >,
addWeighted_gpu<unsigned char, int, int >,
addWeighted_gpu<unsigned char, int, float >,
addWeighted_gpu<unsigned char, int, double>
},
{
addWeighted_gpu<unsigned char, float, unsigned char >,
addWeighted_gpu<unsigned char, float, signed char >,
addWeighted_gpu<unsigned char, float, unsigned short>,
addWeighted_gpu<unsigned char, float, short >,
addWeighted_gpu<unsigned char, float, int >,
addWeighted_gpu<unsigned char, float, float >,
addWeighted_gpu<unsigned char, float, double>
},
{
addWeighted_gpu<unsigned char, double, unsigned char >,
addWeighted_gpu<unsigned char, double, signed char >,
addWeighted_gpu<unsigned char, double, unsigned short>,
addWeighted_gpu<unsigned char, double, short >,
addWeighted_gpu<unsigned char, double, int >,
addWeighted_gpu<unsigned char, double, float >,
addWeighted_gpu<unsigned char, double, double>
}
},
{
{
0/*addWeighted_gpu<signed char, unsigned char, unsigned char >*/,
0/*addWeighted_gpu<signed char, unsigned char, signed char >*/,
0/*addWeighted_gpu<signed char, unsigned char, unsigned short>*/,
0/*addWeighted_gpu<signed char, unsigned char, short >*/,
0/*addWeighted_gpu<signed char, unsigned char, int >*/,
0/*addWeighted_gpu<signed char, unsigned char, float >*/,
0/*addWeighted_gpu<signed char, unsigned char, double>*/
},
{
addWeighted_gpu<signed char, signed char, unsigned char >,
addWeighted_gpu<signed char, signed char, signed char >,
addWeighted_gpu<signed char, signed char, unsigned short>,
addWeighted_gpu<signed char, signed char, short >,
addWeighted_gpu<signed char, signed char, int >,
addWeighted_gpu<signed char, signed char, float >,
addWeighted_gpu<signed char, signed char, double>
},
{
addWeighted_gpu<signed char, unsigned short, unsigned char >,
addWeighted_gpu<signed char, unsigned short, signed char >,
addWeighted_gpu<signed char, unsigned short, unsigned short>,
addWeighted_gpu<signed char, unsigned short, short >,
addWeighted_gpu<signed char, unsigned short, int >,
addWeighted_gpu<signed char, unsigned short, float >,
addWeighted_gpu<signed char, unsigned short, double>
},
{
addWeighted_gpu<signed char, short, unsigned char >,
addWeighted_gpu<signed char, short, signed char >,
addWeighted_gpu<signed char, short, unsigned short>,
addWeighted_gpu<signed char, short, short >,
addWeighted_gpu<signed char, short, int >,
addWeighted_gpu<signed char, short, float >,
addWeighted_gpu<signed char, short, double>
},
{
addWeighted_gpu<signed char, int, unsigned char >,
addWeighted_gpu<signed char, int, signed char >,
addWeighted_gpu<signed char, int, unsigned short>,
addWeighted_gpu<signed char, int, short >,
addWeighted_gpu<signed char, int, int >,
addWeighted_gpu<signed char, int, float >,
addWeighted_gpu<signed char, int, double>
},
{
addWeighted_gpu<signed char, float, unsigned char >,
addWeighted_gpu<signed char, float, signed char >,
addWeighted_gpu<signed char, float, unsigned short>,
addWeighted_gpu<signed char, float, short >,
addWeighted_gpu<signed char, float, int >,
addWeighted_gpu<signed char, float, float >,
addWeighted_gpu<signed char, float, double>
},
{
addWeighted_gpu<signed char, double, unsigned char >,
addWeighted_gpu<signed char, double, signed char >,
addWeighted_gpu<signed char, double, unsigned short>,
addWeighted_gpu<signed char, double, short >,
addWeighted_gpu<signed char, double, int >,
addWeighted_gpu<signed char, double, float >,
addWeighted_gpu<signed char, double, double>
}
},
{
{
0/*addWeighted_gpu<unsigned short, unsigned char, unsigned char >*/,
0/*addWeighted_gpu<unsigned short, unsigned char, signed char >*/,
0/*addWeighted_gpu<unsigned short, unsigned char, unsigned short>*/,
0/*addWeighted_gpu<unsigned short, unsigned char, short >*/,
0/*addWeighted_gpu<unsigned short, unsigned char, int >*/,
0/*addWeighted_gpu<unsigned short, unsigned char, float >*/,
0/*addWeighted_gpu<unsigned short, unsigned char, double>*/
},
{
0/*addWeighted_gpu<unsigned short, signed char, unsigned char >*/,
0/*addWeighted_gpu<unsigned short, signed char, signed char >*/,
0/*addWeighted_gpu<unsigned short, signed char, unsigned short>*/,
0/*addWeighted_gpu<unsigned short, signed char, short >*/,
0/*addWeighted_gpu<unsigned short, signed char, int >*/,
0/*addWeighted_gpu<unsigned short, signed char, float >*/,
0/*addWeighted_gpu<unsigned short, signed char, double>*/
},
{
addWeighted_gpu<unsigned short, unsigned short, unsigned char >,
addWeighted_gpu<unsigned short, unsigned short, signed char >,
addWeighted_gpu<unsigned short, unsigned short, unsigned short>,
addWeighted_gpu<unsigned short, unsigned short, short >,
addWeighted_gpu<unsigned short, unsigned short, int >,
addWeighted_gpu<unsigned short, unsigned short, float >,
addWeighted_gpu<unsigned short, unsigned short, double>
},
{
addWeighted_gpu<unsigned short, short, unsigned char >,
addWeighted_gpu<unsigned short, short, signed char >,
addWeighted_gpu<unsigned short, short, unsigned short>,
addWeighted_gpu<unsigned short, short, short >,
addWeighted_gpu<unsigned short, short, int >,
addWeighted_gpu<unsigned short, short, float >,
addWeighted_gpu<unsigned short, short, double>
},
{
addWeighted_gpu<unsigned short, int, unsigned char >,
addWeighted_gpu<unsigned short, int, signed char >,
addWeighted_gpu<unsigned short, int, unsigned short>,
addWeighted_gpu<unsigned short, int, short >,
addWeighted_gpu<unsigned short, int, int >,
addWeighted_gpu<unsigned short, int, float >,
addWeighted_gpu<unsigned short, int, double>
},
{
addWeighted_gpu<unsigned short, float, unsigned char >,
addWeighted_gpu<unsigned short, float, signed char >,
addWeighted_gpu<unsigned short, float, unsigned short>,
addWeighted_gpu<unsigned short, float, short >,
addWeighted_gpu<unsigned short, float, int >,
addWeighted_gpu<unsigned short, float, float >,
addWeighted_gpu<unsigned short, float, double>
},
{
addWeighted_gpu<unsigned short, double, unsigned char >,
addWeighted_gpu<unsigned short, double, signed char >,
addWeighted_gpu<unsigned short, double, unsigned short>,
addWeighted_gpu<unsigned short, double, short >,
addWeighted_gpu<unsigned short, double, int >,
addWeighted_gpu<unsigned short, double, float >,
addWeighted_gpu<unsigned short, double, double>
}
},
{
{
0/*addWeighted_gpu<short, unsigned char, unsigned char >*/,
0/*addWeighted_gpu<short, unsigned char, signed char >*/,
0/*addWeighted_gpu<short, unsigned char, unsigned short>*/,
0/*addWeighted_gpu<short, unsigned char, short >*/,
0/*addWeighted_gpu<short, unsigned char, int >*/,
0/*addWeighted_gpu<short, unsigned char, float >*/,
0/*addWeighted_gpu<short, unsigned char, double>*/
},
{
0/*addWeighted_gpu<short, signed char, unsigned char >*/,
0/*addWeighted_gpu<short, signed char, signed char >*/,
0/*addWeighted_gpu<short, signed char, unsigned short>*/,
0/*addWeighted_gpu<short, signed char, short >*/,
0/*addWeighted_gpu<short, signed char, int >*/,
0/*addWeighted_gpu<short, signed char, float >*/,
0/*addWeighted_gpu<short, signed char, double>*/
},
{
0/*addWeighted_gpu<short, unsigned short, unsigned char >*/,
0/*addWeighted_gpu<short, unsigned short, signed char >*/,
0/*addWeighted_gpu<short, unsigned short, unsigned short>*/,
0/*addWeighted_gpu<short, unsigned short, short >*/,
0/*addWeighted_gpu<short, unsigned short, int >*/,
0/*addWeighted_gpu<short, unsigned short, float >*/,
0/*addWeighted_gpu<short, unsigned short, double>*/
},
{
addWeighted_gpu<short, short, unsigned char >,
addWeighted_gpu<short, short, signed char >,
addWeighted_gpu<short, short, unsigned short>,
addWeighted_gpu<short, short, short >,
addWeighted_gpu<short, short, int >,
addWeighted_gpu<short, short, float >,
addWeighted_gpu<short, short, double>
},
{
addWeighted_gpu<short, int, unsigned char >,
addWeighted_gpu<short, int, signed char >,
addWeighted_gpu<short, int, unsigned short>,
addWeighted_gpu<short, int, short >,
addWeighted_gpu<short, int, int >,
addWeighted_gpu<short, int, float >,
addWeighted_gpu<short, int, double>
},
{
addWeighted_gpu<short, float, unsigned char >,
addWeighted_gpu<short, float, signed char >,
addWeighted_gpu<short, float, unsigned short>,
addWeighted_gpu<short, float, short >,
addWeighted_gpu<short, float, int >,
addWeighted_gpu<short, float, float >,
addWeighted_gpu<short, float, double>
},
{
addWeighted_gpu<short, double, unsigned char >,
addWeighted_gpu<short, double, signed char >,
addWeighted_gpu<short, double, unsigned short>,
addWeighted_gpu<short, double, short >,
addWeighted_gpu<short, double, int >,
addWeighted_gpu<short, double, float >,
addWeighted_gpu<short, double, double>
}
},
{
{
0/*addWeighted_gpu<int, unsigned char, unsigned char >*/,
0/*addWeighted_gpu<int, unsigned char, signed char >*/,
0/*addWeighted_gpu<int, unsigned char, unsigned short>*/,
0/*addWeighted_gpu<int, unsigned char, short >*/,
0/*addWeighted_gpu<int, unsigned char, int >*/,
0/*addWeighted_gpu<int, unsigned char, float >*/,
0/*addWeighted_gpu<int, unsigned char, double>*/
},
{
0/*addWeighted_gpu<int, signed char, unsigned char >*/,
0/*addWeighted_gpu<int, signed char, signed char >*/,
0/*addWeighted_gpu<int, signed char, unsigned short>*/,
0/*addWeighted_gpu<int, signed char, short >*/,
0/*addWeighted_gpu<int, signed char, int >*/,
0/*addWeighted_gpu<int, signed char, float >*/,
0/*addWeighted_gpu<int, signed char, double>*/
},
{
0/*addWeighted_gpu<int, unsigned short, unsigned char >*/,
0/*addWeighted_gpu<int, unsigned short, signed char >*/,
0/*addWeighted_gpu<int, unsigned short, unsigned short>*/,
0/*addWeighted_gpu<int, unsigned short, short >*/,
0/*addWeighted_gpu<int, unsigned short, int >*/,
0/*addWeighted_gpu<int, unsigned short, float >*/,
0/*addWeighted_gpu<int, unsigned short, double>*/
},
{
0/*addWeighted_gpu<int, short, unsigned char >*/,
0/*addWeighted_gpu<int, short, signed char >*/,
0/*addWeighted_gpu<int, short, unsigned short>*/,
0/*addWeighted_gpu<int, short, short >*/,
0/*addWeighted_gpu<int, short, int >*/,
0/*addWeighted_gpu<int, short, float >*/,
0/*addWeighted_gpu<int, short, double>*/
},
{
addWeighted_gpu<int, int, unsigned char >,
addWeighted_gpu<int, int, signed char >,
addWeighted_gpu<int, int, unsigned short>,
addWeighted_gpu<int, int, short >,
addWeighted_gpu<int, int, int >,
addWeighted_gpu<int, int, float >,
addWeighted_gpu<int, int, double>
},
{
addWeighted_gpu<int, float, unsigned char >,
addWeighted_gpu<int, float, signed char >,
addWeighted_gpu<int, float, unsigned short>,
addWeighted_gpu<int, float, short >,
addWeighted_gpu<int, float, int >,
addWeighted_gpu<int, float, float >,
addWeighted_gpu<int, float, double>
},
{
addWeighted_gpu<int, double, unsigned char >,
addWeighted_gpu<int, double, signed char >,
addWeighted_gpu<int, double, unsigned short>,
addWeighted_gpu<int, double, short >,
addWeighted_gpu<int, double, int >,
addWeighted_gpu<int, double, float >,
addWeighted_gpu<int, double, double>
}
},
{
{
0/*addWeighted_gpu<float, unsigned char, unsigned char >*/,
0/*addWeighted_gpu<float, unsigned char, signed char >*/,
0/*addWeighted_gpu<float, unsigned char, unsigned short>*/,
0/*addWeighted_gpu<float, unsigned char, short >*/,
0/*addWeighted_gpu<float, unsigned char, int >*/,
0/*addWeighted_gpu<float, unsigned char, float >*/,
0/*addWeighted_gpu<float, unsigned char, double>*/
},
{
0/*addWeighted_gpu<float, signed char, unsigned char >*/,
0/*addWeighted_gpu<float, signed char, signed char >*/,
0/*addWeighted_gpu<float, signed char, unsigned short>*/,
0/*addWeighted_gpu<float, signed char, short >*/,
0/*addWeighted_gpu<float, signed char, int >*/,
0/*addWeighted_gpu<float, signed char, float >*/,
0/*addWeighted_gpu<float, signed char, double>*/
},
{
0/*addWeighted_gpu<float, unsigned short, unsigned char >*/,
0/*addWeighted_gpu<float, unsigned short, signed char >*/,
0/*addWeighted_gpu<float, unsigned short, unsigned short>*/,
0/*addWeighted_gpu<float, unsigned short, short >*/,
0/*addWeighted_gpu<float, unsigned short, int >*/,
0/*addWeighted_gpu<float, unsigned short, float >*/,
0/*addWeighted_gpu<float, unsigned short, double>*/
},
{
0/*addWeighted_gpu<float, short, unsigned char >*/,
0/*addWeighted_gpu<float, short, signed char >*/,
0/*addWeighted_gpu<float, short, unsigned short>*/,
0/*addWeighted_gpu<float, short, short >*/,
0/*addWeighted_gpu<float, short, int >*/,
0/*addWeighted_gpu<float, short, float >*/,
0/*addWeighted_gpu<float, short, double>*/
},
{
0/*addWeighted_gpu<float, int, unsigned char >*/,
0/*addWeighted_gpu<float, int, signed char >*/,
0/*addWeighted_gpu<float, int, unsigned short>*/,
0/*addWeighted_gpu<float, int, short >*/,
0/*addWeighted_gpu<float, int, int >*/,
0/*addWeighted_gpu<float, int, float >*/,
0/*addWeighted_gpu<float, int, double>*/
},
{
addWeighted_gpu<float, float, unsigned char >,
addWeighted_gpu<float, float, signed char >,
addWeighted_gpu<float, float, unsigned short>,
addWeighted_gpu<float, float, short >,
addWeighted_gpu<float, float, int >,
addWeighted_gpu<float, float, float >,
addWeighted_gpu<float, float, double>
},
{
addWeighted_gpu<float, double, unsigned char >,
addWeighted_gpu<float, double, signed char >,
addWeighted_gpu<float, double, unsigned short>,
addWeighted_gpu<float, double, short >,
addWeighted_gpu<float, double, int >,
addWeighted_gpu<float, double, float >,
addWeighted_gpu<float, double, double>
}
},
{
{
0/*addWeighted_gpu<double, unsigned char, unsigned char >*/,
0/*addWeighted_gpu<double, unsigned char, signed char >*/,
0/*addWeighted_gpu<double, unsigned char, unsigned short>*/,
0/*addWeighted_gpu<double, unsigned char, short >*/,
0/*addWeighted_gpu<double, unsigned char, int >*/,
0/*addWeighted_gpu<double, unsigned char, float >*/,
0/*addWeighted_gpu<double, unsigned char, double>*/
},
{
0/*addWeighted_gpu<double, signed char, unsigned char >*/,
0/*addWeighted_gpu<double, signed char, signed char >*/,
0/*addWeighted_gpu<double, signed char, unsigned short>*/,
0/*addWeighted_gpu<double, signed char, short >*/,
0/*addWeighted_gpu<double, signed char, int >*/,
0/*addWeighted_gpu<double, signed char, float >*/,
0/*addWeighted_gpu<double, signed char, double>*/
},
{
0/*addWeighted_gpu<double, unsigned short, unsigned char >*/,
0/*addWeighted_gpu<double, unsigned short, signed char >*/,
0/*addWeighted_gpu<double, unsigned short, unsigned short>*/,
0/*addWeighted_gpu<double, unsigned short, short >*/,
0/*addWeighted_gpu<double, unsigned short, int >*/,
0/*addWeighted_gpu<double, unsigned short, float >*/,
0/*addWeighted_gpu<double, unsigned short, double>*/
},
{
0/*addWeighted_gpu<double, short, unsigned char >*/,
0/*addWeighted_gpu<double, short, signed char >*/,
0/*addWeighted_gpu<double, short, unsigned short>*/,
0/*addWeighted_gpu<double, short, short >*/,
0/*addWeighted_gpu<double, short, int >*/,
0/*addWeighted_gpu<double, short, float >*/,
0/*addWeighted_gpu<double, short, double>*/
},
{
0/*addWeighted_gpu<double, int, unsigned char >*/,
0/*addWeighted_gpu<double, int, signed char >*/,
0/*addWeighted_gpu<double, int, unsigned short>*/,
0/*addWeighted_gpu<double, int, short >*/,
0/*addWeighted_gpu<double, int, int >*/,
0/*addWeighted_gpu<double, int, float >*/,
0/*addWeighted_gpu<double, int, double>*/
},
{
0/*addWeighted_gpu<double, float, unsigned char >*/,
0/*addWeighted_gpu<double, float, signed char >*/,
0/*addWeighted_gpu<double, float, unsigned short>*/,
0/*addWeighted_gpu<double, float, short >*/,
0/*addWeighted_gpu<double, float, int >*/,
0/*addWeighted_gpu<double, float, float >*/,
0/*addWeighted_gpu<double, float, double>*/
},
{
addWeighted_gpu<double, double, unsigned char >,
addWeighted_gpu<double, double, signed char >,
addWeighted_gpu<double, double, unsigned short>,
addWeighted_gpu<double, double, short >,
addWeighted_gpu<double, double, int >,
addWeighted_gpu<double, double, float >,
addWeighted_gpu<double, double, double>
}
}
};
CV_Assert(src1.size() == src2.size());
CV_Assert(src1.type() == src2.type() || (dtype >= 0 && src1.channels() == src2.channels()));
dtype = dtype >= 0 ? CV_MAKETYPE(dtype, src1.channels()) : src1.type();
CV_Assert(src1.depth() <= CV_64F && src2.depth() <= CV_64F && CV_MAT_DEPTH(dtype) <= CV_64F);
if (src1.depth() == CV_64F || src2.depth() == CV_64F || CV_MAT_DEPTH(dtype) == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src1.size(), dtype);
const GpuMat* psrc1 = &src1;
const GpuMat* psrc2 = &src2;
if (src1.depth() > src2.depth())
{
std::swap(psrc1, psrc2);
std::swap(alpha, beta);
}
const func_t func = funcs[psrc1->depth()][psrc2->depth()][dst.depth()];
if (!func)
CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of source and destination types");
func(psrc1->reshape(1), alpha, psrc2->reshape(1), beta, gamma, dst.reshape(1), StreamAccessor::getStream(stream));
}
#endif