/*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. // // This software is provided by the copyright holders and contributors "as is" and // any express or bpied warranties, including, but not limited to, the bpied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //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::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 (scale == 1 && 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), 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, const DevMem2Db& dst, cudaStream_t stream); template <typename T> void absdiff_gpu(const DevMem2Db& src1, double val, const DevMem2Db& dst, cudaStream_t stream); }}} void cv::gpu::absdiff(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& s) { using namespace ::cv::gpu::device; typedef void (*func_t)(const DevMem2Db& src1, const DevMem2Db& src2, const DevMem2Db& dst, cudaStream_t stream); static const func_t funcs[] = { absdiff_gpu<unsigned char>, absdiff_gpu<signed char>, absdiff_gpu<unsigned short>, absdiff_gpu<short>, absdiff_gpu<int>, absdiff_gpu<float>, absdiff_gpu<double> }; CV_Assert(src1.size() == src2.size() && src1.type() == src2.type()); dst.create( src1.size(), src1.type() ); cudaStream_t stream = StreamAccessor::getStream(s); NppiSize sz; sz.width = src1.cols * src1.channels(); sz.height = src1.rows; if (src1.depth() == CV_8U) { NppStreamHandler h(stream); nppSafeCall( nppiAbsDiff_8u_C1R(src1.ptr<Npp8u>(), static_cast<int>(src1.step), src2.ptr<Npp8u>(), static_cast<int>(src2.step), dst.ptr<Npp8u>(), static_cast<int>(dst.step), sz) ); if (stream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } else if (src1.depth() == CV_16U) { NppStreamHandler h(stream); nppSafeCall( nppiAbsDiff_16u_C1R(src1.ptr<Npp16u>(), static_cast<int>(src1.step), src2.ptr<Npp16u>(), static_cast<int>(src2.step), dst.ptr<Npp16u>(), static_cast<int>(dst.step), sz) ); if (stream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } else if (src1.depth() == CV_32F) { NppStreamHandler h(stream); nppSafeCall( nppiAbsDiff_32f_C1R(src1.ptr<Npp32f>(), static_cast<int>(src1.step), src2.ptr<Npp32f>(), static_cast<int>(src2.step), dst.ptr<Npp32f>(), static_cast<int>(dst.step), sz) ); if (stream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } else { const func_t func = funcs[src1.depth()]; CV_Assert(func != 0); func(src1.reshape(1), src2.reshape(1), dst.reshape(1), stream); } } namespace { template <int DEPTH> struct NppAbsDiffCFunc { typedef typename NppTypeTraits<DEPTH>::npp_t npp_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 NppStatus (*func_t)(const Npp16u* pSrc1, int nSrc1Step, Npp16u* pDst, int nDstStep, NppiSize oSizeROI, Npp32u nConstant); }; template <int DEPTH, typename NppAbsDiffCFunc<DEPTH>::func_t func> struct NppAbsDiffC { typedef typename NppTypeTraits<DEPTH>::npp_t npp_t; static void call(const DevMem2Db& src1, double val, const 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<npp_t>(val)) ); if (stream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } }; } void cv::gpu::absdiff(const GpuMat& src1, const Scalar& src2, GpuMat& dst, Stream& s) { using namespace cv::gpu::device; typedef void (*func_t)(const DevMem2Db& src1, double val, const 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.channels() == 1); dst.create(src1.size(), src1.type()); cudaStream_t stream = StreamAccessor::getStream(s); funcs[src1.depth()](src1, src2.val[0], dst, 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(const DevMem2Db& src1, const DevMem2Db& src2, const DevMem2Db& dst, cudaStream_t stream); template <typename T> void compare_ne(const DevMem2Db& src1, const DevMem2Db& src2, const DevMem2Db& dst, cudaStream_t stream); template <typename T> void compare_lt(const DevMem2Db& src1, const DevMem2Db& src2, const DevMem2Db& dst, cudaStream_t stream); template <typename T> void compare_le(const DevMem2Db& src1, const DevMem2Db& src2, const 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)(const DevMem2Db& src1, const DevMem2Db& src2, const 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.size() == src2.size() && src1.type() == src2.type()); CV_Assert(cmpop >= CMP_EQ && cmpop <= CMP_NE); 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)); } ////////////////////////////////////////////////////////////////////////////// // 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 (*Caller)(int, int, int, const PtrStepb, const PtrStepb, PtrStepb, cudaStream_t); static Caller callers[] = { bitwiseMaskNotCaller<unsigned char>, bitwiseMaskNotCaller<unsigned char>, bitwiseMaskNotCaller<unsigned short>, bitwiseMaskNotCaller<unsigned short>, bitwiseMaskNotCaller<unsigned int>, bitwiseMaskNotCaller<unsigned int>, bitwiseMaskNotCaller<unsigned int> }; CV_Assert(mask.type() == CV_8U && mask.size() == src.size()); dst.create(src.size(), src.type()); Caller caller = callers[src.depth()]; CV_Assert(caller); int cn = src.depth() != CV_64F ? src.channels() : src.channels() * (sizeof(double) / sizeof(unsigned int)); caller(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 (*Caller)(int, int, int, const PtrStepb, const PtrStepb, const PtrStepb, PtrStepb, cudaStream_t); static Caller callers[] = { bitwiseMaskOrCaller<unsigned char>, bitwiseMaskOrCaller<unsigned char>, bitwiseMaskOrCaller<unsigned short>, bitwiseMaskOrCaller<unsigned short>, bitwiseMaskOrCaller<unsigned int>, bitwiseMaskOrCaller<unsigned int>, bitwiseMaskOrCaller<unsigned int> }; CV_Assert(src1.size() == src2.size() && src1.type() == src2.type()); dst.create(src1.size(), src1.type()); Caller caller = callers[src1.depth()]; CV_Assert(caller); int cn = dst.depth() != CV_64F ? dst.channels() : dst.channels() * (sizeof(double) / sizeof(unsigned int)); caller(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 (*Caller)(int, int, int, const PtrStepb, const PtrStepb, const PtrStepb, PtrStepb, cudaStream_t); static Caller callers[] = { bitwiseMaskAndCaller<unsigned char>, bitwiseMaskAndCaller<unsigned char>, bitwiseMaskAndCaller<unsigned short>, bitwiseMaskAndCaller<unsigned short>, bitwiseMaskAndCaller<unsigned int>, bitwiseMaskAndCaller<unsigned int>, bitwiseMaskAndCaller<unsigned int> }; CV_Assert(src1.size() == src2.size() && src1.type() == src2.type()); dst.create(src1.size(), src1.type()); Caller caller = callers[src1.depth()]; CV_Assert(caller); int cn = dst.depth() != CV_64F ? dst.channels() : dst.channels() * (sizeof(double) / sizeof(unsigned int)); caller(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 (*Caller)(int, int, int, const PtrStepb, const PtrStepb, const PtrStepb, PtrStepb, cudaStream_t); static Caller callers[] = { bitwiseMaskXorCaller<unsigned char>, bitwiseMaskXorCaller<unsigned char>, bitwiseMaskXorCaller<unsigned short>, bitwiseMaskXorCaller<unsigned short>, bitwiseMaskXorCaller<unsigned int>, bitwiseMaskXorCaller<unsigned int>, bitwiseMaskXorCaller<unsigned int> }; CV_Assert(src1.size() == src2.size() && src1.type() == src2.type()); dst.create(src1.size(), src1.type()); Caller caller = callers[src1.depth()]; CV_Assert(caller); int cn = dst.depth() != CV_64F ? dst.channels() : dst.channels() * (sizeof(double) / sizeof(unsigned int)); caller(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 DevMem2D_<T>& src1, const DevMem2D_<T>& src2, const DevMem2D_<T>& dst, cudaStream_t stream); template <typename T> void max_gpu(const DevMem2D_<T>& src1, const DevMem2D_<T>& src2, const DevMem2D_<T>& dst, cudaStream_t stream); template <typename T> void min_gpu(const DevMem2D_<T>& src1, T src2, const DevMem2D_<T>& dst, cudaStream_t stream); template <typename T> void max_gpu(const DevMem2D_<T>& src1, T src2, const DevMem2D_<T>& dst, cudaStream_t stream); }}} namespace { template <typename T> void min_caller(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::min_gpu<T>(src1.reshape(1), src2.reshape(1), dst.reshape(1), stream); } template <typename T> void min_caller(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream) { dst.create(src1.size(), src1.type()); ::cv::gpu::device::min_gpu<T>(src1.reshape(1), saturate_cast<T>(src2), dst.reshape(1), stream); } template <typename T> void max_caller(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::max_gpu<T>(src1.reshape(1), src2.reshape(1), dst.reshape(1), stream); } template <typename T> void max_caller(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream) { dst.create(src1.size(), src1.type()); ::cv::gpu::device::max_gpu<T>(src1.reshape(1), saturate_cast<T>(src2), dst.reshape(1), stream); } } void cv::gpu::min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream) { CV_Assert(src1.size() == src2.size() && src1.type() == src2.type()); CV_Assert((src1.depth() != CV_64F) || (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE))); typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream); static const func_t funcs[] = { min_caller<unsigned char>, min_caller<signed char>, min_caller<unsigned short>, min_caller<short>, min_caller<int>, min_caller<float>, min_caller<double> }; funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream)); } void cv::gpu::min(const GpuMat& src1, double src2, GpuMat& dst, Stream& stream) { CV_Assert((src1.depth() != CV_64F) || (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE))); typedef void (*func_t)(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream); static const func_t funcs[] = { min_caller<unsigned char>, min_caller<signed char>, min_caller<unsigned short>, min_caller<short>, min_caller<int>, min_caller<float>, min_caller<double> }; funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream)); } void cv::gpu::max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream) { CV_Assert(src1.size() == src2.size() && src1.type() == src2.type()); CV_Assert((src1.depth() != CV_64F) || (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE))); typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream); static const func_t funcs[] = { max_caller<unsigned char>, max_caller<signed char>, max_caller<unsigned short>, max_caller<short>, max_caller<int>, max_caller<float>, max_caller<double> }; funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream)); } void cv::gpu::max(const GpuMat& src1, double src2, GpuMat& dst, Stream& stream) { CV_Assert((src1.depth() != CV_64F) || (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE))); typedef void (*func_t)(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream); static const func_t funcs[] = { max_caller<unsigned char>, max_caller<signed char>, max_caller<unsigned short>, max_caller<short>, max_caller<int>, max_caller<float>, max_caller<double> }; funcs[src1.depth()](src1, src2, 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); 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 (*caller_t)(const GpuMat& src, GpuMat& dst, double thresh, double maxVal, int type, cudaStream_t stream); static const caller_t callers[] = { 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); } callers[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> }; 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, 0 }; 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()]; CV_Assert(func != 0); 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(); 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()]; CV_Assert(func != 0); func(psrc1->reshape(1), alpha, psrc2->reshape(1), beta, gamma, dst.reshape(1), StreamAccessor::getStream(stream)); } #endif