/*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&, Stream&) { throw_nogpu(); } void cv::gpu::add(const GpuMat&, const Scalar&, GpuMat&, Stream&) { throw_nogpu(); } void cv::gpu::subtract(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); } void cv::gpu::subtract(const GpuMat&, const Scalar&, GpuMat&, Stream&) { throw_nogpu(); } void cv::gpu::multiply(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); } void cv::gpu::multiply(const GpuMat&, const Scalar&, GpuMat&, Stream&) { throw_nogpu(); } void cv::gpu::divide(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); } void cv::gpu::divide(const GpuMat&, const Scalar&, GpuMat&, 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::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_and(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, Stream&) { throw_nogpu(); } void cv::gpu::bitwise_xor(const GpuMat&, const GpuMat&, GpuMat&, const 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::addWeighted(const GpuMat&, double, const GpuMat&, double, double, GpuMat&, int, Stream&) { throw_nogpu(); } #else //////////////////////////////////////////////////////////////////////// // Basic arithmetical operations (add subtract multiply divide) namespace { typedef NppStatus (*npp_arithm_8u_t)(const Npp8u* pSrc1, int nSrc1Step, const Npp8u* pSrc2, int nSrc2Step, Npp8u* pDst, int nDstStep, NppiSize oSizeROI, int nScaleFactor); typedef NppStatus (*npp_arithm_32s_t)(const Npp32s* pSrc1, int nSrc1Step, const Npp32s* pSrc2, int nSrc2Step, Npp32s* pDst, int nDstStep, NppiSize oSizeROI); typedef NppStatus (*npp_arithm_32f_t)(const Npp32f* pSrc1, int nSrc1Step, const Npp32f* pSrc2, int nSrc2Step, Npp32f* pDst, int nDstStep, NppiSize oSizeROI); void nppArithmCaller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, npp_arithm_8u_t npp_func_8uc1, npp_arithm_8u_t npp_func_8uc4, npp_arithm_32s_t npp_func_32sc1, npp_arithm_32f_t npp_func_32fc1, cudaStream_t stream) { CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type()); CV_Assert(src1.type() == CV_8UC1 || src1.type() == CV_8UC4 || src1.type() == CV_32SC1 || src1.type() == CV_32FC1); dst.create( src1.size(), src1.type() ); NppiSize sz; sz.width = src1.cols; sz.height = src1.rows; NppStreamHandler h(stream); switch (src1.type()) { case CV_8UC1: nppSafeCall( npp_func_8uc1(src1.ptr(), static_cast(src1.step), src2.ptr(), static_cast(src2.step), dst.ptr(), static_cast(dst.step), sz, 0) ); break; case CV_8UC4: nppSafeCall( npp_func_8uc4(src1.ptr(), static_cast(src1.step), src2.ptr(), static_cast(src2.step), dst.ptr(), static_cast(dst.step), sz, 0) ); break; case CV_32SC1: nppSafeCall( npp_func_32sc1(src1.ptr(), static_cast(src1.step), src2.ptr(), static_cast(src2.step), dst.ptr(), static_cast(dst.step), sz) ); break; case CV_32FC1: nppSafeCall( npp_func_32fc1(src1.ptr(), static_cast(src1.step), src2.ptr(), static_cast(src2.step), dst.ptr(), static_cast(dst.step), sz) ); break; default: CV_Assert(!"Unsupported source type"); } if (stream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } template struct NppArithmScalarFunc; template<> struct NppArithmScalarFunc<1> { typedef NppStatus (*func_ptr)(const Npp32f *pSrc, int nSrcStep, Npp32f nValue, Npp32f *pDst, int nDstStep, NppiSize oSizeROI); }; template<> struct NppArithmScalarFunc<2> { typedef NppStatus (*func_ptr)(const Npp32fc *pSrc, int nSrcStep, Npp32fc nValue, Npp32fc *pDst, int nDstStep, NppiSize oSizeROI); }; template::func_ptr func> struct NppArithmScalar; template::func_ptr func> struct NppArithmScalar<1, func> { static void calc(const GpuMat& src, const Scalar& sc, GpuMat& dst, cudaStream_t stream) { dst.create(src.size(), src.type()); NppiSize sz; sz.width = src.cols; sz.height = src.rows; NppStreamHandler h(stream); nppSafeCall( func(src.ptr(), static_cast(src.step), (Npp32f)sc[0], dst.ptr(), static_cast(dst.step), sz) ); if (stream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } }; template::func_ptr func> struct NppArithmScalar<2, func> { static void calc(const GpuMat& src, const Scalar& sc, GpuMat& dst, cudaStream_t stream) { dst.create(src.size(), src.type()); NppiSize sz; sz.width = src.cols; sz.height = src.rows; Npp32fc nValue; nValue.re = (Npp32f)sc[0]; nValue.im = (Npp32f)sc[1]; NppStreamHandler h(stream); nppSafeCall( func(src.ptr(), static_cast(src.step), nValue, dst.ptr(), static_cast(dst.step), sz) ); if (stream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } }; } namespace cv { namespace gpu { namespace device { template void add_gpu(const DevMem2D src1, const DevMem2D src2, DevMem2D dst, cudaStream_t stream); }}} void cv::gpu::add(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream) { if (src1.depth() == CV_16S && src2.depth() == CV_16S) { CV_Assert(src1.size() == src2.size()); dst.create(src1.size(), src1.type()); device::add_gpu(src1.reshape(1), src2.reshape(1), dst.reshape(1), StreamAccessor::getStream(stream)); } else nppArithmCaller(src1, src2, dst, nppiAdd_8u_C1RSfs, nppiAdd_8u_C4RSfs, nppiAdd_32s_C1R, nppiAdd_32f_C1R, StreamAccessor::getStream(stream)); } namespace cv { namespace gpu { namespace device { template void subtractCaller(const DevMem2D src1, const DevMem2D src2, DevMem2D dst, cudaStream_t stream); }}} void cv::gpu::subtract(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream) { if (src1.depth() == CV_16S && src2.depth() == CV_16S) { CV_Assert(src1.size() == src2.size()); dst.create(src1.size(), src1.type()); device::subtractCaller(src1.reshape(1), src2.reshape(1), dst.reshape(1), StreamAccessor::getStream(stream)); } else nppArithmCaller(src2, src1, dst, nppiSub_8u_C1RSfs, nppiSub_8u_C4RSfs, nppiSub_32s_C1R, nppiSub_32f_C1R, StreamAccessor::getStream(stream)); } namespace cv { namespace gpu { namespace device { void multiply_gpu(const DevMem2D_& src1, const DevMem2Df& src2, const DevMem2D_& dst, cudaStream_t stream); void multiply_gpu(const DevMem2D_& src1, const DevMem2Df& src2, const DevMem2D_& dst, cudaStream_t stream); template void multiplyScalar_gpu(const DevMem2D& src, float scale, const DevMem2D& dst, cudaStream_t stream); }}} void cv::gpu::multiply(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream) { if (src1.type() == CV_8UC4 && src2.type() == CV_32FC1) { CV_Assert(src1.size() == src2.size()); dst.create(src1.size(), src1.type()); device::multiply_gpu(static_cast >(src1), static_cast(src2), static_cast >(dst), StreamAccessor::getStream(stream)); } else if (src1.type() == CV_16SC4 && src2.type() == CV_32FC1) { CV_Assert(src1.size() == src2.size()); dst.create(src1.size(), src1.type()); device::multiply_gpu(static_cast >(src1), static_cast(src2), static_cast >(dst), StreamAccessor::getStream(stream)); } else nppArithmCaller(src1, src2, dst, nppiMul_8u_C1RSfs, nppiMul_8u_C4RSfs, nppiMul_32s_C1R, nppiMul_32f_C1R, StreamAccessor::getStream(stream)); } void cv::gpu::multiply(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream) { if (src.depth() == CV_8U) { dst.create(src.size(), src.type()); device::multiplyScalar_gpu(src.reshape(1), (float)(sc[0]), dst, StreamAccessor::getStream(stream)); } else { CV_Assert(src.type() == CV_32FC1); dst.create(src.size(), src.type()); NppiSize sz; sz.width = src.cols; sz.height = src.rows; cudaStream_t cudaStream = StreamAccessor::getStream(stream); NppStreamHandler h(cudaStream); nppSafeCall( nppiMulC_32f_C1R(src.ptr(), static_cast(src.step), (Npp32f)sc[0], dst.ptr(), static_cast(dst.step), sz) ); if (cudaStream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } } namespace cv { namespace gpu { namespace device { void divide_gpu(const DevMem2D_& src1, const DevMem2Df& src2, const DevMem2D_& dst, cudaStream_t stream); void divide_gpu(const DevMem2D_& src1, const DevMem2Df& src2, const DevMem2D_& dst, cudaStream_t stream); }}} void cv::gpu::divide(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream) { if (src1.type() == CV_8UC4 && src2.type() == CV_32FC1) { CV_Assert(src1.size() == src2.size()); dst.create(src1.size(), src1.type()); device::divide_gpu(static_cast >(src1), static_cast(src2), static_cast >(dst), StreamAccessor::getStream(stream)); } else if (src1.type() == CV_16SC4 && src2.type() == CV_32FC1) { CV_Assert(src1.size() == src2.size()); dst.create(src1.size(), src1.type()); device::divide_gpu(static_cast >(src1), static_cast(src2), static_cast >(dst), StreamAccessor::getStream(stream)); } else nppArithmCaller(src2, src1, dst, nppiDiv_8u_C1RSfs, nppiDiv_8u_C4RSfs, nppiDiv_32s_C1R, nppiDiv_32f_C1R, StreamAccessor::getStream(stream)); } void cv::gpu::add(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream) { typedef void (*caller_t)(const GpuMat& src, const Scalar& sc, GpuMat& dst, cudaStream_t stream); static const caller_t callers[] = {0, NppArithmScalar<1, nppiAddC_32f_C1R>::calc, NppArithmScalar<2, nppiAddC_32fc_C1R>::calc}; CV_Assert(src.type() == CV_32FC1 || src.type() == CV_32FC2); callers[src.channels()](src, sc, dst, StreamAccessor::getStream(stream)); } void cv::gpu::subtract(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream) { typedef void (*caller_t)(const GpuMat& src, const Scalar& sc, GpuMat& dst, cudaStream_t stream); static const caller_t callers[] = {0, NppArithmScalar<1, nppiSubC_32f_C1R>::calc, NppArithmScalar<2, nppiSubC_32fc_C1R>::calc}; CV_Assert(src.type() == CV_32FC1 || src.type() == CV_32FC2); callers[src.channels()](src, sc, dst, StreamAccessor::getStream(stream)); } void cv::gpu::divide(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream) { CV_Assert(src.type() == CV_32FC1); dst.create(src.size(), src.type()); NppiSize sz; sz.width = src.cols; sz.height = src.rows; cudaStream_t cudaStream = StreamAccessor::getStream(stream); NppStreamHandler h(cudaStream); nppSafeCall( nppiDivC_32f_C1R(src.ptr(), static_cast(src.step), (Npp32f)sc[0], dst.ptr(), static_cast(dst.step), sz) ); if (cudaStream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } ////////////////////////////////////////////////////////////////////////////// // Absolute difference void cv::gpu::absdiff(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& s) { CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type()); CV_Assert(src1.type() == CV_8UC1 || src1.type() == CV_8UC4 || src1.type() == CV_32SC1 || src1.type() == CV_32FC1); dst.create( src1.size(), src1.type() ); NppiSize sz; sz.width = src1.cols; sz.height = src1.rows; cudaStream_t stream = StreamAccessor::getStream(s); NppStreamHandler h(stream); switch (src1.type()) { case CV_8UC1: nppSafeCall( nppiAbsDiff_8u_C1R(src1.ptr(), static_cast(src1.step), src2.ptr(), static_cast(src2.step), dst.ptr(), static_cast(dst.step), sz) ); break; case CV_8UC4: nppSafeCall( nppiAbsDiff_8u_C4R(src1.ptr(), static_cast(src1.step), src2.ptr(), static_cast(src2.step), dst.ptr(), static_cast(dst.step), sz) ); break; case CV_32SC1: nppSafeCall( nppiAbsDiff_32s_C1R(src1.ptr(), static_cast(src1.step), src2.ptr(), static_cast(src2.step), dst.ptr(), static_cast(dst.step), sz) ); break; case CV_32FC1: nppSafeCall( nppiAbsDiff_32f_C1R(src1.ptr(), static_cast(src1.step), src2.ptr(), static_cast(src2.step), dst.ptr(), static_cast(dst.step), sz) ); break; default: CV_Assert(!"Unsupported source type"); } if (stream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } void cv::gpu::absdiff(const GpuMat& src1, const Scalar& src2, GpuMat& dst, Stream& s) { CV_Assert(src1.type() == CV_32FC1); dst.create( src1.size(), src1.type() ); NppiSize sz; sz.width = src1.cols; sz.height = src1.rows; cudaStream_t stream = StreamAccessor::getStream(s); NppStreamHandler h(stream); nppSafeCall( nppiAbsDiffC_32f_C1R(src1.ptr(), static_cast(src1.step), dst.ptr(), static_cast(dst.step), sz, (Npp32f)src2[0]) ); if (stream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } ////////////////////////////////////////////////////////////////////////////// // Comparison of two matrixes namespace cv { namespace gpu { namespace device { void compare_ne_8uc4(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst, cudaStream_t stream); void compare_ne_32f(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst, cudaStream_t stream); }}} void cv::gpu::compare(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, int cmpop, Stream& s) { CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type()); CV_Assert(src1.type() == CV_8UC4 || src1.type() == CV_32FC1); dst.create( src1.size(), CV_8UC1 ); static const NppCmpOp nppCmpOp[] = { NPP_CMP_EQ, NPP_CMP_GREATER, NPP_CMP_GREATER_EQ, NPP_CMP_LESS, NPP_CMP_LESS_EQ }; NppiSize sz; sz.width = src1.cols; sz.height = src1.rows; cudaStream_t stream = StreamAccessor::getStream(s); if (src1.type() == CV_8UC4) { if (cmpop != CMP_NE) { NppStreamHandler h(stream); nppSafeCall( nppiCompare_8u_C4R(src1.ptr(), static_cast(src1.step), src2.ptr(), static_cast(src2.step), dst.ptr(), static_cast(dst.step), sz, nppCmpOp[cmpop]) ); if (stream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } else { device::compare_ne_8uc4(src1, src2, dst, stream); } } else { if (cmpop != CMP_NE) { NppStreamHandler h(stream); nppSafeCall( nppiCompare_32f_C1R(src1.ptr(), static_cast(src1.step), src2.ptr(), static_cast(src2.step), dst.ptr(), static_cast(dst.step), sz, nppCmpOp[cmpop]) ); if (stream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } else { device::compare_ne_32f(src1, src2, dst, stream); } } } ////////////////////////////////////////////////////////////////////////////// // Unary bitwise logical operations namespace cv { namespace gpu { namespace device { void bitwiseNotCaller(int rows, int cols, size_t elem_size1, int cn, const PtrStep src, PtrStep dst, cudaStream_t stream); template void bitwiseMaskNotCaller(int rows, int cols, int cn, const PtrStep src, const PtrStep mask, PtrStep 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; typedef void (*Caller)(int, int, int, const PtrStep, const PtrStep, PtrStep, cudaStream_t); static Caller callers[] = {device::bitwiseMaskNotCaller, device::bitwiseMaskNotCaller, device::bitwiseMaskNotCaller, device::bitwiseMaskNotCaller, device::bitwiseMaskNotCaller, device::bitwiseMaskNotCaller, device::bitwiseMaskNotCaller}; 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 PtrStep src1, const PtrStep src2, PtrStep dst, cudaStream_t stream); template void bitwiseMaskOrCaller(int rows, int cols, int cn, const PtrStep src1, const PtrStep src2, const PtrStep mask, PtrStep dst, cudaStream_t stream); void bitwiseAndCaller(int rows, int cols, size_t elem_size1, int cn, const PtrStep src1, const PtrStep src2, PtrStep dst, cudaStream_t stream); template void bitwiseMaskAndCaller(int rows, int cols, int cn, const PtrStep src1, const PtrStep src2, const PtrStep mask, PtrStep dst, cudaStream_t stream); void bitwiseXorCaller(int rows, int cols, size_t elem_size1, int cn, const PtrStep src1, const PtrStep src2, PtrStep dst, cudaStream_t stream); template void bitwiseMaskXorCaller(int rows, int cols, int cn, const PtrStep src1, const PtrStep src2, const PtrStep mask, PtrStep 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; typedef void (*Caller)(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t); static Caller callers[] = {device::bitwiseMaskOrCaller, device::bitwiseMaskOrCaller, device::bitwiseMaskOrCaller, device::bitwiseMaskOrCaller, device::bitwiseMaskOrCaller, device::bitwiseMaskOrCaller, device::bitwiseMaskOrCaller}; 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; typedef void (*Caller)(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t); static Caller callers[] = {device::bitwiseMaskAndCaller, device::bitwiseMaskAndCaller, device::bitwiseMaskAndCaller, device::bitwiseMaskAndCaller, device::bitwiseMaskAndCaller, device::bitwiseMaskAndCaller, device::bitwiseMaskAndCaller}; 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; typedef void (*Caller)(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t); static Caller callers[] = {device::bitwiseMaskXorCaller, device::bitwiseMaskXorCaller, device::bitwiseMaskXorCaller, device::bitwiseMaskXorCaller, device::bitwiseMaskXorCaller, device::bitwiseMaskXorCaller, device::bitwiseMaskXorCaller}; 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)); } ////////////////////////////////////////////////////////////////////////////// // Minimum and maximum operations namespace cv { namespace gpu { namespace device { template void min_gpu(const DevMem2D_& src1, const DevMem2D_& src2, const DevMem2D_& dst, cudaStream_t stream); template void max_gpu(const DevMem2D_& src1, const DevMem2D_& src2, const DevMem2D_& dst, cudaStream_t stream); template void min_gpu(const DevMem2D_& src1, T src2, const DevMem2D_& dst, cudaStream_t stream); template void max_gpu(const DevMem2D_& src1, T src2, const DevMem2D_& dst, cudaStream_t stream); }}} namespace { template 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()); device::min_gpu(src1.reshape(1), src2.reshape(1), dst.reshape(1), stream); } template void min_caller(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream) { dst.create(src1.size(), src1.type()); device::min_gpu(src1.reshape(1), saturate_cast(src2), dst.reshape(1), stream); } template 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()); device::max_gpu(src1.reshape(1), src2.reshape(1), dst.reshape(1), stream); } template void max_caller(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream) { dst.create(src1.size(), src1.type()); device::max_gpu(src1.reshape(1), saturate_cast(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, min_caller, min_caller, min_caller, min_caller, min_caller, min_caller }; 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, min_caller, min_caller, min_caller, min_caller, min_caller, min_caller }; 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, max_caller, max_caller, max_caller, max_caller, max_caller, max_caller }; 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, max_caller, max_caller, max_caller, max_caller, max_caller, max_caller }; funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream)); } //////////////////////////////////////////////////////////////////////// // threshold namespace cv { namespace gpu { namespace device { template void threshold_gpu(const DevMem2D& src, const DevMem2D& dst, T thresh, T maxVal, int type, cudaStream_t stream); }}} namespace { template void threshold_caller(const GpuMat& src, GpuMat& dst, double thresh, double maxVal, int type, cudaStream_t stream) { device::threshold_gpu(src, dst, saturate_cast(thresh), saturate_cast(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(), static_cast(src.step), dst.ptr(), static_cast(dst.step), sz, static_cast(thresh), NPP_CMP_GREATER) ); if (stream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } else { CV_Assert((src.depth() != CV_64F) || (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE))); 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, threshold_caller, threshold_caller, threshold_caller, threshold_caller, threshold_caller, threshold_caller }; 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 void pow_caller(const DevMem2D& src, float power, DevMem2D dst, cudaStream_t stream); }}} void cv::gpu::pow(const GpuMat& src, double power, GpuMat& dst, Stream& stream) { CV_Assert( src.depth() != CV_64F ); dst.create(src.size(), src.type()); typedef void (*caller_t)(const DevMem2D& src, float power, DevMem2D dst, cudaStream_t stream); static const caller_t callers[] = { device::pow_caller, device::pow_caller, device::pow_caller, device::pow_caller, device::pow_caller, device::pow_caller }; callers[src.depth()](src.reshape(1), (float)power, dst.reshape(1), StreamAccessor::getStream(stream)); } //////////////////////////////////////////////////////////////////////// // addWeighted namespace cv { namespace gpu { namespace device { template void addWeighted_gpu(const DevMem2D& src1, double alpha, const DevMem2D& src2, double beta, double gamma, const DevMem2D& 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) { 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); } typedef void (*caller_t)(const DevMem2D& src1, double alpha, const DevMem2D& src2, double beta, double gamma, const DevMem2D& dst, cudaStream_t stream); using namespace cv::gpu::device; static const caller_t callers[7][7][7] = { { { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu } }, { { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu } }, { { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu } }, { { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu } }, { { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu } }, { { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu } }, { { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/, 0/*addWeighted_gpu*/ }, { addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu, addWeighted_gpu } } }; callers[psrc1->depth()][psrc2->depth()][dst.depth()](psrc1->reshape(1), alpha, psrc2->reshape(1), beta, gamma, dst.reshape(1), StreamAccessor::getStream(stream)); } #endif