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370 lines
13 KiB
C++
370 lines
13 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other GpuMaterials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or bpied warranties, including, but not limited to, the bpied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "precomp.hpp"
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using namespace cv;
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using namespace cv::gpu;
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using namespace std;
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#if !defined (HAVE_CUDA)
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void cv::gpu::transpose(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
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void cv::gpu::flip(const GpuMat&, GpuMat&, int, Stream&) { throw_nogpu(); }
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void cv::gpu::LUT(const GpuMat&, const Mat&, GpuMat&, Stream&) { throw_nogpu(); }
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void cv::gpu::exp(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
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void cv::gpu::log(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
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void cv::gpu::magnitude(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
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void cv::gpu::magnitudeSqr(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
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void cv::gpu::magnitude(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
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void cv::gpu::magnitudeSqr(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
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void cv::gpu::phase(const GpuMat&, const GpuMat&, GpuMat&, bool, Stream&) { throw_nogpu(); }
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void cv::gpu::cartToPolar(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool, Stream&) { throw_nogpu(); }
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void cv::gpu::polarToCart(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool, Stream&) { throw_nogpu(); }
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#else /* !defined (HAVE_CUDA) */
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////////////////////////////////////////////////////////////////////////
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// transpose
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void cv::gpu::transpose(const GpuMat& src, GpuMat& dst, Stream& s)
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{
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CV_Assert(src.elemSize() == 1 || src.elemSize() == 4 || src.elemSize() == 8);
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dst.create( src.cols, src.rows, src.type() );
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cudaStream_t stream = StreamAccessor::getStream(s);
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if (src.elemSize() == 1)
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{
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NppStreamHandler h(stream);
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NppiSize sz;
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sz.width = src.cols;
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sz.height = src.rows;
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nppSafeCall( nppiTranspose_8u_C1R(src.ptr<Npp8u>(), static_cast<int>(src.step),
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dst.ptr<Npp8u>(), static_cast<int>(dst.step), sz) );
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}
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else if (src.elemSize() == 4)
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{
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NppStStreamHandler h(stream);
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NcvSize32u sz;
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sz.width = src.cols;
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sz.height = src.rows;
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ncvSafeCall( nppiStTranspose_32u_C1R(const_cast<Ncv32u*>(src.ptr<Ncv32u>()), static_cast<int>(src.step),
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dst.ptr<Ncv32u>(), static_cast<int>(dst.step), sz) );
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}
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else // if (src.elemSize() == 8)
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{
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NppStStreamHandler h(stream);
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NcvSize32u sz;
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sz.width = src.cols;
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sz.height = src.rows;
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ncvSafeCall( nppiStTranspose_64u_C1R(const_cast<Ncv64u*>(src.ptr<Ncv64u>()), static_cast<int>(src.step),
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dst.ptr<Ncv64u>(), static_cast<int>(dst.step), sz) );
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}
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if (stream == 0)
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cudaSafeCall( cudaDeviceSynchronize() );
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}
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////////////////////////////////////////////////////////////////////////
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// flip
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void cv::gpu::flip(const GpuMat& src, GpuMat& dst, int flipCode, Stream& s)
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{
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CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC4);
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dst.create( src.size(), src.type() );
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NppiSize sz;
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sz.width = src.cols;
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sz.height = src.rows;
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cudaStream_t stream = StreamAccessor::getStream(s);
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NppStreamHandler h(stream);
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if (src.type() == CV_8UC1)
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{
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nppSafeCall( nppiMirror_8u_C1R(src.ptr<Npp8u>(), static_cast<int>(src.step),
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dst.ptr<Npp8u>(), static_cast<int>(dst.step), sz,
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(flipCode == 0 ? NPP_HORIZONTAL_AXIS : (flipCode > 0 ? NPP_VERTICAL_AXIS : NPP_BOTH_AXIS))) );
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}
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else
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{
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nppSafeCall( nppiMirror_8u_C4R(src.ptr<Npp8u>(), static_cast<int>(src.step),
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dst.ptr<Npp8u>(), static_cast<int>(dst.step), sz,
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(flipCode == 0 ? NPP_HORIZONTAL_AXIS : (flipCode > 0 ? NPP_VERTICAL_AXIS : NPP_BOTH_AXIS))) );
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}
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if (stream == 0)
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cudaSafeCall( cudaDeviceSynchronize() );
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}
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////////////////////////////////////////////////////////////////////////
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// LUT
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void cv::gpu::LUT(const GpuMat& src, const Mat& lut, GpuMat& dst, Stream& s)
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{
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class LevelsInit
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{
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public:
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Npp32s pLevels[256];
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const Npp32s* pLevels3[3];
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int nValues3[3];
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LevelsInit()
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{
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nValues3[0] = nValues3[1] = nValues3[2] = 256;
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for (int i = 0; i < 256; ++i)
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pLevels[i] = i;
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pLevels3[0] = pLevels3[1] = pLevels3[2] = pLevels;
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}
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};
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static LevelsInit lvls;
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int cn = src.channels();
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CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC3);
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CV_Assert(lut.depth() == CV_8U && (lut.channels() == 1 || lut.channels() == cn) && lut.rows * lut.cols == 256 && lut.isContinuous());
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dst.create(src.size(), CV_MAKETYPE(lut.depth(), cn));
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NppiSize sz;
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sz.height = src.rows;
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sz.width = src.cols;
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Mat nppLut;
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lut.convertTo(nppLut, CV_32S);
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cudaStream_t stream = StreamAccessor::getStream(s);
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NppStreamHandler h(stream);
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if (src.type() == CV_8UC1)
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{
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nppSafeCall( nppiLUT_Linear_8u_C1R(src.ptr<Npp8u>(), static_cast<int>(src.step),
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dst.ptr<Npp8u>(), static_cast<int>(dst.step), sz, nppLut.ptr<Npp32s>(), lvls.pLevels, 256) );
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}
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else
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{
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Mat nppLut3[3];
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const Npp32s* pValues3[3];
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if (nppLut.channels() == 1)
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pValues3[0] = pValues3[1] = pValues3[2] = nppLut.ptr<Npp32s>();
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else
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{
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cv::split(nppLut, nppLut3);
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pValues3[0] = nppLut3[0].ptr<Npp32s>();
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pValues3[1] = nppLut3[1].ptr<Npp32s>();
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pValues3[2] = nppLut3[2].ptr<Npp32s>();
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}
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nppSafeCall( nppiLUT_Linear_8u_C3R(src.ptr<Npp8u>(), static_cast<int>(src.step),
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dst.ptr<Npp8u>(), static_cast<int>(dst.step), sz, pValues3, lvls.pLevels3, lvls.nValues3) );
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}
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if (stream == 0)
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cudaSafeCall( cudaDeviceSynchronize() );
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}
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////////////////////////////////////////////////////////////////////////
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// exp
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void cv::gpu::exp(const GpuMat& src, GpuMat& dst, Stream& s)
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{
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CV_Assert(src.type() == CV_32FC1);
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dst.create(src.size(), src.type());
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NppiSize sz;
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sz.width = src.cols;
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sz.height = src.rows;
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cudaStream_t stream = StreamAccessor::getStream(s);
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NppStreamHandler h(stream);
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nppSafeCall( nppiExp_32f_C1R(src.ptr<Npp32f>(), static_cast<int>(src.step), dst.ptr<Npp32f>(), static_cast<int>(dst.step), sz) );
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if (stream == 0)
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cudaSafeCall( cudaDeviceSynchronize() );
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}
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////////////////////////////////////////////////////////////////////////
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// log
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void cv::gpu::log(const GpuMat& src, GpuMat& dst, Stream& s)
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{
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CV_Assert(src.type() == CV_32FC1);
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dst.create(src.size(), src.type());
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NppiSize sz;
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sz.width = src.cols;
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sz.height = src.rows;
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cudaStream_t stream = StreamAccessor::getStream(s);
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NppStreamHandler h(stream);
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nppSafeCall( nppiLn_32f_C1R(src.ptr<Npp32f>(), static_cast<int>(src.step), dst.ptr<Npp32f>(), static_cast<int>(dst.step), sz) );
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if (stream == 0)
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cudaSafeCall( cudaDeviceSynchronize() );
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}
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////////////////////////////////////////////////////////////////////////
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// NPP magnitide
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namespace
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{
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typedef NppStatus (*nppMagnitude_t)(const Npp32fc* pSrc, int nSrcStep, Npp32f* pDst, int nDstStep, NppiSize oSizeROI);
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inline void npp_magnitude(const GpuMat& src, GpuMat& dst, nppMagnitude_t func, cudaStream_t stream)
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{
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CV_Assert(src.type() == CV_32FC2);
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dst.create(src.size(), CV_32FC1);
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NppiSize sz;
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sz.width = src.cols;
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sz.height = src.rows;
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NppStreamHandler h(stream);
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nppSafeCall( func(src.ptr<Npp32fc>(), static_cast<int>(src.step), dst.ptr<Npp32f>(), static_cast<int>(dst.step), sz) );
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if (stream == 0)
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cudaSafeCall( cudaDeviceSynchronize() );
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}
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}
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void cv::gpu::magnitude(const GpuMat& src, GpuMat& dst, Stream& stream)
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{
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::npp_magnitude(src, dst, nppiMagnitude_32fc32f_C1R, StreamAccessor::getStream(stream));
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}
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void cv::gpu::magnitudeSqr(const GpuMat& src, GpuMat& dst, Stream& stream)
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{
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::npp_magnitude(src, dst, nppiMagnitudeSqr_32fc32f_C1R, StreamAccessor::getStream(stream));
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}
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////////////////////////////////////////////////////////////////////////
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// Polar <-> Cart
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namespace cv { namespace gpu { namespace mathfunc
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{
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void cartToPolar_gpu(const DevMem2Df& x, const DevMem2Df& y, const DevMem2Df& mag, bool magSqr, const DevMem2Df& angle, bool angleInDegrees, cudaStream_t stream);
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void polarToCart_gpu(const DevMem2Df& mag, const DevMem2Df& angle, const DevMem2Df& x, const DevMem2Df& y, bool angleInDegrees, cudaStream_t stream);
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}}}
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namespace
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{
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inline void cartToPolar_caller(const GpuMat& x, const GpuMat& y, GpuMat* mag, bool magSqr, GpuMat* angle, bool angleInDegrees, cudaStream_t stream)
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{
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CV_DbgAssert(x.size() == y.size() && x.type() == y.type());
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CV_Assert(x.depth() == CV_32F);
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if (mag)
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mag->create(x.size(), x.type());
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if (angle)
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angle->create(x.size(), x.type());
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GpuMat x1cn = x.reshape(1);
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GpuMat y1cn = y.reshape(1);
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GpuMat mag1cn = mag ? mag->reshape(1) : GpuMat();
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GpuMat angle1cn = angle ? angle->reshape(1) : GpuMat();
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mathfunc::cartToPolar_gpu(x1cn, y1cn, mag1cn, magSqr, angle1cn, angleInDegrees, stream);
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}
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inline void polarToCart_caller(const GpuMat& mag, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees, cudaStream_t stream)
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{
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CV_DbgAssert((mag.empty() || mag.size() == angle.size()) && mag.type() == angle.type());
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CV_Assert(mag.depth() == CV_32F);
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x.create(mag.size(), mag.type());
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y.create(mag.size(), mag.type());
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GpuMat mag1cn = mag.reshape(1);
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GpuMat angle1cn = angle.reshape(1);
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GpuMat x1cn = x.reshape(1);
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GpuMat y1cn = y.reshape(1);
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mathfunc::polarToCart_gpu(mag1cn, angle1cn, x1cn, y1cn, angleInDegrees, stream);
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}
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}
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void cv::gpu::magnitude(const GpuMat& x, const GpuMat& y, GpuMat& dst, Stream& stream)
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{
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::cartToPolar_caller(x, y, &dst, false, 0, false, StreamAccessor::getStream(stream));
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}
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void cv::gpu::magnitudeSqr(const GpuMat& x, const GpuMat& y, GpuMat& dst, Stream& stream)
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{
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::cartToPolar_caller(x, y, &dst, true, 0, false, StreamAccessor::getStream(stream));
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}
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void cv::gpu::phase(const GpuMat& x, const GpuMat& y, GpuMat& angle, bool angleInDegrees, Stream& stream)
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{
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::cartToPolar_caller(x, y, 0, false, &angle, angleInDegrees, StreamAccessor::getStream(stream));
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}
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void cv::gpu::cartToPolar(const GpuMat& x, const GpuMat& y, GpuMat& mag, GpuMat& angle, bool angleInDegrees, Stream& stream)
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{
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::cartToPolar_caller(x, y, &mag, false, &angle, angleInDegrees, StreamAccessor::getStream(stream));
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}
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void cv::gpu::polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees, Stream& stream)
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{
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::polarToCart_caller(magnitude, angle, x, y, angleInDegrees, StreamAccessor::getStream(stream));
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}
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#endif /* !defined (HAVE_CUDA) */
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