51d5959aca
added gpu exp, log, magnitude, based on NPP. updated setTo with new NPP functions. minor fix in tests and comments.
551 lines
18 KiB
C++
551 lines
18 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::add(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::add(const GpuMat&, const Scalar&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::subtract(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::subtract(const GpuMat&, const Scalar&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::multiply(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::multiply(const GpuMat&, const Scalar&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::divide(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::divide(const GpuMat&, const Scalar&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::transpose(const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::absdiff(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::absdiff(const GpuMat&, const Scalar&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::compare(const GpuMat&, const GpuMat&, GpuMat&, int) { throw_nogpu(); }
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void cv::gpu::meanStdDev(const GpuMat&, Scalar&, Scalar&) { throw_nogpu(); }
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double cv::gpu::norm(const GpuMat&, int) { throw_nogpu(); return 0.0; }
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double cv::gpu::norm(const GpuMat&, const GpuMat&, int) { throw_nogpu(); return 0.0; }
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void cv::gpu::flip(const GpuMat&, GpuMat&, int) { throw_nogpu(); }
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Scalar cv::gpu::sum(const GpuMat&) { throw_nogpu(); return Scalar(); }
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void cv::gpu::minMax(const GpuMat&, double*, double*) { throw_nogpu(); }
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void cv::gpu::LUT(const GpuMat&, const Mat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::exp(const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::log(const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::magnitude(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
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#else /* !defined (HAVE_CUDA) */
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////////////////////////////////////////////////////////////////////////
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// add subtract multiply divide
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namespace
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{
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typedef NppStatus (*npp_arithm_8u_t)(const Npp8u* pSrc1, int nSrc1Step, const Npp8u* pSrc2, int nSrc2Step, Npp8u* pDst, int nDstStep,
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NppiSize oSizeROI, int nScaleFactor);
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typedef NppStatus (*npp_arithm_32s_t)(const Npp32s* pSrc1, int nSrc1Step, const Npp32s* pSrc2, int nSrc2Step, Npp32s* pDst,
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int nDstStep, NppiSize oSizeROI);
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typedef NppStatus (*npp_arithm_32f_t)(const Npp32f* pSrc1, int nSrc1Step, const Npp32f* pSrc2, int nSrc2Step, Npp32f* pDst,
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int nDstStep, NppiSize oSizeROI);
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void nppArithmCaller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst,
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npp_arithm_8u_t npp_func_8uc1, npp_arithm_8u_t npp_func_8uc4,
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npp_arithm_32s_t npp_func_32sc1, npp_arithm_32f_t npp_func_32fc1)
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{
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CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type());
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CV_Assert(src1.type() == CV_8UC1 || src1.type() == CV_8UC4 || src1.type() == CV_32SC1 || src1.type() == CV_32FC1);
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dst.create( src1.size(), src1.type() );
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NppiSize sz;
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sz.width = src1.cols;
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sz.height = src1.rows;
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switch (src1.type())
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{
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case CV_8UC1:
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nppSafeCall( npp_func_8uc1(src1.ptr<Npp8u>(), src1.step,
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src2.ptr<Npp8u>(), src2.step,
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dst.ptr<Npp8u>(), dst.step, sz, 0) );
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break;
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case CV_8UC4:
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nppSafeCall( npp_func_8uc4(src1.ptr<Npp8u>(), src1.step,
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src2.ptr<Npp8u>(), src2.step,
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dst.ptr<Npp8u>(), dst.step, sz, 0) );
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break;
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case CV_32SC1:
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nppSafeCall( npp_func_32sc1(src1.ptr<Npp32s>(), src1.step,
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src2.ptr<Npp32s>(), src2.step,
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dst.ptr<Npp32s>(), dst.step, sz) );
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break;
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case CV_32FC1:
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nppSafeCall( npp_func_32fc1(src1.ptr<Npp32f>(), src1.step,
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src2.ptr<Npp32f>(), src2.step,
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dst.ptr<Npp32f>(), dst.step, sz) );
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break;
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default:
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CV_Assert(!"Unsupported source type");
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}
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}
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typedef NppStatus (*npp_arithm_scalar_32f_t)(const Npp32f *pSrc, int nSrcStep, Npp32f nValue, Npp32f *pDst,
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int nDstStep, NppiSize oSizeROI);
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void nppArithmCaller(const GpuMat& src1, const Scalar& sc, GpuMat& dst,
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npp_arithm_scalar_32f_t npp_func)
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{
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CV_Assert(src1.type() == CV_32FC1);
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dst.create(src1.size(), src1.type());
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NppiSize sz;
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sz.width = src1.cols;
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sz.height = src1.rows;
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nppSafeCall( npp_func(src1.ptr<Npp32f>(), src1.step, (Npp32f)sc[0], dst.ptr<Npp32f>(), dst.step, sz) );
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}
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}
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void cv::gpu::add(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
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{
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nppArithmCaller(src1, src2, dst, nppiAdd_8u_C1RSfs, nppiAdd_8u_C4RSfs, nppiAdd_32s_C1R, nppiAdd_32f_C1R);
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}
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void cv::gpu::subtract(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
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{
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nppArithmCaller(src2, src1, dst, nppiSub_8u_C1RSfs, nppiSub_8u_C4RSfs, nppiSub_32s_C1R, nppiSub_32f_C1R);
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}
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void cv::gpu::multiply(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
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{
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nppArithmCaller(src1, src2, dst, nppiMul_8u_C1RSfs, nppiMul_8u_C4RSfs, nppiMul_32s_C1R, nppiMul_32f_C1R);
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}
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void cv::gpu::divide(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
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{
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nppArithmCaller(src2, src1, dst, nppiDiv_8u_C1RSfs, nppiDiv_8u_C4RSfs, nppiDiv_32s_C1R, nppiDiv_32f_C1R);
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}
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void cv::gpu::add(const GpuMat& src, const Scalar& sc, GpuMat& dst)
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{
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nppArithmCaller(src, sc, dst, nppiAddC_32f_C1R);
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}
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void cv::gpu::subtract(const GpuMat& src, const Scalar& sc, GpuMat& dst)
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{
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nppArithmCaller(src, sc, dst, nppiSubC_32f_C1R);
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}
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void cv::gpu::multiply(const GpuMat& src, const Scalar& sc, GpuMat& dst)
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{
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nppArithmCaller(src, sc, dst, nppiMulC_32f_C1R);
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}
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void cv::gpu::divide(const GpuMat& src, const Scalar& sc, GpuMat& dst)
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{
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nppArithmCaller(src, sc, dst, nppiDivC_32f_C1R);
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}
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////////////////////////////////////////////////////////////////////////
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// transpose
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void cv::gpu::transpose(const GpuMat& src, GpuMat& dst)
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{
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CV_Assert(src.type() == CV_8UC1);
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dst.create( src.cols, src.rows, 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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nppSafeCall( nppiTranspose_8u_C1R(src.ptr<Npp8u>(), src.step, dst.ptr<Npp8u>(), dst.step, sz) );
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}
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////////////////////////////////////////////////////////////////////////
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// absdiff
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void cv::gpu::absdiff(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
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{
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CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type());
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CV_Assert(src1.type() == CV_8UC1 || src1.type() == CV_8UC4 || src1.type() == CV_32SC1 || src1.type() == CV_32FC1);
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dst.create( src1.size(), src1.type() );
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NppiSize sz;
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sz.width = src1.cols;
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sz.height = src1.rows;
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switch (src1.type())
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{
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case CV_8UC1:
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nppSafeCall( nppiAbsDiff_8u_C1R(src1.ptr<Npp8u>(), src1.step,
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src2.ptr<Npp8u>(), src2.step,
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dst.ptr<Npp8u>(), dst.step, sz) );
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break;
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case CV_8UC4:
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nppSafeCall( nppiAbsDiff_8u_C4R(src1.ptr<Npp8u>(), src1.step,
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src2.ptr<Npp8u>(), src2.step,
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dst.ptr<Npp8u>(), dst.step, sz) );
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break;
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case CV_32SC1:
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nppSafeCall( nppiAbsDiff_32s_C1R(src1.ptr<Npp32s>(), src1.step,
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src2.ptr<Npp32s>(), src2.step,
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dst.ptr<Npp32s>(), dst.step, sz) );
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break;
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case CV_32FC1:
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nppSafeCall( nppiAbsDiff_32f_C1R(src1.ptr<Npp32f>(), src1.step,
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src2.ptr<Npp32f>(), src2.step,
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dst.ptr<Npp32f>(), dst.step, sz) );
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break;
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default:
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CV_Assert(!"Unsupported source type");
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}
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}
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void cv::gpu::absdiff(const GpuMat& src, const Scalar& s, GpuMat& dst)
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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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nppSafeCall( nppiAbsDiffC_32f_C1R(src.ptr<Npp32f>(), src.step, dst.ptr<Npp32f>(), dst.step, sz, (Npp32f)s[0]) );
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}
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////////////////////////////////////////////////////////////////////////
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// compare
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namespace cv { namespace gpu { namespace matrix_operations
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{
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void compare_ne_8u(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst);
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void compare_ne_32f(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst);
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}}}
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void cv::gpu::compare(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, int cmpop)
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{
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CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type());
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CV_Assert(src1.type() == CV_8UC4 || src1.type() == CV_32FC1);
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dst.create( src1.size(), CV_8UC1 );
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static const NppCmpOp nppCmpOp[] = { NPP_CMP_EQ, NPP_CMP_GREATER, NPP_CMP_GREATER_EQ, NPP_CMP_LESS, NPP_CMP_LESS_EQ };
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NppiSize sz;
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sz.width = src1.cols;
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sz.height = src1.rows;
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if (src1.type() == CV_8UC4)
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{
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if (cmpop != CMP_NE)
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{
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nppSafeCall( nppiCompare_8u_C4R(src1.ptr<Npp8u>(), src1.step,
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src2.ptr<Npp8u>(), src2.step,
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dst.ptr<Npp8u>(), dst.step, sz, nppCmpOp[cmpop]) );
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}
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else
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{
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matrix_operations::compare_ne_8u(src1, src2, dst);
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}
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}
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else
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{
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if (cmpop != CMP_NE)
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{
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nppSafeCall( nppiCompare_32f_C1R(src1.ptr<Npp32f>(), src1.step,
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src2.ptr<Npp32f>(), src2.step,
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dst.ptr<Npp8u>(), dst.step, sz, nppCmpOp[cmpop]) );
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}
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else
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{
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matrix_operations::compare_ne_32f(src1, src2, dst);
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}
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}
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}
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////////////////////////////////////////////////////////////////////////
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// meanStdDev
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void cv::gpu::meanStdDev(const GpuMat& src, Scalar& mean, Scalar& stddev)
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{
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CV_Assert(src.type() == CV_8UC1);
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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( nppiMean_StdDev_8u_C1R(src.ptr<Npp8u>(), src.step, sz, mean.val, stddev.val) );
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}
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////////////////////////////////////////////////////////////////////////
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// norm
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double cv::gpu::norm(const GpuMat& src1, int normType)
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{
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return norm(src1, GpuMat(src1.size(), src1.type(), Scalar::all(0.0)), normType);
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}
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double cv::gpu::norm(const GpuMat& src1, const GpuMat& src2, int normType)
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{
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CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type());
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CV_Assert(src1.type() == CV_8UC1);
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CV_Assert(normType == NORM_INF || normType == NORM_L1 || normType == NORM_L2);
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typedef NppStatus (*npp_norm_diff_func_t)(const Npp8u* pSrc1, int nSrcStep1, const Npp8u* pSrc2, int nSrcStep2,
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NppiSize oSizeROI, Npp64f* pRetVal);
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static const npp_norm_diff_func_t npp_norm_diff_func[] = {nppiNormDiff_Inf_8u_C1R, nppiNormDiff_L1_8u_C1R, nppiNormDiff_L2_8u_C1R};
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NppiSize sz;
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sz.width = src1.cols;
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sz.height = src1.rows;
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int funcIdx = normType >> 1;
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double retVal;
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nppSafeCall( npp_norm_diff_func[funcIdx](src1.ptr<Npp8u>(), src1.step,
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src2.ptr<Npp8u>(), src2.step,
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sz, &retVal) );
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return retVal;
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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)
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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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if (src.type() == CV_8UC1)
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{
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nppSafeCall( nppiMirror_8u_C1R(src.ptr<Npp8u>(), src.step,
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dst.ptr<Npp8u>(), 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>(), src.step,
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dst.ptr<Npp8u>(), 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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}
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////////////////////////////////////////////////////////////////////////
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// sum
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Scalar cv::gpu::sum(const GpuMat& src)
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{
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CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC4);
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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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int bufsz;
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if (src.type() == CV_8UC1)
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{
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nppiReductionGetBufferHostSize_8u_C1R(sz, &bufsz);
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GpuMat buf(1, bufsz, CV_32S);
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Scalar res;
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nppSafeCall( nppiSum_8u_C1R(src.ptr<Npp8u>(), src.step, sz, buf.ptr<Npp32s>(), res.val) );
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return res;
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}
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else
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{
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nppiReductionGetBufferHostSize_8u_C4R(sz, &bufsz);
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|
GpuMat buf(1, bufsz, CV_32S);
|
|
|
|
Scalar res;
|
|
nppSafeCall( nppiSum_8u_C4R(src.ptr<Npp8u>(), src.step, sz, buf.ptr<Npp32s>(), res.val) );
|
|
return res;
|
|
}
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////
|
|
// minMax
|
|
|
|
void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal)
|
|
{
|
|
CV_Assert(src.type() == CV_8UC1);
|
|
|
|
NppiSize sz;
|
|
sz.width = src.cols;
|
|
sz.height = src.rows;
|
|
|
|
Npp8u min_res, max_res;
|
|
|
|
nppSafeCall( nppiMinMax_8u_C1R(src.ptr<Npp8u>(), src.step, sz, &min_res, &max_res) );
|
|
|
|
if (minVal)
|
|
*minVal = min_res;
|
|
|
|
if (maxVal)
|
|
*maxVal = max_res;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////
|
|
// LUT
|
|
|
|
void cv::gpu::LUT(const GpuMat& src, const Mat& lut, GpuMat& dst)
|
|
{
|
|
class LevelsInit
|
|
{
|
|
public:
|
|
Npp32s pLevels[256];
|
|
const Npp32s* pLevels3[3];
|
|
int nValues3[3];
|
|
|
|
LevelsInit()
|
|
{
|
|
nValues3[0] = nValues3[1] = nValues3[2] = 256;
|
|
for (int i = 0; i < 256; ++i)
|
|
pLevels[i] = i;
|
|
pLevels3[0] = pLevels3[1] = pLevels3[2] = pLevels;
|
|
}
|
|
};
|
|
static LevelsInit lvls;
|
|
|
|
int cn = src.channels();
|
|
|
|
CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC3);
|
|
CV_Assert(lut.depth() == CV_8U && (lut.channels() == 1 || lut.channels() == cn) && lut.rows * lut.cols == 256 && lut.isContinuous());
|
|
|
|
dst.create(src.size(), CV_MAKETYPE(lut.depth(), cn));
|
|
|
|
NppiSize sz;
|
|
sz.height = src.rows;
|
|
sz.width = src.cols;
|
|
|
|
Mat nppLut;
|
|
lut.convertTo(nppLut, CV_32S);
|
|
|
|
if (src.type() == CV_8UC1)
|
|
{
|
|
nppSafeCall( nppiLUT_Linear_8u_C1R(src.ptr<Npp8u>(), src.step, dst.ptr<Npp8u>(), dst.step, sz,
|
|
nppLut.ptr<Npp32s>(), lvls.pLevels, 256) );
|
|
}
|
|
else
|
|
{
|
|
Mat nppLut3[3];
|
|
const Npp32s* pValues3[3];
|
|
if (nppLut.channels() == 1)
|
|
pValues3[0] = pValues3[1] = pValues3[2] = nppLut.ptr<Npp32s>();
|
|
else
|
|
{
|
|
cv::split(nppLut, nppLut3);
|
|
pValues3[0] = nppLut3[0].ptr<Npp32s>();
|
|
pValues3[1] = nppLut3[1].ptr<Npp32s>();
|
|
pValues3[2] = nppLut3[2].ptr<Npp32s>();
|
|
}
|
|
nppSafeCall( nppiLUT_Linear_8u_C3R(src.ptr<Npp8u>(), src.step, dst.ptr<Npp8u>(), dst.step, sz,
|
|
pValues3, lvls.pLevels3, lvls.nValues3) );
|
|
}
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////
|
|
// exp
|
|
|
|
void cv::gpu::exp(const GpuMat& src, GpuMat& dst)
|
|
{
|
|
CV_Assert(src.type() == CV_32FC1);
|
|
|
|
dst.create(src.size(), src.type());
|
|
|
|
NppiSize sz;
|
|
sz.width = src.cols;
|
|
sz.height = src.rows;
|
|
|
|
nppSafeCall( nppiExp_32f_C1R(src.ptr<Npp32f>(), src.step, dst.ptr<Npp32f>(), dst.step, sz) );
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////
|
|
// log
|
|
|
|
void cv::gpu::log(const GpuMat& src, GpuMat& dst)
|
|
{
|
|
CV_Assert(src.type() == CV_32FC1);
|
|
|
|
dst.create(src.size(), src.type());
|
|
|
|
NppiSize sz;
|
|
sz.width = src.cols;
|
|
sz.height = src.rows;
|
|
|
|
nppSafeCall( nppiLn_32f_C1R(src.ptr<Npp32f>(), src.step, dst.ptr<Npp32f>(), dst.step, sz) );
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////
|
|
// magnitude
|
|
|
|
void cv::gpu::magnitude(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
|
|
{
|
|
CV_DbgAssert(src1.type() == src2.type() && src1.size() == src2.size());
|
|
CV_Assert(src1.type() == CV_32FC1);
|
|
|
|
GpuMat src(src1.size(), CV_32FC2);
|
|
GpuMat srcs[] = {src1, src2};
|
|
cv::gpu::merge(srcs, 2, src);
|
|
|
|
dst.create(src1.size(), src1.type());
|
|
|
|
NppiSize sz;
|
|
sz.width = src.cols;
|
|
sz.height = src.rows;
|
|
|
|
nppSafeCall( nppiMagnitude_32fc32f_C1R(src.ptr<Npp32fc>(), src.step, dst.ptr<Npp32f>(), dst.step, sz) );
|
|
}
|
|
|
|
#endif /* !defined (HAVE_CUDA) */ |