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606 lines
22 KiB
C++
606 lines
22 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::subtract(const GpuMat&, const GpuMat&, 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::divide(const GpuMat&, const GpuMat&, 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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double cv::gpu::threshold(const GpuMat&, GpuMat&, double, double, int) { throw_nogpu(); return 0.0; }
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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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void cv::gpu::resize(const GpuMat&, GpuMat&, Size, double, double, 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::copyMakeBorder(const GpuMat&, GpuMat&, int, int, int, int, const Scalar&) { throw_nogpu(); }
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void cv::gpu::warpAffine(const GpuMat&, GpuMat&, const Mat&, Size, int) { throw_nogpu(); }
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void cv::gpu::warpPerspective(const GpuMat&, GpuMat&, const Mat&, Size, int) { throw_nogpu(); }
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void cv::gpu::rotate(const GpuMat&, GpuMat&, Size, double, double, double, int) { throw_nogpu(); }
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#else /* !defined (HAVE_CUDA) */
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namespace
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{
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typedef NppStatus (*npp_warp_8u_t)(const Npp8u* pSrc, NppiSize srcSize, int srcStep, NppiRect srcRoi, Npp8u* pDst,
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int dstStep, NppiRect dstRoi, const double coeffs[][3],
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int interpolation);
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typedef NppStatus (*npp_warp_16u_t)(const Npp16u* pSrc, NppiSize srcSize, int srcStep, NppiRect srcRoi, Npp16u* pDst,
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int dstStep, NppiRect dstRoi, const double coeffs[][3],
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int interpolation);
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typedef NppStatus (*npp_warp_32s_t)(const Npp32s* pSrc, NppiSize srcSize, int srcStep, NppiRect srcRoi, Npp32s* pDst,
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int dstStep, NppiRect dstRoi, const double coeffs[][3],
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int interpolation);
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typedef NppStatus (*npp_warp_32f_t)(const Npp32f* pSrc, NppiSize srcSize, int srcStep, NppiRect srcRoi, Npp32f* pDst,
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int dstStep, NppiRect dstRoi, const double coeffs[][3],
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int interpolation);
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typedef NppStatus (*npp_binary_func_8u_scale_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_binary_func_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 nppFuncCaller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst,
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npp_binary_func_8u_scale_t npp_func_8uc1, npp_binary_func_8u_scale_t npp_func_8uc4, npp_binary_func_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_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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if (src1.depth() == CV_8U)
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{
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if (src1.channels() == 1)
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{
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npp_func_8uc1((const Npp8u*)src1.ptr<char>(), src1.step,
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(const Npp8u*)src2.ptr<char>(), src2.step,
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(Npp8u*)dst.ptr<char>(), dst.step, sz, 0);
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}
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else
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{
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npp_func_8uc4((const Npp8u*)src1.ptr<char>(), src1.step,
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(const Npp8u*)src2.ptr<char>(), src2.step,
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(Npp8u*)dst.ptr<char>(), dst.step, sz, 0);
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}
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}
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else //if (src1.depth() == CV_32F)
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{
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npp_func_32fc1((const Npp32f*)src1.ptr<float>(), src1.step,
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(const Npp32f*)src2.ptr<float>(), src2.step,
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(Npp32f*)dst.ptr<float>(), dst.step, sz);
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}
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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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nppFuncCaller(src1, src2, dst, nppiAdd_8u_C1RSfs, nppiAdd_8u_C4RSfs, 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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nppFuncCaller(src2, src1, dst, nppiSub_8u_C1RSfs, nppiSub_8u_C4RSfs, 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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nppFuncCaller(src1, src2, dst, nppiMul_8u_C1RSfs, nppiMul_8u_C4RSfs, 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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nppFuncCaller(src2, src1, dst, nppiDiv_8u_C1RSfs, nppiDiv_8u_C4RSfs, nppiDiv_32f_C1R);
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}
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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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nppiTranspose_8u_C1R((const Npp8u*)src.ptr<char>(), src.step, (Npp8u*)dst.ptr<char>(), dst.step, sz);
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}
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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.depth() == CV_8U || src1.depth() == CV_32F) && src1.channels() == 1);
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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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if (src1.depth() == CV_8U)
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{
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nppiAbsDiff_8u_C1R((const Npp8u*)src1.ptr<char>(), src1.step,
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(const Npp8u*)src2.ptr<char>(), src2.step,
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(Npp8u*)dst.ptr<char>(), dst.step, sz);
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}
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else //if (src1.depth() == CV_32F)
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{
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nppiAbsDiff_32f_C1R((const Npp32f*)src1.ptr<float>(), src1.step,
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(const Npp32f*)src2.ptr<float>(), src2.step,
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(Npp32f*)dst.ptr<float>(), dst.step, sz);
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}
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}
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double cv::gpu::threshold(const GpuMat& src, GpuMat& dst, double thresh, double /*maxVal*/, int thresholdType)
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{
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CV_Assert(src.type() == CV_32FC1 && thresholdType == THRESH_TRUNC);
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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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nppiThreshold_32f_C1R((const Npp32f*)src.ptr<float>(), src.step,
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(Npp32f*)dst.ptr<float>(), dst.step, sz, (Npp32f)thresh, NPP_CMP_GREATER);
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return thresh;
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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) && cmpop != CMP_NE);
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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.depth() == CV_8U)
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{
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nppiCompare_8u_C4R((const Npp8u*)src1.ptr<char>(), src1.step,
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(const Npp8u*)src2.ptr<char>(), src2.step,
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(Npp8u*)dst.ptr<char>(), dst.step, sz, nppCmpOp[cmpop]);
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}
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else //if (src1.depth() == CV_32F)
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{
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nppiCompare_32f_C1R((const Npp32f*)src1.ptr<float>(), src1.step,
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(const Npp32f*)src2.ptr<float>(), src2.step,
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(Npp8u*)dst.ptr<char>(), dst.step, sz, nppCmpOp[cmpop]);
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}
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}
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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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nppiMean_StdDev_8u_C1R((const Npp8u*)src.ptr<char>(), src.step, sz, mean.val, stddev.val);
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}
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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) && (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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Scalar retVal;
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npp_norm_diff_func[funcIdx]((const Npp8u*)src1.ptr<char>(), src1.step,
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(const Npp8u*)src2.ptr<char>(), src2.step,
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sz, retVal.val);
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return retVal[0];
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}
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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.channels() == 1)
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{
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nppiMirror_8u_C1R((const Npp8u*)src.ptr<char>(), src.step,
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(Npp8u*)dst.ptr<char>(), 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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nppiMirror_8u_C4R((const Npp8u*)src.ptr<char>(), src.step,
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(Npp8u*)dst.ptr<char>(), 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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void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, double fy, int interpolation)
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{
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static const int npp_inter[] = {NPPI_INTER_NN, NPPI_INTER_LINEAR, NPPI_INTER_CUBIC, 0, NPPI_INTER_LANCZOS};
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CV_Assert((src.type() == CV_8UC1 || src.type() == CV_8UC4) &&
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(interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || interpolation == INTER_CUBIC || interpolation == INTER_LANCZOS4));
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CV_Assert( src.size().area() > 0 );
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CV_Assert( !(dsize == Size()) || (fx > 0 && fy > 0) );
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if( dsize == Size() )
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{
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dsize = Size(saturate_cast<int>(src.cols * fx), saturate_cast<int>(src.rows * fy));
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}
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else
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{
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fx = (double)dsize.width / src.cols;
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fy = (double)dsize.height / src.rows;
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}
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dst.create(dsize, src.type());
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NppiSize srcsz;
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srcsz.width = src.cols;
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srcsz.height = src.rows;
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NppiRect srcrect;
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srcrect.x = srcrect.y = 0;
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srcrect.width = src.cols;
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srcrect.height = src.rows;
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NppiSize dstsz;
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dstsz.width = dst.cols;
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dstsz.height = dst.rows;
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if (src.channels() == 1)
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{
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nppiResize_8u_C1R((const Npp8u*)src.ptr<char>(), srcsz, src.step, srcrect,
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(Npp8u*)dst.ptr<char>(), dst.step, dstsz, fx, fy, npp_inter[interpolation]);
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}
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else
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{
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nppiResize_8u_C4R((const Npp8u*)src.ptr<char>(), srcsz, src.step, srcrect,
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(Npp8u*)dst.ptr<char>(), dst.step, dstsz, fx, fy, npp_inter[interpolation]);
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}
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}
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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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Scalar res;
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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.channels() == 1)
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{
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nppiSum_8u_C1R((const Npp8u*)src.ptr<char>(), src.step, sz, res.val);
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}
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else
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{
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nppiSum_8u_C4R((const Npp8u*)src.ptr<char>(), src.step, sz, res.val);
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}
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return res;
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}
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void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal)
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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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Npp8u min_res, max_res;
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nppiMinMax_8u_C1R((const Npp8u*)src.ptr<char>(), src.step, sz, &min_res, &max_res);
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if (minVal)
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*minVal = min_res;
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if (maxVal)
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*maxVal = max_res;
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}
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void cv::gpu::copyMakeBorder(const GpuMat& src, GpuMat& dst, int top, int bottom, int left, int right, const Scalar& value)
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{
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CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC4 || src.type() == CV_32SC1);
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dst.create(src.rows + top + bottom, src.cols + left + right, src.type());
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NppiSize srcsz;
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srcsz.width = src.cols;
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srcsz.height = src.rows;
|
|
NppiSize dstsz;
|
|
dstsz.width = dst.cols;
|
|
dstsz.height = dst.rows;
|
|
|
|
if (src.depth() == CV_8U)
|
|
{
|
|
if (src.channels() == 1)
|
|
{
|
|
Npp8u nVal = (Npp8u)value[0];
|
|
nppiCopyConstBorder_8u_C1R((const Npp8u*)src.ptr<char>(), src.step, srcsz,
|
|
(Npp8u*)dst.ptr<char>(), dst.step, dstsz, top, left, nVal);
|
|
}
|
|
else
|
|
{
|
|
Npp8u nVal[] = {(Npp8u)value[0], (Npp8u)value[1], (Npp8u)value[2], (Npp8u)value[3]};
|
|
nppiCopyConstBorder_8u_C4R((const Npp8u*)src.ptr<char>(), src.step, srcsz,
|
|
(Npp8u*)dst.ptr<char>(), dst.step, dstsz, top, left, nVal);
|
|
}
|
|
}
|
|
else //if (src.depth() == CV_32S)
|
|
{
|
|
Npp32s nVal = (Npp32s)value[0];
|
|
nppiCopyConstBorder_32s_C1R((const Npp32s*)src.ptr<char>(), src.step, srcsz,
|
|
(Npp32s*)dst.ptr<char>(), dst.step, dstsz, top, left, nVal);
|
|
}
|
|
}
|
|
|
|
namespace
|
|
{
|
|
void nppWarpCaller(const GpuMat& src, GpuMat& dst, double coeffs[][3], const Size& dsize, int flags,
|
|
npp_warp_8u_t npp_warp_8u[][2], npp_warp_16u_t npp_warp_16u[][2],
|
|
npp_warp_32s_t npp_warp_32s[][2], npp_warp_32f_t npp_warp_32f[][2])
|
|
{
|
|
static const int npp_inter[] = {NPPI_INTER_NN, NPPI_INTER_LINEAR, NPPI_INTER_CUBIC};
|
|
|
|
int interpolation = flags & INTER_MAX;
|
|
|
|
CV_Assert((src.depth() == CV_8U || src.depth() == CV_16U || src.depth() == CV_32S || src.depth() == CV_32F) && src.channels() != 2);
|
|
CV_Assert(interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || interpolation == INTER_CUBIC);
|
|
|
|
dst.create(dsize, src.type());
|
|
|
|
NppiSize srcsz;
|
|
srcsz.height = src.rows;
|
|
srcsz.width = src.cols;
|
|
NppiRect srcroi;
|
|
srcroi.x = srcroi.y = 0;
|
|
srcroi.height = src.rows;
|
|
srcroi.width = src.cols;
|
|
NppiRect dstroi;
|
|
dstroi.x = dstroi.y = 0;
|
|
dstroi.height = dst.rows;
|
|
dstroi.width = dst.cols;
|
|
|
|
int warpInd = (flags & WARP_INVERSE_MAP) >> 4;
|
|
|
|
switch (src.depth())
|
|
{
|
|
case CV_8U:
|
|
npp_warp_8u[src.channels()][warpInd]((const Npp8u*)src.ptr<char>(), srcsz, src.step, srcroi,
|
|
(Npp8u*)dst.ptr<char>(), dst.step, dstroi, coeffs, npp_inter[interpolation]);
|
|
break;
|
|
case CV_16U:
|
|
npp_warp_16u[src.channels()][warpInd]((const Npp16u*)src.ptr<char>(), srcsz, src.step, srcroi,
|
|
(Npp16u*)dst.ptr<char>(), dst.step, dstroi, coeffs, npp_inter[interpolation]);
|
|
break;
|
|
case CV_32SC1:
|
|
npp_warp_32s[src.channels()][warpInd]((const Npp32s*)src.ptr<char>(), srcsz, src.step, srcroi,
|
|
(Npp32s*)dst.ptr<char>(), dst.step, dstroi, coeffs, npp_inter[interpolation]);
|
|
break;
|
|
case CV_32FC1:
|
|
npp_warp_32f[src.channels()][warpInd]((const Npp32f*)src.ptr<char>(), srcsz, src.step, srcroi,
|
|
(Npp32f*)dst.ptr<char>(), dst.step, dstroi, coeffs, npp_inter[interpolation]);
|
|
break;
|
|
default:
|
|
CV_Assert(!"Unsupported source type");
|
|
}
|
|
}
|
|
}
|
|
|
|
void cv::gpu::warpAffine(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags)
|
|
{
|
|
static npp_warp_8u_t npp_warpAffine_8u[][2] =
|
|
{
|
|
{0, 0},
|
|
{nppiWarpAffine_8u_C1R, nppiWarpAffineBack_8u_C1R},
|
|
{0, 0},
|
|
{nppiWarpAffine_8u_C3R, nppiWarpAffineBack_8u_C3R},
|
|
{nppiWarpAffine_8u_C4R, nppiWarpAffineBack_8u_C4R}
|
|
};
|
|
static npp_warp_16u_t npp_warpAffine_16u[][2] =
|
|
{
|
|
{0, 0},
|
|
{nppiWarpAffine_16u_C1R, nppiWarpAffineBack_16u_C1R},
|
|
{0, 0},
|
|
{nppiWarpAffine_16u_C3R, nppiWarpAffineBack_16u_C3R},
|
|
{nppiWarpAffine_16u_C4R, nppiWarpAffineBack_16u_C4R}
|
|
};
|
|
static npp_warp_32s_t npp_warpAffine_32s[][2] =
|
|
{
|
|
{0, 0},
|
|
{nppiWarpAffine_32s_C1R, nppiWarpAffineBack_32s_C1R},
|
|
{0, 0},
|
|
{nppiWarpAffine_32s_C3R, nppiWarpAffineBack_32s_C3R},
|
|
{nppiWarpAffine_32s_C4R, nppiWarpAffineBack_32s_C4R}
|
|
};
|
|
static npp_warp_32f_t npp_warpAffine_32f[][2] =
|
|
{
|
|
{0, 0},
|
|
{nppiWarpAffine_32f_C1R, nppiWarpAffineBack_32f_C1R},
|
|
{0, 0},
|
|
{nppiWarpAffine_32f_C3R, nppiWarpAffineBack_32f_C3R},
|
|
{nppiWarpAffine_32f_C4R, nppiWarpAffineBack_32f_C4R}
|
|
};
|
|
|
|
CV_Assert(M.rows == 2 && M.cols == 3);
|
|
|
|
double coeffs[2][3];
|
|
Mat coeffsMat(2, 3, CV_64F, (void*)coeffs);
|
|
M.convertTo(coeffsMat, coeffsMat.type());
|
|
|
|
nppWarpCaller(src, dst, coeffs, dsize, flags, npp_warpAffine_8u, npp_warpAffine_16u, npp_warpAffine_32s, npp_warpAffine_32f);
|
|
}
|
|
|
|
void cv::gpu::warpPerspective(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags)
|
|
{
|
|
static npp_warp_8u_t npp_warpPerspective_8u[][2] =
|
|
{
|
|
{0, 0},
|
|
{nppiWarpPerspective_8u_C1R, nppiWarpPerspectiveBack_8u_C1R},
|
|
{0, 0},
|
|
{nppiWarpPerspective_8u_C3R, nppiWarpPerspectiveBack_8u_C3R},
|
|
{nppiWarpPerspective_8u_C4R, nppiWarpPerspectiveBack_8u_C4R}
|
|
};
|
|
static npp_warp_16u_t npp_warpPerspective_16u[][2] =
|
|
{
|
|
{0, 0},
|
|
{nppiWarpPerspective_16u_C1R, nppiWarpPerspectiveBack_16u_C1R},
|
|
{0, 0},
|
|
{nppiWarpPerspective_16u_C3R, nppiWarpPerspectiveBack_16u_C3R},
|
|
{nppiWarpPerspective_16u_C4R, nppiWarpPerspectiveBack_16u_C4R}
|
|
};
|
|
static npp_warp_32s_t npp_warpPerspective_32s[][2] =
|
|
{
|
|
{0, 0},
|
|
{nppiWarpPerspective_32s_C1R, nppiWarpPerspectiveBack_32s_C1R},
|
|
{0, 0},
|
|
{nppiWarpPerspective_32s_C3R, nppiWarpPerspectiveBack_32s_C3R},
|
|
{nppiWarpPerspective_32s_C4R, nppiWarpPerspectiveBack_32s_C4R}
|
|
};
|
|
static npp_warp_32f_t npp_warpPerspective_32f[][2] =
|
|
{
|
|
{0, 0},
|
|
{nppiWarpPerspective_32f_C1R, nppiWarpPerspectiveBack_32f_C1R},
|
|
{0, 0},
|
|
{nppiWarpPerspective_32f_C3R, nppiWarpPerspectiveBack_32f_C3R},
|
|
{nppiWarpPerspective_32f_C4R, nppiWarpPerspectiveBack_32f_C4R}
|
|
};
|
|
|
|
CV_Assert(M.rows == 3 && M.cols == 3);
|
|
|
|
double coeffs[3][3];
|
|
Mat coeffsMat(3, 3, CV_64F, (void*)coeffs);
|
|
M.convertTo(coeffsMat, coeffsMat.type());
|
|
|
|
nppWarpCaller(src, dst, coeffs, dsize, flags, npp_warpPerspective_8u, npp_warpPerspective_16u, npp_warpPerspective_32s, npp_warpPerspective_32f);
|
|
}
|
|
|
|
void cv::gpu::rotate(const GpuMat& src, GpuMat& dst, Size dsize, double angle, double xShift, double yShift, int interpolation)
|
|
{
|
|
static const int npp_inter[] = {NPPI_INTER_NN, NPPI_INTER_LINEAR, NPPI_INTER_CUBIC};
|
|
|
|
CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC4);
|
|
CV_Assert(interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || interpolation == INTER_CUBIC);
|
|
|
|
dst.create(dsize, src.type());
|
|
|
|
NppiSize srcsz;
|
|
srcsz.height = src.rows;
|
|
srcsz.width = src.cols;
|
|
NppiRect srcroi;
|
|
srcroi.x = srcroi.y = 0;
|
|
srcroi.height = src.rows;
|
|
srcroi.width = src.cols;
|
|
NppiRect dstroi;
|
|
dstroi.x = dstroi.y = 0;
|
|
dstroi.height = dst.rows;
|
|
dstroi.width = dst.cols;
|
|
|
|
if (src.channels() == 1)
|
|
{
|
|
nppiRotate_8u_C1R((const Npp8u*)src.ptr<char>(), srcsz, src.step, srcroi,
|
|
(Npp8u*)dst.ptr<char>(), dst.step, dstroi, angle, xShift, yShift, npp_inter[interpolation]);
|
|
}
|
|
else
|
|
{
|
|
nppiRotate_8u_C4R((const Npp8u*)src.ptr<char>(), srcsz, src.step, srcroi,
|
|
(Npp8u*)dst.ptr<char>(), dst.step, dstroi, angle, xShift, yShift, npp_inter[interpolation]);
|
|
}
|
|
}
|
|
|
|
#endif /* !defined (HAVE_CUDA) */ |