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298 lines
12 KiB
Plaintext
298 lines
12 KiB
Plaintext
/*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 materials 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 implied warranties, including, but not limited to, the implied
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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 "opencv2/opencv_modules.hpp"
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#ifndef HAVE_OPENCV_CUDEV
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#error "opencv_cudev is required"
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#else
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#include "opencv2/cudaarithm.hpp"
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#include "opencv2/cudev.hpp"
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using namespace cv::cudev;
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namespace
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{
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template <typename T, typename S, typename D>
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void reduceToRowImpl(const GpuMat& _src, GpuMat& _dst, int reduceOp, Stream& stream)
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{
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const GpuMat_<T>& src = (const GpuMat_<T>&) _src;
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GpuMat_<D>& dst = (GpuMat_<D>&) _dst;
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switch (reduceOp)
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{
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case cv::REDUCE_SUM:
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gridReduceToRow< Sum<S> >(src, dst, stream);
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break;
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case cv::REDUCE_AVG:
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gridReduceToRow< Avg<S> >(src, dst, stream);
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break;
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case cv::REDUCE_MIN:
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gridReduceToRow< Min<S> >(src, dst, stream);
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break;
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case cv::REDUCE_MAX:
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gridReduceToRow< Max<S> >(src, dst, stream);
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break;
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};
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}
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template <typename T, typename S, typename D>
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void reduceToColumnImpl_(const GpuMat& _src, GpuMat& _dst, int reduceOp, Stream& stream)
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{
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const GpuMat_<T>& src = (const GpuMat_<T>&) _src;
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GpuMat_<D>& dst = (GpuMat_<D>&) _dst;
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switch (reduceOp)
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{
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case cv::REDUCE_SUM:
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gridReduceToColumn< Sum<S> >(src, dst, stream);
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break;
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case cv::REDUCE_AVG:
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gridReduceToColumn< Avg<S> >(src, dst, stream);
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break;
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case cv::REDUCE_MIN:
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gridReduceToColumn< Min<S> >(src, dst, stream);
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break;
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case cv::REDUCE_MAX:
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gridReduceToColumn< Max<S> >(src, dst, stream);
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break;
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};
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}
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template <typename T, typename S, typename D>
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void reduceToColumnImpl(const GpuMat& src, GpuMat& dst, int reduceOp, Stream& stream)
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{
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typedef void (*func_t)(const GpuMat& src, GpuMat& dst, int reduceOp, Stream& stream);
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static const func_t funcs[4] =
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{
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reduceToColumnImpl_<T, S, D>,
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reduceToColumnImpl_<typename MakeVec<T, 2>::type, typename MakeVec<S, 2>::type, typename MakeVec<D, 2>::type>,
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reduceToColumnImpl_<typename MakeVec<T, 3>::type, typename MakeVec<S, 3>::type, typename MakeVec<D, 3>::type>,
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reduceToColumnImpl_<typename MakeVec<T, 4>::type, typename MakeVec<S, 4>::type, typename MakeVec<D, 4>::type>
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};
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funcs[src.channels() - 1](src, dst, reduceOp, stream);
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}
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}
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void cv::cuda::reduce(InputArray _src, OutputArray _dst, int dim, int reduceOp, int dtype, Stream& stream)
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{
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GpuMat src = _src.getGpuMat();
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CV_Assert( src.channels() <= 4 );
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CV_Assert( dim == 0 || dim == 1 );
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CV_Assert( reduceOp == REDUCE_SUM || reduceOp == REDUCE_AVG || reduceOp == REDUCE_MAX || reduceOp == REDUCE_MIN );
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if (dtype < 0)
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dtype = src.depth();
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_dst.create(1, dim == 0 ? src.cols : src.rows, CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), src.channels()));
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GpuMat dst = _dst.getGpuMat();
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if (dim == 0)
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{
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typedef void (*func_t)(const GpuMat& _src, GpuMat& _dst, int reduceOp, Stream& stream);
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static const func_t funcs[7][7] =
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{
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{
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reduceToRowImpl<uchar, int, uchar>,
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0 /*reduceToRowImpl<uchar, int, schar>*/,
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0 /*reduceToRowImpl<uchar, int, ushort>*/,
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0 /*reduceToRowImpl<uchar, int, short>*/,
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reduceToRowImpl<uchar, int, int>,
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reduceToRowImpl<uchar, float, float>,
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reduceToRowImpl<uchar, double, double>
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},
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{
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0 /*reduceToRowImpl<schar, int, uchar>*/,
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0 /*reduceToRowImpl<schar, int, schar>*/,
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0 /*reduceToRowImpl<schar, int, ushort>*/,
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0 /*reduceToRowImpl<schar, int, short>*/,
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0 /*reduceToRowImpl<schar, int, int>*/,
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0 /*reduceToRowImpl<schar, float, float>*/,
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0 /*reduceToRowImpl<schar, double, double>*/
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},
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{
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0 /*reduceToRowImpl<ushort, int, uchar>*/,
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0 /*reduceToRowImpl<ushort, int, schar>*/,
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reduceToRowImpl<ushort, int, ushort>,
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0 /*reduceToRowImpl<ushort, int, short>*/,
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reduceToRowImpl<ushort, int, int>,
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reduceToRowImpl<ushort, float, float>,
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reduceToRowImpl<ushort, double, double>
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},
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{
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0 /*reduceToRowImpl<short, int, uchar>*/,
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0 /*reduceToRowImpl<short, int, schar>*/,
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0 /*reduceToRowImpl<short, int, ushort>*/,
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reduceToRowImpl<short, int, short>,
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reduceToRowImpl<short, int, int>,
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reduceToRowImpl<short, float, float>,
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reduceToRowImpl<short, double, double>
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},
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{
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0 /*reduceToRowImpl<int, int, uchar>*/,
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0 /*reduceToRowImpl<int, int, schar>*/,
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0 /*reduceToRowImpl<int, int, ushort>*/,
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0 /*reduceToRowImpl<int, int, short>*/,
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reduceToRowImpl<int, int, int>,
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reduceToRowImpl<int, float, float>,
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reduceToRowImpl<int, double, double>
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},
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{
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0 /*reduceToRowImpl<float, float, uchar>*/,
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0 /*reduceToRowImpl<float, float, schar>*/,
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0 /*reduceToRowImpl<float, float, ushort>*/,
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0 /*reduceToRowImpl<float, float, short>*/,
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0 /*reduceToRowImpl<float, float, int>*/,
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reduceToRowImpl<float, float, float>,
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reduceToRowImpl<float, double, double>
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},
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{
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0 /*reduceToRowImpl<double, double, uchar>*/,
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0 /*reduceToRowImpl<double, double, schar>*/,
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0 /*reduceToRowImpl<double, double, ushort>*/,
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0 /*reduceToRowImpl<double, double, short>*/,
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0 /*reduceToRowImpl<double, double, int>*/,
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0 /*reduceToRowImpl<double, double, float>*/,
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reduceToRowImpl<double, double, double>
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}
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};
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const func_t func = funcs[src.depth()][dst.depth()];
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if (!func)
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CV_Error(cv::Error::StsUnsupportedFormat, "Unsupported combination of input and output array formats");
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GpuMat dst_cont = dst.reshape(1);
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func(src.reshape(1), dst_cont, reduceOp, stream);
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}
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else
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{
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typedef void (*func_t)(const GpuMat& _src, GpuMat& _dst, int reduceOp, Stream& stream);
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static const func_t funcs[7][7] =
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{
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{
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reduceToColumnImpl<uchar, int, uchar>,
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0 /*reduceToColumnImpl<uchar, int, schar>*/,
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0 /*reduceToColumnImpl<uchar, int, ushort>*/,
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0 /*reduceToColumnImpl<uchar, int, short>*/,
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reduceToColumnImpl<uchar, int, int>,
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reduceToColumnImpl<uchar, float, float>,
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reduceToColumnImpl<uchar, double, double>
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},
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{
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0 /*reduceToColumnImpl<schar, int, uchar>*/,
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0 /*reduceToColumnImpl<schar, int, schar>*/,
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0 /*reduceToColumnImpl<schar, int, ushort>*/,
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0 /*reduceToColumnImpl<schar, int, short>*/,
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0 /*reduceToColumnImpl<schar, int, int>*/,
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0 /*reduceToColumnImpl<schar, float, float>*/,
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0 /*reduceToColumnImpl<schar, double, double>*/
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},
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{
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0 /*reduceToColumnImpl<ushort, int, uchar>*/,
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0 /*reduceToColumnImpl<ushort, int, schar>*/,
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reduceToColumnImpl<ushort, int, ushort>,
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0 /*reduceToColumnImpl<ushort, int, short>*/,
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reduceToColumnImpl<ushort, int, int>,
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reduceToColumnImpl<ushort, float, float>,
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reduceToColumnImpl<ushort, double, double>
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},
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{
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0 /*reduceToColumnImpl<short, int, uchar>*/,
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0 /*reduceToColumnImpl<short, int, schar>*/,
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0 /*reduceToColumnImpl<short, int, ushort>*/,
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reduceToColumnImpl<short, int, short>,
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reduceToColumnImpl<short, int, int>,
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reduceToColumnImpl<short, float, float>,
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reduceToColumnImpl<short, double, double>
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},
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{
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0 /*reduceToColumnImpl<int, int, uchar>*/,
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0 /*reduceToColumnImpl<int, int, schar>*/,
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0 /*reduceToColumnImpl<int, int, ushort>*/,
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0 /*reduceToColumnImpl<int, int, short>*/,
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reduceToColumnImpl<int, int, int>,
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reduceToColumnImpl<int, float, float>,
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reduceToColumnImpl<int, double, double>
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},
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{
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0 /*reduceToColumnImpl<float, float, uchar>*/,
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0 /*reduceToColumnImpl<float, float, schar>*/,
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0 /*reduceToColumnImpl<float, float, ushort>*/,
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0 /*reduceToColumnImpl<float, float, short>*/,
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0 /*reduceToColumnImpl<float, float, int>*/,
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reduceToColumnImpl<float, float, float>,
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reduceToColumnImpl<float, double, double>
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},
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{
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0 /*reduceToColumnImpl<double, double, uchar>*/,
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0 /*reduceToColumnImpl<double, double, schar>*/,
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0 /*reduceToColumnImpl<double, double, ushort>*/,
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0 /*reduceToColumnImpl<double, double, short>*/,
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0 /*reduceToColumnImpl<double, double, int>*/,
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0 /*reduceToColumnImpl<double, double, float>*/,
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reduceToColumnImpl<double, double, double>
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}
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};
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const func_t func = funcs[src.depth()][dst.depth()];
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if (!func)
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CV_Error(cv::Error::StsUnsupportedFormat, "Unsupported combination of input and output array formats");
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func(src, dst, reduceOp, stream);
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}
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}
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#endif
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