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357 lines
9.8 KiB
Plaintext
357 lines
9.8 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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#include "opencv2/core/private.cuda.hpp"
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using namespace cv;
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using namespace cv::cuda;
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using namespace cv::cudev;
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namespace
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{
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template <typename ScalarDepth> struct TransformPolicy : DefaultTransformPolicy
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{
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};
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template <> struct TransformPolicy<double> : DefaultTransformPolicy
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{
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enum {
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shift = 1
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};
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};
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}
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//////////////////////////////////////////////////////////////////////////////
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/// abs
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namespace
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{
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template <typename T>
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void absMat(const GpuMat& src, const GpuMat& dst, Stream& stream)
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{
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gridTransformUnary_< TransformPolicy<T> >(globPtr<T>(src), globPtr<T>(dst), abs_func<T>(), stream);
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}
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}
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void cv::cuda::abs(InputArray _src, OutputArray _dst, Stream& stream)
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{
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typedef void (*func_t)(const GpuMat& src, const GpuMat& dst, Stream& stream);
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static const func_t funcs[] =
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{
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absMat<uchar>,
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absMat<schar>,
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absMat<ushort>,
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absMat<short>,
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absMat<int>,
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absMat<float>,
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absMat<double>
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};
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GpuMat src = getInputMat(_src, stream);
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CV_Assert( src.depth() <= CV_64F );
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GpuMat dst = getOutputMat(_dst, src.size(), src.type(), stream);
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funcs[src.depth()](src.reshape(1), dst.reshape(1), stream);
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syncOutput(dst, _dst, stream);
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}
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//////////////////////////////////////////////////////////////////////////////
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/// sqr
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namespace
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{
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template <typename T> struct SqrOp : unary_function<T, T>
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{
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__device__ __forceinline__ T operator ()(T x) const
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{
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return cudev::saturate_cast<T>(x * x);
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}
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};
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template <typename T>
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void sqrMat(const GpuMat& src, const GpuMat& dst, Stream& stream)
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{
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gridTransformUnary_< TransformPolicy<T> >(globPtr<T>(src), globPtr<T>(dst), SqrOp<T>(), stream);
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}
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}
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void cv::cuda::sqr(InputArray _src, OutputArray _dst, Stream& stream)
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{
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typedef void (*func_t)(const GpuMat& src, const GpuMat& dst, Stream& stream);
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static const func_t funcs[] =
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{
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sqrMat<uchar>,
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sqrMat<schar>,
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sqrMat<ushort>,
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sqrMat<short>,
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sqrMat<int>,
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sqrMat<float>,
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sqrMat<double>
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};
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GpuMat src = getInputMat(_src, stream);
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CV_Assert( src.depth() <= CV_64F );
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GpuMat dst = getOutputMat(_dst, src.size(), src.type(), stream);
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funcs[src.depth()](src.reshape(1), dst.reshape(1), stream);
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syncOutput(dst, _dst, stream);
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}
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//////////////////////////////////////////////////////////////////////////////
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/// sqrt
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namespace
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{
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template <typename T>
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void sqrtMat(const GpuMat& src, const GpuMat& dst, Stream& stream)
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{
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gridTransformUnary_< TransformPolicy<T> >(globPtr<T>(src), globPtr<T>(dst), sqrt_func<T>(), stream);
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}
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}
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void cv::cuda::sqrt(InputArray _src, OutputArray _dst, Stream& stream)
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{
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typedef void (*func_t)(const GpuMat& src, const GpuMat& dst, Stream& stream);
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static const func_t funcs[] =
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{
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sqrtMat<uchar>,
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sqrtMat<schar>,
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sqrtMat<ushort>,
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sqrtMat<short>,
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sqrtMat<int>,
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sqrtMat<float>,
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sqrtMat<double>
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};
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GpuMat src = getInputMat(_src, stream);
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CV_Assert( src.depth() <= CV_64F );
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GpuMat dst = getOutputMat(_dst, src.size(), src.type(), stream);
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funcs[src.depth()](src.reshape(1), dst.reshape(1), stream);
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syncOutput(dst, _dst, stream);
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}
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////////////////////////////////////////////////////////////////////////
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/// exp
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namespace
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{
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template <typename T> struct ExpOp : unary_function<T, T>
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{
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__device__ __forceinline__ T operator ()(T x) const
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{
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exp_func<T> f;
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return cudev::saturate_cast<T>(f(x));
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}
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};
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template <typename T>
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void expMat(const GpuMat& src, const GpuMat& dst, Stream& stream)
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{
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gridTransformUnary_< TransformPolicy<T> >(globPtr<T>(src), globPtr<T>(dst), ExpOp<T>(), stream);
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}
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}
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void cv::cuda::exp(InputArray _src, OutputArray _dst, Stream& stream)
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{
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typedef void (*func_t)(const GpuMat& src, const GpuMat& dst, Stream& stream);
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static const func_t funcs[] =
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{
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expMat<uchar>,
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expMat<schar>,
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expMat<ushort>,
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expMat<short>,
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expMat<int>,
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expMat<float>,
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expMat<double>
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};
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GpuMat src = getInputMat(_src, stream);
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CV_Assert( src.depth() <= CV_64F );
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GpuMat dst = getOutputMat(_dst, src.size(), src.type(), stream);
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funcs[src.depth()](src.reshape(1), dst.reshape(1), stream);
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syncOutput(dst, _dst, stream);
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}
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////////////////////////////////////////////////////////////////////////
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// log
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namespace
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{
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template <typename T>
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void logMat(const GpuMat& src, const GpuMat& dst, Stream& stream)
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{
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gridTransformUnary_< TransformPolicy<T> >(globPtr<T>(src), globPtr<T>(dst), log_func<T>(), stream);
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}
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}
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void cv::cuda::log(InputArray _src, OutputArray _dst, Stream& stream)
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{
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typedef void (*func_t)(const GpuMat& src, const GpuMat& dst, Stream& stream);
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static const func_t funcs[] =
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{
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logMat<uchar>,
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logMat<schar>,
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logMat<ushort>,
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logMat<short>,
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logMat<int>,
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logMat<float>,
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logMat<double>
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};
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GpuMat src = getInputMat(_src, stream);
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CV_Assert( src.depth() <= CV_64F );
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GpuMat dst = getOutputMat(_dst, src.size(), src.type(), stream);
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funcs[src.depth()](src.reshape(1), dst.reshape(1), stream);
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syncOutput(dst, _dst, stream);
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}
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////////////////////////////////////////////////////////////////////////
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// pow
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namespace
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{
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template<typename T, bool Signed = numeric_limits<T>::is_signed> struct PowOp : unary_function<T, T>
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{
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float power;
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__device__ __forceinline__ T operator()(T e) const
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{
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return cudev::saturate_cast<T>(__powf((float)e, power));
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}
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};
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template<typename T> struct PowOp<T, true> : unary_function<T, T>
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{
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float power;
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__device__ __forceinline__ T operator()(T e) const
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{
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T res = cudev::saturate_cast<T>(__powf((float)e, power));
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if ((e < 0) && (1 & static_cast<int>(power)))
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res *= -1;
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return res;
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}
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};
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template<> struct PowOp<float> : unary_function<float, float>
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{
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float power;
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__device__ __forceinline__ float operator()(float e) const
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{
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return __powf(::fabs(e), power);
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}
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};
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template<> struct PowOp<double> : unary_function<double, double>
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{
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double power;
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__device__ __forceinline__ double operator()(double e) const
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{
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return ::pow(::fabs(e), power);
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}
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};
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template<typename T>
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void powMat(const GpuMat& src, double power, const GpuMat& dst, Stream& stream)
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{
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PowOp<T> op;
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op.power = static_cast<typename LargerType<T, float>::type>(power);
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gridTransformUnary_< TransformPolicy<T> >(globPtr<T>(src), globPtr<T>(dst), op, stream);
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}
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}
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void cv::cuda::pow(InputArray _src, double power, OutputArray _dst, Stream& stream)
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{
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typedef void (*func_t)(const GpuMat& src, double power, const GpuMat& dst, Stream& stream);
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static const func_t funcs[] =
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{
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powMat<uchar>,
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powMat<schar>,
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powMat<ushort>,
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powMat<short>,
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powMat<int>,
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powMat<float>,
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powMat<double>
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};
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GpuMat src = getInputMat(_src, stream);
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CV_Assert( src.depth() <= CV_64F );
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GpuMat dst = getOutputMat(_dst, src.size(), src.type(), stream);
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funcs[src.depth()](src.reshape(1), power, dst.reshape(1), stream);
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syncOutput(dst, _dst, stream);
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}
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#endif
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