2012-08-29 20:49:07 +08:00
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/*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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2012-10-02 02:37:20 +08:00
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#if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)
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2012-08-29 20:49:07 +08:00
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2012-08-30 14:35:32 +08:00
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void cv::gpu::bilateralFilter(const GpuMat&, GpuMat&, int, float, float, int, Stream&) { throw_nogpu(); }
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void cv::gpu::nonLocalMeans(const GpuMat&, GpuMat&, float, int, int, int, Stream&) { throw_nogpu(); }
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2012-08-29 20:49:07 +08:00
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#else
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namespace cv { namespace gpu { namespace device
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{
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namespace imgproc
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{
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template<typename T>
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void bilateral_filter_gpu(const PtrStepSzb& src, PtrStepSzb dst, int kernel_size, float sigma_spatial, float sigma_color, int borderMode, cudaStream_t stream);
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template<typename T>
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void nlm_bruteforce_gpu(const PtrStepSzb& src, PtrStepSzb dst, int search_radius, int block_radius, float h, int borderMode, cudaStream_t stream);
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}
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}}}
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void cv::gpu::bilateralFilter(const GpuMat& src, GpuMat& dst, int kernel_size, float sigma_color, float sigma_spatial, int borderMode, Stream& s)
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{
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using cv::gpu::device::imgproc::bilateral_filter_gpu;
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typedef void (*func_t)(const PtrStepSzb& src, PtrStepSzb dst, int kernel_size, float sigma_spatial, float sigma_color, int borderMode, cudaStream_t s);
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static const func_t funcs[6][4] =
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{
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{bilateral_filter_gpu<uchar> , 0 /*bilateral_filter_gpu<uchar2>*/ , bilateral_filter_gpu<uchar3> , bilateral_filter_gpu<uchar4> },
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{0 /*bilateral_filter_gpu<schar>*/, 0 /*bilateral_filter_gpu<schar2>*/ , 0 /*bilateral_filter_gpu<schar3>*/, 0 /*bilateral_filter_gpu<schar4>*/},
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{bilateral_filter_gpu<ushort> , 0 /*bilateral_filter_gpu<ushort2>*/, bilateral_filter_gpu<ushort3> , bilateral_filter_gpu<ushort4> },
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{bilateral_filter_gpu<short> , 0 /*bilateral_filter_gpu<short2>*/ , bilateral_filter_gpu<short3> , bilateral_filter_gpu<short4> },
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{0 /*bilateral_filter_gpu<int>*/ , 0 /*bilateral_filter_gpu<int2>*/ , 0 /*bilateral_filter_gpu<int3>*/ , 0 /*bilateral_filter_gpu<int4>*/ },
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{bilateral_filter_gpu<float> , 0 /*bilateral_filter_gpu<float2>*/ , bilateral_filter_gpu<float3> , bilateral_filter_gpu<float4> }
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};
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sigma_color = (sigma_color <= 0 ) ? 1 : sigma_color;
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sigma_spatial = (sigma_spatial <= 0 ) ? 1 : sigma_spatial;
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2012-08-30 14:35:32 +08:00
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2012-08-29 20:49:07 +08:00
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int radius = (kernel_size <= 0) ? cvRound(sigma_spatial*1.5) : kernel_size/2;
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kernel_size = std::max(radius, 1)*2 + 1;
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CV_Assert(src.depth() <= CV_32F && src.channels() <= 4);
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const func_t func = funcs[src.depth()][src.channels() - 1];
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CV_Assert(func != 0);
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CV_Assert(borderMode == BORDER_REFLECT101 || borderMode == BORDER_REPLICATE || borderMode == BORDER_CONSTANT || borderMode == BORDER_REFLECT || borderMode == BORDER_WRAP);
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int gpuBorderType;
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CV_Assert(tryConvertToGpuBorderType(borderMode, gpuBorderType));
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dst.create(src.size(), src.type());
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func(src, dst, kernel_size, sigma_spatial, sigma_color, gpuBorderType, StreamAccessor::getStream(s));
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}
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void cv::gpu::nonLocalMeans(const GpuMat& src, GpuMat& dst, float h, int search_window_size, int block_size, int borderMode, Stream& s)
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{
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using cv::gpu::device::imgproc::nlm_bruteforce_gpu;
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typedef void (*func_t)(const PtrStepSzb& src, PtrStepSzb dst, int search_radius, int block_radius, float h, int borderMode, cudaStream_t stream);
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static const func_t funcs[4] = { nlm_bruteforce_gpu<uchar>, 0 /*nlm_bruteforce_gpu<uchar2>*/ , nlm_bruteforce_gpu<uchar3>, 0/*nlm_bruteforce_gpu<uchar4>,*/ };
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CV_Assert(src.type() == CV_8U || src.type() == CV_8UC3);
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const func_t func = funcs[src.channels() - 1];
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CV_Assert(func != 0);
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int b = borderMode;
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CV_Assert(b == BORDER_REFLECT101 || b == BORDER_REPLICATE || b == BORDER_CONSTANT || b == BORDER_REFLECT || b == BORDER_WRAP);
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int gpuBorderType;
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CV_Assert(tryConvertToGpuBorderType(borderMode, gpuBorderType));
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int search_radius = search_window_size/2;
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int block_radius = block_size/2;
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dst.create(src.size(), src.type());
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func(src, dst, search_radius, block_radius, h, gpuBorderType, StreamAccessor::getStream(s));
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}
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2012-08-30 14:35:32 +08:00
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#endif
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