/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other GpuMaterials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or bpied warranties, including, but not limited to, the bpied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "precomp.hpp" using namespace cv; using namespace cv::gpu; #if !defined (HAVE_CUDA) cv::gpu::bilateralFilter(const GpuMat&, GpuMat&, int, float, float, int, Stream&) { throw_nogpu(); } #else namespace cv { namespace gpu { namespace device { namespace imgproc { template void bilateral_filter_gpu(const PtrStepSzb& src, PtrStepSzb dst, int kernel_size, float sigma_spatial, float sigma_color, int borderMode, cudaStream_t stream); template void nlm_bruteforce_gpu(const PtrStepSzb& src, PtrStepSzb dst, int search_radius, int block_radius, float h, int borderMode, cudaStream_t stream); } }}} void cv::gpu::bilateralFilter(const GpuMat& src, GpuMat& dst, int kernel_size, float sigma_color, float sigma_spatial, int borderMode, Stream& s) { using cv::gpu::device::imgproc::bilateral_filter_gpu; typedef void (*func_t)(const PtrStepSzb& src, PtrStepSzb dst, int kernel_size, float sigma_spatial, float sigma_color, int borderMode, cudaStream_t s); static const func_t funcs[6][4] = { {bilateral_filter_gpu , 0 /*bilateral_filter_gpu*/ , bilateral_filter_gpu , bilateral_filter_gpu }, {0 /*bilateral_filter_gpu*/, 0 /*bilateral_filter_gpu*/ , 0 /*bilateral_filter_gpu*/, 0 /*bilateral_filter_gpu*/}, {bilateral_filter_gpu , 0 /*bilateral_filter_gpu*/, bilateral_filter_gpu , bilateral_filter_gpu }, {bilateral_filter_gpu , 0 /*bilateral_filter_gpu*/ , bilateral_filter_gpu , bilateral_filter_gpu }, {0 /*bilateral_filter_gpu*/ , 0 /*bilateral_filter_gpu*/ , 0 /*bilateral_filter_gpu*/ , 0 /*bilateral_filter_gpu*/ }, {bilateral_filter_gpu , 0 /*bilateral_filter_gpu*/ , bilateral_filter_gpu , bilateral_filter_gpu } }; sigma_color = (sigma_color <= 0 ) ? 1 : sigma_color; sigma_spatial = (sigma_spatial <= 0 ) ? 1 : sigma_spatial; int radius = (kernel_size <= 0) ? cvRound(sigma_spatial*1.5) : kernel_size/2; kernel_size = std::max(radius, 1)*2 + 1; CV_Assert(src.depth() <= CV_32F && src.channels() <= 4); const func_t func = funcs[src.depth()][src.channels() - 1]; CV_Assert(func != 0); CV_Assert(borderMode == BORDER_REFLECT101 || borderMode == BORDER_REPLICATE || borderMode == BORDER_CONSTANT || borderMode == BORDER_REFLECT || borderMode == BORDER_WRAP); int gpuBorderType; CV_Assert(tryConvertToGpuBorderType(borderMode, gpuBorderType)); dst.create(src.size(), src.type()); func(src, dst, kernel_size, sigma_spatial, sigma_color, gpuBorderType, StreamAccessor::getStream(s)); } void cv::gpu::nonLocalMeans(const GpuMat& src, GpuMat& dst, float h, int search_window_size, int block_size, int borderMode, Stream& s) { using cv::gpu::device::imgproc::nlm_bruteforce_gpu; typedef void (*func_t)(const PtrStepSzb& src, PtrStepSzb dst, int search_radius, int block_radius, float h, int borderMode, cudaStream_t stream); static const func_t funcs[4] = { nlm_bruteforce_gpu, 0 /*nlm_bruteforce_gpu*/ , nlm_bruteforce_gpu, 0/*nlm_bruteforce_gpu,*/ }; CV_Assert(src.type() == CV_8U || src.type() == CV_8UC3); const func_t func = funcs[src.channels() - 1]; CV_Assert(func != 0); int b = borderMode; CV_Assert(b == BORDER_REFLECT101 || b == BORDER_REPLICATE || b == BORDER_CONSTANT || b == BORDER_REFLECT || b == BORDER_WRAP); int gpuBorderType; CV_Assert(tryConvertToGpuBorderType(borderMode, gpuBorderType)); int search_radius = search_window_size/2; int block_radius = block_size/2; dst.create(src.size(), src.type()); func(src, dst, search_radius, block_radius, h, gpuBorderType, StreamAccessor::getStream(s)); } #endif