/*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. // Copyright (C) 2013, OpenCV Foundation, 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 materials 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 implied warranties, including, but not limited to, the implied // 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*/ #pragma once #ifndef __OPENCV_CUDEV_GRID_REDUCE_TO_VEC_HPP__ #define __OPENCV_CUDEV_GRID_REDUCE_TO_VEC_HPP__ #include "../common.hpp" #include "../util/vec_traits.hpp" #include "../util/limits.hpp" #include "../util/saturate_cast.hpp" #include "../ptr2d/traits.hpp" #include "../ptr2d/gpumat.hpp" #include "../ptr2d/mask.hpp" #include "../functional/functional.hpp" #include "detail/reduce_to_column.hpp" #include "detail/reduce_to_row.hpp" namespace cv { namespace cudev { //! @addtogroup cudev //! @{ template struct Sum : plus { typedef T work_type; template struct rebind { typedef Sum other; }; __device__ __forceinline__ static T initialValue() { return VecTraits::all(0); } __device__ __forceinline__ static T result(T r, int) { return r; } }; template struct Avg : plus { typedef T work_type; template struct rebind { typedef Avg other; }; __device__ __forceinline__ static T initialValue() { return VecTraits::all(0); } __device__ __forceinline__ static T result(T r, float sz) { return saturate_cast(r / sz); } }; template struct Min : minimum { typedef T work_type; template struct rebind { typedef Min other; }; __device__ __forceinline__ static T initialValue() { return VecTraits::all(numeric_limits::elem_type>::max()); } __device__ __forceinline__ static T result(T r, int) { return r; } }; template struct Max : maximum { typedef T work_type; template struct rebind { typedef Max other; }; __device__ __forceinline__ static T initialValue() { return VecTraits::all(-numeric_limits::elem_type>::max()); } __device__ __forceinline__ static T result(T r, int) { return r; } }; template __host__ void gridReduceToRow(const SrcPtr& src, GpuMat_& dst, const MaskPtr& mask, Stream& stream = Stream::Null()) { const int rows = getRows(src); const int cols = getCols(src); CV_Assert( getRows(mask) == rows && getCols(mask) == cols ); dst.create(1, cols); grid_reduce_to_vec_detail::reduceToRow(shrinkPtr(src), dst[0], shrinkPtr(mask), rows, cols, StreamAccessor::getStream(stream)); } template __host__ void gridReduceToRow(const SrcPtr& src, GpuMat_& dst, Stream& stream = Stream::Null()) { const int rows = getRows(src); const int cols = getCols(src); dst.create(1, cols); grid_reduce_to_vec_detail::reduceToRow(shrinkPtr(src), dst[0], WithOutMask(), rows, cols, StreamAccessor::getStream(stream)); } template __host__ void gridReduceToColumn_(const SrcPtr& src, GpuMat_& dst, const MaskPtr& mask, Stream& stream = Stream::Null()) { const int rows = getRows(src); const int cols = getCols(src); CV_Assert( getRows(mask) == rows && getCols(mask) == cols ); dst.create(1, rows); grid_reduce_to_vec_detail::reduceToColumn(shrinkPtr(src), dst[0], shrinkPtr(mask), rows, cols, StreamAccessor::getStream(stream)); } template __host__ void gridReduceToColumn_(const SrcPtr& src, GpuMat_& dst, Stream& stream = Stream::Null()) { const int rows = getRows(src); const int cols = getCols(src); dst.create(1, rows); grid_reduce_to_vec_detail::reduceToColumn(shrinkPtr(src), dst[0], WithOutMask(), rows, cols, StreamAccessor::getStream(stream)); } // default policy struct DefaultReduceToVecPolicy { enum { block_size_x = 32, block_size_y = 8 }; }; template __host__ void gridReduceToColumn(const SrcPtr& src, GpuMat_& dst, const MaskPtr& mask, Stream& stream = Stream::Null()) { gridReduceToColumn_(src, dst, mask, stream); } template __host__ void gridReduceToColumn(const SrcPtr& src, GpuMat_& dst, Stream& stream = Stream::Null()) { gridReduceToColumn_(src, dst, stream); } //! @} }} #endif