/*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_BLOCK_VEC_DISTANCE_HPP__ #define __OPENCV_CUDEV_BLOCK_VEC_DISTANCE_HPP__ #include "../common.hpp" #include "../functional/functional.hpp" #include "../warp/reduce.hpp" #include "reduce.hpp" namespace cv { namespace cudev { //! @addtogroup cudev //! @{ // NormL1 template struct NormL1 { typedef int value_type; typedef uint result_type; result_type mySum; __device__ __forceinline__ NormL1() : mySum(0) {} __device__ __forceinline__ void reduceThread(value_type val1, value_type val2) { mySum = __sad(val1, val2, mySum); } __device__ __forceinline__ void reduceWarp(result_type* smem, uint tid) { warpReduce(smem, mySum, tid, plus()); } template __device__ __forceinline__ void reduceBlock(result_type* smem, uint tid) { blockReduce(smem, mySum, tid, plus()); } __device__ __forceinline__ operator result_type() const { return mySum; } }; template <> struct NormL1 { typedef float value_type; typedef float result_type; result_type mySum; __device__ __forceinline__ NormL1() : mySum(0.0f) {} __device__ __forceinline__ void reduceThread(value_type val1, value_type val2) { mySum += ::fabsf(val1 - val2); } __device__ __forceinline__ void reduceWarp(result_type* smem, uint tid) { warpReduce(smem, mySum, tid, plus()); } template __device__ __forceinline__ void reduceBlock(result_type* smem, uint tid) { blockReduce(smem, mySum, tid, plus()); } __device__ __forceinline__ operator result_type() const { return mySum; } }; // NormL2 struct NormL2 { typedef float value_type; typedef float result_type; result_type mySum; __device__ __forceinline__ NormL2() : mySum(0.0f) {} __device__ __forceinline__ void reduceThread(value_type val1, value_type val2) { const float diff = val1 - val2; mySum += diff * diff; } __device__ __forceinline__ void reduceWarp(result_type* smem, uint tid) { warpReduce(smem, mySum, tid, plus()); } template __device__ __forceinline__ void reduceBlock(result_type* smem, uint tid) { blockReduce(smem, mySum, tid, plus()); } __device__ __forceinline__ operator result_type() const { return ::sqrtf(mySum); } }; // NormHamming struct NormHamming { typedef int value_type; typedef int result_type; result_type mySum; __device__ __forceinline__ NormHamming() : mySum(0) {} __device__ __forceinline__ void reduceThread(value_type val1, value_type val2) { mySum += __popc(val1 ^ val2); } __device__ __forceinline__ void reduceWarp(result_type* smem, uint tid) { warpReduce(smem, mySum, tid, plus()); } template __device__ __forceinline__ void reduceBlock(result_type* smem, uint tid) { blockReduce(smem, mySum, tid, plus()); } __device__ __forceinline__ operator result_type() const { return mySum; } }; //! @} }} #endif