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131 lines
5.0 KiB
C++
131 lines
5.0 KiB
C++
/*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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#ifndef __OPENCV_GPU_TRANSFORM_HPP__
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#define __OPENCV_GPU_TRANSFORM_HPP__
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#include "internal_shared.hpp"
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namespace cv { namespace gpu { namespace device
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{
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//! Mask accessor
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template<class T> struct MaskReader_
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{
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PtrStep_<T> mask;
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explicit MaskReader_(PtrStep_<T> mask): mask(mask) {}
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__device__ bool operator()(int y, int x) const { return mask.ptr(y)[x]; }
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};
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//! Stub mask accessor
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struct NoMask
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{
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__device__ bool operator()(int y, int x) const { return true; }
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};
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//! Transform kernels
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template <typename T, typename D, typename UnOp, typename Mask>
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static __global__ void transform(const DevMem2D_<T> src, PtrStep_<D> dst, const Mask mask, UnOp op)
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{
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const int x = blockDim.x * blockIdx.x + threadIdx.x;
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const int y = blockDim.y * blockIdx.y + threadIdx.y;
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if (x < src.cols && y < src.rows && mask(y, x))
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{
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T src_data = src.ptr(y)[x];
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dst.ptr(y)[x] = op(src_data);
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}
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}
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template <typename T1, typename T2, typename D, typename BinOp, typename Mask>
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static __global__ void transform(const DevMem2D_<T1> src1, const PtrStep_<T2> src2, PtrStep_<D> dst, const Mask mask, BinOp op)
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{
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const int x = blockDim.x * blockIdx.x + threadIdx.x;
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const int y = blockDim.y * blockIdx.y + threadIdx.y;
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if (x < src1.cols && y < src1.rows && mask(y, x))
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{
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T1 src1_data = src1.ptr(y)[x];
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T2 src2_data = src2.ptr(y)[x];
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dst.ptr(y)[x] = op(src1_data, src2_data);
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}
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}
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}}}
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namespace cv
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{
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namespace gpu
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{
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template <typename T, typename D, typename UnOp>
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static void transform(const DevMem2D_<T>& src, const DevMem2D_<D>& dst, UnOp op, cudaStream_t stream)
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{
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dim3 threads(16, 16, 1);
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dim3 grid(1, 1, 1);
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grid.x = divUp(src.cols, threads.x);
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grid.y = divUp(src.rows, threads.y);
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device::transform<T, D><<<grid, threads, 0, stream>>>(src, dst, device::NoMask(), op);
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if (stream == 0)
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cudaSafeCall( cudaThreadSynchronize() );
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}
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template <typename T1, typename T2, typename D, typename BinOp>
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static void transform(const DevMem2D_<T1>& src1, const DevMem2D_<T2>& src2, const DevMem2D_<D>& dst, BinOp op, cudaStream_t stream)
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{
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dim3 threads(16, 16, 1);
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dim3 grid(1, 1, 1);
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grid.x = divUp(src1.cols, threads.x);
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grid.y = divUp(src1.rows, threads.y);
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device::transform<T1, T2, D><<<grid, threads, 0, stream>>>(src1, src2, dst, device::NoMask(), op);
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if (stream == 0)
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cudaSafeCall( cudaThreadSynchronize() );
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}
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}
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}
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#endif // __OPENCV_GPU_TRANSFORM_HPP__
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