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414 lines
17 KiB
Plaintext
414 lines
17 KiB
Plaintext
/*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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#include <stddef.h>
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#include <stdio.h>
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//#include <iostream>
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#include "cuda_shared.hpp"
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#include "cuda_runtime.h"
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using namespace cv::gpu;
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using namespace cv::gpu::impl;
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__constant__ __align__(16) double scalar_d[4];
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namespace mat_operators
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{
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///////////////////////////////////////////////////////////////////////////
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////////////////////////////////// CopyTo /////////////////////////////////
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///////////////////////////////////////////////////////////////////////////
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template<typename T>
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__global__ void kernel_copy_to_with_mask(T * mat_src, T * mat_dst, const unsigned char * mask, int cols, int rows, int step_mat, int step_mask, int channels)
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{
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size_t x = blockIdx.x * blockDim.x + threadIdx.x;
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size_t y = blockIdx.y * blockDim.y + threadIdx.y;
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if ((x < cols * channels ) && (y < rows))
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if (mask[y * step_mask + x / channels] != 0)
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{
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size_t idx = y * (step_mat / sizeof(T)) + x;
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mat_dst[idx] = mat_src[idx];
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}
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}
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///////////////////////////////////////////////////////////////////////////
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////////////////////////////////// SetTo //////////////////////////////////
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///////////////////////////////////////////////////////////////////////////
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template<typename T>
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__global__ void kernel_set_to_without_mask(T * mat, int cols, int rows, int step, int channels)
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{
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size_t x = blockIdx.x * blockDim.x + threadIdx.x;
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size_t y = blockIdx.y * blockDim.y + threadIdx.y;
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if ((x < cols * channels ) && (y < rows))
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{
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size_t idx = y * (step / sizeof(T)) + x;
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mat[idx] = scalar_d[ x % channels ];
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}
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}
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template<typename T>
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__global__ void kernel_set_to_with_mask(T * mat, const unsigned char * mask, int cols, int rows, int step, int channels, int step_mask)
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{
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size_t x = blockIdx.x * blockDim.x + threadIdx.x;
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size_t y = blockIdx.y * blockDim.y + threadIdx.y;
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if ((x < cols * channels ) && (y < rows))
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if (mask[y * step_mask + x / channels] != 0)
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{
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size_t idx = y * (step / sizeof(T)) + x;
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mat[idx] = scalar_d[ x % channels ];
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}
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}
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///////////////////////////////////////////////////////////////////////////
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//////////////////////////////// ConvertTo ////////////////////////////////
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///////////////////////////////////////////////////////////////////////////
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template <typename T, typename DT>
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struct ScaleTraits
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{
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__device__ static DT scale(T src, double alpha, double beta)
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{
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return (DT)__double2int_rn(alpha * src + beta);
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}
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};
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template <typename T>
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struct ScaleTraits<T, float>
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{
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__device__ static float scale(T src, double alpha, double beta)
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{
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return (float)(alpha * src + beta);
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}
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};
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template <typename T>
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struct ScaleTraits<T, double>
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{
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__device__ static double scale(T src, double alpha, double beta)
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{
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return alpha * src + beta;
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}
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};
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template <typename T, typename DT, size_t src_elem_size, size_t dst_elem_size>
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struct ReadWriteTraits
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{
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enum {shift=1};
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typedef T read_type;
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typedef DT write_type;
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};
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template <typename T, typename DT>
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struct ReadWriteTraits<T, DT, 1, 1>
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{
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enum {shift=4};
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typedef char4 read_type;
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typedef char4 write_type;
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};
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template <typename T, typename DT>
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struct ReadWriteTraits<T, DT, 2, 1>
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{
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enum {shift=4};
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typedef short4 read_type;
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typedef char4 write_type;
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};
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template <typename T, typename DT>
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struct ReadWriteTraits<T, DT, 4, 1>
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{
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enum {shift=4};
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typedef int4 read_type;
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typedef char4 write_type;
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};
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template <typename T, typename DT>
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struct ReadWriteTraits<T, DT, 1, 2>
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{
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enum {shift=2};
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typedef char2 read_type;
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typedef short2 write_type;
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};
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template <typename T, typename DT>
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struct ReadWriteTraits<T, DT, 2, 2>
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{
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enum {shift=2};
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typedef short2 read_type;
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typedef short2 write_type;
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};
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template <typename T, typename DT>
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struct ReadWriteTraits<T, DT, 4, 2>
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{
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enum {shift=2};
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typedef int2 read_type;
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typedef short2 write_type;
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};
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template <typename T, typename DT>
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__global__ static void kernel_convert_to(uchar* srcmat, size_t src_step, uchar* dstmat, size_t dst_step, size_t width, size_t height, double alpha, double beta)
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{
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typedef typename ReadWriteTraits<T, DT, sizeof(T), sizeof(DT)>::read_type read_type;
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typedef typename ReadWriteTraits<T, DT, sizeof(T), sizeof(DT)>::write_type write_type;
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const int shift = ReadWriteTraits<T, DT, sizeof(T), sizeof(DT)>::shift;
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const size_t x = threadIdx.x + blockIdx.x * blockDim.x;
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const size_t y = threadIdx.y + blockIdx.y * blockDim.y;
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if (y < height)
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{
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const T* src = (const T*)(srcmat + src_step * y);
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DT* dst = (DT*)(dstmat + dst_step * y);
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if ((x * shift) + shift - 1 < width)
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{
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read_type srcn_el = ((read_type*)src)[x];
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write_type dstn_el;
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const T* src1_el = (const T*) &srcn_el;
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DT* dst1_el = (DT*) &dstn_el;
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for (int i = 0; i < shift; ++i)
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dst1_el[i] = ScaleTraits<T, DT>::scale(src1_el[i], alpha, beta);
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((write_type*)dst)[x] = dstn_el;
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}
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else
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{
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for (int i = 0; i < shift - 1; ++i)
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if ((x * shift) + i < width)
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dst[(x * shift) + i] = ScaleTraits<T, DT>::scale(src[(x * shift) + i], alpha, beta);
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}
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}
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}
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} // namespace mat_operators
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namespace cv
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{
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namespace gpu
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{
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namespace impl
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{
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///////////////////////////////////////////////////////////////////////////
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////////////////////////////////// CopyTo /////////////////////////////////
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///////////////////////////////////////////////////////////////////////////
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typedef void (*CopyToFunc)(const DevMem2D& mat_src, const DevMem2D& mat_dst, const DevMem2D& mask, int channels);
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template<typename T>
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void copy_to_with_mask_run(const DevMem2D& mat_src, const DevMem2D& mat_dst, const DevMem2D& mask, int channels)
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{
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dim3 threadsPerBlock(16,16, 1);
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dim3 numBlocks ( divUp(mat_src.cols * channels , threadsPerBlock.x) , divUp(mat_src.rows , threadsPerBlock.y), 1);
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::mat_operators::kernel_copy_to_with_mask<T><<<numBlocks,threadsPerBlock>>>
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((T*)mat_src.ptr, (T*)mat_dst.ptr, (unsigned char*)mask.ptr, mat_src.cols, mat_src.rows, mat_src.step, mask.step, channels);
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cudaSafeCall ( cudaThreadSynchronize() );
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}
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extern "C" void copy_to_with_mask(const DevMem2D& mat_src, const DevMem2D& mat_dst, int depth, const DevMem2D& mask, int channels)
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{
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static CopyToFunc tab[8] =
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{
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copy_to_with_mask_run<unsigned char>,
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copy_to_with_mask_run<char>,
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copy_to_with_mask_run<unsigned short>,
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copy_to_with_mask_run<short>,
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copy_to_with_mask_run<int>,
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copy_to_with_mask_run<float>,
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copy_to_with_mask_run<double>,
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0
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};
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CopyToFunc func = tab[depth];
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if (func == 0) error("Operation \'ConvertTo\' doesn't supported on your GPU model", __FILE__, __LINE__);
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func(mat_src, mat_dst, mask, channels);
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}
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///////////////////////////////////////////////////////////////////////////
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////////////////////////////////// SetTo //////////////////////////////////
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///////////////////////////////////////////////////////////////////////////
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typedef void (*SetToFunc_with_mask)(const DevMem2D& mat, const DevMem2D& mask, int channels);
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typedef void (*SetToFunc_without_mask)(const DevMem2D& mat, int channels);
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template <typename T>
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void set_to_with_mask_run(const DevMem2D& mat, const DevMem2D& mask, int channels)
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{
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dim3 threadsPerBlock(32, 8, 1);
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dim3 numBlocks (mat.cols * channels / threadsPerBlock.x + 1, mat.rows / threadsPerBlock.y + 1, 1);
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::mat_operators::kernel_set_to_with_mask<T><<<numBlocks,threadsPerBlock>>>((T*)mat.ptr, (unsigned char *)mask.ptr, mat.cols, mat.rows, mat.step, channels, mask.step);
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cudaSafeCall ( cudaThreadSynchronize() );
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}
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template <typename T>
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void set_to_without_mask_run(const DevMem2D& mat, int channels)
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{
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dim3 threadsPerBlock(32, 8, 1);
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dim3 numBlocks (mat.cols * channels / threadsPerBlock.x + 1, mat.rows / threadsPerBlock.y + 1, 1);
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::mat_operators::kernel_set_to_without_mask<T><<<numBlocks,threadsPerBlock>>>((T*)mat.ptr, mat.cols, mat.rows, mat.step, channels);
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cudaSafeCall ( cudaThreadSynchronize() );
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}
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extern "C" void set_to_without_mask(const DevMem2D& mat, int depth, const double * scalar, int channels)
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{
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double data[4];
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data[0] = scalar[0];
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data[1] = scalar[1];
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data[2] = scalar[2];
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data[3] = scalar[3];
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cudaSafeCall( cudaMemcpyToSymbol(scalar_d, &data, sizeof(data)));
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static SetToFunc_without_mask tab[8] =
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{
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set_to_without_mask_run<unsigned char>,
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set_to_without_mask_run<char>,
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set_to_without_mask_run<unsigned short>,
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set_to_without_mask_run<short>,
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set_to_without_mask_run<int>,
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set_to_without_mask_run<float>,
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set_to_without_mask_run<double>,
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0
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};
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SetToFunc_without_mask func = tab[depth];
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if (func == 0) error("Operation \'ConvertTo\' doesn't supported on your GPU model", __FILE__, __LINE__);
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func(mat, channels);
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}
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extern "C" void set_to_with_mask(const DevMem2D& mat, int depth, const double * scalar, const DevMem2D& mask, int channels)
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{
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double data[4];
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data[0] = scalar[0];
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data[1] = scalar[1];
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data[2] = scalar[2];
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data[3] = scalar[3];
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cudaSafeCall( cudaMemcpyToSymbol(scalar_d, &data, sizeof(data)));
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static SetToFunc_with_mask tab[8] =
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{
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set_to_with_mask_run<unsigned char>,
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set_to_with_mask_run<char>,
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set_to_with_mask_run<unsigned short>,
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set_to_with_mask_run<short>,
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set_to_with_mask_run<int>,
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set_to_with_mask_run<float>,
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set_to_with_mask_run<double>,
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0
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};
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SetToFunc_with_mask func = tab[depth];
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if (func == 0) error("Operation \'ConvertTo\' doesn't supported on your GPU model", __FILE__, __LINE__);
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func(mat, mask, channels);
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}
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///////////////////////////////////////////////////////////////////////////
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//////////////////////////////// ConvertTo ////////////////////////////////
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///////////////////////////////////////////////////////////////////////////
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typedef void (*CvtFunc)(const DevMem2D& src, DevMem2D& dst, size_t width, size_t height, double alpha, double beta);
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template<typename T, typename DT>
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void cvt_(const DevMem2D& src, DevMem2D& dst, size_t width, size_t height, double alpha, double beta)
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{
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const int shift = ::mat_operators::ReadWriteTraits<T, DT, sizeof(T), sizeof(DT)>::shift;
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dim3 block(32, 8);
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dim3 grid(divUp(width, block.x * shift), divUp(height, block.y));
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::mat_operators::kernel_convert_to<T, DT><<<grid, block>>>(src.ptr, src.step, dst.ptr, dst.step, width, height, alpha, beta);
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cudaSafeCall( cudaThreadSynchronize() );
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}
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extern "C" void convert_to(const DevMem2D& src, int sdepth, DevMem2D dst, int ddepth, size_t width, size_t height, double alpha, double beta)
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{
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static CvtFunc tab[8][8] =
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{
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{cvt_<uchar, uchar>, cvt_<uchar, schar>, cvt_<uchar, ushort>, cvt_<uchar, short>,
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cvt_<uchar, int>, cvt_<uchar, float>, cvt_<uchar, double>, 0},
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{cvt_<schar, uchar>, cvt_<schar, schar>, cvt_<schar, ushort>, cvt_<schar, short>,
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cvt_<schar, int>, cvt_<schar, float>, cvt_<schar, double>, 0},
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{cvt_<ushort, uchar>, cvt_<ushort, schar>, cvt_<ushort, ushort>, cvt_<ushort, short>,
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cvt_<ushort, int>, cvt_<ushort, float>, cvt_<ushort, double>, 0},
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{cvt_<short, uchar>, cvt_<short, schar>, cvt_<short, ushort>, cvt_<short, short>,
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cvt_<short, int>, cvt_<short, float>, cvt_<short, double>, 0},
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{cvt_<int, uchar>, cvt_<int, schar>, cvt_<int, ushort>,
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cvt_<int, short>, cvt_<int, int>, cvt_<int, float>, cvt_<int, double>, 0},
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{cvt_<float, uchar>, cvt_<float, schar>, cvt_<float, ushort>,
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cvt_<float, short>, cvt_<float, int>, cvt_<float, float>, cvt_<float, double>, 0},
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{cvt_<double, uchar>, cvt_<double, schar>, cvt_<double, ushort>,
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cvt_<double, short>, cvt_<double, int>, cvt_<double, float>, cvt_<double, double>, 0},
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{0,0,0,0,0,0,0,0}
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};
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CvtFunc func = tab[sdepth][ddepth];
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if (func == 0)
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cv::gpu::error("Unsupported convert operation", __FILE__, __LINE__);
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func(src, dst, width, height, alpha, beta);
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}
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} // namespace impl
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} // namespace gpu
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} // namespace cv
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