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- /*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_TRANSFORM_DETAIL_HPP
- #define OPENCV_CUDEV_GRID_TRANSFORM_DETAIL_HPP
- #include "../../common.hpp"
- #include "../../util/tuple.hpp"
- #include "../../util/saturate_cast.hpp"
- #include "../../util/vec_traits.hpp"
- #include "../../ptr2d/glob.hpp"
- #include "../../ptr2d/traits.hpp"
- namespace cv { namespace cudev {
- namespace grid_transform_detail
- {
- // OpUnroller
- template <int cn> struct OpUnroller;
- template <> struct OpUnroller<1>
- {
- template <typename T, typename D, class UnOp, class MaskPtr>
- __device__ __forceinline__ static void unroll(const T& src, D& dst, const UnOp& op, const MaskPtr& mask, int x_shifted, int y)
- {
- if (mask(y, x_shifted))
- dst.x = op(src.x);
- }
- template <typename T1, typename T2, typename D, class BinOp, class MaskPtr>
- __device__ __forceinline__ static void unroll(const T1& src1, const T2& src2, D& dst, const BinOp& op, const MaskPtr& mask, int x_shifted, int y)
- {
- if (mask(y, x_shifted))
- dst.x = op(src1.x, src2.x);
- }
- };
- template <> struct OpUnroller<2>
- {
- template <typename T, typename D, class UnOp, class MaskPtr>
- __device__ __forceinline__ static void unroll(const T& src, D& dst, const UnOp& op, const MaskPtr& mask, int x_shifted, int y)
- {
- if (mask(y, x_shifted))
- dst.x = op(src.x);
- if (mask(y, x_shifted + 1))
- dst.y = op(src.y);
- }
- template <typename T1, typename T2, typename D, class BinOp, class MaskPtr>
- __device__ __forceinline__ static void unroll(const T1& src1, const T2& src2, D& dst, const BinOp& op, const MaskPtr& mask, int x_shifted, int y)
- {
- if (mask(y, x_shifted))
- dst.x = op(src1.x, src2.x);
- if (mask(y, x_shifted + 1))
- dst.y = op(src1.y, src2.y);
- }
- };
- template <> struct OpUnroller<3>
- {
- template <typename T, typename D, class UnOp, class MaskPtr>
- __device__ __forceinline__ static void unroll(const T& src, D& dst, const UnOp& op, const MaskPtr& mask, int x_shifted, int y)
- {
- if (mask(y, x_shifted))
- dst.x = op(src.x);
- if (mask(y, x_shifted + 1))
- dst.y = op(src.y);
- if (mask(y, x_shifted + 2))
- dst.z = op(src.z);
- }
- template <typename T1, typename T2, typename D, class BinOp, class MaskPtr>
- __device__ __forceinline__ static void unroll(const T1& src1, const T2& src2, D& dst, const BinOp& op, const MaskPtr& mask, int x_shifted, int y)
- {
- if (mask(y, x_shifted))
- dst.x = op(src1.x, src2.x);
- if (mask(y, x_shifted + 1))
- dst.y = op(src1.y, src2.y);
- if (mask(y, x_shifted + 2))
- dst.z = op(src1.z, src2.z);
- }
- };
- template <> struct OpUnroller<4>
- {
- template <typename T, typename D, class UnOp, class MaskPtr>
- __device__ __forceinline__ static void unroll(const T& src, D& dst, const UnOp& op, const MaskPtr& mask, int x_shifted, int y)
- {
- if (mask(y, x_shifted))
- dst.x = op(src.x);
- if (mask(y, x_shifted + 1))
- dst.y = op(src.y);
- if (mask(y, x_shifted + 2))
- dst.z = op(src.z);
- if (mask(y, x_shifted + 3))
- dst.w = op(src.w);
- }
- template <typename T1, typename T2, typename D, class BinOp, class MaskPtr>
- __device__ __forceinline__ static void unroll(const T1& src1, const T2& src2, D& dst, const BinOp& op, const MaskPtr& mask, int x_shifted, int y)
- {
- if (mask(y, x_shifted))
- dst.x = op(src1.x, src2.x);
- if (mask(y, x_shifted + 1))
- dst.y = op(src1.y, src2.y);
- if (mask(y, x_shifted + 2))
- dst.z = op(src1.z, src2.z);
- if (mask(y, x_shifted + 3))
- dst.w = op(src1.w, src2.w);
- }
- };
- // transformSimple
- template <class SrcPtr, typename DstType, class UnOp, class MaskPtr>
- __global__ void transformSimple(const SrcPtr src, GlobPtr<DstType> dst, const UnOp op, const MaskPtr mask, const int rows, const int cols)
- {
- const int x = blockIdx.x * blockDim.x + threadIdx.x;
- const int y = blockIdx.y * blockDim.y + threadIdx.y;
- if (x >= cols || y >= rows || !mask(y, x))
- return;
- dst(y, x) = saturate_cast<DstType>(op(src(y, x)));
- }
- template <class SrcPtr1, class SrcPtr2, typename DstType, class BinOp, class MaskPtr>
- __global__ void transformSimple(const SrcPtr1 src1, const SrcPtr2 src2, GlobPtr<DstType> dst, const BinOp op, const MaskPtr mask, const int rows, const int cols)
- {
- const int x = blockIdx.x * blockDim.x + threadIdx.x;
- const int y = blockIdx.y * blockDim.y + threadIdx.y;
- if (x >= cols || y >= rows || !mask(y, x))
- return;
- dst(y, x) = saturate_cast<DstType>(op(src1(y, x), src2(y, x)));
- }
- // transformSmart
- template <int SHIFT, typename SrcType, typename DstType, class UnOp, class MaskPtr>
- __global__ void transformSmart(const GlobPtr<SrcType> src_, GlobPtr<DstType> dst_, const UnOp op, const MaskPtr mask, const int rows, const int cols)
- {
- typedef typename MakeVec<SrcType, SHIFT>::type read_type;
- typedef typename MakeVec<DstType, SHIFT>::type write_type;
- const int x = blockIdx.x * blockDim.x + threadIdx.x;
- const int y = blockIdx.y * blockDim.y + threadIdx.y;
- const int x_shifted = x * SHIFT;
- if (y < rows)
- {
- const SrcType* src = src_.row(y);
- DstType* dst = dst_.row(y);
- if (x_shifted + SHIFT - 1 < cols)
- {
- const read_type src_n_el = ((const read_type*)src)[x];
- OpUnroller<SHIFT>::unroll(src_n_el, ((write_type*)dst)[x], op, mask, x_shifted, y);
- }
- else
- {
- for (int real_x = x_shifted; real_x < cols; ++real_x)
- {
- if (mask(y, real_x))
- dst[real_x] = op(src[real_x]);
- }
- }
- }
- }
- template <int SHIFT, typename SrcType1, typename SrcType2, typename DstType, class BinOp, class MaskPtr>
- __global__ void transformSmart(const GlobPtr<SrcType1> src1_, const GlobPtr<SrcType2> src2_, GlobPtr<DstType> dst_, const BinOp op, const MaskPtr mask, const int rows, const int cols)
- {
- typedef typename MakeVec<SrcType1, SHIFT>::type read_type1;
- typedef typename MakeVec<SrcType2, SHIFT>::type read_type2;
- typedef typename MakeVec<DstType, SHIFT>::type write_type;
- const int x = blockIdx.x * blockDim.x + threadIdx.x;
- const int y = blockIdx.y * blockDim.y + threadIdx.y;
- const int x_shifted = x * SHIFT;
- if (y < rows)
- {
- const SrcType1* src1 = src1_.row(y);
- const SrcType2* src2 = src2_.row(y);
- DstType* dst = dst_.row(y);
- if (x_shifted + SHIFT - 1 < cols)
- {
- const read_type1 src1_n_el = ((const read_type1*)src1)[x];
- const read_type2 src2_n_el = ((const read_type2*)src2)[x];
- OpUnroller<SHIFT>::unroll(src1_n_el, src2_n_el, ((write_type*)dst)[x], op, mask, x_shifted, y);
- }
- else
- {
- for (int real_x = x_shifted; real_x < cols; ++real_x)
- {
- if (mask(y, real_x))
- dst[real_x] = op(src1[real_x], src2[real_x]);
- }
- }
- }
- }
- // TransformDispatcher
- template <bool UseSmart, class Policy> struct TransformDispatcher;
- template <class Policy> struct TransformDispatcher<false, Policy>
- {
- template <class SrcPtr, typename DstType, class UnOp, class MaskPtr>
- __host__ static void call(const SrcPtr& src, const GlobPtr<DstType>& dst, const UnOp& op, const MaskPtr& mask, int rows, int cols, cudaStream_t stream)
- {
- const dim3 block(Policy::block_size_x, Policy::block_size_y);
- const dim3 grid(divUp(cols, block.x), divUp(rows, block.y));
- transformSimple<<<grid, block, 0, stream>>>(src, dst, op, mask, rows, cols);
- CV_CUDEV_SAFE_CALL( cudaGetLastError() );
- if (stream == 0)
- CV_CUDEV_SAFE_CALL( cudaDeviceSynchronize() );
- }
- template <class SrcPtr1, class SrcPtr2, typename DstType, class BinOp, class MaskPtr>
- __host__ static void call(const SrcPtr1& src1, const SrcPtr2& src2, const GlobPtr<DstType>& dst, const BinOp& op, const MaskPtr& mask, int rows, int cols, cudaStream_t stream)
- {
- const dim3 block(Policy::block_size_x, Policy::block_size_y);
- const dim3 grid(divUp(cols, block.x), divUp(rows, block.y));
- transformSimple<<<grid, block, 0, stream>>>(src1, src2, dst, op, mask, rows, cols);
- CV_CUDEV_SAFE_CALL( cudaGetLastError() );
- if (stream == 0)
- CV_CUDEV_SAFE_CALL( cudaDeviceSynchronize() );
- }
- };
- template <class Policy> struct TransformDispatcher<true, Policy>
- {
- template <typename T>
- __host__ static bool isAligned(const T* ptr, size_t size)
- {
- return reinterpret_cast<size_t>(ptr) % size == 0;
- }
- __host__ static bool isAligned(size_t step, size_t size)
- {
- return step % size == 0;
- }
- template <typename SrcType, typename DstType, class UnOp, class MaskPtr>
- __host__ static void call(const GlobPtr<SrcType>& src, const GlobPtr<DstType>& dst, const UnOp& op, const MaskPtr& mask, int rows, int cols, cudaStream_t stream)
- {
- if (Policy::shift == 1 ||
- !isAligned(src.data, Policy::shift * sizeof(SrcType)) || !isAligned(src.step, Policy::shift * sizeof(SrcType)) ||
- !isAligned(dst.data, Policy::shift * sizeof(DstType)) || !isAligned(dst.step, Policy::shift * sizeof(DstType)))
- {
- TransformDispatcher<false, Policy>::call(src, dst, op, mask, rows, cols, stream);
- return;
- }
- const dim3 block(Policy::block_size_x, Policy::block_size_y);
- const dim3 grid(divUp(cols, block.x * Policy::shift), divUp(rows, block.y));
- transformSmart<Policy::shift><<<grid, block, 0, stream>>>(src, dst, op, mask, rows, cols);
- CV_CUDEV_SAFE_CALL( cudaGetLastError() );
- if (stream == 0)
- CV_CUDEV_SAFE_CALL( cudaDeviceSynchronize() );
- }
- template <typename SrcType1, typename SrcType2, typename DstType, class BinOp, class MaskPtr>
- __host__ static void call(const GlobPtr<SrcType1>& src1, const GlobPtr<SrcType2>& src2, const GlobPtr<DstType>& dst, const BinOp& op, const MaskPtr& mask, int rows, int cols, cudaStream_t stream)
- {
- if (Policy::shift == 1 ||
- !isAligned(src1.data, Policy::shift * sizeof(SrcType1)) || !isAligned(src1.step, Policy::shift * sizeof(SrcType1)) ||
- !isAligned(src2.data, Policy::shift * sizeof(SrcType2)) || !isAligned(src2.step, Policy::shift * sizeof(SrcType2)) ||
- !isAligned(dst.data, Policy::shift * sizeof(DstType)) || !isAligned(dst.step, Policy::shift * sizeof(DstType)))
- {
- TransformDispatcher<false, Policy>::call(src1, src2, dst, op, mask, rows, cols, stream);
- return;
- }
- const dim3 block(Policy::block_size_x, Policy::block_size_y);
- const dim3 grid(divUp(cols, block.x * Policy::shift), divUp(rows, block.y));
- transformSmart<Policy::shift><<<grid, block, 0, stream>>>(src1, src2, dst, op, mask, rows, cols);
- CV_CUDEV_SAFE_CALL( cudaGetLastError() );
- if (stream == 0)
- CV_CUDEV_SAFE_CALL( cudaDeviceSynchronize() );
- }
- };
- template <class Policy, class SrcPtr, typename DstType, class UnOp, class MaskPtr>
- __host__ void transform_unary(const SrcPtr& src, const GlobPtr<DstType>& dst, const UnOp& op, const MaskPtr& mask, int rows, int cols, cudaStream_t stream)
- {
- TransformDispatcher<false, Policy>::call(src, dst, op, mask, rows, cols, stream);
- }
- template <class Policy, class SrcPtr1, class SrcPtr2, typename DstType, class BinOp, class MaskPtr>
- __host__ void transform_binary(const SrcPtr1& src1, const SrcPtr2& src2, const GlobPtr<DstType>& dst, const BinOp& op, const MaskPtr& mask, int rows, int cols, cudaStream_t stream)
- {
- TransformDispatcher<false, Policy>::call(src1, src2, dst, op, mask, rows, cols, stream);
- }
- template <class Policy, typename SrcType, typename DstType, class UnOp, class MaskPtr>
- __host__ void transform_unary(const GlobPtr<SrcType>& src, const GlobPtr<DstType>& dst, const UnOp& op, const MaskPtr& mask, int rows, int cols, cudaStream_t stream)
- {
- TransformDispatcher<VecTraits<SrcType>::cn == 1 && VecTraits<DstType>::cn == 1 && Policy::shift != 1, Policy>::call(src, dst, op, mask, rows, cols, stream);
- }
- template <class Policy, typename SrcType1, typename SrcType2, typename DstType, class BinOp, class MaskPtr>
- __host__ void transform_binary(const GlobPtr<SrcType1>& src1, const GlobPtr<SrcType2>& src2, const GlobPtr<DstType>& dst, const BinOp& op, const MaskPtr& mask, int rows, int cols, cudaStream_t stream)
- {
- TransformDispatcher<VecTraits<SrcType1>::cn == 1 && VecTraits<SrcType2>::cn == 1 && VecTraits<DstType>::cn == 1 && Policy::shift != 1, Policy>::call(src1, src2, dst, op, mask, rows, cols, stream);
- }
- // transform_tuple
- template <int count> struct Unroll
- {
- template <class SrcVal, class DstPtrTuple, class OpTuple>
- __device__ static void transform(const SrcVal& srcVal, DstPtrTuple& dst, const OpTuple& op, int y, int x)
- {
- typedef typename tuple_element<count - 1, DstPtrTuple>::type dst_ptr_type;
- typedef typename PtrTraits<dst_ptr_type>::value_type dst_type;
- get<count - 1>(dst)(y, x) = saturate_cast<dst_type>(get<count - 1>(op)(srcVal));
- Unroll<count - 1>::transform(srcVal, dst, op, y, x);
- }
- };
- template <> struct Unroll<0>
- {
- template <class SrcVal, class DstPtrTuple, class OpTuple>
- __device__ __forceinline__ static void transform(const SrcVal&, DstPtrTuple&, const OpTuple&, int, int)
- {
- }
- };
- template <class SrcPtr, class DstPtrTuple, class OpTuple, class MaskPtr>
- __global__ void transform_tuple(const SrcPtr src, DstPtrTuple dst, const OpTuple op, const MaskPtr mask, const int rows, const int cols)
- {
- const int x = blockIdx.x * blockDim.x + threadIdx.x;
- const int y = blockIdx.y * blockDim.y + threadIdx.y;
- if (x >= cols || y >= rows || !mask(y, x))
- return;
- typename PtrTraits<SrcPtr>::value_type srcVal = src(y, x);
- Unroll<tuple_size<DstPtrTuple>::value>::transform(srcVal, dst, op, y, x);
- }
- template <class Policy, class SrcPtrTuple, class DstPtrTuple, class OpTuple, class MaskPtr>
- __host__ void transform_tuple(const SrcPtrTuple& src, const DstPtrTuple& dst, const OpTuple& op, const MaskPtr& mask, int rows, int cols, cudaStream_t stream)
- {
- const dim3 block(Policy::block_size_x, Policy::block_size_y);
- const dim3 grid(divUp(cols, block.x), divUp(rows, block.y));
- transform_tuple<<<grid, block, 0, stream>>>(src, dst, op, mask, rows, cols);
- CV_CUDEV_SAFE_CALL( cudaGetLastError() );
- if (stream == 0)
- CV_CUDEV_SAFE_CALL( cudaDeviceSynchronize() );
- }
- }
- }}
- #endif
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