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AVX optimized implementation of resize and warp functions migrated to separate file
This commit is contained in:
Vitaly Tuzov
parent
20f603a217
commit
3681dcef1a
289
modules/imgproc/src/imgwarp.avx2.cpp
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289
modules/imgproc/src/imgwarp.avx2.cpp
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/*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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// Copyright (C) 2014-2015, Itseez 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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/* ////////////////////////////////////////////////////////////////////
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//
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// Geometrical transforms on images and matrices: rotation, zoom etc.
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//
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// */
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#include "precomp.hpp"
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#include "imgwarp.hpp"
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namespace cv
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{
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namespace opt_AVX2
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{
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class resizeNNInvokerAVX4 :
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public ParallelLoopBody
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{
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public:
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resizeNNInvokerAVX4(const Mat& _src, Mat &_dst, int *_x_ofs, int _pix_size4, double _ify) :
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ParallelLoopBody(), src(_src), dst(_dst), x_ofs(_x_ofs), pix_size4(_pix_size4),
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ify(_ify)
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{
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}
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#if defined(__INTEL_COMPILER)
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#pragma optimization_parameter target_arch=AVX
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#endif
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virtual void operator() (const Range& range) const
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{
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Size ssize = src.size(), dsize = dst.size();
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int y, x;
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int width = dsize.width;
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int avxWidth = width - (width & 0x7);
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const __m256i CV_DECL_ALIGNED(64) mask = _mm256_set1_epi32(-1);
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if(((int64)(dst.data + dst.step) & 0x1f) == 0)
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{
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for(y = range.start; y < range.end; y++)
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{
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uchar* D = dst.data + dst.step*y;
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uchar* Dstart = D;
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int sy = std::min(cvFloor(y*ify), ssize.height-1);
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const uchar* S = src.data + sy*src.step;
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#pragma unroll(4)
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for(x = 0; x < avxWidth; x += 8)
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{
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const __m256i CV_DECL_ALIGNED(64) *addr = (__m256i*)(x_ofs + x);
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__m256i CV_DECL_ALIGNED(64) indices = _mm256_lddqu_si256(addr);
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__m256i CV_DECL_ALIGNED(64) pixels = _mm256_i32gather_epi32((const int*)S, indices, 1);
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_mm256_maskstore_epi32((int*)D, mask, pixels);
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D += 32;
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}
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for(; x < width; x++)
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{
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*(int*)(Dstart + x*4) = *(int*)(S + x_ofs[x]);
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}
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}
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}
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else
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{
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for(y = range.start; y < range.end; y++)
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{
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uchar* D = dst.data + dst.step*y;
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uchar* Dstart = D;
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int sy = std::min(cvFloor(y*ify), ssize.height-1);
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const uchar* S = src.data + sy*src.step;
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#pragma unroll(4)
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for(x = 0; x < avxWidth; x += 8)
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{
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const __m256i CV_DECL_ALIGNED(64) *addr = (__m256i*)(x_ofs + x);
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__m256i CV_DECL_ALIGNED(64) indices = _mm256_lddqu_si256(addr);
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__m256i CV_DECL_ALIGNED(64) pixels = _mm256_i32gather_epi32((const int*)S, indices, 1);
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_mm256_storeu_si256((__m256i*)D, pixels);
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D += 32;
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}
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for(; x < width; x++)
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{
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*(int*)(Dstart + x*4) = *(int*)(S + x_ofs[x]);
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}
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}
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}
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}
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private:
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const Mat src;
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Mat dst;
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int* x_ofs, pix_size4;
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double ify;
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resizeNNInvokerAVX4(const resizeNNInvokerAVX4&);
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resizeNNInvokerAVX4& operator=(const resizeNNInvokerAVX4&);
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};
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class resizeNNInvokerAVX2 :
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public ParallelLoopBody
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{
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public:
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resizeNNInvokerAVX2(const Mat& _src, Mat &_dst, int *_x_ofs, int _pix_size4, double _ify) :
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ParallelLoopBody(), src(_src), dst(_dst), x_ofs(_x_ofs), pix_size4(_pix_size4),
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ify(_ify)
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{
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}
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#if defined(__INTEL_COMPILER)
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#pragma optimization_parameter target_arch=AVX
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#endif
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virtual void operator() (const Range& range) const
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{
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Size ssize = src.size(), dsize = dst.size();
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int y, x;
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int width = dsize.width;
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//int avxWidth = (width - 1) - ((width - 1) & 0x7);
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int avxWidth = width - (width & 0xf);
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const __m256i CV_DECL_ALIGNED(64) mask = _mm256_set1_epi32(-1);
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const __m256i CV_DECL_ALIGNED(64) shuffle_mask = _mm256_set_epi8(15,14,11,10,13,12,9,8,7,6,3,2,5,4,1,0,
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15,14,11,10,13,12,9,8,7,6,3,2,5,4,1,0);
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const __m256i CV_DECL_ALIGNED(64) permute_mask = _mm256_set_epi32(7, 5, 3, 1, 6, 4, 2, 0);
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const __m256i CV_DECL_ALIGNED(64) shift_shuffle_mask = _mm256_set_epi8(13,12,15,14,9,8,11,10,5,4,7,6,1,0,3,2,
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13,12,15,14,9,8,11,10,5,4,7,6,1,0,3,2);
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if(((int64)(dst.data + dst.step) & 0x1f) == 0)
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{
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for(y = range.start; y < range.end; y++)
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{
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uchar* D = dst.data + dst.step*y;
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uchar* Dstart = D;
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int sy = std::min(cvFloor(y*ify), ssize.height-1);
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const uchar* S = src.data + sy*src.step;
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const uchar* S2 = S - 2;
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#pragma unroll(4)
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for(x = 0; x < avxWidth; x += 16)
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{
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const __m256i CV_DECL_ALIGNED(64) *addr = (__m256i*)(x_ofs + x);
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__m256i CV_DECL_ALIGNED(64) indices = _mm256_lddqu_si256(addr);
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__m256i CV_DECL_ALIGNED(64) pixels1 = _mm256_i32gather_epi32((const int*)S, indices, 1);
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const __m256i CV_DECL_ALIGNED(64) *addr2 = (__m256i*)(x_ofs + x + 8);
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__m256i CV_DECL_ALIGNED(64) indices2 = _mm256_lddqu_si256(addr2);
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__m256i CV_DECL_ALIGNED(64) pixels2 = _mm256_i32gather_epi32((const int*)S2, indices2, 1);
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__m256i CV_DECL_ALIGNED(64) unpacked = _mm256_blend_epi16(pixels1, pixels2, 0xaa);
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__m256i CV_DECL_ALIGNED(64) bytes_shuffled = _mm256_shuffle_epi8(unpacked, shuffle_mask);
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__m256i CV_DECL_ALIGNED(64) ints_permuted = _mm256_permutevar8x32_epi32(bytes_shuffled, permute_mask);
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_mm256_maskstore_epi32((int*)D, mask, ints_permuted);
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D += 32;
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}
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for(; x < width; x++)
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{
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*(ushort*)(Dstart + x*2) = *(ushort*)(S + x_ofs[x]);
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}
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}
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}
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else
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{
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for(y = range.start; y < range.end; y++)
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{
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uchar* D = dst.data + dst.step*y;
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uchar* Dstart = D;
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int sy = std::min(cvFloor(y*ify), ssize.height-1);
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const uchar* S = src.data + sy*src.step;
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const uchar* S2 = S - 2;
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#pragma unroll(4)
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for(x = 0; x < avxWidth; x += 16)
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{
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const __m256i CV_DECL_ALIGNED(64) *addr = (__m256i*)(x_ofs + x);
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__m256i CV_DECL_ALIGNED(64) indices = _mm256_lddqu_si256(addr);
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__m256i CV_DECL_ALIGNED(64) pixels1 = _mm256_i32gather_epi32((const int*)S, indices, 1);
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const __m256i CV_DECL_ALIGNED(64) *addr2 = (__m256i*)(x_ofs + x + 8);
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__m256i CV_DECL_ALIGNED(64) indices2 = _mm256_lddqu_si256(addr2);
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__m256i CV_DECL_ALIGNED(64) pixels2 = _mm256_i32gather_epi32((const int*)S2, indices2, 1);
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__m256i CV_DECL_ALIGNED(64) unpacked = _mm256_blend_epi16(pixels1, pixels2, 0xaa);
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__m256i CV_DECL_ALIGNED(64) bytes_shuffled = _mm256_shuffle_epi8(unpacked, shuffle_mask);
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__m256i CV_DECL_ALIGNED(64) ints_permuted = _mm256_permutevar8x32_epi32(bytes_shuffled, permute_mask);
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_mm256_storeu_si256((__m256i*)D, ints_permuted);
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D += 32;
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}
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for(; x < width; x++)
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{
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*(ushort*)(Dstart + x*2) = *(ushort*)(S + x_ofs[x]);
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}
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}
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}
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}
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private:
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const Mat src;
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Mat dst;
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int* x_ofs, pix_size4;
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double ify;
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resizeNNInvokerAVX2(const resizeNNInvokerAVX2&);
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resizeNNInvokerAVX2& operator=(const resizeNNInvokerAVX2&);
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};
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void resizeNN2_AVX2(const Range& range, const Mat& src, Mat &dst, int *x_ofs, int pix_size4, double ify)
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{
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resizeNNInvokerAVX2 invoker(src, dst, x_ofs, pix_size4, ify);
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parallel_for_(range, invoker, dst.total() / (double)(1 << 16));
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}
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void resizeNN4_AVX2(const Range& range, const Mat& src, Mat &dst, int *x_ofs, int pix_size4, double ify)
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{
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resizeNNInvokerAVX4 invoker(src, dst, x_ofs, pix_size4, ify);
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parallel_for_(range, invoker, dst.total() / (double)(1 << 16));
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}
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int warpAffineBlockline(int *adelta, int *bdelta, short* xy, short* alpha, int X0, int Y0, int bw)
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{
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const int AB_BITS = MAX(10, (int)INTER_BITS);
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int x1 = 0;
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__m256i fxy_mask = _mm256_set1_epi32(INTER_TAB_SIZE - 1);
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__m256i XX = _mm256_set1_epi32(X0), YY = _mm256_set1_epi32(Y0);
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for (; x1 <= bw - 16; x1 += 16)
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{
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__m256i tx0, tx1, ty0, ty1;
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tx0 = _mm256_add_epi32(_mm256_loadu_si256((const __m256i*)(adelta + x1)), XX);
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ty0 = _mm256_add_epi32(_mm256_loadu_si256((const __m256i*)(bdelta + x1)), YY);
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tx1 = _mm256_add_epi32(_mm256_loadu_si256((const __m256i*)(adelta + x1 + 8)), XX);
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ty1 = _mm256_add_epi32(_mm256_loadu_si256((const __m256i*)(bdelta + x1 + 8)), YY);
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tx0 = _mm256_srai_epi32(tx0, AB_BITS - INTER_BITS);
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ty0 = _mm256_srai_epi32(ty0, AB_BITS - INTER_BITS);
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tx1 = _mm256_srai_epi32(tx1, AB_BITS - INTER_BITS);
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ty1 = _mm256_srai_epi32(ty1, AB_BITS - INTER_BITS);
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__m256i fx_ = _mm256_packs_epi32(_mm256_and_si256(tx0, fxy_mask),
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_mm256_and_si256(tx1, fxy_mask));
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__m256i fy_ = _mm256_packs_epi32(_mm256_and_si256(ty0, fxy_mask),
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_mm256_and_si256(ty1, fxy_mask));
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tx0 = _mm256_packs_epi32(_mm256_srai_epi32(tx0, INTER_BITS),
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_mm256_srai_epi32(tx1, INTER_BITS));
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ty0 = _mm256_packs_epi32(_mm256_srai_epi32(ty0, INTER_BITS),
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_mm256_srai_epi32(ty1, INTER_BITS));
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fx_ = _mm256_adds_epi16(fx_, _mm256_slli_epi16(fy_, INTER_BITS));
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fx_ = _mm256_permute4x64_epi64(fx_, (3 << 6) + (1 << 4) + (2 << 2) + 0);
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_mm256_storeu_si256((__m256i*)(xy + x1 * 2), _mm256_unpacklo_epi16(tx0, ty0));
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_mm256_storeu_si256((__m256i*)(xy + x1 * 2 + 16), _mm256_unpackhi_epi16(tx0, ty0));
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_mm256_storeu_si256((__m256i*)(alpha + x1), fx_);
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}
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_mm256_zeroupper();
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return x1;
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}
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}
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}
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/* End of file. */
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@ -52,6 +52,7 @@
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#include "hal_replacement.hpp"
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#include "hal_replacement.hpp"
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#include "opencv2/core/openvx/ovx_defs.hpp"
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#include "opencv2/core/openvx/ovx_defs.hpp"
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#include "imgwarp.hpp"
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using namespace cv;
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using namespace cv;
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@ -417,308 +418,6 @@ private:
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resizeNNInvoker& operator=(const resizeNNInvoker&);
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resizeNNInvoker& operator=(const resizeNNInvoker&);
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};
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};
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#if CV_AVX2
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class resizeNNInvokerAVX4 :
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public ParallelLoopBody
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{
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public:
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resizeNNInvokerAVX4(const Mat& _src, Mat &_dst, int *_x_ofs, int _pix_size4, double _ify) :
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ParallelLoopBody(), src(_src), dst(_dst), x_ofs(_x_ofs), pix_size4(_pix_size4),
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ify(_ify)
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{
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}
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#if defined(__INTEL_COMPILER)
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|
||||||
#pragma optimization_parameter target_arch=AVX
|
|
||||||
#endif
|
|
||||||
virtual void operator() (const Range& range) const
|
|
||||||
{
|
|
||||||
Size ssize = src.size(), dsize = dst.size();
|
|
||||||
int y, x, pix_size = (int)src.elemSize();
|
|
||||||
int width = dsize.width;
|
|
||||||
int avxWidth = width - (width & 0x7);
|
|
||||||
const __m256i CV_DECL_ALIGNED(64) mask = _mm256_set1_epi32(-1);
|
|
||||||
if(((int64)(dst.data + dst.step) & 0x1f) == 0)
|
|
||||||
{
|
|
||||||
for(y = range.start; y < range.end; y++)
|
|
||||||
{
|
|
||||||
uchar* D = dst.data + dst.step*y;
|
|
||||||
uchar* Dstart = D;
|
|
||||||
int sy = std::min(cvFloor(y*ify), ssize.height-1);
|
|
||||||
const uchar* S = src.data + sy*src.step;
|
|
||||||
#pragma unroll(4)
|
|
||||||
for(x = 0; x < avxWidth; x += 8)
|
|
||||||
{
|
|
||||||
const __m256i CV_DECL_ALIGNED(64) *addr = (__m256i*)(x_ofs + x);
|
|
||||||
__m256i CV_DECL_ALIGNED(64) indices = _mm256_lddqu_si256(addr);
|
|
||||||
__m256i CV_DECL_ALIGNED(64) pixels = _mm256_i32gather_epi32((const int*)S, indices, 1);
|
|
||||||
_mm256_maskstore_epi32((int*)D, mask, pixels);
|
|
||||||
D += 32;
|
|
||||||
}
|
|
||||||
for(; x < width; x++)
|
|
||||||
{
|
|
||||||
*(int*)(Dstart + x*4) = *(int*)(S + x_ofs[x]);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
else
|
|
||||||
{
|
|
||||||
for(y = range.start; y < range.end; y++)
|
|
||||||
{
|
|
||||||
uchar* D = dst.data + dst.step*y;
|
|
||||||
uchar* Dstart = D;
|
|
||||||
int sy = std::min(cvFloor(y*ify), ssize.height-1);
|
|
||||||
const uchar* S = src.data + sy*src.step;
|
|
||||||
#pragma unroll(4)
|
|
||||||
for(x = 0; x < avxWidth; x += 8)
|
|
||||||
{
|
|
||||||
const __m256i CV_DECL_ALIGNED(64) *addr = (__m256i*)(x_ofs + x);
|
|
||||||
__m256i CV_DECL_ALIGNED(64) indices = _mm256_lddqu_si256(addr);
|
|
||||||
__m256i CV_DECL_ALIGNED(64) pixels = _mm256_i32gather_epi32((const int*)S, indices, 1);
|
|
||||||
_mm256_storeu_si256((__m256i*)D, pixels);
|
|
||||||
D += 32;
|
|
||||||
}
|
|
||||||
for(; x < width; x++)
|
|
||||||
{
|
|
||||||
*(int*)(Dstart + x*4) = *(int*)(S + x_ofs[x]);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
private:
|
|
||||||
const Mat src;
|
|
||||||
Mat dst;
|
|
||||||
int* x_ofs, pix_size4;
|
|
||||||
double ify;
|
|
||||||
|
|
||||||
resizeNNInvokerAVX4(const resizeNNInvokerAVX4&);
|
|
||||||
resizeNNInvokerAVX4& operator=(const resizeNNInvokerAVX4&);
|
|
||||||
};
|
|
||||||
|
|
||||||
class resizeNNInvokerAVX2 :
|
|
||||||
public ParallelLoopBody
|
|
||||||
{
|
|
||||||
public:
|
|
||||||
resizeNNInvokerAVX2(const Mat& _src, Mat &_dst, int *_x_ofs, int _pix_size4, double _ify) :
|
|
||||||
ParallelLoopBody(), src(_src), dst(_dst), x_ofs(_x_ofs), pix_size4(_pix_size4),
|
|
||||||
ify(_ify)
|
|
||||||
{
|
|
||||||
}
|
|
||||||
|
|
||||||
#if defined(__INTEL_COMPILER)
|
|
||||||
#pragma optimization_parameter target_arch=AVX
|
|
||||||
#endif
|
|
||||||
virtual void operator() (const Range& range) const
|
|
||||||
{
|
|
||||||
Size ssize = src.size(), dsize = dst.size();
|
|
||||||
int y, x, pix_size = (int)src.elemSize();
|
|
||||||
int width = dsize.width;
|
|
||||||
//int avxWidth = (width - 1) - ((width - 1) & 0x7);
|
|
||||||
int avxWidth = width - (width & 0xf);
|
|
||||||
const __m256i CV_DECL_ALIGNED(64) mask = _mm256_set1_epi32(-1);
|
|
||||||
const __m256i CV_DECL_ALIGNED(64) shuffle_mask = _mm256_set_epi8(15,14,11,10,13,12,9,8,7,6,3,2,5,4,1,0,
|
|
||||||
15,14,11,10,13,12,9,8,7,6,3,2,5,4,1,0);
|
|
||||||
const __m256i CV_DECL_ALIGNED(64) permute_mask = _mm256_set_epi32(7, 5, 3, 1, 6, 4, 2, 0);
|
|
||||||
const __m256i CV_DECL_ALIGNED(64) shift_shuffle_mask = _mm256_set_epi8(13,12,15,14,9,8,11,10,5,4,7,6,1,0,3,2,
|
|
||||||
13,12,15,14,9,8,11,10,5,4,7,6,1,0,3,2);
|
|
||||||
if(((int64)(dst.data + dst.step) & 0x1f) == 0)
|
|
||||||
{
|
|
||||||
for(y = range.start; y < range.end; y++)
|
|
||||||
{
|
|
||||||
uchar* D = dst.data + dst.step*y;
|
|
||||||
uchar* Dstart = D;
|
|
||||||
int sy = std::min(cvFloor(y*ify), ssize.height-1);
|
|
||||||
const uchar* S = src.data + sy*src.step;
|
|
||||||
const uchar* S2 = S - 2;
|
|
||||||
#pragma unroll(4)
|
|
||||||
for(x = 0; x < avxWidth; x += 16)
|
|
||||||
{
|
|
||||||
const __m256i CV_DECL_ALIGNED(64) *addr = (__m256i*)(x_ofs + x);
|
|
||||||
__m256i CV_DECL_ALIGNED(64) indices = _mm256_lddqu_si256(addr);
|
|
||||||
__m256i CV_DECL_ALIGNED(64) pixels1 = _mm256_i32gather_epi32((const int*)S, indices, 1);
|
|
||||||
const __m256i CV_DECL_ALIGNED(64) *addr2 = (__m256i*)(x_ofs + x + 8);
|
|
||||||
__m256i CV_DECL_ALIGNED(64) indices2 = _mm256_lddqu_si256(addr2);
|
|
||||||
__m256i CV_DECL_ALIGNED(64) pixels2 = _mm256_i32gather_epi32((const int*)S2, indices2, 1);
|
|
||||||
__m256i CV_DECL_ALIGNED(64) unpacked = _mm256_blend_epi16(pixels1, pixels2, 0xaa);
|
|
||||||
|
|
||||||
__m256i CV_DECL_ALIGNED(64) bytes_shuffled = _mm256_shuffle_epi8(unpacked, shuffle_mask);
|
|
||||||
__m256i CV_DECL_ALIGNED(64) ints_permuted = _mm256_permutevar8x32_epi32(bytes_shuffled, permute_mask);
|
|
||||||
_mm256_maskstore_epi32((int*)D, mask, ints_permuted);
|
|
||||||
D += 32;
|
|
||||||
}
|
|
||||||
for(; x < width; x++)
|
|
||||||
{
|
|
||||||
*(ushort*)(Dstart + x*2) = *(ushort*)(S + x_ofs[x]);
|
|
||||||
}
|
|
||||||
|
|
||||||
}
|
|
||||||
}
|
|
||||||
else
|
|
||||||
{
|
|
||||||
for(y = range.start; y < range.end; y++)
|
|
||||||
{
|
|
||||||
uchar* D = dst.data + dst.step*y;
|
|
||||||
uchar* Dstart = D;
|
|
||||||
int sy = std::min(cvFloor(y*ify), ssize.height-1);
|
|
||||||
const uchar* S = src.data + sy*src.step;
|
|
||||||
const uchar* S2 = S - 2;
|
|
||||||
#pragma unroll(4)
|
|
||||||
for(x = 0; x < avxWidth; x += 16)
|
|
||||||
{
|
|
||||||
const __m256i CV_DECL_ALIGNED(64) *addr = (__m256i*)(x_ofs + x);
|
|
||||||
__m256i CV_DECL_ALIGNED(64) indices = _mm256_lddqu_si256(addr);
|
|
||||||
__m256i CV_DECL_ALIGNED(64) pixels1 = _mm256_i32gather_epi32((const int*)S, indices, 1);
|
|
||||||
const __m256i CV_DECL_ALIGNED(64) *addr2 = (__m256i*)(x_ofs + x + 8);
|
|
||||||
__m256i CV_DECL_ALIGNED(64) indices2 = _mm256_lddqu_si256(addr2);
|
|
||||||
__m256i CV_DECL_ALIGNED(64) pixels2 = _mm256_i32gather_epi32((const int*)S2, indices2, 1);
|
|
||||||
__m256i CV_DECL_ALIGNED(64) unpacked = _mm256_blend_epi16(pixels1, pixels2, 0xaa);
|
|
||||||
|
|
||||||
__m256i CV_DECL_ALIGNED(64) bytes_shuffled = _mm256_shuffle_epi8(unpacked, shuffle_mask);
|
|
||||||
__m256i CV_DECL_ALIGNED(64) ints_permuted = _mm256_permutevar8x32_epi32(bytes_shuffled, permute_mask);
|
|
||||||
_mm256_storeu_si256((__m256i*)D, ints_permuted);
|
|
||||||
D += 32;
|
|
||||||
}
|
|
||||||
for(; x < width; x++)
|
|
||||||
{
|
|
||||||
*(ushort*)(Dstart + x*2) = *(ushort*)(S + x_ofs[x]);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
private:
|
|
||||||
const Mat src;
|
|
||||||
Mat dst;
|
|
||||||
int* x_ofs, pix_size4;
|
|
||||||
double ify;
|
|
||||||
|
|
||||||
resizeNNInvokerAVX2(const resizeNNInvokerAVX2&);
|
|
||||||
resizeNNInvokerAVX2& operator=(const resizeNNInvokerAVX2&);
|
|
||||||
};
|
|
||||||
#endif
|
|
||||||
|
|
||||||
#if CV_SSE4_1
|
|
||||||
class resizeNNInvokerSSE2 :
|
|
||||||
public ParallelLoopBody
|
|
||||||
{
|
|
||||||
public:
|
|
||||||
resizeNNInvokerSSE2(const Mat& _src, Mat &_dst, int *_x_ofs, int _pix_size4, double _ify) :
|
|
||||||
ParallelLoopBody(), src(_src), dst(_dst), x_ofs(_x_ofs), pix_size4(_pix_size4),
|
|
||||||
ify(_ify)
|
|
||||||
{
|
|
||||||
}
|
|
||||||
|
|
||||||
#if defined(__INTEL_COMPILER)
|
|
||||||
#pragma optimization_parameter target_arch=SSE4.2
|
|
||||||
#endif
|
|
||||||
virtual void operator() (const Range& range) const
|
|
||||||
{
|
|
||||||
Size ssize = src.size(), dsize = dst.size();
|
|
||||||
int y, x;
|
|
||||||
int width = dsize.width;
|
|
||||||
int sseWidth = width - (width & 0x7);
|
|
||||||
for(y = range.start; y < range.end; y++)
|
|
||||||
{
|
|
||||||
uchar* D = dst.data + dst.step*y;
|
|
||||||
uchar* Dstart = D;
|
|
||||||
int sy = std::min(cvFloor(y*ify), ssize.height-1);
|
|
||||||
const uchar* S = src.data + sy*src.step;
|
|
||||||
__m128i CV_DECL_ALIGNED(64) pixels = _mm_set1_epi16(0);
|
|
||||||
for(x = 0; x < sseWidth; x += 8)
|
|
||||||
{
|
|
||||||
ushort imm = *(ushort*)(S + x_ofs[x + 0]);
|
|
||||||
pixels = _mm_insert_epi16(pixels, imm, 0);
|
|
||||||
imm = *(ushort*)(S + x_ofs[x + 1]);
|
|
||||||
pixels = _mm_insert_epi16(pixels, imm, 1);
|
|
||||||
imm = *(ushort*)(S + x_ofs[x + 2]);
|
|
||||||
pixels = _mm_insert_epi16(pixels, imm, 2);
|
|
||||||
imm = *(ushort*)(S + x_ofs[x + 3]);
|
|
||||||
pixels = _mm_insert_epi16(pixels, imm, 3);
|
|
||||||
imm = *(ushort*)(S + x_ofs[x + 4]);
|
|
||||||
pixels = _mm_insert_epi16(pixels, imm, 4);
|
|
||||||
imm = *(ushort*)(S + x_ofs[x + 5]);
|
|
||||||
pixels = _mm_insert_epi16(pixels, imm, 5);
|
|
||||||
imm = *(ushort*)(S + x_ofs[x + 6]);
|
|
||||||
pixels = _mm_insert_epi16(pixels, imm, 6);
|
|
||||||
imm = *(ushort*)(S + x_ofs[x + 7]);
|
|
||||||
pixels = _mm_insert_epi16(pixels, imm, 7);
|
|
||||||
_mm_storeu_si128((__m128i*)D, pixels);
|
|
||||||
D += 16;
|
|
||||||
}
|
|
||||||
for(; x < width; x++)
|
|
||||||
{
|
|
||||||
*(ushort*)(Dstart + x*2) = *(ushort*)(S + x_ofs[x]);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
private:
|
|
||||||
const Mat src;
|
|
||||||
Mat dst;
|
|
||||||
int* x_ofs, pix_size4;
|
|
||||||
double ify;
|
|
||||||
|
|
||||||
resizeNNInvokerSSE2(const resizeNNInvokerSSE2&);
|
|
||||||
resizeNNInvokerSSE2& operator=(const resizeNNInvokerSSE2&);
|
|
||||||
};
|
|
||||||
|
|
||||||
class resizeNNInvokerSSE4 :
|
|
||||||
public ParallelLoopBody
|
|
||||||
{
|
|
||||||
public:
|
|
||||||
resizeNNInvokerSSE4(const Mat& _src, Mat &_dst, int *_x_ofs, int _pix_size4, double _ify) :
|
|
||||||
ParallelLoopBody(), src(_src), dst(_dst), x_ofs(_x_ofs), pix_size4(_pix_size4),
|
|
||||||
ify(_ify)
|
|
||||||
{
|
|
||||||
}
|
|
||||||
#if defined(__INTEL_COMPILER)
|
|
||||||
#pragma optimization_parameter target_arch=SSE4.2
|
|
||||||
#endif
|
|
||||||
virtual void operator() (const Range& range) const
|
|
||||||
{
|
|
||||||
Size ssize = src.size(), dsize = dst.size();
|
|
||||||
int y, x;
|
|
||||||
int width = dsize.width;
|
|
||||||
int sseWidth = width - (width & 0x3);
|
|
||||||
for(y = range.start; y < range.end; y++)
|
|
||||||
{
|
|
||||||
uchar* D = dst.data + dst.step*y;
|
|
||||||
uchar* Dstart = D;
|
|
||||||
int sy = std::min(cvFloor(y*ify), ssize.height-1);
|
|
||||||
const uchar* S = src.data + sy*src.step;
|
|
||||||
__m128i CV_DECL_ALIGNED(64) pixels = _mm_set1_epi16(0);
|
|
||||||
for(x = 0; x < sseWidth; x += 4)
|
|
||||||
{
|
|
||||||
int imm = *(int*)(S + x_ofs[x + 0]);
|
|
||||||
pixels = _mm_insert_epi32(pixels, imm, 0);
|
|
||||||
imm = *(int*)(S + x_ofs[x + 1]);
|
|
||||||
pixels = _mm_insert_epi32(pixels, imm, 1);
|
|
||||||
imm = *(int*)(S + x_ofs[x + 2]);
|
|
||||||
pixels = _mm_insert_epi32(pixels, imm, 2);
|
|
||||||
imm = *(int*)(S + x_ofs[x + 3]);
|
|
||||||
pixels = _mm_insert_epi32(pixels, imm, 3);
|
|
||||||
_mm_storeu_si128((__m128i*)D, pixels);
|
|
||||||
D += 16;
|
|
||||||
}
|
|
||||||
for(; x < width; x++)
|
|
||||||
{
|
|
||||||
*(int*)(Dstart + x*4) = *(int*)(S + x_ofs[x]);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
private:
|
|
||||||
const Mat src;
|
|
||||||
Mat dst;
|
|
||||||
int* x_ofs, pix_size4;
|
|
||||||
double ify;
|
|
||||||
|
|
||||||
resizeNNInvokerSSE4(const resizeNNInvokerSSE4&);
|
|
||||||
resizeNNInvokerSSE4& operator=(const resizeNNInvokerSSE4&);
|
|
||||||
};
|
|
||||||
#endif
|
|
||||||
|
|
||||||
static void
|
static void
|
||||||
resizeNN( const Mat& src, Mat& dst, double fx, double fy )
|
resizeNN( const Mat& src, Mat& dst, double fx, double fy )
|
||||||
{
|
{
|
||||||
@ -737,35 +436,23 @@ resizeNN( const Mat& src, Mat& dst, double fx, double fy )
|
|||||||
}
|
}
|
||||||
|
|
||||||
Range range(0, dsize.height);
|
Range range(0, dsize.height);
|
||||||
#if CV_AVX2
|
#if CV_TRY_AVX2
|
||||||
if(checkHardwareSupport(CV_CPU_AVX2) && ((pix_size == 2) || (pix_size == 4)))
|
if(CV_CPU_HAS_SUPPORT_AVX2 && ((pix_size == 2) || (pix_size == 4)))
|
||||||
{
|
{
|
||||||
if(pix_size == 2)
|
if(pix_size == 2)
|
||||||
{
|
opt_AVX2::resizeNN2_AVX2(range, src, dst, x_ofs, pix_size4, ify);
|
||||||
resizeNNInvokerAVX2 invoker(src, dst, x_ofs, pix_size4, ify);
|
else
|
||||||
parallel_for_(range, invoker, dst.total()/(double)(1<<16));
|
opt_AVX2::resizeNN4_AVX2(range, src, dst, x_ofs, pix_size4, ify);
|
||||||
}
|
|
||||||
else if (pix_size == 4)
|
|
||||||
{
|
|
||||||
resizeNNInvokerAVX4 invoker(src, dst, x_ofs, pix_size4, ify);
|
|
||||||
parallel_for_(range, invoker, dst.total()/(double)(1<<16));
|
|
||||||
}
|
|
||||||
}
|
}
|
||||||
else
|
else
|
||||||
#endif
|
#endif
|
||||||
#if CV_SSE4_1
|
#if CV_TRY_SSE4_1
|
||||||
if(checkHardwareSupport(CV_CPU_SSE4_1) && ((pix_size == 2) || (pix_size == 4)))
|
if(CV_CPU_HAS_SUPPORT_SSE4_1 && ((pix_size == 2) || (pix_size == 4)))
|
||||||
{
|
{
|
||||||
if(pix_size == 2)
|
if(pix_size == 2)
|
||||||
{
|
opt_SSE41::resizeNN2_SSE4_1(range, src, dst, x_ofs, pix_size4, ify);
|
||||||
resizeNNInvokerSSE2 invoker(src, dst, x_ofs, pix_size4, ify);
|
else
|
||||||
parallel_for_(range, invoker, dst.total()/(double)(1<<16));
|
opt_SSE41::resizeNN4_SSE4_1(range, src, dst, x_ofs, pix_size4, ify);
|
||||||
}
|
|
||||||
else if(pix_size == 4)
|
|
||||||
{
|
|
||||||
resizeNNInvokerSSE4 invoker(src, dst, x_ofs, pix_size4, ify);
|
|
||||||
parallel_for_(range, invoker, dst.total()/(double)(1<<16));
|
|
||||||
}
|
|
||||||
}
|
}
|
||||||
else
|
else
|
||||||
#endif
|
#endif
|
||||||
@ -5864,8 +5551,8 @@ public:
|
|||||||
const int AB_BITS = MAX(10, (int)INTER_BITS);
|
const int AB_BITS = MAX(10, (int)INTER_BITS);
|
||||||
const int AB_SCALE = 1 << AB_BITS;
|
const int AB_SCALE = 1 << AB_BITS;
|
||||||
int round_delta = interpolation == INTER_NEAREST ? AB_SCALE/2 : AB_SCALE/INTER_TAB_SIZE/2, x, y, x1, y1;
|
int round_delta = interpolation == INTER_NEAREST ? AB_SCALE/2 : AB_SCALE/INTER_TAB_SIZE/2, x, y, x1, y1;
|
||||||
#if CV_AVX2
|
#if CV_TRY_AVX2
|
||||||
bool useAVX2 = checkHardwareSupport(CV_CPU_AVX2);
|
bool useAVX2 = CV_CPU_HAS_SUPPORT_AVX2;
|
||||||
#endif
|
#endif
|
||||||
#if CV_SSE2
|
#if CV_SSE2
|
||||||
bool useSSE2 = checkHardwareSupport(CV_CPU_SSE2);
|
bool useSSE2 = checkHardwareSupport(CV_CPU_SSE2);
|
||||||
@ -5947,41 +5634,9 @@ public:
|
|||||||
{
|
{
|
||||||
short* alpha = A + y1*bw;
|
short* alpha = A + y1*bw;
|
||||||
x1 = 0;
|
x1 = 0;
|
||||||
#if CV_AVX2
|
#if CV_TRY_AVX2
|
||||||
if ( useAVX2 )
|
if ( useAVX2 )
|
||||||
{
|
x1 = opt_AVX2::warpAffineBlockline(adelta + x, bdelta + x, xy, alpha, X0, Y0, bw);
|
||||||
__m256i fxy_mask = _mm256_set1_epi32(INTER_TAB_SIZE - 1);
|
|
||||||
__m256i XX = _mm256_set1_epi32(X0), YY = _mm256_set1_epi32(Y0);
|
|
||||||
for( ; x1 <= bw - 16; x1 += 16 )
|
|
||||||
{
|
|
||||||
__m256i tx0, tx1, ty0, ty1;
|
|
||||||
tx0 = _mm256_add_epi32(_mm256_loadu_si256((const __m256i*)(adelta + x + x1)), XX);
|
|
||||||
ty0 = _mm256_add_epi32(_mm256_loadu_si256((const __m256i*)(bdelta + x + x1)), YY);
|
|
||||||
tx1 = _mm256_add_epi32(_mm256_loadu_si256((const __m256i*)(adelta + x + x1 + 8)), XX);
|
|
||||||
ty1 = _mm256_add_epi32(_mm256_loadu_si256((const __m256i*)(bdelta + x + x1 + 8)), YY);
|
|
||||||
|
|
||||||
tx0 = _mm256_srai_epi32(tx0, AB_BITS - INTER_BITS);
|
|
||||||
ty0 = _mm256_srai_epi32(ty0, AB_BITS - INTER_BITS);
|
|
||||||
tx1 = _mm256_srai_epi32(tx1, AB_BITS - INTER_BITS);
|
|
||||||
ty1 = _mm256_srai_epi32(ty1, AB_BITS - INTER_BITS);
|
|
||||||
|
|
||||||
__m256i fx_ = _mm256_packs_epi32(_mm256_and_si256(tx0, fxy_mask),
|
|
||||||
_mm256_and_si256(tx1, fxy_mask));
|
|
||||||
__m256i fy_ = _mm256_packs_epi32(_mm256_and_si256(ty0, fxy_mask),
|
|
||||||
_mm256_and_si256(ty1, fxy_mask));
|
|
||||||
tx0 = _mm256_packs_epi32(_mm256_srai_epi32(tx0, INTER_BITS),
|
|
||||||
_mm256_srai_epi32(tx1, INTER_BITS));
|
|
||||||
ty0 = _mm256_packs_epi32(_mm256_srai_epi32(ty0, INTER_BITS),
|
|
||||||
_mm256_srai_epi32(ty1, INTER_BITS));
|
|
||||||
fx_ = _mm256_adds_epi16(fx_, _mm256_slli_epi16(fy_, INTER_BITS));
|
|
||||||
fx_ = _mm256_permute4x64_epi64(fx_, (3 << 6) + (1 << 4) + (2 << 2) + 0);
|
|
||||||
|
|
||||||
_mm256_storeu_si256((__m256i*)(xy + x1*2), _mm256_unpacklo_epi16(tx0, ty0));
|
|
||||||
_mm256_storeu_si256((__m256i*)(xy + x1*2 + 16), _mm256_unpackhi_epi16(tx0, ty0));
|
|
||||||
_mm256_storeu_si256((__m256i*)(alpha + x1), fx_);
|
|
||||||
}
|
|
||||||
_mm256_zeroupper();
|
|
||||||
}
|
|
||||||
#endif
|
#endif
|
||||||
#if CV_SSE2
|
#if CV_SSE2
|
||||||
if( useSSE2 )
|
if( useSSE2 )
|
||||||
|
|||||||
73
modules/imgproc/src/imgwarp.hpp
Normal file
73
modules/imgproc/src/imgwarp.hpp
Normal file
@ -0,0 +1,73 @@
|
|||||||
|
/*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) 2014-2015, Itseez Inc., 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*/
|
||||||
|
|
||||||
|
/* ////////////////////////////////////////////////////////////////////
|
||||||
|
//
|
||||||
|
// Geometrical transforms on images and matrices: rotation, zoom etc.
|
||||||
|
//
|
||||||
|
// */
|
||||||
|
|
||||||
|
#ifndef OPENCV_IMGPROC_IMGWARP_HPP
|
||||||
|
#define OPENCV_IMGPROC_IMGWARP_HPP
|
||||||
|
#include "precomp.hpp"
|
||||||
|
|
||||||
|
namespace cv
|
||||||
|
{
|
||||||
|
namespace opt_AVX2
|
||||||
|
{
|
||||||
|
#if CV_TRY_AVX2
|
||||||
|
void resizeNN2_AVX2(const Range&, const Mat&, Mat&, int*, int, double);
|
||||||
|
void resizeNN4_AVX2(const Range&, const Mat&, Mat&, int*, int, double);
|
||||||
|
int warpAffineBlockline(int *adelta, int *bdelta, short* xy, short* alpha, int X0, int Y0, int bw);
|
||||||
|
#endif
|
||||||
|
}
|
||||||
|
namespace opt_SSE41
|
||||||
|
{
|
||||||
|
#if CV_TRY_SSE4_1
|
||||||
|
void resizeNN2_SSE4_1(const Range&, const Mat&, Mat&, int*, int, double);
|
||||||
|
void resizeNN4_SSE4_1(const Range&, const Mat&, Mat&, int*, int, double);
|
||||||
|
#endif
|
||||||
|
}
|
||||||
|
}
|
||||||
|
#endif
|
||||||
|
/* End of file. */
|
||||||
192
modules/imgproc/src/imgwarp.sse4_1.cpp
Normal file
192
modules/imgproc/src/imgwarp.sse4_1.cpp
Normal file
@ -0,0 +1,192 @@
|
|||||||
|
/*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) 2014-2015, Itseez Inc., 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*/
|
||||||
|
|
||||||
|
/* ////////////////////////////////////////////////////////////////////
|
||||||
|
//
|
||||||
|
// Geometrical transforms on images and matrices: rotation, zoom etc.
|
||||||
|
//
|
||||||
|
// */
|
||||||
|
|
||||||
|
#include "precomp.hpp"
|
||||||
|
#include "imgwarp.hpp"
|
||||||
|
|
||||||
|
namespace cv
|
||||||
|
{
|
||||||
|
namespace opt_SSE41
|
||||||
|
{
|
||||||
|
|
||||||
|
class resizeNNInvokerSSE2 :
|
||||||
|
public ParallelLoopBody
|
||||||
|
{
|
||||||
|
public:
|
||||||
|
resizeNNInvokerSSE2(const Mat& _src, Mat &_dst, int *_x_ofs, int _pix_size4, double _ify) :
|
||||||
|
ParallelLoopBody(), src(_src), dst(_dst), x_ofs(_x_ofs), pix_size4(_pix_size4),
|
||||||
|
ify(_ify)
|
||||||
|
{
|
||||||
|
}
|
||||||
|
|
||||||
|
#if defined(__INTEL_COMPILER)
|
||||||
|
#pragma optimization_parameter target_arch=SSE4.2
|
||||||
|
#endif
|
||||||
|
virtual void operator() (const Range& range) const
|
||||||
|
{
|
||||||
|
Size ssize = src.size(), dsize = dst.size();
|
||||||
|
int y, x;
|
||||||
|
int width = dsize.width;
|
||||||
|
int sseWidth = width - (width & 0x7);
|
||||||
|
for(y = range.start; y < range.end; y++)
|
||||||
|
{
|
||||||
|
uchar* D = dst.data + dst.step*y;
|
||||||
|
uchar* Dstart = D;
|
||||||
|
int sy = std::min(cvFloor(y*ify), ssize.height-1);
|
||||||
|
const uchar* S = src.data + sy*src.step;
|
||||||
|
__m128i CV_DECL_ALIGNED(64) pixels = _mm_set1_epi16(0);
|
||||||
|
for(x = 0; x < sseWidth; x += 8)
|
||||||
|
{
|
||||||
|
ushort imm = *(ushort*)(S + x_ofs[x + 0]);
|
||||||
|
pixels = _mm_insert_epi16(pixels, imm, 0);
|
||||||
|
imm = *(ushort*)(S + x_ofs[x + 1]);
|
||||||
|
pixels = _mm_insert_epi16(pixels, imm, 1);
|
||||||
|
imm = *(ushort*)(S + x_ofs[x + 2]);
|
||||||
|
pixels = _mm_insert_epi16(pixels, imm, 2);
|
||||||
|
imm = *(ushort*)(S + x_ofs[x + 3]);
|
||||||
|
pixels = _mm_insert_epi16(pixels, imm, 3);
|
||||||
|
imm = *(ushort*)(S + x_ofs[x + 4]);
|
||||||
|
pixels = _mm_insert_epi16(pixels, imm, 4);
|
||||||
|
imm = *(ushort*)(S + x_ofs[x + 5]);
|
||||||
|
pixels = _mm_insert_epi16(pixels, imm, 5);
|
||||||
|
imm = *(ushort*)(S + x_ofs[x + 6]);
|
||||||
|
pixels = _mm_insert_epi16(pixels, imm, 6);
|
||||||
|
imm = *(ushort*)(S + x_ofs[x + 7]);
|
||||||
|
pixels = _mm_insert_epi16(pixels, imm, 7);
|
||||||
|
_mm_storeu_si128((__m128i*)D, pixels);
|
||||||
|
D += 16;
|
||||||
|
}
|
||||||
|
for(; x < width; x++)
|
||||||
|
{
|
||||||
|
*(ushort*)(Dstart + x*2) = *(ushort*)(S + x_ofs[x]);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
private:
|
||||||
|
const Mat src;
|
||||||
|
Mat dst;
|
||||||
|
int* x_ofs, pix_size4;
|
||||||
|
double ify;
|
||||||
|
|
||||||
|
resizeNNInvokerSSE2(const resizeNNInvokerSSE2&);
|
||||||
|
resizeNNInvokerSSE2& operator=(const resizeNNInvokerSSE2&);
|
||||||
|
};
|
||||||
|
|
||||||
|
class resizeNNInvokerSSE4 :
|
||||||
|
public ParallelLoopBody
|
||||||
|
{
|
||||||
|
public:
|
||||||
|
resizeNNInvokerSSE4(const Mat& _src, Mat &_dst, int *_x_ofs, int _pix_size4, double _ify) :
|
||||||
|
ParallelLoopBody(), src(_src), dst(_dst), x_ofs(_x_ofs), pix_size4(_pix_size4),
|
||||||
|
ify(_ify)
|
||||||
|
{
|
||||||
|
}
|
||||||
|
#if defined(__INTEL_COMPILER)
|
||||||
|
#pragma optimization_parameter target_arch=SSE4.2
|
||||||
|
#endif
|
||||||
|
virtual void operator() (const Range& range) const
|
||||||
|
{
|
||||||
|
Size ssize = src.size(), dsize = dst.size();
|
||||||
|
int y, x;
|
||||||
|
int width = dsize.width;
|
||||||
|
int sseWidth = width - (width & 0x3);
|
||||||
|
for(y = range.start; y < range.end; y++)
|
||||||
|
{
|
||||||
|
uchar* D = dst.data + dst.step*y;
|
||||||
|
uchar* Dstart = D;
|
||||||
|
int sy = std::min(cvFloor(y*ify), ssize.height-1);
|
||||||
|
const uchar* S = src.data + sy*src.step;
|
||||||
|
__m128i CV_DECL_ALIGNED(64) pixels = _mm_set1_epi16(0);
|
||||||
|
for(x = 0; x < sseWidth; x += 4)
|
||||||
|
{
|
||||||
|
int imm = *(int*)(S + x_ofs[x + 0]);
|
||||||
|
pixels = _mm_insert_epi32(pixels, imm, 0);
|
||||||
|
imm = *(int*)(S + x_ofs[x + 1]);
|
||||||
|
pixels = _mm_insert_epi32(pixels, imm, 1);
|
||||||
|
imm = *(int*)(S + x_ofs[x + 2]);
|
||||||
|
pixels = _mm_insert_epi32(pixels, imm, 2);
|
||||||
|
imm = *(int*)(S + x_ofs[x + 3]);
|
||||||
|
pixels = _mm_insert_epi32(pixels, imm, 3);
|
||||||
|
_mm_storeu_si128((__m128i*)D, pixels);
|
||||||
|
D += 16;
|
||||||
|
}
|
||||||
|
for(; x < width; x++)
|
||||||
|
{
|
||||||
|
*(int*)(Dstart + x*4) = *(int*)(S + x_ofs[x]);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
private:
|
||||||
|
const Mat src;
|
||||||
|
Mat dst;
|
||||||
|
int* x_ofs, pix_size4;
|
||||||
|
double ify;
|
||||||
|
|
||||||
|
resizeNNInvokerSSE4(const resizeNNInvokerSSE4&);
|
||||||
|
resizeNNInvokerSSE4& operator=(const resizeNNInvokerSSE4&);
|
||||||
|
};
|
||||||
|
|
||||||
|
void resizeNN2_SSE4_1(const Range& range, const Mat& src, Mat &dst, int *x_ofs, int pix_size4, double ify)
|
||||||
|
{
|
||||||
|
resizeNNInvokerSSE2 invoker(src, dst, x_ofs, pix_size4, ify);
|
||||||
|
parallel_for_(range, invoker, dst.total() / (double)(1 << 16));
|
||||||
|
}
|
||||||
|
|
||||||
|
void resizeNN4_SSE4_1(const Range& range, const Mat& src, Mat &dst, int *x_ofs, int pix_size4, double ify)
|
||||||
|
{
|
||||||
|
resizeNNInvokerSSE4 invoker(src, dst, x_ofs, pix_size4, ify);
|
||||||
|
parallel_for_(range, invoker, dst.total() / (double)(1 << 16));
|
||||||
|
}
|
||||||
|
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
/* End of file. */
|
||||||
Loading…
Reference in New Issue
Block a user