c++ - 使用 ARM NEON 内部函数对 cvtColor 进行 SIMD 优化

Question

我正在研究 BGR 到灰度转换的 SIMD 优化，相当于 OpenCV's cvtColor() function .这个函数有一个 Intel SSE 版本，我指的是它。 (我所做的基本上是将 SSE 代码转换为 NEON 代码。)

我快写完代码了，可以用g++编译了，但是我得不到正确的输出。有谁知道错误可能是什么？

我得到的(不正确的):

我应该得到的:

这是我的代码:

#include <opencv/cv.hpp>
#include <opencv/highgui.h>
#include <arm_neon.h>
//#include <iostream>

using namespace std;
//using namespace cv;

#define int8x16_to_8x8x2(v) ((int8x8x2_t) { vget_low_s8(v), vget_high_s8(v) })

void cvtBGR2GrayNEON(cv::Mat& src, cv::Mat& dest)
{
  const int size = src.size().area()*src.channels();
  uchar* s = src.ptr<uchar>(0);
  uchar* d = dest.ptr<uchar>(0);

  const int8x16_t mask1 = {0,3,6,9,12,15,1,4,7,10,13,2,5,8,11,14};
  const int8x16_t smask1 = {6,7,8,9,10,0,1,2,3,4,5,11,12,13,14,15};
  const int8x16_t ssmask1 = {11,12,13,14,15,0,1,2,3,4,5,6,7,8,9,10};

  const int8x16_t mask2 = {0,3,6,9,12,15, 2,5,8,11,14,1,4,7,10,13};
  const int8x16_t ssmask2 = {0,1,2,3,4,11,12,13,14,15,5,6,7,8,9,10};

  const int8x16_t bmask1 = {255,255,255,255,255,255,0,0,0,0,0,0,0,0,0,0};
  const int8x16_t bmask2 = {255,255,255,255,255,255,255,255,255,255,255,0,0,0,0,0};
  const int8x16_t bmask3 = {255,255,255,255,255,0,0,0,0,0,0,0,0,0,0,0};
  const int8x16_t bmask4 = {255,255,255,255,255,255,255,255,255,255,0,0,0,0,0,0};

  const int shift = 8;
  const int amp = 1<<shift;

  const int16_t _R_ = (int16_t)(amp*0.299);
  const int16_t _G_ = (int16_t)(amp*0.587);
  const int16_t _B_ = (int16_t)(amp*0.114);
  const int16x8_t R = vdupq_n_s16(_R_);
  const int16x8_t G = vdupq_n_s16(_G_);
  const int16x8_t B = vdupq_n_s16(_B_);
  const int8x16_t zero = vdupq_n_s8(0);

  for(int i = 0; i < size; i += 48)
    {
      int8x16_t a = vld1q_s8((int8_t *) s + i);
      int8x16_t b = vld1q_s8((int8_t *) s + i + 16);
      int8x16_t c = vld1q_s8((int8_t *) s + i + 32);

      a = vcombine_s8(vtbl2_s8(int8x16_to_8x8x2(a),vget_low_s8(mask1)),vtbl2_s8(int8x16_to_8x8x2(a),vget_high_s8(mask1)));
      b = vcombine_s8(vtbl2_s8(int8x16_to_8x8x2(b), vget_low_s8(mask2)), vtbl2_s8(int8x16_to_8x8x2(b), vget_high_s8(mask2)));
      c = vcombine_s8(vtbl2_s8(int8x16_to_8x8x2(c), vget_low_s8(mask2)), vtbl2_s8(int8x16_to_8x8x2(c), vget_high_s8(mask2)));

      //BBBBBB
      const int8x16_t aaaa = vbslq_s8(c, vbslq_s8(b, a, bmask1), bmask2);

      a = vcombine_s8(vtbl2_s8(int8x16_to_8x8x2(a), vget_low_s8(smask1)), vtbl2_s8(int8x16_to_8x8x2(a), vget_high_s8(smask1)));
      b = vcombine_s8(vtbl2_s8(int8x16_to_8x8x2(b), vget_low_s8(smask1)), vtbl2_s8(int8x16_to_8x8x2(b), vget_high_s8(smask1)));
      c = vcombine_s8(vtbl2_s8(int8x16_to_8x8x2(c), vget_low_s8(smask1)), vtbl2_s8(int8x16_to_8x8x2(c), vget_high_s8(smask1)));

      //GGGGGG
      const int8x16_t bbbb = vbslq_s8(c, vbslq_s8(b, a, bmask3), bmask2);

      a = vcombine_s8(vtbl2_s8(int8x16_to_8x8x2(a), vget_low_s8(ssmask1)), vtbl2_s8(int8x16_to_8x8x2(a), vget_high_s8(ssmask1)));
      c = vcombine_s8(vtbl2_s8(int8x16_to_8x8x2(c), vget_low_s8(ssmask1)), vtbl2_s8(int8x16_to_8x8x2(c), vget_high_s8(ssmask1)));
      b = vcombine_s8(vtbl2_s8(int8x16_to_8x8x2(b), vget_low_s8(ssmask2)), vtbl2_s8(int8x16_to_8x8x2(b), vget_high_s8(ssmask2)));

      //RRRRRR
      const int8x16_t cccc = vbslq_s8(c, vbslq_s8(b, a, bmask3), bmask4);

      /*
      int8x8x2_t a1 = vzip_s8(vget_high_s8(aaaa), vget_high_s8(zero));
      int8x8x2_t a2 = vzip_s8(vget_low_s8(aaaa), vget_low_s8(zero));
      */

      int8x16_t a1 = aaaa;
      int8x16_t a2 = zero;
      int8x16x2_t temp1 =  vzipq_s8(a1, a2);
      a1 = temp1.val[0];
      a2 = temp1.val[1];
      int16x8_t aa1 = vmulq_s16((int16x8_t)a2, B);
      int16x8_t aa2 = vmulq_s16((int16x8_t)a1, B);

      int8x16_t b1 = bbbb;
      int8x16_t b2 = zero;
      int8x16x2_t temp2 =  vzipq_s8(b1, b2);
      b1 = temp2.val[0];
      b2 = temp2.val[1];
      int16x8_t bb1 = vmulq_s16((int16x8_t)b2, G);
      int16x8_t bb2 = vmulq_s16((int16x8_t)b1, G);

      int8x16_t c1 = cccc;
      int8x16_t c2 = zero;
      int8x16x2_t temp3 =  vzipq_s8(c1, c2);
      c1 = temp3.val[0];
      c2 = temp3.val[1];
      int16x8_t cc1 = vmulq_s16((int16x8_t)c2, R);
      int16x8_t cc2 = vmulq_s16((int16x8_t)c1, R);

      aa1 = vaddq_s16(aa1, bb1);
      aa1 = vaddq_s16(aa1, cc1);
      aa2 = vaddq_s16(aa2, bb2);
      aa2 = vaddq_s16(aa2, cc2);

      const int shift1 = 8;
      aa1 = vshrq_n_s16(aa1, shift1);
      aa2 = vshrq_n_s16(aa2, shift1);

      uint8x8_t aaa1 = vqmovun_s16(aa1);
      uint8x8_t aaa2 = vqmovun_s16(aa2);

      uint8x16_t result = vcombine_u8(aaa1, aaa2);

      vst1q_u8((uint8_t *)(d), result);

      d+=16;
    }    
}

int main() 
{
  cv::Mat src = cv::imread("Lenna.bmp");
  cv::Mat dest(src.rows, src.cols, CV_8UC1);

  cvtBGR2GrayNEON(src, dest);

  cv::imwrite("grey.jpg", dest);

  return 0;
}

这是等效的 SSE 代码(来自 here):

void cvtBGR2GraySSEShort(Mat& src, Mat& dest)
{
    const int size = src.size().area()*src.channels();
    uchar* s = src.ptr<uchar>(0);
    uchar* d = dest.ptr<uchar>(0);

    //data structure
    //BGR BGR BGR BGR BGR B
    //GR BGR BGR BGR BGR BG
    //R BGR BGR BGR BGR BGR
    //shuffle to BBBBBBGGGGGRRRRR
    const __m128i mask1 = _mm_setr_epi8(0,3,6,9,12,15,1,4,7,10,13,2,5,8,11,14);
    const __m128i smask1 = _mm_setr_epi8(6,7,8,9,10,0,1,2,3,4,5,11,12,13,14,15);
    const __m128i ssmask1 = _mm_setr_epi8(11,12,13,14,15,0,1,2,3,4,5,6,7,8,9,10);

    //shuffle to GGGGGGBBBBBRRRRR
    const __m128i mask2 = _mm_setr_epi8(0,3,6,9,12,15, 2,5,8,11,14,1,4,7,10,13);
    //const __m128i smask2 = _mm_setr_epi8(6,7,8,9,10,0,1,2,3,4,5,11,12,13,14,15);same as smask1
    const __m128i ssmask2 = _mm_setr_epi8(0,1,2,3,4,11,12,13,14,15,5,6,7,8,9,10);

    //shuffle to RRRRRRGGGGGBBBBB
    //__m128i mask3 = _mm_setr_epi8(0,3,6,9,12,15, 2,5,8,11,14,1,4,7,10,13);//same as mask2
    //const __m128i smask3 = _mm_setr_epi8(6,7,8,9,10,0,1,2,3,4,5,6,7,8,9,10);//same as smask1
    //const __m128i ssmask3 = _mm_setr_epi8(11,12,13,14,15,0,1,2,3,4,5,6,7,8,9,10);//same as ssmask1

    //blend mask
    const __m128i bmask1 = _mm_setr_epi8
        (255,255,255,255,255,255,0,0,0,0,0,0,0,0,0,0);

    const __m128i bmask2 = _mm_setr_epi8
        (255,255,255,255,255,255,255,255,255,255,255,0,0,0,0,0);

    const __m128i bmask3 = _mm_setr_epi8
        (255,255,255,255,255,0,0,0,0,0,0,0,0,0,0,0);

    const __m128i bmask4 = _mm_setr_epi8
        (255,255,255,255,255,255,255,255,255,255,0,0,0,0,0,0);  

    const int shift = 8;
    const int amp = 1<<shift;
    const int _R_=(int)(amp*0.299);
    const int _G_=(int)(amp*0.587);
    const int _B_=(int)(amp*0.114);
    const __m128i R = _mm_set1_epi16(_R_);
    const __m128i G = _mm_set1_epi16(_G_);
    const __m128i B = _mm_set1_epi16(_B_);
    const __m128i zero = _mm_setzero_si128();   

    for(int i=0;i<size;i+=48)
    {
        __m128i a = _mm_shuffle_epi8(_mm_load_si128((__m128i*)(s+i)),mask1);
        __m128i b = _mm_shuffle_epi8(_mm_load_si128((__m128i*)(s+i+16)),mask2);
        __m128i c = _mm_shuffle_epi8(_mm_load_si128((__m128i*)(s+i+32)),mask2);
        const __m128i aaaa = _mm_blendv_epi8(c,_mm_blendv_epi8(b,a,bmask1),bmask2);

        a = _mm_shuffle_epi8(a,smask1);
        b = _mm_shuffle_epi8(b,smask1);
        c = _mm_shuffle_epi8(c,smask1);
        const __m128i bbbb =_mm_blendv_epi8(c,_mm_blendv_epi8(b,a,bmask3),bmask2);

        a = _mm_shuffle_epi8(a,ssmask1);
        c = _mm_shuffle_epi8(c,ssmask1);
        b = _mm_shuffle_epi8(b,ssmask2);
        const __m128i cccc =_mm_blendv_epi8(c,_mm_blendv_epi8(b,a,bmask3),bmask4);

        __m128i a1 = _mm_unpackhi_epi8(aaaa,zero);
        __m128i a2 = _mm_unpacklo_epi8(aaaa,zero);
        a1 = _mm_mullo_epi16(a1,B);
        a2 = _mm_mullo_epi16(a2,B);
        __m128i b1 = _mm_unpackhi_epi8(bbbb,zero);
        __m128i b2 = _mm_unpacklo_epi8(bbbb,zero);
        b1 = _mm_mullo_epi16(b1,G);
        b2 = _mm_mullo_epi16(b2,G);

        __m128i c1 = _mm_unpackhi_epi8(cccc,zero);
        __m128i c2 = _mm_unpacklo_epi8(cccc,zero);
        c1 = _mm_mullo_epi16(c1,R);
        c2 = _mm_mullo_epi16(c2,R);

        a1 = _mm_add_epi16(a1,b1);
        a1 = _mm_add_epi16(a1,c1);
        a2 = _mm_add_epi16(a2,b2);
        a2 = _mm_add_epi16(a2,c2);

        a1 = _mm_srli_epi16(a1,8);
        a2 = _mm_srli_epi16(a2,8);

        a = _mm_packus_epi16(a1,a2);

        _mm_stream_si128((__m128i*)(d),a);
        d+=16;
    } 
}

Answer 1

好的，下面是我刚刚编写的函数的完全优化版本(请注意，如果大小小于 32，此函数只会返回。)

/*
 *  Created on: 2014. 7. 27.
 *      Author: Jake Lee
 *      Project FANIC - Fastest ARM NEON Implementaion Challenge
 */

// void fanicCvtBGR2GrayNEON(void *pDst, void *pSrc, unsigned int size);
// Y = 0.114*B + 0.587*G + 0.299*R
    .text
    .arm
    .global fanicCvtBGR2GrayNEON

    pDst    .req    r0
    pSrc    .req    r1
    size    .req    r2

    .align 5
    .func
fanicCvtBGR2GrayNEON:
    pld     [pSrc]
    subs    size, size, #32
    pld     [pSrc, #64]
    bxmi    lr
    pld     [pSrc, #64*2]
    vmov.i8     d0, #29
    vmov.i8     d1, #150
    vmov.i8     d2, #77

    .align 5
1:
    vld3.8      {d20, d21, d22}, [pSrc]!
    vld3.8      {d23, d24, d25}, [pSrc]!
    vld3.8      {d26, d27, d28}, [pSrc]!
    vld3.8      {d29, d30, d31}, [pSrc]!

    vmull.u8    q8, d20, d0
    vmlal.u8    q8, d21, d1
    vmlal.u8    q8, d22, d2
    vmull.u8    q9, d23, d0
    vmlal.u8    q9, d24, d1
    vmlal.u8    q9, d25, d2
    vmull.u8    q10, d26, d0
    vmlal.u8    q10, d27, d1
    vmlal.u8    q10, d28, d2
    vmull.u8    q11, d29, d0
    vmlal.u8    q11, d30, d1
    vmlal.u8    q11, d31, d2

    vrshrn.u16  d24, q8, #8
    vrshrn.u16  d25, q9, #8
    vrshrn.u16  d26, q10, #8
    vrshrn.u16  d27, q11, #8

    subs    size, size, #32
    pld     [pSrc, #64*3]
    pld     [pSrc, #64*4]

    vst1.8      {q12, q13}, [pDst]!
    bpl     1b

    cmp     size, #-32
    add     pSrc, pSrc, size
    bxle    lr
    add     pSrc, pSrc, size, lsl #1
    add     pDst, pDst, size
    b       1b

    .endfunc
    .end

如您所见，尽管展开繁重，但在汇编中编写 NEON 代码比在内部函数中编写更容易、更短。

玩得开心。