开源库Simd在vs2010中的编译及简单使用

Simd是开源的图像处理库，它提供了很多高性能的算法，这些优化算法主要由SIMD指令来实现，包括SSE、SSE2、SSSE3、SSE4.1、SSE4.2、AVX等，此库可以应用在windows/linux 32bit/64bit等系统中。此库更新较频繁。此库的license是MIT。

下面详细介绍其在vs2010中的编译及使用：

1.        从https://sourceforge.net/projects/simd/?source=typ_redirect下载最新版本simd.2.2.27.443，解压缩；

2.        新建一个libSimd静态库工程，将/simd.2.2.27.443/simd/src/Simd目录下的.h、.cpp文件加入到此工程中，将../../../src/simd.2.2.27.443/simd/src/加入到C/C++--> General --> Additional Include Directories中，编译即可生成静态库，其实/simd.2.2.27.443/simd/prj/vs11中已经有了vs2012的工程配置，只是工程数太多，我把它们都放在一个工程里了；

3. 新建一个testSimd控制台工程，测试生成的libSimd库的正确性，相关代码如下：

stdafx.h:

#pragma once#include "targetver.h"#include <stdio.h>#include "Simd/SimdSse2.h"#include "Simd/SimdBase.h"#include "../../OpenCV/2.4.9/vs2010/install/include/opencv2/core/core.hpp"#include "../../OpenCV/2.4.9/vs2010/install/include/opencv2/highgui/highgui.hpp"#include "../../OpenCV/2.4.9/vs2010/install/include/opencv2/imgproc/imgproc.hpp"

stdafx.cpp:

#include "stdafx.h"#ifdef _DEBUG#pragma comment(lib, "../../../lib/dbg/x86_vc10/libSimd[dbg_x86_vc10].lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/zlibd.lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/IlmImfd.lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/libjasperd.lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/libjpegd.lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/libpngd.lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/libtiffd.lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/opencv_core249d.lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/opencv_highgui249d.lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/opencv_imgproc249d.lib")#pragma comment(lib, "comctl32.lib") #else#pragma comment(lib, "../../../lib/rel/x86_vc10/libSimd[rel_x86_vc10].lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/zlib.lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/IlmImf.lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/libjasper.lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/libjpeg.lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/libpng.lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/libtiff.lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/opencv_core249.lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/opencv_highgui249.lib")#pragma comment(lib, "../../../../OpenCV/2.4.9/vs2010/install/x86/vc10/staticlib/opencv_imgproc249.lib")#pragma comment(lib, "comctl32.lib")#endif

testSimd.cpp:

#include "stdafx.h"#include <iostream>#include <string>using namespace std;void BgraToGrayTest(){string strImageName = "../../../testdata/cat.jpg";int iImageWidth = 10000;int iImageHeight = 10000;cv::Mat matSrc = cv::imread(strImageName, 1);cv::cvtColor(matSrc, matSrc, cv::COLOR_BGR2BGRA);cv::resize(matSrc, matSrc, cv::Size(iImageWidth, iImageHeight), 0, 0, 1);cv::Mat matDst1, matDst2;matDst1 = cv::Mat::zeros(iImageHeight, iImageWidth, CV_8UC1);matDst2 = cv::Mat::zeros(iImageHeight, iImageWidth, CV_8UC1);int iRemainder = iImageWidth & 0x03;int iGrayStride =  iRemainder ? iImageWidth + 4 - iRemainder : iImageWidth;CV_Assert(iRemainder == 0);double dTimeC = cv::getTickCount();Simd::Base::BgraToGray(matSrc.data, iImageWidth, iImageHeight, iImageWidth * 4, matDst1.data, iGrayStride);dTimeC = ((double)cv::getTickCount() - dTimeC) / cv::getTickFrequency();double dTimeSimd = cv::getTickCount();Simd::Sse2::BgraToGray(matSrc.data, iImageWidth, iImageHeight, iImageWidth * 4, matDst2.data, iGrayStride);dTimeSimd = ((double)cv::getTickCount() - dTimeSimd) / cv::getTickFrequency();cout<<"C run time : "<<dTimeC<<endl;cout<<"Simd run time : "<<dTimeSimd<<endl;int iDiffCount = 0;for (int i = 0; i < iImageHeight; i++) {uchar* p1 = matDst1.ptr<uchar>(i);uchar* p2 = matDst2.ptr<uchar>(i);for (int j = 0; j < iImageWidth; j++) {if (p1[j] != p2[j])iDiffCount ++;}}cout<<"the different count: "<<iDiffCount<<endl;}int main(int argc, char* argv[]){BgraToGrayTest();cout<<"ok!"<<endl;return 0;}

运行结果见下 图：

运行多次，SIMD的执行速度基本上比C快3倍，它们的结果是完全一致的。

GitHub：https://github.com/fengbingchun/Simd_Test