OPENCV 2.4.9 +VS2013 开发环境配置.pdf

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1、OpenCV2.4.9+VS2013开发环境配置OpenCV的全称是：OpenSourceComputerVisionLibrary。OpenCV是一个基于（开源）发行的跨平台计算机视觉库，可以运行在Linux、Windows和MacOS操作系统上。它轻量级而且高效——由一系列C函数和少量C++类构成，同时提供了Python、Ruby、MATLAB等语言的接口，实现了图像处理和计算机视觉方面的很多通用算法。现本教程，是在windows平台下使用visualstudio2013和opencv2.4.9配置一个开发环境。工具/原料opencv2

2、.4.9vs2013方法/步骤1安装opencv2.4.9，解压，请务必记住自己解压的路径。宜家以我自己的路径为例D:ProgramFiles2配置环境变量1、系统变量Path：添加D:ProgramFilesopencvbuildx86vc12bin2、用户变量：添加opencv变量，值D:ProgramFilesopencvbuild，添加PATH变量（有就不需要添加，但是值需要添加）值D:ProgramFilesopencvbuildx86vc12bin说明：不管你系统是32位还是64位，路径目录均选择

3、X86，因为编译都是使用32位编译；如果选用X64，则程序运行时候会出错。3新建visualC项目新建visualC++项目，如下图所示，项目选项注意：如下图。4工程目录的配置（Debug）找到属性管理器，如果找不到，请安装下图方法找到。双击Debug

4、Win32打开如下窗口，设置如下：（下图红框项为设置项）1、包含目录：（VC++目录）D:ProgramFilesopencvbuildincludeD:ProgramFilesopencvbuildincludeopencvD:ProgramFilesopencvb

5、uildincludeopencv22、库目录：（VC++目录）D:ProgramFilesopencvbuildx86vc12lib3、连接器->输入->附加依赖项：opencv_ml249d.libopencv_calib3d249d.libopencv_contrib249d.libopencv_core249d.libopencv_features2d249d.libopencv_flann249d.libopencv_gpu249d.libopencv_highgui249d.libopencv_imgproc24

6、9d.libopencv_legacy249d.libopencv_objdetect249d.libopencv_ts249d.libopencv_video249d.libopencv_nonfree249d.libopencv_ocl249d.libopencv_photo249d.libopencv_stitching249d.libopencv_superres249d.libopencv_videostab249d.lib其实以上都是D:ProgramFilesopencvbuildx86vc12lib下所有的lib

7、文件，你会发现，有的后面带上d，有的没有d，这是因为Debug的就有d，Release则没有d。工程目录的配置（Release）其他与Debug一样，只是连接器->输入->附加依赖项不一样，设置如下：opencv_objdetect249.libopencv_ts249.libopencv_video249.libopencv_nonfree249.libopencv_ocl249.libopencv_photo249.libopencv_stitching249.libopencv_superres249.libopencv_videos

8、tab249.libopencv_calib3d249.libopencv_contrib249.libopencv_core249.libopencv_features2d249.libopencv_flann249.libopencv_gpu249.libopencv_highgui249.libopencv_imgproc249.libopencv_legacy249.libopencv_ml249.lib最终的测试1、新建一个cpp文件，如下图：在cpp文件上输入以下代码：#include#include

9、.h>usingnamespacestd;intmain(){IplImage*test;test=cvLoadImage("D:\Sample_8.bmp");//图片路径c