Ubuntu 配置 opencv , CodeBlocks 开发环境

最新推荐文章于 2023-09-23 04:46:41 发布

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最新推荐文章于 2023-09-23 04:46:41 发布

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分类专栏：配置文章标签： ubuntu library translation processing descriptor

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转自：

主要：http://blog.youkuaiyun.com/cenziboy/article/details/7570139

参考：http://blog.youkuaiyun.com/yr119111/article/details/7666106

一、安装CodeBlocks（我用的是方法一）

方法一：直接在Ubuntu软件中心中找到CodeBlocks软件，直接安装；

方法二：命令行安装

# apt-getinstall codeblocks 
# apt-getinstall codeblocks-contrib     #wxWidgets 貌似要用 
# apt-get install libwxbase2.8-dev       # 还是 wxWidgets 的东东

二、安装opencv

1、先查询opencv

~#apt-cache search opencv  #输入此行命令，下面为系统查询结果
libcv-dev- Translation package for libcv-dev 
libcv2.3- computer vision library - libcv* translation package 
libcvaux-dev- Translation package for libcvaux-dev 
libcvaux2.3- computer vision library - libcvaux translation package 
libhighgui-dev- Translation package for libhighgui-dev 
libhighgui2.3- computer vision library - libhighgui translation package 
libopencv-calib3d-dev- development files for libopencv-calib3d 
libopencv-calib3d2.3- computer vision Camera Calibration library 
libopencv-contrib-dev- development files for libopencv-contrib 
libopencv-contrib2.3- computer vision contrib library 
libopencv-core-dev- development files for libopencv-core 
libopencv-core2.3- computer vision core library 
libopencv-dev- development files for opencv 
libopencv-features2d-dev- development files for libopencv-features2d 
libopencv-features2d2.3- computer vision Feature Detection and Descriptor Extraction library 
libopencv-flann-dev- development files for libopencv-flann 
libopencv-flann2.3- computer vision Clustering and Search in Multi-Dimensional spaceslibrary 
libopencv-gpu-dev- development files for libopencv-gpu 
libopencv-gpu2.3- computer vision GPU Processing library 
libopencv-highgui-dev- development files for libopencv-highgui 
libopencv-highgui2.3- computer vision High-level GUI and Media I/O library 
libopencv-imgproc-dev- development files for libopencv-imgproc 
libopencv-imgproc2.3- computer vision Image Processing library 
libopencv-legacy-dev- development files for libopencv-legacy 
libopencv-legacy2.3- computer vision legacy library 
libopencv-ml-dev- development files for libopencv-ml 
libopencv-ml2.3- computer vision Machine Learning library 
libopencv-objdetect-dev- development files for libopencv-objdetect 
libopencv-objdetect2.3- computer vision Object Detection library 
libopencv-video-dev- development files for libopencv-video 
libopencv-video2.3- computer vision Video analysis library 
opencv-doc- OpenCV documentation and examples 
python-opencv - Python bindings forthe computer vision library

2、根据查询结果安装

#1  输入命令
#  apt-get install libcv2.3 libcvaux2.3 libhighgui2.3 
 
#2  输入命令
#  apt-get install libcv-dev libcvaux-dev libhighgui-dev

三、codeblocks+opencv的配置

1 相关文件位置

输入命令~# pkg-config --cflags opencv  # opencv 头文件（.h） 位置
输出：-I/usr/include/opencv 
 
输入命令：~# pkg-config --libs opencv        # opencv 库文件
输出：-lopencv_core -lopencv_imgproc -lopencv_highgui -lopencv_ml-lopencv_video -lopencv_features2d -lopencv_calib3d -lopencv_objdetect-lopencv_contrib -lopencv_legacy -lopencv_flann

这样就装好了!

（

如果以上两步得不到对应结果则参考http://blog.youkuaiyun.com/yr119111/article/details/7666106中以下配置试试

======================================================

配置Linux.openCV参数设置

在/etc/ld.so.conf.d/opencv.conf文件中加入一行：/usr/local/lib ,
可能会没有opencv.conf这个文件，那我们就自己创建一个:
sudo gedit /etc/ld.so.conf.d/opencv.conf。
使用下面这条命令：
sudo ldconfig         
在 /etc/ bash.bashrc中加入:（sudo gedit /etc/bash.bashrc以root进入才能修改）
PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/usr/local/lib/pkgconfig
export PKG_CONFIG_PATH

======================================================

）

2 codeBlocks链接库配置: Project -> Build Options 如下图：（最好将所有关于opencv的so库文件都选中）

3 codeBlocks 头文件目录配置（pkg-config --cflags opencv 结果）

4 codeBlocks 路文件目录配置

测试代码：

#include"cv.h" 
#include"highgui.h" 
#include<iostream>
int main() 
{ 
    IplImage* pImg= cvLoadImage("/home/jh/CBWorkspace/Test1/mao.jpg",1); 
         if(pImg==NULL)
         {
                   std::cout << "Notfound Iamge!"<<std::endl;
                   return 0;
         }
    cvNamedWindow("Image", 1); 
    cvShowImage("Image", pImg); 
 
    cvWaitKey(0); 
 
    cvDestroyWindow("Image"); 
    cvReleaseImage(&pImg); 
 
    return 0; 
}

测试结果：