Ubuntu环境下VScode配置OpenCV的C++开发环境

 任务描述：ubuntu下在vs code内配置opencv的c++环境， 并运行示例代码。

 

step 0. 写在前面的话

我的环境是Ubuntu18，OpenCV3.4.1+contrib3.4.1，VScode都是已经安装好的。

其中opencv的配置请参考ubuntu下opencv的配置。VScode是直接在商城中搜索下载即可。

 

step 1. vs code插件安装

如下图，给vs code安装C/C++插件。

step 2. 新建一个文件夹，在vs code内新建文件，编写如下调试代码。

我们的配置过程分为两个阶段：C++编译环境和opencv开发环境。

step 3. C++编译环境的配置

Debug -> Open Configurations -> 打开备选框 -> C++(GDB/LLDB) -> g++ build and debug active file

上述操作打开launch.json文件，修改其中的设置项。修改后如下：

    "version": "0.2.0",
    "configurations": [
        {
            "name": "g++ build and debug active file",
            "type": "cppdbg",
            "request": "launch",
            "program": "${fileDirname}/${fileBasenameNoExtension}",
            "args": [],
            "stopAtEntry": false,
            "cwd": "${workspaceFolder}",
            "environment": [],
            "externalConsole": true,
            "MIMode": "gdb",
            "setupCommands": [
                {
                    "description": "Enable pretty-printing for gdb",
                    "text": "-enable-pretty-printing",
                    "ignoreFailures": true
                }
            ],
            "preLaunchTask": "g++ build active file",
            "miDebuggerPath": "/usr/bin/gdb"
        }
    ]

其中需要重点注意的几个地方在于：

（1）"externalConsole": true  关键字修改为true，指的是弹出命令窗口。

（2）"preLaunchTask": "g++ build active file"  后面的配置需要用到这个关键字。

然后回到测试代码的文件，注销掉与opencv相关的代码（因为）我们目前仅针对C++编译环境进行配置，点击F5运行，出现如下提示：

选择Configure Task，在备选框中选择C/C++:cpp build active file选项，则新建一个task.json文件。

修改文件配置如下：

//> 编译单个文件

    "version": "2.0.0",
    "tasks": [
        {
            "type": "shell",
            "label": "g++ build active file",
            "command": "g++",
            "args": [
                "-g","-std=c++11", "${file}", "-o", "${fileDirname}/${fileBasenameNoExtension}",
            ],
            "options": {
                "cwd": "/usr/bin"
            },
            "problemMatcher": [
                "$gcc"
            ],
            "group": "build"
        }
    ]


//> 编译多个文件

    "version": "2.0.0",
    "tasks": [
        {
            "type": "shell",
            "label": "g++ build active file",
            "command": "g++",
            "args": [
                "-g","-std=c++11", "${fileDirname}/*.cpp", "-o", "${fileDirname}/${fileBasenameNoExtension}",
            ],
            "options": {
                "cwd": "/usr/bin"
            },
            "problemMatcher": [
                "$gcc"
            ],
            "group": "build"
        }
    ]

其中，需要注意的几点是：

（1）"label": "g++ build active file"  关键字必须与前述launch.json文件的"preLaunchTask": "g++ build active file"关键字一致。

（2）"command": "g++" 关键字要修改为g++，否则可能会报不能debug的提示。

（3）"args": [ "-g", "-std=c++11", "${file}", "-o", "${fileDirname}/${fileBasenameNoExtension}" ] 关键字就是g++的编译指令。

此时，就可以运行CPP代码了，回到测试文件，点击F5，会在控制台输出Hello world的字符，如图。

step 4. 配置Opencv的开发环境

这一步的主要思路，与在windows环境下为VS配置Opencv开发环境是一致的，即：将include的头文件所在路径和函数库的路径 

设置给编译器。

Ctrl + Shift + P 打开搜索框，键入c++，会出现备选项目，选择图示Edit configurations (JSON)，

进入c_cpp_properties.json文件内进行配置修改。修改如下：

"configurations": [
        {
            "name": "Linux",
            "includePath": [
                "${workspaceFolder}/**",
                "/usr/local/include"
            ],
            "defines": [],
            "compilerPath": "/usr/bin/gcc",
            "cStandard": "c11",
            "cppStandard": "c++17",
            "intelliSenseMode": "clang-x64"
        }
    ],
    "version": 4

主要注意的地方在于：

"includePath" 选项内添加关键字路径 "/usr/local/include"，这里面存放的是opencv和opencv2两个文件，如图：

另外在task.json文件内添加如下修改：

"args": [
                "-g", "-std=c++11", "${file}", "-o", "${fileDirname}/${fileBasenameNoExtension}",
                "-I", "/usr/local/include",
                "-I", "/usr/local/include/opencv",
                "-I", "/usr/local/include/opencv2",
                "-L", "/usr/local/lib",
                "-l", "opencv_aruco",
                "-l", "opencv_bgsegm",
                "-l", "opencv_bioinspired",
                "-l", "opencv_calib3d",
                "-l", "opencv_ccalib",
                "-l", "opencv_core",
                "-l", "opencv_datasets",
                "-l", "opencv_dnn_objdetect",
                "-l", "opencv_dnn",
                "-l", "opencv_dpm",
                "-l", "opencv_face",
                "-l", "opencv_features2d",
                "-l", "opencv_flann",
                "-l", "opencv_freetype",
                "-l", "opencv_fuzzy",
                "-l", "opencv_hfs",
                "-l", "opencv_highgui",                
                "-l", "opencv_imgcodecs",
                "-l", "opencv_img_hash",
                "-l", "opencv_imgproc",
                "-l", "opencv_line_descriptor",
                "-l", "opencv_ml",
                "-l", "opencv_objdetect",
                "-l", "opencv_optflow",
                "-l", "opencv_phase_unwrapping",
                "-l", "opencv_photo",
                "-l", "opencv_plot",
                "-l", "opencv_reg",
                "-l", "opencv_rgbd",
                "-l", "opencv_saliency",
                "-l", "opencv_shape",
                "-l", "opencv_stereo",
                "-l", "opencv_stitching",
                "-l", "opencv_structured_light",
                "-l", "opencv_superres",
                "-l", "opencv_surface_matching",
                "-l", "opencv_text",
                "-l", "opencv_tracking",
                "-l", "opencv_videoio",
                "-l", "opencv_video",
                "-l", "opencv_videostab",
                "-l", "opencv_xfeatures2d",
                "-l", "opencv_ximgproc",
                "-l", "opencv_xobjdetect",
                "-l", "opencv_xphoto",
            ],

其中：“-I”指令后面的头文件坐在路径，“-L”后面是库文件所在路径，“-l” 后面是库的名字。

注意：此处有个坑就是，库的名字一定要按照上述文档中的方式写，即“opencv_XXX”，而不能按照传统上linux的库名“libopencv_XXX”，否则编译会报错说找不到函数库。

step 5. 回到测试文件，F5运行如下

但是似乎这种方法每次新开一个工程都需要再配置一遍，后面再研究一下一劳永逸的方法吧！

本文内容参考了参考1，参考2，参考3，感谢这些博主们的分享！