50 ubuntu下pcl编译以及用 VSCode配置pcl / opencv开发环境

0 引言

最近在VSCode下搞开发，于是将pcl库迁移到这个环境下，用来跑一些依赖pcl的开源的代码以及自己做一些快速开发等。

1 pcl编译

主要参考了这篇博客，链接如下。

https://blog.csdn.net/e_small/article/details/79581484

我编译时遇到的主要问题也是在这篇博客的留言下解决的。我安装了Anaconda，结果编译出错，我还一直找不着错哪儿了。。。解决方式记录如下。

$ sudo gedit ~/.bashrc   # 打开环境变量文件 将Anaconda的环境变量给注销掉
$ source /etc/profile       # 使环境变量生效
$ python                         # 测试目前系统默认的python是不是改正了   

然后再重新编译。

另外，在编译时，我改变了CMakeList.txt中的配置，采用的方式是

$ mkdir build
$ cd  build
$ cmake-gui ..     # 打开cmake界面，把一些不需要编译的东西去掉（比如我为了提高编译成功率，去掉了cuda选项），客户端点击configuration-》 generation 即可完成cmake，再回到终端继续make
$ make -j8         # 采用8个线程同时进行编译，有时候可以极大提高编译速度
$ sudo make install   # 安装，该命令将pcl库的头文件、动态链接库文件、静态链接库文件和其他文件拷贝到/usr 的各个子目录下 

2 opencv 编译

参考如下链接。

https://www.cnblogs.com/darkknightzh/p/5638117.html

3 VSCode下pcl配置文件编写

直接把自己的配置文件贴出来给大家看好了。

 lauch.json

{
    // 使用 IntelliSense 了解相关属性。
    // 悬停以查看现有属性的描述。
    // 欲了解更多信息，请访问: https://go.microsoft.com/fwlink/?linkid=830387
    "version": "0.2.0",
    "configurations": [
        {
            "name": "(gdb) Launch",
            "type": "cppdbg",
            "request": "launch",
            "program": "${workspaceFolder}/${fileBasenameNoExtension}.out", 　　　　　　
            "miDebuggerPath": "/usr/bin/gdb",
            "preLaunchTask":"build",
            "args": [],
            "stopAtEntry": false,
            "cwd": "${workspaceFolder}",
            "environment": [],
            "externalConsole": true,
            "MIMode": "gdb",
            "setupCommands": [
                {
                    "description": "Enable pretty-printing for gdb",
                    "text": "-enable-pretty-printing",
                    "ignoreFailures": true
                }
            ]
        }
    ]
}

tasks.json

{
    // See https://go.microsoft.com/fwlink/?LinkId=733558
    // for the documentation about the tasks.json format
    "version": "2.0.0",
    "tasks":[  // 可以有多个参数
        {
            "label": "build",       // 编译任务名
            "type": "shell",        // 编译任务的类型，通常为shell/process类型
            "command": "g++",       // 编译命令
            "args":[
                "-g",
                "${workspaceFolder}/${fileBasename}",   // include path指令
                "-I", "/usr/local/include/pcl-1.8",
                "-I", "/usr/include/eigen3",
                "-I", "/usr/include/vtk-5.10",
                "-I", "/usr/include/qhull",
                "-I", "/usr/include/flann",
                "-I", "/usr/include/boost",
                // lib 库文件地址
                "-L", "/usr/local/lib",
                "-l", "pcl_io",
                "-l", "pcl_visualization",
                "-l", "pcl_common",
                "-l", "vtkFiltering",
                "-l", "vtkCommon",
                "-l", "vtkRendering",
                "-l", "vtkGraphics",
                "-L", "/usr/include/x86_64-linux-gnu",
                "-l", "boost_system",
                "-o",                                    // 生成指定名称的可执行文件
                "${workspaceFolder}/${fileBasenameNoExtension}.out"
            ],
            "group": {
                "kind": "build",
                "isDefault": true
            }
        },
        {
            "label": "cmakebuild",
            "type": "shell",
            "command": "cd build && cmake ../ && make",
            "args": []
        }
    ]
}   

其中，采用cmake方式进行编译时的CMakeLists.txt文件是这样写的。

cmake_minimum_required(VERSION 2.8 FATAL_ERROR)

project(myPCLProject)

find_package(PCL 1.2 REQUIRED)

include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
add_definitions(${PCL_DEFINITIONS})

add_executable (cloud_viewer cloud_viewer.cpp)
target_link_libraries (cloud_viewer ${PCL_LIBRARIES})

c_cpp_properties.json，主要是给intelliSense看的，避免写代码时，intelliSense瞎比划红线报错。

{
    "configurations": [
        {
            "name": "Linux",
            "includePath": [
                "${workspaceFolder}/**",
                "${workspaceFolder}",
                "/usr/local/include/pcl-1.8",
                "/usr/include",
                "/usr/include/vtk-5.10",
                "/usr/include/qhull",
                "/usr/include/flann",
                "/usr/include/boost",
                "/usr/include/eigen3",
                "/usr/include/eigen3/Eigen/",
                "/usr/include/x86_64-linux-gnu/sys"
            ],
            "defines": [],
            "browse":{
                "path":[
                    "/usr/include",
                    "/usr/local/include/pcl-1.8"
                ]
            },
            "compilerPath": "/usr/bin/gcc",
            "cStandard": "c11",
            "cppStandard": "c++17",
            "intelliSenseMode": "gcc-x64"
        }
    ],
    "version":
}

3 测试代码

是官网的一段可视化代码，展示如下。

#include <iostream>
#include <pcl/io/io.h>
#include <pcl/io/pcd_io.h>
#include <pcl/visualization/cloud_viewer.h>

int user_data;
void
viewerOneOff (pcl::visualization::PCLVisualizer& viewer)
{
    viewer.setBackgroundColor (0.0, 0.0, 0.0);
    pcl::PointXYZ o;
    o.x = 1.0;
    o.y = ;
    o.z = ;
    viewer.addSphere (o, 0.25, "sphere", );
    std::cout << "i only run once" << std::endl;
}

void
viewerPsycho (pcl::visualization::PCLVisualizer& viewer)
{
    static unsigned count = ;
    std::stringstream ss;
    ss << "Once per viewer loop: " << count++;
    viewer.removeShape ("text", );
    viewer.addText (ss.str(), , , "text", );

    //FIXME: possible race condition here:
    user_data++;
}

int
main ()
{
    //pcl::PointCloud<pcl::PointXYZRGBA>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZRGBA>);
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
    pcl::io::loadPCDFile ("bun4.pcd", *cloud);

    pcl::visualization::CloudViewer viewer("Cloud Viewer");

    //blocks until the cloud is actually rendered
    viewer.showCloud(cloud);

    //use the following functions to get access to the underlying more advanced/powerful
    //PCLVisualizer

    //This will only get called once
    viewer.runOnVisualizationThreadOnce (viewerOneOff);

    //This will get called once per visualization iteration
    viewer.runOnVisualizationThread (viewerPsycho);
    while (!viewer.wasStopped ())
    {
    //you can also do cool processing here
    //FIXME: Note that this is running in a separate thread from viewerPsycho
    //and you should guard against race conditions yourself...
    user_data++;
    }
    return ;
}

4 效果图