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