PCL 1.60 +windows+vs2010 安装与配置

时间:2022-11-26 21:14:52

PCL简介

  PCL(Point Cloud Library)是在吸收了前人点云相关研究基础上建立起来的大型跨平台开源C++编程库,它实现了大量点云相关的通用算法和高效数据结构,涉及到点云获取、滤波、分割、配准、检索、特征提取、识别、追踪、曲面重建、可视化等。支持多种操作系统平台,可在Windows、Linux、Android、Mac OS X、部分嵌入式实时系统上运行。如果说OpenCV是2D信息获取与处理的结晶,那么PCL就在3D信息获取与处理上具有同等地位,PCL是BSD授权方式,可以免费进行商业和学术应用。

最近刚接触PCL,发现用到PCL的人还是比较少,可供学习的资料也不多,所以,我想从头开始学习,并记录下学习的过程。如果有兴趣一起学习的同学可以加我微信号zcs9602,我们一起交流学习。

学习资源:

PCL 1.8.0 比较全的安装包及安装步骤:http://unanancyowen.com/en/pcl18/

PCL 相关资料汇总:https://github.com/neilgu00365/Survey-for-SfMMission

PCL 中国点云库:http://www.pclcn.org/

 

环境:windows+vs2010

如果你没有vs2010我给你分享一个安装包链接:http://pan.baidu.com/s/1pL3I0dH 密码:a53o

一、下载

我用的是PCL 1.6.0 All-In-One Installer,Windows MSVC 2010 (32bit),所以,下面是以这个版本为主。其实,只要下载PCL-1.6.0-AllInOne-msvc2010-win32.exe、OpenNI 1.5.4 (patched)Sensor 5.1.0 (patched)三个文件就可以了,PCL-1.6.0-AllInOne-msvc2010-win32.exe内部已经包含了全部的依赖库,安装的过程中,OpenNI会安装不上,所以要单独下载,其它的依赖库都可以不用下载。

二、安装

分别安装

1、PCL-1.6.0-AllInOne-msvc2010-win32.exe

2、OpenNI-Win32-1.5.4-Dev.msi

3、Sensor-Win-OpenSource32-5.1.0.msi

注意:你要编译的是Win32和Win64的版本要区别开,PCL和依赖库都统一用同一个版本的,否则运行的时候会报错。

三、配置

PCL 1.60 +windows+vs2010 安装与配置

1、配置包含路径

将PCL安装路径下的3rdParty目录下的include添加进去,另外OpenNI单独安装的路径也添加进去,还有PCL安装路径下的Include\pcl-1.6也添加进去。

PCL 1.60 +windows+vs2010 安装与配置

2、配置库路径

将PCL安装路径下的3rdParty目录下的lib添加进去,另外OpenNI单独安装的路径也添加进去,还有PCL安装路径下的lib也添加进去。

PCL 1.60 +windows+vs2010 安装与配置

3、配置输入库文件

添加下列文件名

opengl32.lib

pcl_apps_debug.lib

pcl_common_debug.lib

pcl_features_debug.lib

pcl_filters_debug.lib

pcl_io_debug.lib

pcl_io_ply_debug.lib

pcl_kdtree_debug.lib

pcl_keypoints_debug.lib

pcl_octree_debug.lib

pcl_registration_debug.lib

pcl_sample_consensus_debug.lib

pcl_search_debug.lib

pcl_segmentation_debug.lib

pcl_surface_debug.lib

pcl_tracking_debug.lib

pcl_visualization_debug.lib

flann_cpp_s-gd.lib

boost_chrono-vc100-mt-gd-1_49.lib

boost_date_time-vc100-mt-gd-1_47.lib

boost_date_time-vc100-mt-gd-1_49.lib

boost_filesystem-vc100-mt-gd-1_47.lib

boost_filesystem-vc100-mt-gd-1_49.lib

boost_graph-vc100-mt-gd-1_49.lib

boost_graph_parallel-vc100-mt-gd-1_49.lib

boost_iostreams-vc100-mt-gd-1_47.lib

boost_iostreams-vc100-mt-gd-1_49.lib

boost_locale-vc100-mt-gd-1_49.lib

boost_math_c99-vc100-mt-gd-1_49.lib

boost_math_c99f-vc100-mt-gd-1_49.lib

boost_math_tr1-vc100-mt-gd-1_49.lib

boost_math_tr1f-vc100-mt-gd-1_49.lib

boost_mpi-vc100-mt-gd-1_49.lib

boost_prg_exec_monitor-vc100-mt-gd-1_49.lib

boost_program_options-vc100-mt-gd-1_49.lib

boost_random-vc100-mt-gd-1_49.lib

boost_regex-vc100-mt-gd-1_49.lib

boost_serialization-vc100-mt-gd-1_49.lib

boost_signals-vc100-mt-gd-1_49.lib

boost_system-vc100-mt-gd-1_47.lib

boost_system-vc100-mt-gd-1_49.lib

boost_thread-vc100-mt-gd-1_47.lib

boost_thread-vc100-mt-gd-1_49.lib

boost_timer-vc100-mt-gd-1_49.lib

boost_unit_test_framework-vc100-mt-gd-1_49.lib

boost_wave-vc100-mt-gd-1_49.lib

boost_wserialization-vc100-mt-gd-1_49.lib

libboost_chrono-vc100-mt-gd-1_49.lib

libboost_date_time-vc100-mt-gd-1_47.lib

libboost_date_time-vc100-mt-gd-1_49.lib

libboost_filesystem-vc100-mt-gd-1_47.lib

libboost_filesystem-vc100-mt-gd-1_49.lib

libboost_graph_parallel-vc100-mt-gd-1_49.lib

libboost_iostreams-vc100-mt-gd-1_47.lib

libboost_iostreams-vc100-mt-gd-1_49.lib

libboost_locale-vc100-mt-gd-1_49.lib

libboost_math_c99-vc100-mt-gd-1_49.lib

libboost_math_c99f-vc100-mt-gd-1_49.lib

libboost_math_tr1-vc100-mt-gd-1_49.lib

libboost_math_tr1f-vc100-mt-gd-1_49.lib

libboost_mpi-vc100-mt-gd-1_49.lib

libboost_prg_exec_monitor-vc100-mt-gd-1_49.lib

libboost_program_options-vc100-mt-gd-1_49.lib

libboost_random-vc100-mt-gd-1_49.lib

libboost_regex-vc100-mt-gd-1_49.lib

libboost_serialization-vc100-mt-gd-1_49.lib

libboost_signals-vc100-mt-gd-1_49.lib

libboost_system-vc100-mt-gd-1_47.lib

libboost_system-vc100-mt-gd-1_49.lib

libboost_test_exec_monitor-vc100-mt-gd-1_49.lib

libboost_thread-vc100-mt-gd-1_47.lib

libboost_thread-vc100-mt-gd-1_49.lib

libboost_timer-vc100-mt-gd-1_49.lib

libboost_unit_test_framework-vc100-mt-gd-1_49.lib

libboost_wave-vc100-mt-gd-1_49.lib

libboost_wserialization-vc100-mt-gd-1_49.lib

vtkalglib-gd.lib

vtkCharts-gd.lib

vtkCommon-gd.lib

vtkDICOMParser-gd.lib

vtkexoIIc-gd.lib

vtkexpat-gd.lib

vtkFiltering-gd.lib

vtkfreetype-gd.lib

vtkftgl-gd.lib

vtkGenericFiltering-gd.lib

vtkGeovis-gd.lib

vtkGraphics-gd.lib

vtkhdf5-gd.lib

vtkHybrid-gd.lib

vtkImaging-gd.lib

vtkInfovis-gd.lib

vtkIO-gd.lib

vtkjpeg-gd.lib

vtklibxml2-gd.lib

vtkmetaio-gd.lib

vtkNetCDF-gd.lib

vtkNetCDF_cxx-gd.lib

vtkpng-gd.lib

vtkproj4-gd.lib

vtkRendering-gd.lib

vtksqlite-gd.lib

vtksys-gd.lib

vtktiff-gd.lib

vtkverdict-gd.lib

vtkViews-gd.lib

vtkVolumeRendering-gd.lib

vtkWidgets-gd.lib

vtkzlib-gd.lib

PCL 1.60 +windows+vs2010 安装与配置

文件有点多,这里可以有个比较快的方法:这里以vtk为例,

打开CMD->进入PCL的安装目录->进入3rdParty\VTK\lib\vtk-5.8目录->输入命令:dir /b *gd.lib -> list.txt

命令的意思是找出gd.lib结尾的文件并保存到list.txt文档里面。然后当前目录就会生成list.txt

PCL 1.60 +windows+vs2010 安装与配置

四、Demo

例程:

#include <pcl/visualization/cloud_viewer.h>
#include <iostream>
#include <pcl/io/io.h>
#include <pcl/io/pcd_io.h> int user_data; void viewerOneOff (pcl::visualization::PCLVisualizer& viewer)
{
viewer.setBackgroundColor (, , );
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::io::loadPCDFile ("my_point_cloud.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 ;
}

PCL 1.60 +windows+vs2010 安装与配置

以上效果图是用realsense的SR300获取到我桌面的点云。

my_point_cloud.pcd 文件 链接:http://pan.baidu.com/s/1gfD2lF1 密码:cexi

五、总结分享

1、pcd读取有点慢,据说pcd数据以有序点云的方式保存会好一点,但是没我试了没看出来能快多少,这个有待研究。

2、SR300直接获取的深度图像和RGB图像坐标上有偏差,这个考虑下怎么做对齐。

3、如果工程配置上SR300的SDK和opencv,我们就不需要在另一个工程先保存pcd文件再读取,中间就可以省了很多步骤。

4、PCL的学习资料还是很少,目前听说比较好也就只有《点云库PCL学习教程》,我也买了一本,慢慢学吧。

公众号奉上~欢迎来搞!

PCL 1.60 +windows+vs2010 安装与配置