PCL 1.60 +windows+vs2010 安裝與配置

時間 2019-11-08

標籤 pcl 1.60 windows+vs2010 windows 安裝配置欄目 Windows 简体版

原文原文鏈接

PCL簡介html

　　PCL（Point Cloud Library）是在吸取了前人點雲相關研究基礎上創建起來的大型跨平臺開源C++編程庫，它實現了大量點雲相關的通用算法和高效數據結構，涉及到點雲獲取、濾波、分割、配準、檢索、特徵提取、識別、追蹤、曲面重建、可視化等。支持多種操做系統平臺，可在Windows、Linux、Android、Mac OS X、部分嵌入式實時系統上運行。若是說OpenCV是2D信息獲取與處理的結晶，那麼PCL就在3D信息獲取與處理上具備同等地位，PCL是BSD受權方式，能夠免費進行商業和學術應用。ios

最近剛接觸PCL，發現用到PCL的人仍是比較少，可供學習的資料也很少，因此，我想從頭開始學習，並記錄下學習的過程。若是有興趣一塊兒學習的同窗能夠加我微信號zcs9602，咱們一塊兒交流學習。git

學習資源：github

PCL 1.8.0 比較全的安裝包及安裝步驟：http://unanancyowen.com/en/pcl18/算法

PCL 相關資料彙總：https://github.com/neilgu00365/Survey-for-SfMMissionsql

PCL 中國點雲庫：http://www.pclcn.org/編程

環境：windows+vs2010windows

若是你沒有vs2010我給你分享一個安裝包連接：http://pan.baidu.com/s/1pL3I0dH 密碼：a53o微信

1、下載數據結構

我用的是PCL 1.6.0 All-In-One Installer，Windows MSVC 2010 (32bit)，因此，下面是以這個版本爲主。其實，只要下載PCL-1.6.0-AllInOne-msvc2010-win32.exe、OpenNI 1.5.4 (patched)和Sensor 5.1.0 (patched)三個文件就能夠了，PCL-1.6.0-AllInOne-msvc2010-win32.exe內部已經包含了所有的依賴庫，安裝的過程當中，OpenNI會安裝不上，因此要單獨下載，其它的依賴庫均可以不用下載。

官方下載地址：http://pointclouds.org/downloads/windows.html

2、安裝

分別安裝

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

二、OpenNI-Win32-1.5.4-Dev.msi

三、Sensor-Win-OpenSource32-5.1.0.msi

注意：你要編譯的是Win32和Win64的版本要區別開，PCL和依賴庫都統一用同一個版本的，不然運行的時候會報錯。

3、配置

一、配置包含路徑

將PCL安裝路徑下的3rdParty目錄下的include添加進去，另外OpenNI單獨安裝的路徑也添加進去，還有PCL安裝路徑下的Include\pcl-1.6也添加進去。

二、配置庫路徑

將PCL安裝路徑下的3rdParty目錄下的lib添加進去，另外OpenNI單獨安裝的路徑也添加進去，還有PCL安裝路徑下的lib也添加進去。

三、配置輸入庫文件

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

文件有點多，這裏能夠有個比較快的方法：這裏以vtk爲例，

打開CMD->進入PCL的安裝目錄->進入3rdParty\VTK\lib\vtk-5.8目錄->輸入命令：dir /b *gd.lib -> list.txt

命令的意思是找出gd.lib結尾的文件並保存到list.txt文檔裏面。而後當前目錄就會生成list.txt

4、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 (0, 0, 0);
    pcl::PointXYZ o;
    o.x = 1.0;
    o.y = 0;
    o.z = 0;
    viewer.addSphere (o, 0.25, "sphere", 0);
    std::cout << "i only run once" << std::endl;

}

void viewerPsycho (pcl::visualization::PCLVisualizer& viewer)
{
    static unsigned count = 0;
    std::stringstream ss;
    ss << "Once per viewer loop: " << count++;
    viewer.removeShape ("text", 0);
    viewer.addText (ss.str(), 200, 300, "text", 0);

    //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 0;
}