作者經(jīng)歷了從PCL1.7-PCL1.9,VS2013-VS2017的反復(fù)配置，其過程是坎坷與辛酸，踩過各種坑，現(xiàn)在配置起來真的是爐火純青了?，F(xiàn)在又來臺新電腦了，沒錯，再來配置一次吧。此次配置VS2017+PCL1.9.1

準(zhǔn)備工作

• VS2017 自行下載
• PCL1.9.1
  點(diǎn)擊鏈接跳轉(zhuǎn)Github下載，根據(jù)自己的環(huán)境選擇 win64或win32,作者下載的是：PCL-1.9.1-AllInOne-msvc2017-win64.exe
pcl-1.9.1-pdb-msvc2017-win64.zip

安裝PCL

雙擊點(diǎn)開PCL-1.9.1-AllInOne-msvc2017-win64.exe，選擇Add PCL to the system PATH for all users,

安裝完畢。

解壓pcl-1.9.1-pdb-msvc2017-win64.zip，將PDB文件拷貝到PCL安裝路徑下的bin文件夾中。

環(huán)境配置

• 系統(tǒng)環(huán)境配置
  計(jì)算機(jī)->屬性->高級系統(tǒng)變量->環(huán)境變量，雙擊Path，
  

添加如下路徑(路徑根據(jù)自己的安裝目錄添加)

添加完畢后，電腦注銷后生效。

• VS開發(fā)環(huán)境配置

1. 打開VS2017，新建空項(xiàng)目

2.菜單欄點(diǎn)擊視圖->其他窗口->屬性管理器，選擇releaseordebug,win32orx64，這里以release|x64為例，右鍵新建添加新項(xiàng)目屬性表，取名config,添加，

E:\Program Files\PCL 1.9.1\include\pcl-1.9
E:\Program Files\PCL 1.9.1\3rdParty\Boost\include\boost-1_68
E:\Program Files\PCL 1.9.1\3rdParty\Eigen\eigen3
E:\Program Files\PCL 1.9.1\3rdParty\FLANN\include
E:\Program Files\PCL 1.9.1\3rdParty\OpenNI2\Include
E:\Program Files\PCL 1.9.1\3rdParty\Qhull\include
E:\Program Files\PCL 1.9.1\3rdParty\VTK\include\vtk-8.1

VC++ 目錄->庫目錄->添加庫文件：(根據(jù)自己pcl的路徑添加)

E:\Program Files\PCL 1.9.1\lib
E:\Program Files\PCL 1.9.1\3rdParty\Boost\lib
E:\Program Files\PCL 1.9.1\3rdParty\FLANN\lib
E:\Program Files\PCL 1.9.1\3rdParty\OpenNI2\Lib
E:\Program Files\PCL 1.9.1\3rdParty\Qhull\lib
E:\Program Files\PCL 1.9.1\3rdParty\VTK\lib

鏈接器->輸入->附加依賴項(xiàng)添加lib文件：(這里是release版本),如果你上面選擇的是debug win32 or debug x64,則添加debug版本的lib文件，請看下面的Tips,教你如何獲取lib目錄。

pcl_common_release.lib
pcl_features_release.lib
pcl_filters_release.lib
pcl_io_ply_release.lib
pcl_io_release.lib
pcl_kdtree_release.lib
pcl_keypoints_release.lib
pcl_ml_release.lib
pcl_octree_release.lib
pcl_outofcore_release.lib
pcl_people_release.lib
pcl_recognition_release.lib
pcl_registration_release.lib
pcl_sample_consensus_release.lib
pcl_search_release.lib
pcl_segmentation_release.lib
pcl_stereo_release.lib
pcl_surface_release.lib
pcl_tracking_release.lib
pcl_visualization_release.lib
libboost_atomic-vc141-mt-x64-1_68.lib
libboost_bzip2-vc141-mt-x64-1_68.lib
libboost_chrono-vc141-mt-x64-1_68.lib
libboost_container-vc141-mt-x64-1_68.lib
libboost_context-vc141-mt-x64-1_68.lib
libboost_contract-vc141-mt-x64-1_68.lib
libboost_coroutine-vc141-mt-x64-1_68.lib
libboost_date_time-vc141-mt-x64-1_68.lib
libboost_exception-vc141-mt-x64-1_68.lib
libboost_fiber-vc141-mt-x64-1_68.lib
libboost_filesystem-vc141-mt-x64-1_68.lib
libboost_graph-vc141-mt-x64-1_68.lib
libboost_graph_parallel-vc141-mt-x64-1_68.lib
libboost_iostreams-vc141-mt-x64-1_68.lib
libboost_locale-vc141-mt-x64-1_68.lib
libboost_log-vc141-mt-x64-1_68.lib
libboost_log_setup-vc141-mt-x64-1_68.lib
libboost_math_c99-vc141-mt-x64-1_68.lib
libboost_math_c99f-vc141-mt-x64-1_68.lib
libboost_math_c99l-vc141-mt-x64-1_68.lib
libboost_math_tr1-vc141-mt-x64-1_68.lib
libboost_math_tr1f-vc141-mt-x64-1_68.lib
libboost_math_tr1l-vc141-mt-x64-1_68.lib
libboost_mpi-vc141-mt-x64-1_68.lib
libboost_numpy27-vc141-mt-x64-1_68.lib
libboost_numpy37-vc141-mt-x64-1_68.lib
libboost_prg_exec_monitor-vc141-mt-x64-1_68.lib
libboost_program_options-vc141-mt-x64-1_68.lib
libboost_python27-vc141-mt-x64-1_68.lib
libboost_python37-vc141-mt-x64-1_68.lib
libboost_random-vc141-mt-x64-1_68.lib
libboost_regex-vc141-mt-x64-1_68.lib
libboost_serialization-vc141-mt-x64-1_68.lib
libboost_signals-vc141-mt-x64-1_68.lib
libboost_stacktrace_noop-vc141-mt-x64-1_68.lib
libboost_stacktrace_windbg-vc141-mt-x64-1_68.lib
libboost_stacktrace_windbg_cached-vc141-mt-x64-1_68.lib
libboost_system-vc141-mt-x64-1_68.lib
libboost_test_exec_monitor-vc141-mt-x64-1_68.lib
libboost_thread-vc141-mt-x64-1_68.lib
libboost_timer-vc141-mt-x64-1_68.lib
libboost_type_erasure-vc141-mt-x64-1_68.lib
libboost_unit_test_framework-vc141-mt-x64-1_68.lib
libboost_wave-vc141-mt-x64-1_68.lib
libboost_wserialization-vc141-mt-x64-1_68.lib
libboost_zlib-vc141-mt-x64-1_68.lib
OpenNI2.lib
flann.lib
flann_cpp.lib
flann_cpp_s.lib
flann_s.lib
qhull.lib
qhullcpp.lib
qhullstatic.lib
qhullstatic_r.lib
qhull_p.lib
qhull_r.lib
vtkalglib-8.1.lib
vtkChartsCore-8.1.lib
vtkCommonColor-8.1.lib
vtkCommonComputationalGeometry-8.1.lib
vtkCommonCore-8.1.lib
vtkCommonDataModel-8.1.lib
vtkCommonExecutionModel-8.1.lib
vtkCommonMath-8.1.lib
vtkCommonMisc-8.1.lib
vtkCommonSystem-8.1.lib
vtkCommonTransforms-8.1.lib
vtkDICOMParser-8.1.lib
vtkDomainsChemistry-8.1.lib
vtkexoIIc-8.1.lib
vtkexpat-8.1.lib
vtkFiltersAMR-8.1.lib
vtkFiltersCore-8.1.lib
vtkFiltersExtraction-8.1.lib
vtkFiltersFlowPaths-8.1.lib
vtkFiltersGeneral-8.1.lib
vtkFiltersGeneric-8.1.lib
vtkFiltersGeometry-8.1.lib
vtkFiltersHybrid-8.1.lib
vtkFiltersHyperTree-8.1.lib
vtkFiltersImaging-8.1.lib
vtkFiltersModeling-8.1.lib
vtkFiltersParallel-8.1.lib
vtkFiltersParallelImaging-8.1.lib
vtkFiltersPoints-8.1.lib
vtkFiltersProgrammable-8.1.lib
vtkFiltersSelection-8.1.lib
vtkFiltersSMP-8.1.lib
vtkFiltersSources-8.1.lib
vtkFiltersStatistics-8.1.lib
vtkFiltersTexture-8.1.lib
vtkFiltersTopology-8.1.lib
vtkFiltersVerdict-8.1.lib
vtkfreetype-8.1.lib
vtkGeovisCore-8.1.lib
vtkgl2ps-8.1.lib
vtkhdf5-8.1.lib
vtkhdf5_hl-8.1.lib
vtkImagingColor-8.1.lib
vtkImagingCore-8.1.lib
vtkImagingFourier-8.1.lib
vtkImagingGeneral-8.1.lib
vtkImagingHybrid-8.1.lib
vtkImagingMath-8.1.lib
vtkImagingMorphological-8.1.lib
vtkImagingSources-8.1.lib
vtkImagingStatistics-8.1.lib
vtkImagingStencil-8.1.lib
vtkInfovisCore-8.1.lib
vtkInfovisLayout-8.1.lib
vtkInteractionImage-8.1.lib
vtkInteractionStyle-8.1.lib
vtkInteractionWidgets-8.1.lib
vtkIOAMR-8.1.lib
vtkIOCore-8.1.lib
vtkIOEnSight-8.1.lib
vtkIOExodus-8.1.lib
vtkIOExport-8.1.lib
vtkIOExportOpenGL-8.1.lib
vtkIOGeometry-8.1.lib
vtkIOImage-8.1.lib
vtkIOImport-8.1.lib
vtkIOInfovis-8.1.lib
vtkIOLegacy-8.1.lib
vtkIOLSDyna-8.1.lib
vtkIOMINC-8.1.lib
vtkIOMovie-8.1.lib
vtkIONetCDF-8.1.lib
vtkIOParallel-8.1.lib
vtkIOParallelXML-8.1.lib
vtkIOPLY-8.1.lib
vtkIOSQL-8.1.lib
vtkIOTecplotTable-8.1.lib
vtkIOVideo-8.1.lib
vtkIOXML-8.1.lib
vtkIOXMLParser-8.1.lib
vtkjpeg-8.1.lib
vtkjsoncpp-8.1.lib
vtklibharu-8.1.lib
vtklibxml2-8.1.lib
vtklz4-8.1.lib
vtkmetaio-8.1.lib
vtkNetCDF-8.1.lib
vtknetcdfcpp-8.1.lib
vtkoggtheora-8.1.lib
vtkParallelCore-8.1.lib
vtkpng-8.1.lib
vtkproj4-8.1.lib
vtkRenderingAnnotation-8.1.lib
vtkRenderingContext2D-8.1.lib
vtkRenderingContextOpenGL-8.1.lib
vtkRenderingCore-8.1.lib
vtkRenderingFreeType-8.1.lib
vtkRenderingGL2PS-8.1.lib
vtkRenderingImage-8.1.lib
vtkRenderingLabel-8.1.lib
vtkRenderingLIC-8.1.lib
vtkRenderingLOD-8.1.lib
vtkRenderingOpenGL-8.1.lib
vtkRenderingVolume-8.1.lib
vtkRenderingVolumeOpenGL-8.1.lib
vtksqlite-8.1.lib
vtksys-8.1.lib
vtktiff-8.1.lib
vtkverdict-8.1.lib
vtkViewsContext2D-8.1.lib
vtkViewsCore-8.1.lib
vtkViewsInfovis-8.1.lib
vtkzlib-8.1.lib

Tips：如何獲得lib目錄？
舉個例子：我們要獲得.\PCL 1.9.1\lib目錄下的lib目錄，在此文件夾下新建一個.txt文本，在文本中寫入下列代碼，保存。

dir /b *debug.lib>1.txt 

將文本后綴名.txt改為.bat，運(yùn)行腳本，

至此，配置完成！

程序測試

#include <iostream>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
#include <pcl/ModelCoefficients.h>
#include <pcl/filters/project_inliers.h>
 
int main(int argc, char** argv)
{
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_projected(new pcl::PointCloud<pcl::PointXYZ>);
 
    // Fill in the cloud data
    cloud->width = 5;
    cloud->height = 1;
    cloud->points.resize(cloud->width * cloud->height);
 
    for (size_t i = 0; i < cloud->points.size(); ++i)
    {
        cloud->points[i].x = 1024 * rand() / (RAND_MAX + 1.0f);
        cloud->points[i].y = 1024 * rand() / (RAND_MAX + 1.0f);
        cloud->points[i].z = 1024 * rand() / (RAND_MAX + 1.0f);
    }
 
    std::cerr << "Cloud before projection: " << std::endl;
    for (size_t i = 0; i < cloud->points.size(); ++i)
        std::cerr << "    " << cloud->points[i].x << " "
        << cloud->points[i].y << " "
        << cloud->points[i].z << std::endl;
 
    // Create a set of planar coefficients with X=Y=0,Z=1
    pcl::ModelCoefficients::Ptr coefficients(new pcl::ModelCoefficients());
    coefficients->values.resize(4);
    coefficients->values[0] = coefficients->values[1] = 0;
    coefficients->values[2] = 1.0;
    coefficients->values[3] = 0;
 
    // Create the filtering object
    pcl::ProjectInliers<pcl::PointXYZ> proj;
    proj.setModelType(pcl::SACMODEL_PLANE);
    proj.setInputCloud(cloud);
    proj.setModelCoefficients(coefficients);
    proj.filter(*cloud_projected);
 
    std::cerr << "Cloud after projection: " << std::endl;
    for (size_t i = 0; i < cloud_projected->points.size(); ++i)
        std::cerr << "    " << cloud_projected->points[i].x << " "
        << cloud_projected->points[i].y << " "
        << cloud_projected->points[i].z << std::endl;
 
    system("pause");
    return (0);
}

如果生成成功，并能運(yùn)行得到結(jié)果，表明配置成功！

相關(guān)問題

如果出現(xiàn)如下報錯，

_CRT_SECURE_NO_WARNINGS
_SCL_SECURE_NO_WARNINGS
_SILENCE_FPOS_SEEKPOS_DEPRECATION_WARNING

結(jié)語

至此，相信你也和我一樣，已經(jīng)配置成功了。
如有任何問題或是書寫紕漏，請給我留言，我會幫你們耐心解決。
感謝觀看，希望對你們有所幫助！