View source for PCL 2016

== Introduction ==
The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. PCL is released under the terms of the BSD license, and thus free for commercial and research use. [https://pointclouds.org/ <sup>1</sup>]
== Installed version(s) ==
The following versions are installed and currently available... <br/>

... on environment ''hpc-env/8.3'':

*'''PCL/1.12.0'''-fosscuda-2019b-Python-3.7.4 

== Loading / Using PCL==
To load the desired version of the module, use the ''module load'' command, e.g.

 module load hpc-env/8.3
 module load PCL

Always remember: this command is case sensitive!

PCL comes with a lot of executables which you can look up after loading PCL as shown above with tht command <tt>ls -l $EBROOTPCL/bin</tt> <br>
As of version 1.12.0, the following executables are available:

<pre>
pcl_add_gaussian_noise
pcl_linemod_detection
pcl_openni2_viewer
pcl_progressive_morphological_filter
pcl_boundary_estimation
pcl_local_max
pcl_outlier_removal
pcl_radius_filter
pcl_cluster_extraction
pcl_lum
pcl_outofcore_print
pcl_registration_visualizer
pcl_compute_cloud_error
pcl_marching_cubes_reconstruction
pcl_outofcore_process
pcl_sac_segmentation_plane
pcl_compute_hausdorff
pcl_match_linemod_template
pcl_outofcore_viewer
pcl_spin_estimation
pcl_compute_hull
pcl_mesh2pcd
pcl_passthrough_filter
pcl_tiff2pcd
pcl_concatenate_points_pcd
pcl_mesh_sampling
pcl_pcd2ply
pcl_timed_trigger_test
pcl_converter
pcl_mls_smoothing
pcl_pcd2png
pcl_train_linemod_template
pcl_convert_pcd_ascii_binary
pcl_morph
pcl_pcd2vtk
pcl_train_unary_classifier
pcl_crf_segmentation
pcl_ndt2d
pcl_pcd_change_viewpoint
pcl_transform_from_viewpoint
pcl_crop_to_hull
pcl_ndt3d
pcl_pcd_convert_NaN_nan
pcl_transform_point_cloud
pcl_demean_cloud
pcl_normal_estimation
pcl_pcd_image_viewer
pcl_unary_classifier_segment
pcl_elch
pcl_obj2pcd
pcl_pcd_introduce_nan
pcl_uniform_sampling
pcl_extract_feature
pcl_obj2ply
pcl_pclzf2pcd
pcl_vfh_estimation
pcl_fast_bilateral_filter
pcl_obj2vtk
pcl_plane_projection
pcl_viewer
pcl_fpfh_estimation
pcl_obj_rec_ransac_accepted_hypotheses
pcl_ply2obj
pcl_virtual_scanner
pcl_generate
pcl_obj_rec_ransac_hash_table
pcl_ply2pcd
pcl_vlp_viewer
pcl_gp3_surface
pcl_obj_rec_ransac_model_opps
pcl_ply2ply
pcl_voxel_grid
pcl_grid_min
pcl_obj_rec_ransac_orr_octree
pcl_ply2raw
pcl_voxel_grid_occlusion_estimation
pcl_hdl_grabber
pcl_obj_rec_ransac_orr_octree_zprojection
pcl_ply2vtk
pcl_vtk2obj
pcl_hdl_viewer_simple
pcl_obj_rec_ransac_result
pcl_plyheader
pcl_vtk2pcd
pcl_icp
pcl_obj_rec_ransac_scene_opps
pcl_png2pcd
pcl_vtk2ply
pcl_icp2d
pcl_octree_viewer
pcl_poisson_reconstruction
pcl_xyz2pcd
</pre>

Since we built PCL with CUDA GPU support, some of the executables need to be executed on a GPU node. Should you encounter the following error message after trying to use one of the executables, you will have to allocate a GPU:
 pcl_octree_viewer: error while loading shared libraries: libOpenGL.so.0: cannot open shared object file: No such file or directory
To learn more on how to allocate GPU nodes, you can read the articles about the [[SLURM_Job_Management (Queueing) System | SLURM job management]] and [[Partitions]]


== Documentation ==
The full documentation can be found at the [https://github.com/PointCloudLibrary/pcl/wiki github wiki].