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Tutorial
  • INTRO
  • Part 0 (개요)
    • README
    • 3D 영상처리
    • [별첨] PCL & PCD란 (100%)
    • chapter02 : PCL 설치 (100%)
    • chapter03 : ROS 실습 준비(100%)
  • Part 1 (초급)
    • README
    • PCL 기반 로봇 비젼
    • [별첨] 파일 생성 및 입출력 (70%)
      • PCL-Cpp (70%)
      • PCL-Python (70%)
      • Open3D-Python (70%)
      • ROS 실습 (90%)
    • Filter
    • [별첨] 샘플링 (70%)
      • 다운샘플링-PCL-Cpp (70%)
      • 다운샘플링-PCL-Python (50%)
      • 업샘플링-PCL-Cpp (70%)
      • ROS 실습 (90%)
    • [별첨] 관심 영역 설정 (70%)
      • PCL-Cpp (70%)
      • PCL-Python (70%)
      • ROS 실습 (90%)
    • [별첨] 노이즈 제거 (70%)
      • PCL-Cpp (70%)
      • PCL-Python (50%)
      • ROS 실습 (90%)
  • Part 2 (중급)
    • README
    • Kd-Tree/Octree Search
    • Chapter03 : Sample Consensus
    • [별첨] 바닥제거 (RANSAC) (70%)
      • PCL-Cpp (70%)
      • PCL-Python (70%)
      • ROS 실습 (90%)
    • 군집화 (70%)
      • Euclidean-PCL-Cpp (70%)
      • Euclidean-PCL-Python (0%)
      • Conditional-Euclidean-PCL-Cpp (50%)
      • DBSCAN-PCL-Python (0%)
      • Region-Growing-PCL-Cpp (50%)
      • Region-Growing-RGB-PCL-Cpp (50%)
      • Min-Cut-PCL-Cpp (50%)
      • Model-Outlier-Removal-PCL-Cpp (50%)
      • Progressive-Morphological-Filter-PCL-Cpp (50%)
    • 포인트 탐색과 배경제거 (60%)
      • Search-Octree-PCL-Cpp (70%)
      • Search-Octree-PCL-Python (70%)
      • Search-Kdtree-PCL-Cpp (70%)
      • Search-Kdtree-PCL-Python (70%)
      • Compression-PCL-Cpp (70%)
      • DetectChanges-PCL-Cpp (50%)
      • DetectChanges-PCL-Python (50%)
    • 특징 찾기 (50%)
      • PFH-PCL-Cpp
      • FPFH-PCL-Cpp
      • Normal-PCL-Cpp (70%)
      • Normal-PCL-Python (80%)
      • Tmp
    • 분류/인식 (30%)
      • 인식-GeometricConsistencyGrouping
      • SVM-RGBD-PCL-Python (70%)
      • SVM-LIDAR-PCL-Python (0%)
      • SVM-ROS (0%)
    • 정합 (70%)
      • ICP-PCL-Cpp (70%)
      • ICP-ROS 실습 (10%)
    • 재구성 (30%)
      • Smoothig-PCL-Cpp (70%)
      • Smoothig-PCL-Python (70%)
      • Triangulation-PCL-Cpp (70%)
  • Part 3 (고급)
    • README
    • 딥러닝 기반 학습 데이터 생성 (0%)
      • PointGAN (90%)
      • AutoEncoder (0%)
    • 딥러닝 기반 샘플링 기법 (0%)
      • DenseLidarNet (50%)
      • Point Cloud Upsampling Network
      • Pseudo-LiDAR
    • 딥러닝 기반 자율주행 탐지 기술 (0%)
    • 딥러닝 기반 자율주행 분류 기술 (0%)
      • Multi3D
      • PointNet
      • VoxelNet (50%)
      • YOLO3D
      • SqueezeSeg
      • butNet
  • Snippets
    • PCL-Snippets
    • PCL-Python-Helper (10%)
    • Lidar Data Augmentation
  • Appendix
    • 시각화Code
    • 시각화툴
    • Annotation툴
    • Point Cloud Libraries (0%)
    • 데이터셋
    • Cling_PCL
    • 참고 자료
    • 작성 계획_Tips
    • 용어집
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  • 1. 설치
  • 2. 테스트
  • 2.1 print
  • 2.2 시각화
  • 3. 도움말

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  1. Appendix

Cling_PCL

Previous데이터셋Next참고 자료

Last updated 5 years ago

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1. 설치

# 사전 설치 
$ sudo apt install zeromq #ubuntu 16
$ sudo apt instal libzmq3-dev
$ wget https://gist.githubusercontent.com/katopz/8b766a5cb0ca96c816658e9407e83d00/raw/bc93fda1fe2fe5c6f45648ba131596134d92f7dc/setup-zeromq.sh

# 바이너리 다운로드 및 설치 
$ tar xvf cling_2020-03-11_ubuntu18.tar.bz2 # https://root.cern.ch/download/cling/
$ cd cling_2020-03-11_ubuntu18/share/cling/Jupyter/kernel/
$ pip3 install -e .

# 쥬피터 등록 
$ jupyter-kernelspec install --user cling-cpp17
# 필요시 PATH등록

2. 테스트

2.1 print

#pragma cling add_library_path("/usr/lib/x86_64-linux-gnu")
#pragma cling load("libboost_system.so")
#pragma cling load("libpcl_io.so")
#pragma cling add_include_path("/usr/include/pcl-1.8")
#pragma cling add_include_path("/usr/include/eigen3")
#pragma cling add_include_path("/usr/include/vtk-6.3")

#include <iostream>
#include <pcl/ModelCoefficients.h>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
#include <pcl/sample_consensus/method_types.h>
#include <pcl/sample_consensus/model_types.h>
#include <pcl/segmentation/sac_segmentation.h>
#include <pcl/filters/extract_indices.h>

pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
pcl::io::loadPCDFile<pcl::PointXYZRGB> ("tabletop_passthrough.pcd", *cloud);
std::cerr << "PointCloud before filtering: " << cloud->width * cloud->height << " data points (" << pcl::getFieldsList (*cloud) << ").";
#pragma cling add_library_path("/usr/lib/x86_64-linux-gnu")
#pragma cling load("libpcl_visualization.so") // .L /usr/local/lib/libpcl_visualization.so

// Include dirs
#pragma cling add_include_path("/usr/include/pcl-1.8") // .I /usr/local/include/pcl-1.8
#pragma cling add_include_path("/usr/include/eigen3") // .I /usr/local/include/eigen3
#pragma cling add_include_path("/usr/include/vtk-6.3") // .I /usr/include/vtk-6.2

#include <pcl/visualization/pcl_visualizer.h>
auto viewer = pcl::visualization::PCLVisualizer("test");

viewer.setBackgroundColor(0,0,0);
viewer.addCoordinateSystem(0.5);
viewer.initCameraParameters();
viewer.addSphere(pcl::PointXYZ{1,1,1}, 0.2, 0.3, 0.3, 0.0, "sphere");
viewer.spin();
.? // help
.I <path> //Adds an include path;
.include //Show include path
.L <library | filename.cxx> // loads library or filename.cxx
.files //Show all loaded files
.q // quit ROOT
.L  file.C // Load  file.C
.x  file.C //Load  file.C  and run its function  file()
.U  file.C //Unload  file.C
.class C // Print what cling knows about class C
.O0 // (dot oh-zero) // Disable cling's optimization (for debugging)
.! cmd // Run shell command cmd
.@ //Cancels the multiline input
.printAST // (DEBUG ONLY) Turns on the printing of the compiler's abstract syntax tree (AST);

2.2

3.

소스 설치
[스크립트]
시각화
도움말
Advices and Gotchas when using cling and jupyter