README.md

pointcloudprocessing

This repository contains the code examples of my medium tutorial "Point Cloud Processing".
"Point Cloud Processing" tutorial is beginner-friendly in which we will simply introduce the point cloud processing pipeline from data preparation to data segmentation and classification.

Content

In this repository you will find:

• data folder:
  Includes the input files that are used for demonstration.

• output folder:
  Includes some saved output data.

• introduction folder:
  includes the examples of the first tutorial: Introduction to Point Cloud Processing.

  • introduction_random_points.py : creates a random point cloud and display it using Matplotlib.
  • introduction_sampling.py : samples point cloud from a mesh and display it using Open3D.
  • introduction_np_o3d.py : switching between Open3D and NumPy.
  • introduction_rgbd.py : computing point clours from RGB-D data using Open3D functions.

• pointcloudfromdepth folder:
  includes the examples of the second tutorial: Point cloud computing from RGB-D images.

  • pointcloud_from_depth.py : compute point clouds from RGB-D data without using Open3D functions.
  • colored_pointcloud_from_depth.py : compute colored point clouds.

• grounddetection folder:
  Includes the examples of the third tutorial: Understand point clouds: a simple ground detection algorithm

  • computer_vision_coordinate_system.py : Understand the computer vision system coordinate.
  • ground_detection.py : A simple ground detection algorithm.
  • organized_pointcloud.py : compute organized point cloud.

• preprocessing folder:
  Includes the examples of the 4th tutorial: Point Cloud Filtering in Python.

  • crop_pointcloud_o3d.py : pass-through filter using Open3D.
  • passthrough_filter_np.py : a NumPy implementation of pass-through filter.
  • downsampling.py : down-sampling methods.
  • point_cloud_filtering.py : outlier removal filters: statistical outlier removal and radius outlier removal demonstration.

• segmentation folder:
  Includes the examples of the 5th tutorial: Point Cloud Segmentation in Python.

  • clustering.py: point cloud clustering.
  • projection_clustering.py: clustering of a projected point cloud.

Requirements

• Open3D : 0.15.1
• NumPy : 1.21.6