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This repository contains materials for researching semantic and instance plane segmentation from point clouds collected from LiDARs.

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Plane segmentation research

Unit tests

Description

This repository contains materials for researching semantic and instance plane segmentation from point clouds collected from LiDARs.

Content

  • src
    • algorithmsForPointCloud - this folder contains files with methods that allow you to transform point clouds, extract some information from them and label files.
    • open3DTool - this folder contains an MVP application containing: presegmentation by planar labels, segmenting planes by n points.
  • notebooks
    • About_segment_plane - some information about segment_plane method from the Open3D library
    • Some_functions - some set of functions for working with point clouds
    • LeastSquaresFitting - implementation of linear regression and SVD-fitting methods to solve an optimization problem, as well as a few examples.

Running unit tests

  1. Installing packages for testing
    python3 -m pip install -r requirements.txt
  2. Running unit tests
    python3 ./scripts/run_tests.py

Installing packages for src folders

  1. Go to the required directory
cd src/algorithmsForPointCloud
or
cd src/open3DTool
  1. Install required packages
python3 -m pip install -r requirements.txt
  1. A detailed README can be found in each of the directories

Example of running Open3DTool

python -m src --path_to_bin_file data/000.bin \
        --path_to_save_label_file data/labelFile.pcd.labels \
        --path_to_save_object_file data/labelFile.pcd.objects \
        --path_to_pcd_file data/000.pcd \ 
        --distance_to_plane 0.06 \
        --count_points_to_pick 5

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This repository contains materials for researching semantic and instance plane segmentation from point clouds collected from LiDARs.

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