This repository contains materials for researching semantic and instance plane segmentation from point clouds collected from LiDARs.
- 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.
- Installing packages for testing
python3 -m pip install -r requirements.txt
- Running unit tests
python3 ./scripts/run_tests.py
- Go to the required directory
cd src/algorithmsForPointCloud
or
cd src/open3DTool
- Install required packages
python3 -m pip install -r requirements.txt
- A detailed README can be found in each of the directories
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