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linefit is a ground segmentation algorithm for 3D point clouds. This repo we setup a python binding for the original C++ code and push to pypi for easy installation through pip install linefit
.
Author: C++ code from Lorenz Wellhausen, nanobind by Qingwen Zhang.
Running on macOS, Windows and Linux, with Python Version >= 3.8.
📜 Change Log:
np.array
<-> std::vector<Eigen:: Vector3d>
conversion and also NOMINSIZE
in make. Speed difference: 0.1s -> 0.01s. Based on discussion here.Choose one of the following options to install the package (recommended to use Option A pip install linefit
):
Option A: Install from pypi pip install linefit
Option B: Clone this repo and run following to build:
cmake -B build && cmake --build build
pip install .
python3 -c 'import linefit; print("success")'
After installation, you can run the example by, it will directly show a default effect of demo data.
python example.py
A window will pop up and show the ground segmentation result.
TL;DR: tune the sensor_height
to offset the ground point z to 0
. Others are optional for better performance. If you are interested in the details, please read the following.
Parameters are set in assets/config.toml
This algorithm works on the assumption that you known the height of the sensor above ground.
Therefore, you have to adjust the sensor_height
to your robot specifications, otherwise, it will not work.
The default parameters should work on the KITTI dataset.
The original C++ code is from the repo we forked: lorenwel/linefit_ground_segmentation.
The original methods are described in the following paper:
@inproceedings{himmelsbach2010fast,
title={Fast segmentation of 3d point clouds for ground vehicles},
author={Himmelsbach, Michael and Hundelshausen, Felix V and Wuensche, H-J},
booktitle={Intelligent Vehicles Symposium (IV), 2010 IEEE},
pages={560--565},
year={2010},
organization={IEEE}
}
More python binding examples can be found in our other project:
FAQs
linefit ground segmentation algorithm Python bindings
We found that linefit demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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