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CenterLineDet
This is the official repo of paper CenterLineDet: Road Lane CenterLine Graph Detection With Vehicle-Mounted Sensors by Transformer for High-definition Map Creation by Zhenhua Xu, Yuxuan Liu, Yuxiang Sun, Ming Liu and Lujia Wang.
Update
Feb/17/2023: Add raw outputs of CenterLineDet
Jan/18/2023: Release the training code
Jan/17/2023: Accepted by ICRA 2023
Oct/15/2022: Release the inference code
Platform info
Hardware:
GPU: 4 RTX3090
CPU: Intel(R) Xeon(R) Gold 6230 CPU @ 2.10GHz
RAM: 256G
SSD: 4T
Software:
Ubuntu 20.04.3 LTS
CUDA 11.1
Docker 20.10.7
Nvidia-driver 495.29.05
Docker
This repo is implemented in the docker container. Make sure you have docker installed. Please refer to install Docker and Docker beginner tutorial for more information.
Docker image
For train and inference:
cd docker
./build_image.bash
For evaluation:
cd docker_py2
./build_image.bash
Docker container
In ./build_continer.bash and ./build_continer_py2.bash, set home_dir as the directory of this repo, and set dataset_dir as the directory of the downloaded nuscenes dataset.
For train and inference, run
./build_continer.bash
For evaluation, run
./build_continer_py2.bash
Data preparation and pretrained checkpoints
Check ./data for data preparation and pretrained checkpoints.
Implementation
For baseline models (i.e., segmentation based approachs including HDMapNet and our proposed FusionNet), please refer to ./segmentation_baselines.
For CenterLineDet with different perspective transformation models, please refer to ./CenterLineDet.
Contact
For any questions, please open an issue.
Ackonwledgement
We thank the following open-sourced projects:
Citation
@article{xu2022centerlinedet, title={CenterLineDet: Road Lane CenterLine Graph Detection With Vehicle-Mounted Sensors by Transformer for High-definition Map Creation}, author={Xu, Zhenhua and Liu, Yuxuan and Sun, Yuxiang and Liu, Ming and Wang, Lujia}, journal={arXiv preprint arXiv:2209.07734}, year={2022} }
License
GNU General Public License v3.0