This project has been accepted by IEEE ITSC 2022. If you find this work useful in your research, please consider cite:
@article{bai2022pillargrid,
title={PillarGrid: Deep Learning-based Cooperative Perception for 3D Object Detection from Onboard-Roadside LiDAR},
author={Bai, Zhengwei and Wu, Guoyuan and Barth, Matthew J and Liu, Yongkang and Sisbot, Akin and Oguchi, Kentaro},
journal={arXiv preprint arXiv:2203.06319},
year={2022}
}CARLA-based 3D object detection and tracking dataset generator using KITTI-format
Please install CARLA==0.9.13 and MMDetection3D==0.18.0
- Linux (Ubuntu 18.04)
- Python 3.7
- PyTorch 1.3+
- CUDA 11.1
- GCC 5+
- MMCV
Download the CARLA 0.9.13 at Here
git clone https://github.com/zwbai/CARTI_Dataset.gitRun CARLA server
python CARTI_Dataset_V1.0.pyThe required versions of MMCV, MMDetection and MMSegmentation for different versions of MMDetection3D are as below. Please install the correct version of MMCV, MMDetection and MMSegmentation to avoid installation issues.
| MMDetection3D version | MMDetection version | MMSegmentation version | MMCV version |
|---|---|---|---|
| v1.0.0rc2 | mmdet>=2.19.0, <=3.0.0 | mmseg>=0.20.0, <=1.0.0 | mmcv-full>=1.4.8, <=1.7.0 |
| 0.18.0 | mmdet>=2.19.0, <=3.0.0 | mmseg>=0.20.0, <=1.0.0 | mmcv-full>=1.3.17, <=1.5.0 |
Assuming that you already have CUDA 11.0 installed, here is a full script for quick installation of MMDetection3D with conda. Otherwise, you should refer to the step-by-step installation instructions in the next section.
conda create -n open-mmlab python=3.7 -y
conda activate open-mmlab
pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html --no-cache
pip install mmcv-full==1.3.17 -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.9.0/index.html
pip install mmdet==2.19.0
pip install mmsegmentation==0.20.0
pip install setuptools==59.5.0
git clone https://github.com/open-mmlab/mmdetection3d.git
git checkout tags/0.18.0
cd mmdetection3d
pip install -v -e .
pip install open3dDo not forget to add ./checkpoints/{}.pth and ./demo/data/kitti/{}.bin
python demo/pcd_demo.py demo/data/kitti/kitti_000008.bin configs/second/hv_second_secfpn_6x8_80e_kitti-3d-car.py checkpoints/hv_second_secfpn_6x8_80e_kitti-3d-car_20200620_230238-393f000c.pth --showThis repo is built based on the following outstanding works, which are greatly appreciated by the authors.