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<div align="center"> <a href="https://innovation-mobility.com/tumtraf-dataset"><img src="https://img.shields.io/badge/Datasets-TUMTraf-0065BD.svg" alt="Dataset Badge"/></a> <a href="https://tum-traffic-dataset.github.io/tumtraf-v2x"><img src="https://img.shields.io/badge/TUMTraf-V2X-0065BD.svg" alt="Github Badge"/></a> <a href="https://github.com/tum-traffic-dataset/tum-traffic-dataset-dev-kit"><img src="https://img.shields.io/badge/Dev_Kit-code-E37222.svg?style=flat&logo=github&logoColor=white" alt="Github Badge"/></a> <a href="https://ieeexplore.ieee.org/document/8814071"><img src="https://img.shields.io/badge/Paper-3D_BAT-0E2B3A.svg?style=flat&logo=ieee" alt="Paper Badge"/></a> <a href="https://arxiv.org/pdf/2403.01316.pdf"><img src="https://img.shields.io/badge/Paper-TUMTraf_V2X-a2ad00.svg" alt="Paper Badge"/></a> <a href="https://github.com/walzimmer/3d-bat/stargazers"><img src="https://img.shields.io/github/stars/walzimmer/3d-bat" alt="Stars Badge"/></a> <a href="https://github.com/walzimmer/3d-bat/network/members"><img src="https://img.shields.io/github/forks/walzimmer/3d-bat" alt="Forks Badge"/></a> <a href="https://github.com/walzimmer/3d-bat/pulls"><img src="https://img.shields.io/github/issues-pr/walzimmer/3d-bat" alt="Pull Requests Badge"/></a> <a href="https://github.com/walzimmer/3d-bat/issues"><img src="https://img.shields.io/github/issues/walzimmer/3d-bat" alt="Issues Badge"/></a> <a href="https://a9-dataset.innovation-mobility.com/license"><img src="https://img.shields.io/badge/license-custom-2b9348.svg" alt="Issues Badge"/></a> </div> <h1 align="center">3D Bounding Box Annotation Toolbox</h1>

Overview ✨

News 📢

Video

Features 🔥

Comparison

Animation

Release Notes 📝

Quick Start 🚀

1. Install npm

2. Clone repository:

git clone https://github.com/walzimmer/3d-bat.git & cd 3d-bat

3. Install required python packages:

conda create -n 3d-bat python==3.11.3
conda activate 3d-bat
pip install -r requirements.txt
conda install -c conda-forge nodejs==10.13.0

4. Install required node packages:

npm install

5. Start the backend-server

npm run start-server

6. Start the labeling tool application

npm run start

The index.html file should open now in the specified browser (chromium-browser by default). The default browser can be changed in the package.json file, line 32:

"start": "webpack serve --inline --open chromium-browser",

Custom Data Annotation 🌟

See Custom Data Annotation for more details.

Labeling Instructions 🗒

Instructions for data annotation can be found here.

Timelapse

Commands and Shortcuts 👨🏽‍💻

See Commands and Shortcuts for more details.

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Tutorial Videos 📹

📚 Documentation

A readthedocs documentation will be available soon.

📝 Citation

If you use 3D Bounding Box Annotation Toolbox in your research, please cite the following papers:

@inproceedings{zimmermann20193d,
  title={3D BAT: A Semi-Automatic, Web-based 3D Annotation Toolbox for Full-Surround, Multi-Modal Data Streams},
  author={Zimmer, Walter and Rangesh, Akshay and Trivedi, Mohan M.},
  booktitle={2019 IEEE Intelligent Vehicles Symposium (IV)},
  pages={1--8},
  year={2019},
  organization={IEEE}
}
@inproceedings{cress2022a9,
  author={Creß, Christian and Zimmer, Walter and Strand, Leah and Fortkord, Maximilian and Dai, Siyi and Lakshminarasimhan, Venkatnarayanan and Knoll, Alois},
  booktitle={2022 IEEE Intelligent Vehicles Symposium (IV)}, 
  title={A9-Dataset: Multi-Sensor Infrastructure-Based Dataset for Mobility Research}, 
  year={2022},
  volume={},
  number={},
  pages={965-970},
  doi={10.1109/IV51971.2022.9827401}
}
@inproceedings{zimmer2023tumtraf,
  title={TUMTraf Intersection Dataset: All You Need for Urban 3D Camera-LiDAR Roadside Perception [Best Student Paper Award]},
  author={Zimmer, Walter and Cre{\ss}, Christian and Nguyen, Huu Tung and Knoll, Alois C},
  publisher = {IEEE},
  booktitle={2023 IEEE Intelligent Transportation Systems ITSC},
  year={2023}
}
@inproceedings{zimmer2024tumtrafv2x,
  title={TUMTraf V2X Cooperative Perception Dataset},
  author={Zimmer, Walter and Wardana, Gerhard Arya and Sritharan, Suren and Zhou, Xingcheng and Song, Rui and Knoll, Alois C.},
  publisher={IEEE/CVF},
  booktitle={2024 IEEE/CVF International Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2024}
}

📜 License

Copyright © 2019 The Regents of the University of California

All Rights Reserved. Permission to copy, modify, and distribute this tool for educational, research and non-profit purposes, without fee, and without a written agreement is hereby granted, provided that the above copyright notice, this paragraph and the following three paragraphs appear in all copies. Permission to make commercial use of this software may be obtained by contacting:

Office of Innovation and Commercialization
9500 Gilman Drive, Mail Code 0910
University of California
La Jolla, CA 92093-0910
(858) 534-5815
innovation@ucsd.edu

This tool is copyrighted by The Regents of the University of California. The code is supplied “as is”, without any accompanying services from The Regents. The Regents does not warrant that the operation of the tool will be uninterrupted or error-free. The end-user understands that the tool was developed for research purposes and is advised not to rely exclusively on the tool for any reason.

IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS TOOL, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE TOOL PROVIDED HEREUNDER IS ON AN “AS IS” BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.