https://github.com/tumftm/truckscenes-devkit
Development Kit for the MAN TruckScenes Dataset
https://github.com/tumftm/truckscenes-devkit
autonomous-driving camera dataset devkit lidar perception radar
Last synced: 17 days ago
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Development Kit for the MAN TruckScenes Dataset
- Host: GitHub
- URL: https://github.com/tumftm/truckscenes-devkit
- Owner: TUMFTM
- License: other
- Created: 2024-07-15T08:47:56.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-03-10T12:37:41.000Z (about 2 months ago)
- Last Synced: 2025-04-03T03:11:27.987Z (24 days ago)
- Topics: autonomous-driving, camera, dataset, devkit, lidar, perception, radar
- Language: Jupyter Notebook
- Homepage:
- Size: 9.61 MB
- Stars: 39
- Watchers: 3
- Forks: 6
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
Awesome Lists containing this project
README
MAN TruckScenes devkit
World's First Public Dataset For Autonomous Trucking
[](https://www.python.org/downloads/)
[](https://www.linux.org/)
[](https://www.microsoft.com/windows/)
[](https://arxiv.org/abs/2407.07462)
[](https://cdn-assets-eu.frontify.com/s3/frontify-enterprise-files-eu/eyJwYXRoIjoibWFuXC9maWxlXC9lb2s3TGF5V1RXMXYxZU1TUk02US5tcDQifQ:man:MuLfMZFfol1xfBIL7rNw0W4SqczZqwTuzhvI-yxJmdY?width={width}&format=mp4)
## Overview
- [Website](#🌐-website)
- [Installation](#💾-installation)
- [Setup](#🔨-setup)
- [Usage](#🚀-usage)
- [Citation](#📄-citation)
## 🌐 Website
To read more about the dataset or download it, please visit [https://www.man.eu/truckscenes](https://www.man.eu/truckscenes)
## 💾 Installation
Our devkit is available and can be installed via pip:
```
pip install truckscenes-devkit
```
If you also want to install all the (optional) dependencies for running the visualizations:
```
pip install "truckscenes-devkit[all]"
```
For more details on the installation see [installation](./docs/installation.md)
## 🔨 Setup
Download **all** archives from our [download page](https://www.man.eu/truckscenes/) or the [AWS Open Data Registry](https://registry.opendata.aws/).
Unpack the archives to the `/data/man-truckscenes` folder **without** overwriting folders that occur in multiple archives.
Eventually you should have the following folder structure:
```
/data/man-truckscenes
samples - Sensor data for keyframes.
sweeps - Sensor data for intermediate frames.
v1.0-* - JSON tables that include all the meta data and annotations. Each split (trainval, test, mini) is provided in a separate folder.
```
## 🚀 Usage
Please follow these steps to make yourself familiar with the MAN TruckScenes dataset:
- Read the [dataset description](https://www.man.eu/truckscenes/).
- Explore the dataset [videos](https://cdn-assets-eu.frontify.com/s3/frontify-enterprise-files-eu/eyJwYXRoIjoibWFuXC9maWxlXC9lb2s3TGF5V1RXMXYxZU1TUk02US5tcDQifQ:man:MuLfMZFfol1xfBIL7rNw0W4SqczZqwTuzhvI-yxJmdY?width={width}&format=mp4).
- [Download](https://www.man.eu/truckscenes/) the dataset from our website.
- Make yourself familiar with the [dataset schema](./docs/schema_truckscenes.md)
- Run the [tutorial](./tutorials/truckscenes_tutorial.ipynb) to get started:
- Read the [MAN TruckScenes paper](https://arxiv.org/abs/2407.07462) for a detailed analysis of the dataset.
## 📄 Citation
```
@inproceedings{truckscenes2024,
title = {MAN TruckScenes: A multimodal dataset for autonomous trucking in diverse conditions},
author = {Fent, Felix and Kuttenreich, Fabian and Ruch, Florian and Rizwin, Farija and Juergens, Stefan and Lechermann, Lorenz and Nissler, Christian and Perl, Andrea and Voll, Ulrich and Yan, Min and Lienkamp, Markus},
booktitle = {Advances in Neural Information Processing Systems},
editor = {A. Globerson and L. Mackey and D. Belgrave and A. Fan and U. Paquet and J. Tomczak and C. Zhang},
pages = {62062--62082},
publisher = {Curran Associates, Inc.},
url = {https://proceedings.neurips.cc/paper_files/paper/2024/file/71ac06f0f8450e7d49063c7bfb3257c2-Paper-Datasets_and_Benchmarks_Track.pdf},
volume = {37},
year = {2024}
}
```
_Copied and adapted from [nuscenes-devkit](https://github.com/nutonomy/nuscenes-devkit)_