{"id":22745919,"url":"https://github.com/tumftm/truckscenes-devkit","last_synced_at":"2025-04-10T04:57:55.493Z","repository":{"id":251732668,"uuid":"828847905","full_name":"TUMFTM/truckscenes-devkit","owner":"TUMFTM","description":"Development Kit for the MAN TruckScenes Dataset","archived":false,"fork":false,"pushed_at":"2025-03-10T12:37:41.000Z","size":10074,"stargazers_count":39,"open_issues_count":1,"forks_count":6,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-04-03T03:11:27.987Z","etag":null,"topics":["autonomous-driving","camera","dataset","devkit","lidar","perception","radar"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n\n\u003ch1\u003eMAN TruckScenes devkit\u003c/h1\u003e\n\nWorld's First Public Dataset For Autonomous Trucking\n\n[![Python](https://img.shields.io/badge/python-3-blue.svg)](https://www.python.org/downloads/)\n[![Linux](https://img.shields.io/badge/os-linux-blue.svg)](https://www.linux.org/)\n[![Windows](https://img.shields.io/badge/os-windows-blue.svg)](https://www.microsoft.com/windows/)\n[![arXiv](https://img.shields.io/badge/arXiv-Paper-blue.svg)](https://arxiv.org/abs/2407.07462)\n\n[![Watch the video](https://raw.githubusercontent.com/ffent/truckscenes-media/main/thumbnail.jpg)](https://cdn-assets-eu.frontify.com/s3/frontify-enterprise-files-eu/eyJwYXRoIjoibWFuXC9maWxlXC9lb2s3TGF5V1RXMXYxZU1TUk02US5tcDQifQ:man:MuLfMZFfol1xfBIL7rNw0W4SqczZqwTuzhvI-yxJmdY?width={width}\u0026format=mp4)\n\n\u003c/div\u003e\n\n## Overview\n- [Website](#🌐-website)\n- [Installation](#💾-installation)\n- [Setup](#🔨-setup)\n- [Usage](#🚀-usage)\n- [Citation](#📄-citation)\n\n## 🌐 Website\nTo read more about the dataset or download it, please visit [https://www.man.eu/truckscenes](https://www.man.eu/truckscenes)\n\n## 💾 Installation\nOur devkit is available and can be installed via pip:\n```\npip install truckscenes-devkit\n```\n\nIf you also want to install all the (optional) dependencies for running the visualizations:\n```\npip install \"truckscenes-devkit[all]\"\n```\n\nFor more details on the installation see [installation](./docs/installation.md)\n\n## 🔨 Setup\nDownload **all** archives from our [download page](https://www.man.eu/truckscenes/) or the [AWS Open Data Registry](https://registry.opendata.aws/).  \n\nUnpack the archives to the `/data/man-truckscenes` folder **without** overwriting folders that occur in multiple archives.  \nEventually you should have the following folder structure:\n```\n/data/man-truckscenes\n    samples\t-\tSensor data for keyframes.\n    sweeps\t-\tSensor data for intermediate frames.\n    v1.0-*\t-\tJSON tables that include all the meta data and annotations. Each split (trainval, test, mini) is provided in a separate folder.\n```\n\n## 🚀 Usage\nPlease follow these steps to make yourself familiar with the MAN TruckScenes dataset:\n- Read the [dataset description](https://www.man.eu/truckscenes/).\n- Explore the dataset [videos](https://cdn-assets-eu.frontify.com/s3/frontify-enterprise-files-eu/eyJwYXRoIjoibWFuXC9maWxlXC9lb2s3TGF5V1RXMXYxZU1TUk02US5tcDQifQ:man:MuLfMZFfol1xfBIL7rNw0W4SqczZqwTuzhvI-yxJmdY?width={width}\u0026format=mp4).\n- [Download](https://www.man.eu/truckscenes/) the dataset from our website.\n- Make yourself familiar with the [dataset schema](./docs/schema_truckscenes.md)\n- Run the [tutorial](./tutorials/truckscenes_tutorial.ipynb) to get started:\n- Read the [MAN TruckScenes paper](https://arxiv.org/abs/2407.07462) for a detailed analysis of the dataset.\n\n## 📄 Citation\n```\n@inproceedings{truckscenes2024,\n title = {MAN TruckScenes: A multimodal dataset for autonomous trucking in diverse conditions},\n 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},\n booktitle = {Advances in Neural Information Processing Systems},\n editor = {A. Globerson and L. Mackey and D. Belgrave and A. Fan and U. Paquet and J. Tomczak and C. Zhang},\n pages = {62062--62082},\n publisher = {Curran Associates, Inc.},\n url = {https://proceedings.neurips.cc/paper_files/paper/2024/file/71ac06f0f8450e7d49063c7bfb3257c2-Paper-Datasets_and_Benchmarks_Track.pdf},\n volume = {37},\n year = {2024}\n}\n```\n\n_Copied and adapted from [nuscenes-devkit](https://github.com/nutonomy/nuscenes-devkit)_\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftumftm%2Ftruckscenes-devkit","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftumftm%2Ftruckscenes-devkit","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftumftm%2Ftruckscenes-devkit/lists"}