aimotive / aimotive-dataset-loader

Dataset loader and renderer for aiMotive Multimodal Dataset
https://openreview.net/forum?id=LW3bRLlY-SA
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autonomous-driving multimodal-deep-learning

aiMotive Multimodal Dataset Loader

Download

The dataset can be downloaded from this repository.

Installation

The repository has been tested on Ubuntu with Python 3.8. Currently no Windows support is available.

Create a conda environment

conda create --name aimdataset python=3.8
conda activate aimdataset

Clone repository

git clone https://github.com/aimotive/aimotive-dataset-loader.git
cd aimotive-dataset-loader

Install requirements

pip install -r requirements.txt

Examples

The repository includes a small sample dataset with 50 keyframes. The examples demonstrate how the data can be rendered and loaded to PyTorch framework.

Run rendering example

PYTHONPATH=$PYTHONPATH: python examples/example_render.py

Run PyTorch loader example

Install torch

pip install torch==1.9.0+cu102 torchvision==0.10.0+cu102 -f https://download.pytorch.org/whl/torch_stable.html

Run script

PYTHONPATH=$PYTHONPATH: python examples/pytorch_loader.py

Cite our work

If you use this code or aiMotive Multimodal Dataset in your research, please cite our work by using the following BibTeX entries:

 @article{matuszka2022aimotivedataset,
  title = {aiMotive Dataset: A Multimodal Dataset for Robust Autonomous Driving with Long-Range Perception},
  author = {Matuszka, Tamás and Barton, Iván and Butykai, Ádám and Hajas, Péter and Kiss, Dávid and Kovács, Domonkos and Kunsági-Máté, Sándor and Lengyel, Péter and Németh, Gábor and Pető, Levente and Ribli, Dezső and Szeghy, Dávid and Vajna, Szabolcs and Varga, Bálint},
  doi = {10.48550/ARXIV.2211.09445},
  url = {https://arxiv.org/abs/2211.09445},
  publisher = {arXiv},
  year = {2022},
}

@inproceedings{
matuszka2023aimotive,
title={aiMotive Dataset: A Multimodal Dataset for Robust Autonomous Driving with Long-Range Perception},
author={Tamas Matuszka},
booktitle={International Conference on Learning Representations 2023 Workshop on Scene Representations for Autonomous Driving},
year={2023},
url={https://openreview.net/forum?id=LW3bRLlY-SA}
}