mhnazeri/verti-wheelers

Training code for Verti-Wheelers

This repository contains PyTorch training code for Verti-Wheelers.

Installation

Main libraries:

• PyTorch: as the main ML framework
• Comet.ml: tracking code, logging experiments
• OmegaConf: for managing configuration files

First create a virtual env for the project.

python3 -m venv .venv
source .venv/bin/activate

Then install the latest version of PyTorch from the official site. Finally, run the following:

pip install -r requirements

To set up Comet.Ml follow the official documentations.

Dataset

To download the dataset please follow the instructions here.

Run

To run parser, first edit the config file in conf/parser_config directory. Then run:

./run.sh parse

To run the training pipeline, make sure everything in the config file is correct, then run:

./run.sh train

Deployment

To deploy the trained model, please follow the instructions here.

Reference

If you find this repo to be helpful, please consider citing our work:

@article{datar2023a,
  title={Toward Wheeled Mobility on Vertically Challenging Terrain: Platforms, Datasets, and Algorithms},
  author={Datar, Aniket and Pan, Chenhui and Nazeri, Mohammad and Xiao, Xuesu},
  journal={arXiv preprint arXiv:2303.00998},
  year={2023}
}