This is the official code of TRG-Net, the proposal of our paper A Lightweight Gaussian-Based Model for Fast Detection and Classification of Moving Objects. TRG-Net is a unified model that can be executed on computationally limited devices to detect and classify only moving objects. This solution is based on the Faster R-CNN architecture, but with a novel GMM-based region proposal method.
Install with:
$ pip install -r requirements.txt
$ python setup.py install
Paste the pre-trained model in the following route: ~/.trgnet/checkpoints/
, feel free to send us an email for the .pt
file. If you want to train the model by yourself run the train.py
file. TRG-Net uses the Kitti dataset, the dataset will be automatically downloaded if not present.
Finally, run the sample.py
script to run the model and start detecting moving objects.
@conference{visapp23trgnet,
author={Joaquin Palma{-}Ugarte. and Laura Estacio{-}Cerquin. and Victor Flores{-}Benites. and Rensso Mora{-}Colque.},
title={A Lightweight Gaussian-Based Model for Fast Detection and Classification of Moving Objects},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2023},
pages={173-184},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011697200003417},
isbn={978-989-758-634-7},
issn={2184-4321},
}