DroneVis: Versatile Computer Vision Library for Drones
Computer Vision and Pattern Recognition
2024-06-04 v1 Artificial Intelligence
Computers and Society
Machine Learning
Robotics
Abstract
This paper introduces DroneVis, a novel library designed to automate computer vision algorithms on Parrot drones. DroneVis offers a versatile set of features and provides a diverse range of computer vision tasks along with a variety of models to choose from. Implemented in Python, the library adheres to high-quality code standards, facilitating effortless customization and feature expansion according to user requirements. In addition, comprehensive documentation is provided, encompassing usage guidelines and illustrative use cases. Our documentation, code, and examples are available in https://github.com/ahmedheakl/drone-vis.
Cite
@article{arxiv.2406.00447,
title = {DroneVis: Versatile Computer Vision Library for Drones},
author = {Ahmed Heakl and Fatma Youssef and Victor Parque and Walid Gomaa},
journal= {arXiv preprint arXiv:2406.00447},
year = {2024}
}
Comments
23 pages, 15 figure, 2 tables