Microsoft COCO is a large-scale dataset and data annotation format. Today, COCO is a widely adopted standard for object detection, segmentation, and captioning.
COCOHelper makes working with the COCO format super-easy! You can use it to efficiently run complex operations such as statistical analysis and dataset arithmetic with just a few lines of code. Check our documentation and tutorials to learn how!
Quick Links:
To install the library, download the latest wheel package from this repo and install through pip, poetry, or other python package managers.
NB: We are still working to publish the library to public PyPi.
You can find examples of usage in usage.md and notebooks folder.
Contributors are always welcome to help us fix an issue, add tests, improve code and documentation quality. If you'd like to contribute, please see our contributing guide.
Thanks a lot to all of our outstanding contributors!
We would appreciate your citation if you find COCOHelper useful in your research.
You can cite COCOHelper using the following BibTeX entry:
@misc{cocohelper,
title={COCOHelper},
author={Riccardo Del Chiaro, Andrea Panizza, Giacomo Veneri, Gabriele Valvano},
year={2022},
howpublished={https://github.com/baker-hughes/cocohelper},
} We thank the main authors and all the contributors for their help in developing the library. We also thank Elia Lotti for his precious work on this project.