README.md

---
license: apache-2.0
language:
- en
---
# Ocularone: Hazard Vest Dataset

<p align="center">
🤗 <a href="https://huggingface.co/datasets/Bhavani-23/Ocularone-Hazard-Vest-Dataset">Hugging Face</a>&nbsp&nbsp | &nbsp&nbsp🚀 <a href="https://github.com/dream-lab/ocularone-dataset-v0.git">Github</a> &nbsp&nbsp
</p>

Note: The dataset was used to train YOLO models (v8 and v11) to detect the hazard vest on a person. The models can be found [here](https://huggingface.co/Bhavani-23/Ocularone-Hazard-Vest-Dataset-Models).

<!-- Provide a quick summary of the dataset. -->

The dataset has two files: one which contains all the images that were collected by a drone of a person wearing a hazard vest and walking around our University campus; the other file contains the training data with images that were randomly picked from the total dataset.

<!-- ## Dataset Details

### Dataset Description -->

## Dataset Structure

The dataset consists of multiple subfolders which describe the categories/conditions under which the images were collected. Each category folder has multiple subfolders for the images.

## References

<!-- ```text
@misc{ocularone-dataset-v0,
  title = {Ocularone: Hazard Vest Dataset},
  publisher = {GitHub},
  howpublished = {\url{https://github.com/dream-lab/ocularone-dataset}},
}
``` -->


``` text
@misc{raj2024adaptiveheuristicsschedulingdnn,
      title={Adaptive Heuristics for Scheduling DNN Inferencing on Edge and Cloud for Personalized UAV Fleets}, 
      author={Suman Raj and Radhika Mittal and Harshil Gupta and Yogesh Simmhan},
      year={2024},
      eprint={2412.20860},
      archivePrefix={arXiv},
      primaryClass={cs.DC},
      url={https://arxiv.org/abs/2412.20860}, 
}
```