Full Dataset Computer Vision Project
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Overview This dataset is for the Hanover Bike Walk Census Tool YOLO model. It contains pedestrians, people riding on bicycles, people riding on e-scooters, and people in wheelchairs. We have trained a custom YOLOv8s model on this dataset and have found that the model generalizes quite well to stationary videos of urban environments. If you want to see the full project, please visit this github: https://github.com/rolson24/BWCT-Tracker/tree/electron-app
Classes
- Pedestrian
- Bikex
- Scooter
- Wheelchair
Detailed Annotation Style We decided to annotate the pedestrians as full people including their head, feet, and their arms. If a pedestrian's arms are sticking directly out to the side, we choose to not include them in the bounding box to make the box smaller for use with an object tracker. For bikes, scooters, and wheelchairs we included both the device that people are using for movement as well as the person's full body. This decision was made to ensure that the other classes would not be incorrectly detected as a pedestrian on top of an object.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
full-dataset-ncrgq_dataset,
title = { Full Dataset Dataset },
type = { Open Source Dataset },
author = { ENGS 89 },
howpublished = { \url{ https://universe.roboflow.com/engs-89/full-dataset-ncrgq } },
url = { https://universe.roboflow.com/engs-89/full-dataset-ncrgq },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { mar },
note = { visited on 2024-12-18 },
}