School Bus Detection Using YOLOv5 (Tutorial – Part 2)

Kristen Kehrer, a Developer Advocate at CometML, shares her experience in the second part of a tutorial series on creating a school bus detector using YOLOv5. The process involves using Roboflow for image annotation and data management before exporting the annotated data for use in CometML, where data lineage can be tracked. Kehrer emphasizes the importance of keeping data organized, reflecting on past challenges with scattered image data. Roboflow's UI facilitated quick annotation, while its Python SDK allowed seamless data export to a staging directory. The annotated data is then uploaded to CometML as a data artifact, enabling efficient tracking and version control of different data sets. The tutorial outlines the preparation for training the YOLOv5 model using the CometML integration, with a focus on running the model on local GPUs following PyTorch setup instructions. This part of the series concludes with the anticipation of detecting buses live and setting up alerts using AWS in future installments.