Giving YOLOv8 a Second Look (Part 3)

This article is the third and final part of a series that demonstrates how to work with YOLOv8, from downloading off-the-shelf models to fine-tuning these models for specific use cases. The author uses two libraries, FiftyOne and Ultralytics, to fine-tune a YOLOv8 model for custom computer vision applications. The article covers the process of defining a use case, choosing training data, fine-tuning the YOLOv8 model, and assessing the improvement in performance. It also discusses potential approaches to further improve the model's performance.