This tutorial is also available as a Jupyter Notebook, which can be cloned directly from GitHub. See the installation guide for instructions on running this tutorial locally on Windows, Linux, or macOS.
The YOLOv8 algorithm developed by Ultralytics is a cutting-edge, state-of-the-art (SOTA) model designed to be fast, accurate, and easy to use, making it ideal for a variety of object detection, image segmentation, and image classification tasks.
YOLO stands for "You Only Look Once", and it is a popular family of real-time object detection algorithms. The original YOLO object detector was first released in 2016. Since then, different versions and variants of YOLO have been proposed, each offering significant improvements in performance and efficiency. YOLOv8 builds on the success of previous YOLO versions and introduces new features and improvements to further improve performance and flexibility.