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The newest model, YOLOv8, is a member of the most well-known family of object recognition and classification models in the field of computer vision (CV), the YOLO algorithm series.Thanks to the incorporation of many modifications including spatial attention, feature fusion, and context aggregation modules, it performs better than previous iterations.These improvements result in faster and more accurate object detection, making YOLOv8 one of the most significant object detection algorithms in the market.

This article introduces the most recent version of Ultralytics' YOLOv8, a well-known real-time object recognition and image segmentation model. This version offers remarkable speed and accuracy by utilising the most recent advancements in computer vision and deep learning. Because it's implemented in the user-friendly Ultralytics Python package, its effective architecture supports a broad range of applications and can be easily adapted to a variety of hardware platforms, from edge devices to cloud APIs.precise identification of objects.