Ultralytic's' YOLOv8 is the latest version of the acclaimed real-time object detection and image segmentation model. YOLOv8 is built on cutting-edge advancements in deep learning and computer vision, offering unparalleled performance in terms of speed and accuracy.

Intended Use

The YOLOv8 segmentation model is designed to find image segments in images and video in real-time, making it suitable for a wide range of applications such as surveillance, self-driving cars, and robotics. This model is intended for use by developers and researchers who are experienced in computer vision and deep learning.

Performance

• Fast inference speed suitable for real-time applications

• High accuracy in segmentation tasks

• Capable of detecting and segmenting multiple object classes

Limitations

• May struggle with very small objects or crowded scenes

• Performance can degrade in low-light or poor visibility conditions

• Limited by the object classes it was trained on

• Cannot understand context or relationships between objects

• May have difficulty with highly occluded objects

Citation

Bochkovskiy, A., Wang, C. Y., & Liao, H. Y. M. (2021). YOLOv5: End-to-End Object Detection with Transformers. arXiv preprint arXiv:2104.07458.