Comparing YOLOv5 and YOLOv8: Which one should you use?
In the field of object detection, YOLO (You Only Look Once) has been a breakthrough algorithm. Since the inception of the YOLO algorithm, it has evolved into many versions, and the two most popular versions are YOLOv5 and YOLOv8. Both versions have unique features and advantages that make them exceptional in their way.
In this article, we will compare YOLOv5 and YOLOv8 and see which one is better in terms of accuracy and FPS. So let’s start!
Similarities (YOLOv5 vs YOLOv8)
Backbone: Both YOLOv5 and YOLOv8 use the CSPDarknet53 backbone architecture.
Anchor Boxes: Both algorithms use anchor boxes to improve object detection accuracy.
Non-Maximum Suppression (NMS): Both algorithms use NMS to suppress multiple detections of the same object.
Post-processing: Both algorithms use post-processing techniques to improve the accuracy of object detection.
Optimizer: Both YOLOv5 and YOLOv8 use the Adam optimizer for training the model.
Activation Function: Both algorithms use the Mish activation function in their architecture.
Accuracy Comparison (YOLOv5 vs YOLOv8)
