The present invention discloses a cloud-based intelligent table tennis training
system based on YOLOv5, which relates to the field of
artificial intelligence technology and is targeted at enterprise-level users. The enterprise-level users include a host
computer module, a ball feeder module, a
client module, a cloud-based table tennis
landing point detection and scoring module, a function module for displaying detection results, an audio prompt interaction module, and a control module. The present invention uses an improved YOLO v5 model, combines the coordinate detection of table tennis balls, training scoring with multi-threaded timing
signal interaction, and performs detection based on Jetson nano and a single industrial camera, saving a large amount of costs and being able to successfully complete closed-loop intelligent training. And aiming at the problem of low precision in small
object detection, an exponential mean brightness
equalization algorithm capable of automatically adjusting brightness and an improved YOLO v5 anchor generation mechanism are proposed, which not only improve the accuracy of model detection, but also can improve the accuracy of table tennis
landing point detection, giving users a better experience.