A Detection Method of Modern Hanfu Style Based on RSS-YOLOv5s Model
Hanfu has become a kind of wearing fashion for young people,but its modern style information is diffi-cult to be accurately identified by many Hanfu fans.Therefore,based on the YOLOv5s model,this paper improved the network feature extraction capability by inserting the Repvgg module and introducing the SE attention mecha-nism at the same time,and optimized the loss function using SIoU_Loss to improve the bounding box positioning ac-curacy,so as to realize the real-time detection of Hanfu style.The experimental results show that the algorithm a-chieves significant improvement in a number of evaluation indexes,with an overall precision rate of 92.4％,a re-call rate of 91.6％,an average precision mean of 91.8％,and a single-image inference time of only 15.0 ms.The method can recognize the style of Hanfu quickly and accurately,thus helping people to understand the stylistic characteristics of modern Hanfu and providing technical support for the inheritance and development of Chinese ex-cellent traditional culture.
万方数据
维普
