THE RECOGNITION OF CLOTHING LOGO BASED ON ENHANCED YOLOV5

In this paper, the enhanced YOLOv5 algorithm is applied to clothing brand logo recognition. We used the weighted k-means algorithm to obtain 9 initial anchor boxes, and transformer self-attention mechanism and SPPF model were added to the original YOLOv5 backbone. We made some adjustments on the base of the existing FlickrSportlogos-10 dataset, such as removing some low quality and similar images and adding some high-quality images. The experimental results show that the mAP@0.5 and mAP@0.5:0.95 of the enhanced YOLOv5 algorithm reach 90.7% and 60.1%, which are 0.033 and 0.016 higher than the original YOLOv5 algorithm respectively.