Lightweight human body detection algorithm suitable for edge devices
A lightweight human detection algorithm based on YOLOv7 is proposed to address the issue of complex human de-tection networks that perform poorly when deployed on edge devices.The algorithm first replaces the original network ELAN mod-ule with the improved ShuffleNev2 basic module;Next,add SE attention and SPPF pooling at the end of the backbone network;Then,in the Neck section,the improved GSConv is used to replace the standard convolution,and the GSConv based VoVGSCSP is introduced to replace the ELAN-W module.The validation results on GPU and Sophon SE5 show that this lightweight human detec-tion algorithm loses 2.6%accuracy compared to YOLOv7,but significantly reduces computational complexity.The inference speed on Sophon SE5 reaches 54 FPS,which is 39 FPS higher than YOLOv7.
NETL
NSTL
万方数据
