Using YOLOv5 for Garbage Classification
Ziliang Wu, Duo Zhang, Yanhua Shao, Xiaoqiang Zhang, Xingping Zhang, Yupei Feng, Peng Cui · 2021
At present, people's daily garbage is increasing day by day. How to intelligently classify garbage can save manpower and improve work efficiency. In this paper, a garbage classification model based on YOLOv5 object detection network named GC-YOLOv5 is designed. First, according to the common daily garbage category, five typical kinds of garbage were selected, data cleaned, labeled, and constructed a garbage dataset. Second, the GC-YOLOv5 was built and trained on our datasets. Third, in view of the convenience of multi-terminal access in the cloud and the reduction of computing pressure on edge devices, we deploy the garbage classification model in the cloud. The experimental results show that GC-YOLOv5 can accurately identify the garbage's types and find out the location of garbage.