Research and Design of Intelligent Detection Algorithm for Library Occupation Based on YOLOv5
The author design a YOLOv5 based on the target detection algorithm to identify the occupying behavior in the library,including two specific processes of initialization and judgment,in which YOLOv5 and HSV partitioning are used to accurately divide the target tables,and then the tables are divided equally by edge detection algorithm,convex packet algorithm and perspective transformation algorithm.Then,the tables are equally divided into seating areas by edge detection algorithm,convex wrapping algorithm and perspective transformation algorithm.In this paper,we first describe the existing library occupancy management solutions and analyze their potential drawbacks and inconveniences,so we propose a vision-based management method;then we introduce the development tools and algorithms used,including the Canny edge detection algorithm and the convex packet algorithm;then we analyze the feasibility of the system algorithm into technical aspects and environmental aspects,and then we design the algorithm flow based on these conditions;we implement the system algorithm through code,and then we design the algorithm flow.The design of the process;the implementation of the system algorithm through the code,the simulation data for testing,and the final result can meet the expected results.
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