A Peach Maturity Detection Algorithm Based on YOLOV5 Attention Mechanism

Abstract

With the rapid development of computer vision technology, the original method of rapid non-destructive testing of peach maturity has been unable to meet the management requirements, and the management efficiency and accuracy cannot meet the daily needs. Based on the above reasons, this paper proposes a peach maturity detection algorithm based on YOLOV5 attention mechanism. The algorithm shows the whole process of management through data collection, model training, and model application. It adopts the prototype method and the object-oriented system development method. The external camera network configuration is used to connect the image display interface of the web display screen, and the server is used as the support and the bearer network is used as the system basis. Through the experimental results, it is found that the new algorithm proposed in this paper has obvious advantages compared with other comparison algorithms, and the experimental results more precise.