This system is based on the popular deep learning algorithm—the YOLOv8 framework,and has trained an intelli-gent target detection model for identifying corn pests.A visual UI interface was developed using PyQt5,enabling image detection,video detection,and real-time camera tracking and recognition.The system can accurately detect 13 common types of corn pests in the Ningxia region,and the test results can be saved for subsequent data analysis.The corn pest detection system based on YOLOv8 is simple to use,with a user-friendly interface,good real-time performance,and high accuracy.It provides a solution for the identification of pests in corn cultivation in Ningxia,meets the real needs of farmers,and has potential for widespread application.
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