Development of intelligent recognition program for traffic signal lamps based on Yolov5
Traffic signal detection is an important auxiliary technology for intelligent vehicles to identify traffic environment.Existing algorithms can solve the problem of signal detection in a single intersection environment,but it is necessary to improve the accuracy and interference reliability of the algorithm in the complex traffic environment of intersections.Based on the application of one-stage target detection algorithm Yolov5,this paper realizes the automatic detection and recognition of traffic lights in multiple scenes.Labeling is used to annotate pictures,the data set is enhanced by mirroring,cropping,reversing,etc.,and the parameter adjustment experiment and iterative model training are continuously carried out.The target detection accuracy reaches 80%.
target detectionYolov5Labeling picture annotationmodel training
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