Target detection method based on YOLO-Terse network and storage medium

The invention discloses a target detection method based on a YOLO-Terse network. The method comprises the steps of obtaining a to-be-detected image containing a to-be-detected target; inputting the to-be-detected image into a pre-trained YOLO-Terse network, and determining the category to which the to-be-detected target belongs and the position of the to-be-detected target in the to-be-detected image according to the features of the to-be-detected image, wherein the YOLO-Terse network is formed by adopting hierarchical and channel-level pruning on the basis of the YOLOv3 network and guiding the network to recover by combining knowledge distillation. According to the invention, layer pruning, sparse training, channel pruning and knowledge distillation processing are carried out on the YOLOv3, optimized processing parameters are selected, the simplified YOLO-Terse network is obtained, the size of the network is greatly reduced, most redundant calculation is eliminated, the target detection speed based on the network is greatly increased, and the detection precision can be maintained.