Research on Instrument Positioning and Detection Based on Lightweight Improved YOLOv7 Network
In order to efficiently and accurately detect the dial of industrial pointer instrument,a lightweight YOLOv7 target detection network algorithm is studied.According to the various shape features of the target in the instrument image,the network convolution kernel is improved by using the depth separable convolution instead of the common convolution to reduce the number of parameters and improve the detection accuracy and speed of the network model.Experiments show that the mAP index of the light-weight and improved YOLOv7 network is increased by 3.03%,the number of parameters and model size are decreased by 35.1%,the accuracy is increased by 4.61%,and the detection speed is increased by 21.3%,realizing the high efficiency and high precision instrument detection.
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