Aiming at the problems of high misdetection rate and poor accuracy in the localization of codepoints,a circular codepoint localization method fusing improved YOLOv7 and UNet is proposed.In the first stage,the improved YOLOv7 is used to detect the location of coding points.The improved YOLOv7 firstly introduces DCN-v2 deformable convolution into the ELAN module to improve the feature extraction ability.Secondly,the CBAM attention mechanism is embedded into the backbone network to make the network pay more attention to the target features.Then,Focal-EloU loss is used to improve the convergence speed.Finally,OD-Cat is constructed to replace the ConCat module to improve the network detection accuracy.Module to replace the ConCat module to improve the network detection accuracy.After extracting the ROI of each circular coding point,the center contour of the coding point is segmented by UNet in the second stage, and then the center of the coding point is fitted using the least squares method.The experimental results show that the improved model improves the precision by 6.33%and the mean average precision(mAP)by 5.76%over the original YOLOv7.The proposed localisation method verifies that it can accurately locate the central ellipse contour of the coded point under complex environments such as noise,insufficient brightness or exposure,and is robust in practical industrial vision measurements.