Aiming at the low efficiency and stability of the traditional two-dimensional bar code positioning algorithm in complex industrial and logistics transportation scenarios, a two-dimensional bar code positioning algorithm based on lightweight CenterNet network is proposed, a lightweight CenterNet detection algorithm is proposed. In view of the size change of two-dimensional bar code in the actual situation, CSPDarknet53-tiny is used as the backbone network and modified SPP module is added to improve the accuracy of the network. The upsampling and detection head of CenterNet are lightweight transformed. 5 × 5 depth separable convolution is used to replace ordinary convolution. The change strategy of learning rate during training adopts cosine annealing learning rate to prevent over fitting. The experimental results show that the positioning accuracy is only 0. 64% lower than YOLOv4 tiny. It not only avoids the problems that the accuracy of the traditional algorithm is greatly affected by the background and the robustness is not strong, the real-time reasoning speed also reaches 124 fps, which can be better used for all kinds of two-dimensional bar code location under low hardware configuration.