In order to solve the problems of low accuracy and slow speed of detecting complex defects on the surface of mobile phone cover glass and the difficulty of deploying the detection technology on the applica-tion side,a fast detection method based on YOLOx-pro model is proposed.According to the optical properties of cover glass,design the lighting scheme and build the image acquisition system,combined with image en-hancement technology to enrich the defect samples.The YOLOx-tiny-based lightening model is used,and the CA attention mechanism is added to the main output part to strengthen the attention to the defective region.Introducing the spatial pooling pyramid SPPF and replacing the activation function with ReLU,which consti-tutes the Sim-SPPF module,acquires richer multi-scale information expression,and combines with specific training strategies to further improve the detection efficiency.The experimental results show that the YOLOx-pro model achieves a mAP of 85.73% and an FPS of 39.17 f/s,while the Params is only 10.58 M,which outperforms other mainstream algorithms.The model is deployed in the application software for actual tes-ting,and the results show that YOLOx-pro has good response speed and accuracy,and can achieve efficient detection of cover glass surface defects under real working conditions.
维普
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