【摘要】 针对压铸件缺陷检测的数据集难以收集、检测效率较低以及工作环境较差等问题，开发了基于YOLOX模型的压铸件缺陷检测软件。用自开发软件的数据增强模块对原始数据集进行增强，解决了压铸件缺陷数据集不充裕的问题；随后将YOLOX算法的Darknet53结构替换为ShuffleNetv2-plus结构，使得利用YOLOX模型检测压铸件缺陷的平均检测精度由原模型的86.51%提升至89.19%，提升了YOLOX模型识别压铸件缺陷的准确率。更多还原

【Abstract】 Owing to the difficulty in defect detection of die-casting, lower detection efficiency and poor working environment, a defect detection software for die casting products based on YOLOX model was developed, and the original data set was enhanced by the data enhancement module in the software, solving the problem of the lack of data set.Then, the Darknet53 structure of YOLOX was skillfully replaced by ShuffleNetv2-plus, and finally improved the average detection accuracy of die-casting part defect based on YOLOX model detection from 86. 51% of the original model to 89. 19%, which greatly improves the recognition precision of die-casting defects by YOLOX model.更多还原