In this paper, we propose a data enhancement method based on dual-domain constrained generative adversarial network for the problem of scarcity of defective image data of small industrial targets. The data is enhanced by structure-texture dual-domain extension and adversarial generative network, which effectively improves the accuracy of the defect classifier. Experiments show that the method can significantly improve the performance of industrial defect detection and has practical value.