Under the background of the digital era, Wuhu iron painting, as one of the traditional Chinese folk art forms, needs to undergo digital transformation for its artistic inheritance and innovative development. This paper explores the automated generation path of digital teaching resources for Wuhu iron painting, proposes an art style migration model based on the improved CycleGAN model, and uses the Kano model to analyze the demand level of digital teaching resources for Wuhu iron painting, so as to realize the automated generation of digital resources for Wuhu iron painting in line with the needs of teachers and the actual teaching. It is shown that compared with the original CycleGAN model, the SSIM and PSNR index values of the images generated by the improved CycleGAN model in this paper are improved by 11.61% and 1.53% on average, and the FID index value is decreased by 47.76% on average, meanwhile, the improved CycleGAN model performs better than CycleGAN in the retention of color features, which proves the effectiveness of this paper’s model in the migration of Wuhu iron painting art style. In addition, this paper constructs a demand model for digital teaching resources of Wuhu Iron Painting, which can be used as an important basis for the automated generation of teaching resources.
