Aiming at the lack of digital inheritance and innovation technology of blue calico patterns of Chinese intangible cultural heritage, this paper proposes a method for generating blue calico patterns based on the improved stable diffusion (SD) model, which realizing the active generation of single and multiple blue calico patterns through text-to-image and image-to-image technology. For the problem that the blue calico pattern datasets is less and it is difficult to train a large model, a low-rank adaptation algorithm (LoRA) fine-tuning network with blue calico characteristics is trained by combining the stable diffusion model and the LoRA fine-tuning network. Aiming at the problem that the output of the stable diffusion model is random, the stable diffusion model is combined with the discriminative network to judge the generated images and filter out the texture images that are consistent with the characteristics of blue calico. The experimental results show that the new blue calico patterns with semantic information and picture characteristics can be generated by the key prompt words or pictures.