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This study introduces a design transformation model for AI-generated Chinese traditional architectural images (SD Lora&Canny) based on Stable Diffusion (SD). By integrating parameterization techniques such as Low-Rank Adaptation (Lora) and edge detection algorithms (Canny), the model achieves precise restoration of the architectural form, color elements, and decorative symbols in Chinese traditional architecture. Using the Beijing Drum Tower as the experimental subject, statistical analysis software (SPSS V28.0) was employed to conduct a quantitative evaluation and comparative analysis of architectural images generated by the DALL-E, MidJourney, SD, and SD Lora&Canny models. The results demonstrate that the SD Lora&Canny model significantly outperforms traditional generation tools in restoration accuracy and visual fidelity. Finally, this study applied the SD Lora&Canny model to create the digital cultural product AR Drum and Bell Tower Fridge Magnet, showcasing its practical application in digital cultural creation and verifying its innovative potential in the digital preservation and transmission of Chinese traditional architecture.
Lu et al. (Sun,) studied this question.
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