Application of interactive AI system based on image recognition in rural landscape design

Rural landscape design plays a critical role in improving the quality of rural environment and residents' quality of life. However, the relevant material library is not sufficient and some original styles need to be preserved, making the design work difficult. The research aims to construct an intelligent and interactive rural landscape design system to improve design efficiency and optimize design outcomes. The study uses attention generative adversarial networks to enrich elements in rural landscape design, improving the problem of inaccurate mapping. In addition, a stable diffusion model is introduced to optimize the quality of its landscape mapping. The findings denoted that the intelligent landscape design system designed in the study had an 8-fold reduction in drawing time compared to designer drawings. The generated rural landscape plan was evaluated in detail, including image quality, element diversity, similarity, and referenceability, with a total score of 99.3 points. The overall evaluation score for the overall image performance was 93.9 points, both of which were superior to other intelligent landscape design systems. From this, it can be seen that the research system not only has efficient design efficiency but also meets the requirements for the image quality of the landscape plan drawn and adaptability to the environment. The study proposes a new landscape design tool that contributes to the environmental improvement of rural landscapes.