Research on the Method of Intelligent Generation of Landscape Design Based on AttnGAN
Abstract
The image generation algorithm in artificial intelligence brings new solutions to the drawing of landscape maps, thus solving the problems of insufficient diversity and longtime consumption in landscape design. The research aims to establish an intelligent landscape design model using deep learning algorithms to improve design efficiency and the diversity of landscape schemes. The study adopts an improved attention generative adversarial network to generate the approximate structure and content of the landscape, introduces a stable diffusion model to fill in details and textures, and thus generates landscape images with high realism and diversity. The results showed that the improved attention generative adversarial network generated landscape hard maps with an initial score of 341 and soft maps with an initial score of 339. The drawing time of the research model was 1.9 hours, and the initial Frechet distance for generating landscape maps was 0.9. The results indicate that the research model has higher drawing efficiency and drawing quality compared to other models. The research results provide a new design aid tool for landscape design, which can effectively improve design efficiency and creativity.
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