Environmental Landscape Art Design Based on Visual Neural Network Model in Rural Construction

Lun Wang, Yiwen He
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Abstract

Abstract As the resources of social development continue to tilt to the countryside, the speed of rural construction continues to accelerate. In recent years, because of the higher quality of lifestyles, the demand of rural environment landscape art has gradually increased. In order to assist rural construction and improve the artistic quality of its environmental landscape, this paper proposes an environmental landscape art design method based on a visual neural network model. Firstly, the Swin Transformer text encoder is used to characterise the landscape art demand in rural construction. Then, the text feature vector of landscape art demand is input into the GAN model to generate the image content of rural construction. Finally, to better evaluate the landscape art level of the above methods in this paper, we propose an evaluating method for the landscape designing tasks. We conduct the experiments and achieve the FID value of 15.23, which can demonstrate that our method can effectively carry out an environmental landscape design for rural construction and simplify the process of rural construction. The landscape design evaluation method can evaluate the environmental landscape design accurately by the accuracy of over 80 %, and further improve and optimise the acceptance link of rural construction.
基于视觉神经网络模型的乡村建设环境景观艺术设计
随着社会发展的资源不断向农村倾斜,农村建设的速度不断加快。近年来,由于生活品质的提高,对乡村环境景观艺术的需求逐渐增加。为了辅助乡村建设,提高乡村环境景观的艺术品质,本文提出了一种基于视觉神经网络模型的环境景观艺术设计方法。首先,利用Swin Transformer文本编码器对乡村建设中的景观艺术需求进行表征。然后,将景观艺术需求的文本特征向量输入GAN模型,生成乡村建设的图像内容。最后,为了更好地评价上述方法的景观艺术水平,本文提出了一种景观设计任务的评价方法。我们进行了实验,得到了FID值为15.23,可以证明我们的方法可以有效地进行乡村建设的环境景观设计,简化了乡村建设的过程。该景观设计评价方法能够以80%以上的准确率对环境景观设计进行准确评价,进一步完善和优化乡村建设验收环节。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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