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基于AI技术的花境设计应用分析

花匠小妙招
2024-11-23 03:40

基于AI技术的花境设计应用分析

基金项目:

河南省重点研发与推广专项“城镇化对农业景观中生态系统服务间关系的影响研究”（编号：222102320064）

Analysis of AI-Enabled Floral Design Applications

Author:

CUI Sixian

1. School of Architecture, Politecnico di Milano, Piacenza, Italia, 29121;
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ZHANG Yaowen

2. School of Architecture, North China University of Water Resources and Electric Power, Zhengzhou, Henan, China, 450000
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JIA Jie

2. School of Architecture, North China University of Water Resources and Electric Power, Zhengzhou, Henan, China, 450000
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WANG Xudong

2. School of Architecture, North China University of Water Resources and Electric Power, Zhengzhou, Henan, China, 450000
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摘要 | | 访问统计 | | | |

摘要:

人工智能（AI）在各个领域都展现出巨大的潜能，如何利用AI技术辅助风景园林领域正处于初步摸索与完善阶段。通过计算机视觉和机器学习算法，训练一种自动化的花境设计模型，以探索AI技术在花境设计领域中的应用。以河南省首届花境大赛——北龙湖湿地公园花境展为案例素材库，收集了大量的花境作品照片作为模型训练数据，利用计算机视觉算法对花境实景图像进行分析和特征提取；使用机器学习算法训练模型，根据语义分割图和输入的关键词生成新的花境设计方案。机器学习模型可以为不同类型的花境场景生成高质量和多样化的设计方案，并且可以识别和提取一些花卉植物特征，如植物种类、尺度、空间关系等。此外，对AI生成的花境配置方案效果进行了评价，验证AI技术在花境设计应用中的可行性及适用性。旨在为AI技术在植物景观设计领域的理论研究及设计实践应用提供创新研究视角及思路。

Abstract:

Artificial Intelligence (AI) has shown immense potential in various fields, and its utilization in landscape architecture is still in the early stages of exploration and refinement. An automated floral landscape design model has been developed by harnessing computer vision and machine learning, paving the way for AI applications in floral landscape design. As a case study, the North Long Lake Wetland Park floral exhibition from the first Henan Province Floral Landscape Competition was used as a reference material repository. An extensive collection of floral landscape photographs was gathered as training data for the model. Computer vision algorithms were employed to analyze and extract features from real-world floral landscape images. A machine learning model was trained to generate new floral landscape design concepts based on semantic segmentation maps and input keywords. This machine learning model can produce high-quality and diverse design proposals for various types of floral landscapes, while also identifying and extracting characteristics of floral plants, such as species, scale, and spatial relationships. Furthermore, the effectiveness of AI-generated floral layout proposals was evaluated to validate the feasibility and applicability of AI technology in floral landscape design. This research aims to provide innovative perspectives and insights for the theoretical research and practical application of AI technology in the field of plant landscape design.