目的 调研当前校园视觉标识系统的新兴需求,研究利用图像生成式人工智能扩散模型辅助设计的方法,开发出能够融合学校IP且高效率的视觉标识辅助设计方法。方法 首先,调研分析了将学校IP形象融入视觉标识设计的需求;其次,基于这些需求,制订了人工智能辅助视觉标识系统设计的整体方案;最后,研究了利用扩散模型辅助校园视觉标识系统设计的具体方法,包括智能算法原理的分析、风格模型的训练、图像生成控制变量的调整、生成测试、后期的合成和评估等步骤。结果 通过这一研究,利用扩散模型的Lora模型训练技术,成功发展出一套能够为融合学校IP形象的校园标识辅助设计的模式,实现了设计实践过程的创新。结论 校园视觉标识系统的设计应采用一种既高效又能够融合学校IP形象的模式,与传统设计流程相比,利用人工智能扩散模型进行视觉标识的辅助设计无疑能更好地满足这些需求。
Abstract
The work aims to investigate the emerging needs of visual signage systems in current campuses, explore the method of utilizing image generative artificial intelligence diffusion models to assist in design, and develop an efficient visual signage design assistance method that integrates school IP. Firstly, the needs for integrating school IP images into visual signage design were analyzed. Secondly, based on these needs, an overall scheme for AI-assisted visual signage system design was formulated. Finally, the specific methods for utilizing diffusion models to assist in the design of campus visual signage systems were studied, including the analysis of intelligent algorithm principles, the training of style models, the adjustment of image generation control variables, generation testing, post-processing synthesis, and evaluation. Through this research, with the Lora model training technology of diffusion models, a mode able to assist in the design of campus logos integrating school IP images was successfully developed, realizing innovation in the design practice process. The design of campus visual signage systems should adopt a mode that is both efficient and capable of integrating school IP images. Compared with traditional design processes, utilizing AI diffusion models for visual signage assistance design undoubtedly better meets these needs.
关键词
校园标识系统 /
学校IP形象 /
人工智能 /
扩散模型
Key words
campus signage system /
school IP image /
artificial intelligence /
diffusion model
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