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Visually appealing product images are likely to positively impact online purchase behavior. This chapter presents a framework using Google Colab with Gemini and Vertex AI to create attractive product images, reducing design time and increasing personalization. Compared to models like Midjourney, it is more reliable by training on secondary and primary user data. Designers input simple text, and the AI generates a high-quality product image in seconds, which can be tailored iteratively. An example of bicycle design validated the output’s aesthetics and personalization. Improvement features include gender considerations and ergonomics. The model is fast, simple, customizable, and suitable for non-technical users, but still requires human input to fix imperfections and address risks.

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Developing a Framework for Using Generative AI in Product Design

  • 章节

  • 发表日期：

    2026年

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  • Tung Nhu Nguyen

摘要

Visually appealing product images are likely to positively impact online purchase behavior. This chapter presents a framework using Google Colab with Gemini and Vertex AI to create attractive product images, reducing design time and increasing personalization. Compared to models like Midjourney, it is more reliable by training on secondary and primary user data. Designers input simple text, and the AI generates a high-quality product image in seconds, which can be tailored iteratively. An example of bicycle design validated the output’s aesthetics and personalization. Improvement features include gender considerations and ergonomics. The model is fast, simple, customizable, and suitable for non-technical users, but still requires human input to fix imperfections and address risks.