A method for generating narratives by analyzing single images or image sequences is presented, inspired by the time immemorial tradition of Narrative Art. The proposed method explores the multimodal capabilities of GPT-4o to interpret visual content and create engaging stories, which are illustrated by a Stable Diffusion XL model. The method is supported by a fully implemented tool, called ImageTeller, which accepts images from diverse sources as input. Users can guide the narrative's development according to the conventions of fundamental genres - such as Comedy, Romance, Tragedy, Satire or Mystery -, opt to generate data-driven stories, or to leave the prototype free to decide how to handle the narrative structure. User interaction is provided along the generation process, allowing the user to request alternative chapters or illustrations, and even reject and restart the story generation based on the same input. Additionally, users can attach captions to the input images, influencing the system's interpretation of the visual content. Examples of generated stories are provided, along with details on how to access the prototype.

本文探讨了如何通过分析单幅图像或图像序列生成叙事，以填补传统叙事艺术与现代技术之间的空白。提出的新方法利用GPT-4o的多模态能力解读视觉内容，生成引人入胜的故事，同时介绍了一个名为ImageTeller的工具，用户可根据不同文学类型自定义故事发展。最显著的发现是，该工具提供了高度互动的用户体验，使用户能够实时调整故事内容和结构。 

通过图片想象的AI讲故事工具