  Generative text-to-image models, which allow users to create appealing images
through a text prompt, have seen a dramatic increase in popularity in recent
years. However, most users have a limited understanding of how such models work
and it often requires many trials and errors to achieve satisfactory results.
The prompt history contains a wealth of information that could provide users
with insights into what have been explored and how the prompt changes impact
the output image, yet little research attention has been paid to the visual
analysis of such process to support users. We propose the Image Variant Graph,
a novel visual representation designed to support comparing prompt-image pairs
and exploring the editing history. The Image Variant Graph models prompt
differences as edges between corresponding images and presents the distances
between images through projection. Based on the graph, we developed the
PrompTHis system through co-design with artists. Besides Image Variant Graph,
PrompTHis also incorporates a detailed prompt-image history and a navigation
mini-map. Based on the review and analysis of the prompting history, users can
better understand the impact of prompt changes and have a more effective
control of image generation. A quantitative user study with eleven amateur
participants and qualitative interviews with five professionals and one amateur
user were conducted to evaluate the effectiveness of PrompTHis. The results
demonstrate PrompTHis can help users review the prompt history, make sense of
the model, and plan their creative process.
