Towards the Evolution of Prompts with MetaPrompter

Abstract

The dissemination of open-source text-to-image generative models and the increasing quality of their output has led to a growth in interest in the field. The quality of the images greatly depends on the prompt used, i.e. a phrase that includes descriptive terms to be used as input on text-to-image model. However, choosing the right prompt is a complex task, often relying on a trial-and-error approach. In this paper, we introduce an evolutionary approach to prompt generation where users begin by creating a blueprint for what might be a candidate prompt and then initiate an evolutionary process to interactively explore the space of prompts encoded by the initial blueprint and according to their preferences. Our work is a step towards a more dynamic and interactive way to generate prompts that lead to a wide variety of visual outputs, with which users can easily obtain prompts that match their goals.