  How to bridge generative procedural art and visual generative artificial
intelligence (AI) for visual content creation is an under-explored topic. On
the one hand, there are many cases where creative programmers can make use of
generative AI, including stylizing canvas content and creating new content
based on the existing styles of certain procedural art (style learning). On the
other hand, existing approaches don't support creative programmers to flexibly
leverage visual generative AI methods within the creative coding environment.
  In this work, we explore how to bridge generative procedural art creation and
visual generative AI (specifically diffusion models) by programming
functionalities integrated into the creative environment. Specifically, we want
to explore methodologies to condition/stylize art content and perform style
learning upon procedural art via accessible interactions for artists and
programmers.
  We proposed two methods: GenP5, a novel p5.js library enabling generative
procedural art creation with flexibly stylizing canvas content and conveniently
condition art creation with pre-determined patterns; and P52Style, an extended
library built upon p5.gui allowing flexible adjustment of art content and
leverage of visual generative AI for style learning tasks.
