  I consider how to influence CycleGAN, image-to-image translation, by using
additional constraints from a neural network trained on art composition
attributes. I show how I trained the the Art Composition Attributes Network
(ACAN) by incorporating domain knowledge based on the rules of art evaluation
and the result of applying each art composition attribute to apple2orange image
translation.
