AI & Art with Cali Rezo #3: Analytical models

⬅️ #2: Generative models | #4: Explainability and uncertainty of AI models ➡️

In the last article, we focused on VAEs and GANs for image generation. This time, we’ll talk about analysing images and trying to identify classes. We will also take this opportunity to talk about the usual traps and limits of AI classification.

To create analytical models, Cali and I decided on a set of “painting series” for our different examples and then trained some models to group the images into these classes.

In total, we had 9 groups for 3 selection criteria:

As you can see, some images can be assigned to multiple groups, as long as the groups are not for the same criterion; for example, a circular shape is both a “circular” and a “1 stroke” shape. Our goal was to study how well-known classification algorithms could perform on this dataset, each model training focusing on one criterion at a time.

Note: in this article (and in Cali’s work in general, by the way!), when we talk about “eyes” we refer to areas of white that are completely enclosed into black. This is why most circular shapes are considered to be in…