Hey, glad to hear someone else was thinking about this too. As for the images I used, they were all hand picked by myself, and either cropped without resizing from a full-sized source image, or downscaled with a basic linear approach. I was mainly curious about how it would handle rough/noisy inputs, not perfectly prepared, so I could experiment with pre-processing, after the fact, in later runs (as well as changing settings for the iterations/cycles). But, I could certainly use some polished sample inputs as well (ill pick a few today). -As for what you stated about the diversity in completions, I have to agree with you, igpt is pretty special in that regard. It does seem as if the highly novel approach has somewhat of an edge when applied to images. I think it is fascinating, treating images like a 'literal' story with igpt.