Random experiments with generative machine learning models.
LOOKING GLASS V1.1
First up, we have Looking Glass, notebook link:
https://colab.research.google.com/drive/11vdS9dpcZz2Q2efkOjcwyax4oob6N40G
This uses both an input image and input text to generate multiple images file. There weren’t many parameters to play with but the input image and text made major differences in the output image. You can adjust the number of training epochs to change the similarity between images.
Trial #1
Flavor Text: Blood flows from ancient text
Image Name: 01608
Epochs: 50
Images Generated: 9
Image
Output Images
Output Images
Output Images
Output Images
Output Images
Output Images
FLESH DIGRESSIONS
For the next set of experiments I used the “Flesh Digressions” colab notebook link:
https://colab.research.google.com/github/dvschultz/ml-art-colabs/blob/master/flesh_digressions.ipynb
I produced three different video outputs using three different .pkl files they can be found at the link below.
https://drive.google.com/drive/folders/1TtgUHAHH6mdXHeO12wQWWp7_Ev4VLxLn?usp=sharing
DISCO DIFFUSION
I also tried a purely text to image model called “disco-diffusion”.
my input was the following:
“I’ve been crawling on my belly” Tool Lyric
“I think drugs have done some good things for us” Bill Hicks Quote
“prayed like a martyr dusk till dawn” Tool Lyric
“somniferous almond eyes” Tool Lyric
“blue color scheme” Descriptor
Output Image
For a lot of the following work I used seed images generated with a notebook created by Jeramy Torman link:
https://colab.research.google.com/drive/1Zny3nZwzkGqzVd-PBQaEK48w9HC2SaL_?usp=sharing