I released the dragon and pointed @arrendek towards VQGN+CLIP deep learning image generation. He has been experimenting on qt3 user names. It’s like Frankenstein, but with 2D art.
If you want to try this yourself, here’s what you need to do:
You can do less insane things, should you choose. Here is “A charcoal sketch of me standing on a lawn throwing a ball to a black dog.”
Any prompt requests? I should add that the results are more interesting when there are a lot of adjectives and sometimes longer strings/paragraphs work well.
Sure, but you’ll need to use venv and create different environments for the image generation and upscaling because they use different versions of python.
python generate.py -p "Dingus standing up in a movie theater pumping his fist and shouting NICE | trending on Artstation" -s 448 448 -o "dingus.png"
“Trending on Artstation” is my go-to for getting better results. I need to explore the other models and modifiers. In general, images look far more chaotic if you don’t use a modifier.
