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I love these so much! How did you direct the GAN to generate them?

• Yenrabbit 5y ago
  I made a prompt generator that creates descriptions like 'A biological illustration of an alien plant near sand, watercolor'. A model called CLIP gives a way to compare an image with a text prompt and then I can optimise the image to match the prompt
  • datameta 5y ago
    You've been able to get some interesting output! I've been playing with the following notebook: https://colab.research.google.com/drive/1oA1fZP7N1uPBxwbGIvOEXbTsq2ORa9vb https://colab.research.google.com/drive/1oA1fZP7N1uPBxwbGIvO... but my results are not quite so well put together as yours. What are some tweaks you've made to the model? I'd like to better understand what is going on under the hood.
    • Yenrabbit 5y ago
      The big difference is the model used to generate the images. VQGAN (which I use) tends to look a lot nicer to my eye than some of the other approaches.