"The Lost Boys" (2 images) using Colab notebook ClipBigGAN by eyaler with a modification to one line (for testing purposes) and 2 changed defaults. This notebook, unlike the original Big Sleep notebook, uses unmodified BigGAN code. Test results are in a comment.

This page summarizes the projects mentioned and recommended in the original post on /r/bigsleep
Artificial intelligence Deep Learning text-to-image generative-adversarial-networks multimodality

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  • big-sleep

    A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN. Technique was originally created by https://twitter.com/advadnoun

    • A class vector is necessary for BigGAN; BigGAN is a class-conditioned generator. For the original Big Sleep code, see the variable "params_other". Unmodified BigGAN (well, actually BigGAN-deep) uses 1128 parameters: 1000 for the class vector, and 128 for the noise vector. The original BigSleep modified the BigGAN code to have each of 32 BigGAN layers (well, actually not all of them) use its own set of 1128 parameters. I have concerns that doing this might make it statistically less likely to get the type of near-photorealistic images that BigGAN can produce.

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