3 ms·
First, you have to collect a few thousand images of the same thing (maybe more or less depending on how complex your thing is or how good the results should be)
by johndough 5y ago
First, you have to collect a few thousand images of the same thing (maybe more or less depending on how complex your thing is or how good the results should be). Then, you train a generative adversarial neural network on those images to generate new images. https://github.com/NVlabs/stylegan2-ada-pytorch https://github.com/NVlabs/stylegan2-ada-pytorch works quite well. https://github.com/NVlabs/stylegan3 https://github.com/NVlabs/stylegan3 is supposedly even better, but I did not try it yet.
- lkbm 5y agoThis is an excellent summary. Thanks! My follow-up question is whether anything will work with an M1 yet. I'm guessing nothing from NVlabs. :-)
- shmageggy 5y agoThose are implemented in pytorch which can use various backend including CPU-based ones. https://pytorch.org/docs/stable/backends.html https://pytorch.org/docs/stable/backends.html Whether or not it would be prohibitively slow is another question, however.
- hwers 5y agoI would suggest getting a colab pro account. If you only use it for a month that's only $10 but it's plenty for training lots of these models (maybe 1-3 days per dataset depending on resolution and dataset diversity). https://colab.research.google.com/github/dvschultz/ml-art-colabs/blob/master/Stylegan2_ada_Custom_Training.ipynb https://colab.research.google.com/github/dvschultz/ml-art-co...