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I am trying to use StyleGAN3 with an evolving dataset, my current logic is as follows:

  • Train for about half an hour
  • Regenerate dataset with added images
  • Resume training with --resume

For testing, I've been using the metfaces dataset and started out with around 100 images, adding about 50 new images to the dataset every half an hour.

Upon resuming the results gradually become very dark or very light.

I am training with parameters as suggested at stylegan3 github:

train.py --cfg=stylegan3-r --gpus=1 --batch=32 --gamma=2 --batch-gpu=8 --mirror=1

Any suggestions on how to go about training with a growing dataset?

Taavi
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1 Answers1

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100 images to start with is not enough and the network will collapse. Start with at least 1,000 images but preferably 10,000.

Vojtech Semecky
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