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?