Comments (3)
Hi, I suggest increasing the number of --trained_stages
(default is 6) in general. This should already improve results for higher resolutions.
If this is not enough you can also increase the --lr_scale
(default is 0.1 - you could try 0.5).
Finally, it might be necessary to train for more iterations on higher stages/resolutions and/or adapt other hyperparameters (receptive field of the discriminator/generator, learning rate, etc).
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Thanks for your reply,I tried increase the --trained_stages and the lr_scale,but it might did't work,I want to know the --max_size and the --min_size should be setted to have some kind of proportional relationship?
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--min_size
should be left at some small value, so I wouldn't change it or at least not increase it. --min_size
and --max_size
do not need to have a proportional relationship, rather --max_size
and --trained_stages
should be somewhat proportional, i.e. the larger --max_size
the larger --trained_stages
should be.
How high did you set --trained_stages
to be? What exactly is the problem with the higher-resolution images? Is the global structure wrong or are there artifacts in the images?
from consingan.
Related Issues (20)
- Image Animation
- fine-tune error HOT 3
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