Trained model from KAIR (40000_optimizerG.pth) gives error on testing about swinir HOT 6 CLOSED

Do you use the latest code? We have fixed the bug as follows in KAIR (see https://github.com/cszn/KAIR/blob/60ddfc0ffb320182c82f7c93f741615dd6a7033b/main_test_swinir.py#L176) and this repo

See more discussions here #20

from swinir.

Yes I am using latest code for SwinIR/main_test_swinir.py. It worked for other 2 models: 40000_G.pth and 40000_E.pth
However, 40000_optimizerG.pth is giving error.

from swinir.

Yes I am using latest code for SwinIR/main_test_swinir.py. It worked for other 2 models: 40000_G.pth and 40000_E.pth
However, 40000_optimizerG.pth is giving error.

The word "optimizer" in "40000_optimizerG.pth" means that it is an optimizer, not a model.
The optimizer is saved so that you can continue learning after a break.

"40000_G.pth" - is the model.
"40000_E.pth" - is the model using the EMA strategy.

The authors recommend using EMA - this model is more stable.

from swinir.

You only need the "40000_E.pth" (the EMA version of model) for testing.

"40000_G.pth" stores the original version of model (can also be used for testing, has similar performance as "40000_E.pth" for classical sr, but is inferior to "40000_E.pth" for GAN-based real-world image sr).

"40000_optimizerG.pth" only stores the optimizer information, no model parameters.

from swinir.

Thank you. Can you provide details on what is 4000_E? How does GAN came into the picture?

from swinir.

EMA strategy can make GAN training more stable. You can find some insights here.

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