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VITA-Group / All-In-One-Underwater-Image-Enhancement-using-Domain-Adversarial-Learning

[CVPRW 2019] All-In-One Underwater Image Enhancement using Domain-Adversarial Learning

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fE_55.pth

T147 opened this issue · comments

commented

Hello!
I am interested in your "visualize.py ",but i need your fE_55.pth.
Meanwhile,i don't konw the 'name' in the file you made,becuse there's no 'nyu_uw_dataset'.
THANKS!

commented

Hi,
As you might have figured out, fE_86.pth and fI_86.pth are provided instead, which are simply the model after 86 instead of 55 epochs of training. And the dataset must be generated by running dataset_synthesis/nyu_uw_syn_script.py on a copy of this file (warning: 2.8GB).

I comment here also to note that this repo must be used to generate the plots instead of pip install ggplot.