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This repository has been archived by the owner on Jan 7, 2025. It is now read-only.
In the training object, the default losses are MSE, binary cross-entropy, and MAE. Is this what the models are minimizing? If so, how can we make the losses the same as the super-resolution metrics? Why aren't they the super-resolution metrics like PSNR and perceptual loss?
The text was updated successfully, but these errors were encountered:
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In the training object, the default losses are MSE, binary cross-entropy, and MAE. Is this what the models are minimizing? If so, how can we make the losses the same as the super-resolution metrics? Why aren't they the super-resolution metrics like PSNR and perceptual loss?
The text was updated successfully, but these errors were encountered: