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I'm very new to all this so this question might not make sense, but am I right in the assumption that FID relies on some pretrained model to evaluate the difference between the "fake" and "real" folders? If so, I assume such a model was trained only on generic photo content, which will limit its efficiency for drawn pictures and anime in particular. Or just having a large enough "real" folder will be enough?
If not, do I have to fine-tune said model for this specific content or there are pretrained models for 2D images that I could use here?
The text was updated successfully, but these errors were encountered:
I'm very new to all this so this question might not make sense, but am I right in the assumption that FID relies on some pretrained model to evaluate the difference between the "fake" and "real" folders? If so, I assume such a model was trained only on generic photo content, which will limit its efficiency for drawn pictures and anime in particular. Or just having a large enough "real" folder will be enough?
If not, do I have to fine-tune said model for this specific content or there are pretrained models for 2D images that I could use here?
The text was updated successfully, but these errors were encountered: