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Evaluating first stage autoencoders

Open leod opened this issue 2 years ago • 3 comments

First of all, thank you so much for making this high-quality repository as well as pretrained models publicly available! This is highly useful for exploring your research.

I am currently training first stage autoencoders on a custom dataset (SoundCloud images) and am struggling with evaluating these models (other than with the loss values logged in TensorBoard). I plan to compare the performance of initializing the autoencoder weights randomly vs. fine-tuning one of your pretrained autoencoders.

I would prefer to calculate rFID, PSNR, and PSIM the same way as you did for your results table. Could you please provide a hint as to how you evaluate your autoencoders? Is there some other repository or toolkit that you rely on?

leod avatar Apr 20 '22 09:04 leod

@leod Hi, I want to do the same evaluation. Have you figured it out how to do that? Thanks!

wtliao avatar Feb 07 '23 11:02 wtliao

@wtliao @leod @rromb FYI, I added some evaluation scripts for first stage autoencoders https://github.com/CompVis/latent-diffusion/pull/353/files

Eurus-Holmes avatar Feb 29 '24 05:02 Eurus-Holmes

@wtliao @leod @rromb FYI, I added some evaluation scripts for first stage autoencoders https://github.com/CompVis/latent-diffusion/pull/353/files

It is really appreciate! I will try and discuss with you further!

wtliao avatar Mar 01 '24 11:03 wtliao