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enhancementNew feature or requestNew feature or requesthelp wantedExtra attention is neededExtra attention is needed
Description
Started here and preliminary results are promising: https://github.com/wendlerc/latent_downscaling
First checkpoints: https://huggingface.co/wendlerc/latent-downscale-madebyollin-sdxl-vae-fp16-fix
Currently we have a 10% improvement on SDXL generated imagenet vs naive downscaling with image interpolation.
Nearest interpolation
b-4: 66.4 (88.6)
b-8: 60.3 (84.4)
Latent downscaler
b-4: 75.6 (94.1) [+9.2]
b-8: 72.2 (92.4) [+11.9]
VAE decode, image resize, VAE encode (~upper bound)
b-4: 84.2 (97.0)
b-8: 81.5 (96.3)
So there are still another 10% on the table. It would be nice to close this gap.
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enhancementNew feature or requestNew feature or requesthelp wantedExtra attention is neededExtra attention is needed