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This allows to create latent spaces filled with perlin-based noise that can actually be used by the samplers.
Hey this is a great idea. I'm trying to integrate it into imaginairy
I'm getting these spots in the sd15 images when I use the perlin noise. Is this something you've encountered?
I wonder if I need to use a different VAE
If I change the clamp from
result = torch.clamp(result, -5, 5)
to
result = torch.clamp(result, -4, 4)
it significantly reduces the spots but I'm not sure what other negative consequences there might be.
Very interesting experimentation.
I was able to get crispy 1024x1024 images like this one
I didn't tried to SD upscale it yet though because I tried to modify some settings to get different resolutions/ratios but failed everytime.
Is there a way to do it or (for now) we're stuck to 1024x1024 images ?
I'm still testing it out but It looks like the perlin-based noise is working great for larger images.
Would it be possible to change the functions to request a "subset" of noise at a higher resolution? For example, lets say I wanted to generate a larger version of one of the flowers below. This would help enable some interesting "infinite zoom" applications.
I believe it should be possible, and I'll look into it more, but just checking in to see if you have any pointers.
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