Closed TyleRxYan closed 4 weeks ago
It first does a model upscale and then does an image rescale (usually downscale).
using say 4x_NMKD-superscale model on a 512x512 image, it will 1) 4x model upscale > 2048x2048 2) 50% image scale > 1024x1024
that node (and the hiresfix upscale method within the ttN sampler nodes) performs a similar process to the nodes between the two samplers here:
It first does a model upscale and then does an image rescale (usually downscale).
using say 4x_NMKD-superscale model on a 512x512 image, it will
- 4x model upscale > 2048x2048
- 50% image scale > 1024x1024
the pipeKSamplerSDXL is not quite like ttN hiresfixScale, the sample process is final stage, sorry I wasn't make it clear at first. If the progress like what you said, I think the problem is SDXL node
The same process happens inside the SDXL kSampler.
Are you using the upscale within the ksampler?
in that case the upscale occurs first before the re-sampling (in the example image that would be the same as the second ksampler with the previous upscaling)
The same process happens inside the SDXL kSampler.
Are you using the upscale within the ksampler?
in that case the upscale occurs first before the re-sampling (in the example image that would be the same as the second ksampler with the previous upscaling)
yeah, the upscale within the ksampler.
Here you are upscaling an empty latent - which is why this issue is happening.
The upscale is meant to be used after the initial sampling
A side note - If you're not using a refiner i'd recommend just using the regular pipeKsampler
I see, thank you for the patience.
How is this thing work? the function seems not work like simple tiled resample, also not upscale by model, I've keep get multiple objects in final image if I bump the rescale percent above 50.