Closed saddam213 closed 1 year ago
Upon further investigation into implementation it seems the max sample size for upscale is 128
128 -> 512
For images over 128 we are going to have to split into tiles, upscale and reassemble
512 -> [128, 128, 128, 128] -> [512, 512, 512, 512] -> 2048
there is an upscaler in onnx named SwinIR, which included some models in it like RealSR [best upscaler i ever used] it is a very small onnx model that can be found here: https://huggingface.co/rocca/swin-ir-onnx/tree/main it will be great if it be included as another model for ur upscaler
there is an upscaler in onnx named SwinIR, which included some models in it like RealSR [best upscaler i ever used] it is a very small onnx model that can be found here: https://huggingface.co/rocca/swin-ir-onnx/tree/main it will be great if it be included as another model for ur upscaler
Thanks for this link dude.
I have been trying for weeks to get a diffusion upscaler to work, but never got a good result I tried this one and it worked first time, plus you don't have to tile the images, I can just give it a 512 image and it spits out a 2048
However these type of upscalers do not work like diffusion ones, e.g no steps, prompt needed, so I need to think of a good way to add this to the codebase
I will add the x2 and x4 versions along with smaller ones like Face Upscalers etc
u r welcome, thanks!
Closing PR, new implementation needed
Add a new pipeline for image up-scaling
vae
folder and novae_encoder/vae_decoder
foldersWill be using the following model for development https://huggingface.co/ssube/stable-diffusion-x4-upscaler-onnx