SwinIR VS image-super-resolution

003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pth

I was trying to get a new upscaler working, as someone pointed me to one that did a good job of preserving and creating new details: https://github.com/JingyunLiang/SwinIR

SwinIR: https://github.com/JingyunLiang/SwinIR

Upscalers that I use SwinIR https://github.com/JingyunLiang/SwinIR https://github.com/AUTOMATIC1111/stable-diffusion-webui (Use 'extras' tab for the upscaler function) Topaz Gigapixel AI https://www.topazlabs.com/gigapixel-ai

You could try out chaiNNer, it is a free local/offline application. There are a lot of (upscaling) models which you can download an use with it. You can for example try out SwinIR-L (link will start a model download) or any other model you like depending on your input images.

the relative attention bias can be made non-square in the original implementation, there is a parameter window_size, at 7, that is forced to (7,7) directly, but you can change it easily. https://github.com/JingyunLiang/SwinIR/blob/main/models/network_swinir.py

Use SwinIR medium model to upscale by 2 times. This will result in a video of 2048x1152.

Currently, I have already implemented the pretrained GAN model from here, however I am not yet satisfied with the results. Indeed, I will go with this one if there's no other option, but I was hoping maybe someone here can point me to a better direction. Thank you!