Fix tuple error, mentioned in some of the issues

[ankuPRK]

Summary

• We see some GitHub issues when some folks were trying to use the refinement step for non-fourier models. So we add a fix for that.
• (minor) We also correct a typo in the website link to Geomagical.com

Issues

#274
#167

Problem

In the lama-regular model, the latent feature is a single Tensor, while in lama-fourier and big-lama, the latent feature is a tuple of two tensors. In our refinement code, we assumed the feature to be a tuple.

Solution

This PR adds a function that adapts the feature appropriately. We can't just keep it as-it-is because when Pytorch optimizers (like Adam) don't take a tuple as input.

Visual Results

• Input Images
  
  

• Big LaMa (before and after refinement)
  
  
  
  

• LaMa-Fourier (before and after refinement, of course, parameters tuned to this model could make results even better)
  
  
  
  

• LaMa-Regular (the one on which refinement was failing)
  
  
  
  

[jf1957]

Summary

• We see some GitHub issues when some folks were trying to use the refinement step for non-fourier models. So we add a fix for that.
• (minor) We also correct a typo in the website link to Geomagical.com

Issues

#274 #167

Problem

In the lama-regular model, the latent feature is a single Tensor, while in lama-fourier and big-lama, the latent feature is a tuple of two tensors. In our refinement code, we assumed the feature to be a tuple.

Solution

This PR adds a function that adapts the feature appropriately. We can't just keep it as-it-is because when Pytorch optimizers (like Adam) don't take a tuple as input.

Visual Results

• Input Images
  
  
• Big LaMa (before and after refinement)
  
  
  
  
• LaMa-Fourier (before and after refinement, of course, parameters tuned to this model could make results even better)
  
  
  
  
• LaMa-Regular (the one on which refinement was failing)
  
  
  
  

Dear Author,

I would like to kindly ask you some questions regarding training on the CelebA dataset. Specifically, based on LaMa-Fourier, what small modifications or fine-tuning strategies could be applied to slightly improve the final performance metrics?

I am currently working on my undergraduate graduation thesis, and these suggestions would be extremely helpful to my research. I would sincerely appreciate it if you could share some advice or insights.

Thank you very much for your time and help.