I have started a similar project and written about it in this post.
The idea is to train using pytorch and then run it on Rust wgpu shaders.
I found your post here and I like your approach. I was hoping to pick your brain a bit when it comes to neural architectures for demosaicing.
Would you mind sharing if you have done any more experimenting since your post and maybe give some thoughts around how you arrived at the architecture you used?
Do you have any general recommendations to me and others and have you given any thoughts to extending your architecture to include different CFA patterns?