Hopefully that will result in something. The author of nind-denoise was looking into that, too, but it didn’t get much interest from the darktable devs to move forward.
Rewriting nind-denoise in C to be integrated into darktable was also on the author’s to-do list, but looks like the author got better things to focus on 
There are a few reasons that pushed me to work on this script:
- not enough devs and interest: I’m not familiar with C/C++, and don’t know much about the internal architecture of darktable, can’t contribute to coding directly.
- I need an immediate solution to make use of the readily available nind-denoise, thus, hacking/injecting it into the workflow instead of integrating (thanks to the available darktable-cli).
- the darkroom needs to be responsive in real time, it’s already slightly laggy without a GPU. Whichever neural-network denoise integrated into DT will need to be on-demand or at export only, otherwise the UI will be unacceptably laggy (nind-denoise takes about 8-9 seconds for a 24MP RAF on my 8GB RTX3060)
- training data for different sensors/demosaics is still the biggest hurdle for FOSS as we don’t have budget for samples. Community contribution didn’t take off for the NIND dataset so far. Hopefully ONNX with the backing of big players will.
This stopgap solution is all I have at the moment, while waiting for a proper long-terms solution like ONNX 