My next little project: An A.I colorization model in perceptilabs 
Instead of writing i decided to make a video where i breafly explain how the model works here: https://youtu.be/3j1sARksK1k
The result is far from perfect as i’m using the same app for inference as for the super-resolution model, which splits the whole image into chunks. Also the dataset is rather small at about 6000 imgs for the task. It does still do well on some images
That’s fun! Glad to see you are still pursuing practical modelling (I’ve been deep in papers on trying to work out how to make the best possible models: beyond overfitting and into interpolation. Robert and I have been debating (loosely) what else is going on when e.g. there is weight decay. I am thinking about experiments now…
It’s doing rather well for such a small dataset - it’s interesting to think about why the same thing can be coloured so differently: the fence that is mostly wood coloured except for the section with a strong blue tint. (Is that a shadow on the road or a change in the stone texture/pattern).
If you can work out why same thing ends up a different colour/shade depending which segment it’s in I think it will be rather revealing/impressive!
Working in RGB space or tempted to try out HSV/HSL? 
I think the problem with things being differently colored is the way i do the inference here. I was lazy and just used the same app as for the upscaling which uses a “rolling window” approach. And so the model color each window separately. I guess maybe it could do better with a larger dataset though…
I’m working in YUV colorspace so the model only needs to predict 2 channels instead of 3 (RGB)
YUV… so you predict the red and blue projections… and recalculate the luma from them?
Not sure whether/when this could be done in PL, but saw this for GAN face restoration - thought you might be interested! Linked in post
The luma is not recalculated, I just take the input luma channel and stack it together with the predicted red and blue projections Then it’s converted to RGB to match the target.
Ah, I guess it can be done in PL, but as GAN is removed for now it would be a bit cumbersome, i think 