Richard Zhang

Load them in python using numpy. They represent the points in the quantized ab space.

You'll have to convert the images to Lab colorspace, and do a 2d histogram to get the empirical probabilities p_tilde in Equation 4, which is "prior_probs.npy". The bin centers are...

We divide the ab-gamut into 10x10 bins. However, not all ab values are in-gamut (see Figure 2b in our paper: https://arxiv.org/pdf/1603.08511.pdf). We keep the bin centers which are in-gamut.

Thanks for looking into this. Yes I added some bins due to the soft-encoding. I don't have the exact procedure I used. However, if you have some extra ones, it's...

I used random crops (176 out of 256) and flipping in the original paper. It was trained in caffe, a long time ago now

Thanks for the question. I should add some documentation and examples eventually. But it is from this paper and is better documented in this repo: https://github.com/junyanz/interactive-deep-colorization.

Please refer to the papers and accompanying materials. Thanks!

The associated paper and presentation to this github repo are online: http://richzhang.github.io/colorization/

Sorry, I'm not sure what's going on here.

Took me 10.5 days on a Titan X PASCAL.