How to colorize black & white photos with just 100 lines of neural network code

Earlier this year, Amir Avni used neural networks to troll the subreddit/r/Colorization -- a community where people colorize historical black and white images manually using Photoshop. They were astonished with Amir's deep learning bot. What could take up to a month of manual labour could now be done in just a few seconds. I was fascinated by Amir's neural network, so I reproduced it and documented the process. First off, let's look at some of the results/failures from my experiments (scroll to the bottom for the final result). Today, colorization is usually done by hand in Photoshop. In short, a picture can take up to one month to colorize. A face alone needs up to 20 layers of pink, green and blue shades to get it just right. This article is for beginners. Yet, if you're new to deep learning terminology, you can read my previous two posts here and here, and watch Andrej Karpathy's lecture for more background. I'll show you how to build your own colorization neural net in three steps. We'll build a bare-bones 40-line neural network as an "alpha" colorization bot.