QingmuDeng / Coloring-greyscale-images-in-Keras

Coloring B&W portraits with neural networks.

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Coloring B&W portraits with neural networks.

This is the code for my article "Coloring B&W portraits with neural networks"

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. Read the article to understand the context of the code.

Fusion Layer

Deploying the code on FloydHub

If you are new to FloydHub, do their 2-min installation, check my 5-min video tutorial or my step-to-step guide - it’s the best (and easiest) way to train deep learning models on cloud GPUs.

Once FloydHub is installed, use the following commands:

git clone https://github.com/emilwallner/Coloring-greyscale-images-in-Keras

Open the folder and initiate FloydHub.

cd Coloring-greyscale-images-in-Keras/floydhub
floyd init colornet

The FloydHub web dashboard will open in your browser, and you will be prompted to create a new FloydHub project called colornet. Once that's done, go back to your terminal and run the same init command.

floyd init colornet

Okay, let's run our job:

floyd run --data emilwallner/datasets/colornet/2:data --mode jupyter --tensorboard

Some quick notes about our job:

  • We mounted a public dataset on FloydHub (which I've already uploaded) at the data directory with --data emilwallner/datasets/colornet/2:data. You can explore and use this dataset (and many other public datasets) by viewing it on FloydHub
  • We enabled Tensorboard with --tensorboard
  • We ran the job in Jupyter Notebook mode with --mode jupyter
  • If you have GPU credit, you can also add the GPU flag --gpu to your command - this will make it ~50x faster

Go to your the Jupyter notebook under the Jobs tab on the FloydHub website, click on the Jupyter Notebook link, and navigate to this file: floydhub/Alpha version/alpha_version.ipynb. Open it and click shift+enter on all the cells. It's the same process for the beta_version.ipynb and the full_version.ipynb.

Gradually increase the epoch value to get a feel for how the neural network learns.

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Coloring B&W portraits with neural networks.

License:MIT License


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