Today, colorization is done by hand in Photoshop, a picture can take
up to one month to colorize. It requires extensive research. A face
alone needs up to 20 layers of pink, green and blue shades to get it
just right. But something changed this year when 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.
Try it now
Click this button to open a Workspace on FloydHub that will train this model.
Colorizing Black&White photos
Fascinated by Amir’s neural network, Emill reproduced it and documented the process in the famous blog post: Colorizing B&W Photos with Neural Networks. In this notebook we will reproduce Emil's work by using the Full Version of his experiments.
The middle picture is done with our neural network and the picture to the right is the original color photo - Image from the Blog
We will:
Preprocess the image data for this CV task
Build and train the colornet model using Keras and Tensorflow
Evaluate our model on the test set
Run the model on your own black&white and colored pictures!
Serve an interactive web page for your own model
You can easily spin up a serve job on FloydHub to demo your model through an
interactive web site. Just run the following command from workspace terminal or
your local machine:
floyd run --mode serve
You should be able to see the following page when visiting the FloydHub serve url: