Gimp and neural networks
Matching Paint Job
![© Lead Image © Orlando Rosu, 123RF.com © Lead Image © Orlando Rosu, 123RF.com](/var/linux_magazin/storage/images/issues/2016/193/deep-learning/po-24340-123rf-orlando_rosu_123rf-eimer_rote_farbe_mit_pinsel__resized.png/681197-1-eng-US/PO-24340-123RF-Orlando_Rosu_123RF-Eimer_rote_Farbe_mit_Pinsel__resized.png1_medium.png)
© Lead Image © Orlando Rosu, 123RF.com
Deep learning isn't just for industrial automation tasks. With a little help from Gimp and some special neural network tools, you can add color to your old black and white images.
Neural networks (NN) don't just play the traditional Japanese board game Go better than the best human player; they can also solve more practical tasks. For example, a project from Japan colors old black-and-white photos with the help of a neural network – and without asking the user to get involved with the image editing.
Researchers at Waseda University in Tokyo used a database that contains several objects to train a neural model to correctly recognize objects in images and fill them with appropriate color information. Using this model, the network then identifies the individual parts of the image, say, trees and people, and assigns matching colors.
The Waseda team presented this deep learning tool at the SIGGRAPH 2016 computer graphics conference [1]; you will find the code for their photo-coloring tool on Github [2]. The university website [3] provides a research paper on the subject [4], as well as some sample images.
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