Applying Stylenet/Neural-Style

Once we have an image recognition CNN trained, we can use the network itself for some interesting data and image processing. Stylenet is a procedure that attempts to learn an image style from one picture and apply it to a second picture while keeping the second image structure (or content). This may be possible if we can find intermediate CNN nodes that correlate strongly with a style separately from the content of the image.

Getting ready

Stylenet is a procedure that takes two images and applies the style of one image to the content of the second image. It is based on a famous paper in 2015, A Neural Algorithm of Artistic Style (refer to the first bullet point under See also section). The authors found a property of some CNNs where intermediate layers exist that seem to encode the style of a picture and some encode the content of the picture. To this end, if we train the style layers on the style picture and the content layers on the original image, and back...