I am interested in a recent blog post by Google that describes the use of NN to make art.
I am particularly interested in one technique:
'In this case, we simply feed the network an arbitrary image or photo and let the network analyze the picture. We then pick a layer and ask the network to enhance whatever is detected. Each layer of the network deals with features at a different level of abstraction, so the complexity of features we generate depends on which layer we choose to enhance. For example, lower layers tend to produce strokes or simple ornament-like patterns, because those layers are sensitive to basic features such as edges and their orientations.'
The post is http://googleresearch.blogspot.co.uk/2015/06/inceptionism-going-deeper-into-neural.html?m=1.
My question: the post describes this as a 'simple' case--is there an open-source implementation of an NN that could be used for this purpose in a relatively plug-and-play process? For just the technique described, does the network need to be trained?
No doubt for other techniques mentioned in the paper one needs a network already trained on a large number of images, but for the one, I've described is there already some kind of open-source network layer visualization package?