Creating a DeepDream network

Another interesting application of CNNs is DeepDream, a computer vision program created by Google [8] that uses a CNN to find and enhance patterns in images. The result is a dream-like hallucinogenic effect. Similar to the previous example, we are going to use a pretrained network to extract features. However, in this case, we want to “enhance” patterns in images, meaning that we need to maximize some functions. This tells us that we need to use a gradient ascent and not a descent. First, let’s see an example from Google gallery (available at https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/generative/deepdream.ipynb) where the classic Seattle landscape is “incepted” with hallucinogenic dreams such as birds, cards, and strange flying objects.

Google released the DeepDream code as open source (available at https://github.com/google/deepdream), but we will use a simplified example...