I haven’t found that much useful information regarding the different layers in the Caffe deep learning model provided by Google. Some layers seem to emphasize dogs, others interesting patterns, or contours. Inspired by this amazing page I set out to create my own guide to the layers. So, here goes. For each layer listed, I have iterated the image five times, to bring out the characteristics (everything beyond five iterations seems not to change things too much, only deepen them)
I haven’t had time to render all possible layers yet, and actually ran into a crash which I haven’t yet sorted out, so expect this page to grow further over time.
The starting image was this lovely selfie to the right (apologies for pretentious pose)
Filters and categories
Contour and texture
Swirls and fur
|inception_3a/3x3_reduce||Tobacco-like cell structure. Or something.|
Everything above “inception_4b” takes us into high-level dream territory. This is where dogs, buildings, birds, insects etc. are found most prominent. I may add a more detailed section to this eventually, but note that it will be more dependent on the training data and thus more likely to suggest different things based on the types of images the net “knows”. A few interesting things can be noted with the current dataset (bvlc_googlenet) as seen below.
When we reach inception_4e it’s a free-for all, and every layer above adds complexity. It is interesting to note that each different layer still brings out different aspects of the image. I may add thumbnails to all variantions later.
Original images (C) Mikael Lundgren 2015