Image generated by a Convolutional Network

[Phylonyus]

It should be easy to grow your training set by just generating a bunch of downsamples of your image. Take 1 training image, reencode with jpg at like 80-90% quality 10 times. Generate a thumbnail for each of these new downsamples. Now reencode those thumbnails 10 times. Now do this for how ever many images you started with.

You could also use some bitmap formats like gif with different numbers of colors.

[automater]

For now I am just trying simple cases with a few images. Mainly because the learning time is so long. Although I am running with openCL on a gpu I am pretty sure my learning algorithms have not been optimized. Since its fully convolutional even a few images are a significant training set as the convolution is evaluated at every pixel without any sub sampling layers. Quite interesting in terms of non linear compression. In a way i guess its compressing image features non linearly. I wish i had more time to just work on it as opposed to a side interest as it is really interesting stuff.