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The autoencoder converts an image to a reduced code then back to the original image. The idea is similar to lossy compression, but it's geared specifically for the dataset that it's trained on.

According to the defaults in the code, it uses float32 arrays of the following sizes:

  image: 144 x 256 x 3 = 110,592 
  code:  200
Note that the sequence of codes that the movie is converted to could possibly be further compressed.


This should be mentioned in the article, I was looking for a simple mathematical comparison.


Point taken! I have edited the article now, there has obviously been some confusion and was an oversight on my part not to have explained that properly.




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