In Keras' documentation for the InceptionResNetV2 model, it says the following:

input_shape: (...). It should have exactly 3 inputs channels, and width and height should be no smaller than 139.

I'm trying to figure out the reason behind the minimum size of 139px for this model, because I'm looking to train this model on smaller images (128px for starters).

I can't find any clues in the model's source code or in the paper which describes the model.

Assuming this number is not arbitrary, what is the reason behind this minimum size of 139px?

  • $\begingroup$ The idea behind using images of certain sizes are based on how the architecture has been implemented. The minimum size ensures the results that are achieved is good. $\endgroup$ – Nischal Hp Nov 16 '17 at 14:20
  • $\begingroup$ Thanks for your answer @NischalHp. I was wondering if there was an explanation for the specific minimum size in this model (139px). All input equal or larger than 139px is accepted by the model, what exactly in this specific model makes it (potentially) perform poorly for 138px or smaller sized input? $\endgroup$ – Robin Nov 16 '17 at 14:28

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