I have tried to get the basic grasp of the following deep learning frameworks with python:

  1. Keras
  2. Pytorch
  3. Caffe

However, I have lately noticed that people in the computer vision community care less and less about Caffe as being somehow unpopular these days apart from its easy implementation and learning pace.

What are the pros and cons of Keras, PyTorch, and Caffe for computer vision? Which problems are they more suited for, with respect to one another?

I am not looking for answers such as "Keras is easier in my opinion". I am looking for facts or specific features that make one library more suited than the other for computer vision tasks.


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