# Reason for square images in deep learning

Most of the advanced deep learning models like VGG, ResNet, etc. require square images as input, usually with a pixel size of $$224x224$$.

Is there a reason why the input has to be of equal shape, or can I build a convnet model with say $$100x200$$ as well (if I want to do facIAL recognition for example and I have portrait images)?

Is there increased benefit with a larger pixel size, say $$512x512$$?