Resize to 224×224 directly or resize to 256 ×256 then crop 224×224？
My images in training set are leaves like this.
enter image description here
Its size is 572*108 and my resnet network need 224×224 images as input.
I found most of the codes process the images with the second way(resize to 256 ×256 then crop 224×224) so I did that.
As a result,parts of my leaves were cut which may influence the effect of leaves classification.Like this:
enter image description here
The first way (resize to 256×256 directly) may keep more complete structure.Like this:
enter image description here
I am worrying that if choose the first way I will lose many training images since random crop 224×224 may generate more samples for training.
Which should I choose？

Running two experiments and compare their evalution results is the simplest solution.
A complete view is not neccessary for model to classify images, so as it to human. On the contrary, learning from cropped image normally can improve the generalization capacity of a model.
