input shape of convolutional neural network in keras
It will throw an error. You can resize you images with cv2.resize() or you can put the right input shape in your cnn layer and then put a maxpooling layer to reduce the number of parameters.
I am trying to build a image classifier using cnn. My images are of (256,256) pixel size. 
What will happen if i train the cnn by setting the input shape as (64,64) or (128,128), since (256,256) will take a lot of time to process?