How to reshape the res5c layer of ResNet (3D to 2D)?

Question

I extract the features of an image with ResNet of the 'res5c' layer, resulting of a numpy array of shape (2048, 14, 14)

I have trouble manipulating these dimensions. I understand there is 14*14 features of size 2048. I would like to iterate over to access every feature at a time.

Therefore, how I can reshape this to an array of (14*14, 2048) without mistakes and then easily iterate over it with a for loop?

Answer 1

You can read the features after net.forward():

feat = net.blobs['res5c'].data.cop() # copy to be on the safe side.

As you describe, feat is an np.array with shape = (2048, 14, 14).
You can reshape it:

feat.reshape((2048,-1)) # fix the first dimension to 2048, -1 set the number of features to match that of `feat`.

Now you can iterate over features:

for fi in xrange(feat.shape[1]):
    f = feat[:,fi] # get the fi-th feature
    # do somethinf to the feature f