import caffe

import numpy as np

mean = np.load('mean.npy').mean(1).mean(1)
image_dims = (224, 244)
model = 'deploy.prototxt'
weights = 'resnet-50.caffemodel'

net = caffe.Classifier(model, weights, image_dims=image_dims, mean=mean, raw_scale=255, channel_swap=[2, 1, 0])
nb = net.blobs
for ctr, name in enumerate(nb):
  print(ctr, name, nb[name].data.shape)