## extract weights and biases from caffemodel to numpy arrays
## require pycaffe interface

import caffe
import numpy as np

def caffemodel2npy(defFile, modelFile):
  net = caffe.Net(defFile, modelFile, caffe.TEST)
  newModel = {}
  for p in net.params:
    newModel[p] = {}
    if len(net.params[p]) != 2:
      print 'error in params', p
      continue
    for idx, name in enumerate(['weight', 'bias']):
      newModel[p][name] = net.params[p][idx].data
      print 'extract', p, name, net.params[p][idx].data.shape
  return newModel