def getModelWeightsAsDict():

 keras.backend.clear_session()
 tf.reset_default_graph()
 model = keras.applications.VGG19(input_shape=(IMAGE_SIZE,IMAGE_SIZE,3),include_top=False,weights='imagenet')

 with keras.backend.get_session() as sess:
 weights_dict = {}
 for i in range(len(model.layers)):
  weights_dict['layer_' + str(i)] = []
  for j in range(len(model.layers[i].weights)):
   weights_dict['layer_' + str(i)].append(sess.run(model.layers[i].weights[j]))
 tf.reset_default_graph()

 return weights_dict