import caffe
import numpy as np

MEAN_PROTO_PATH = 'mean.binaryproto'        # 待转换的pb格式图像均值文件路径
MEAN_NPY_PATH = 'mean.npy'             # 转换后的numpy格式图像均值文件路径

blob = caffe.proto.caffe_pb2.BlobProto()      # 创建protobuf blob
data = open(MEAN_PROTO_PATH, 'rb' ).read()     # 读入mean.binaryproto文件内容
blob.ParseFromString(data)             # 解析文件内容到blob

array = np.array(caffe.io.blobproto_to_array(blob))# 将blob中的均值转换成numpy格式，array的shape （mean_number，channel, hight, width）
mean_npy = array[0]                # 一个array中可以有多组均值存在，故需要通过下标选择其中一组均值
np.save(MEAN_NPY_PATH ,mean_npy)

import numpy as np

MEAN_NPY_PATH = 'mean.npy'

mean = np.ones([3,256, 256], dtype=np.float)
mean[0,:,:] = 104
mean[1,:,:] = 117
mean[2,:,:] = 123

np.save(MEAN_NPY, mean)

import numpy as np

mean_npy = np.load(MEAN_NPY_PATH)
mean = mean_npy.mean(1).mean(1)