下载inception v3 google训练好的模型并解压08-3

 

# -*- coding: UTF-8 -*-

import tensorflow as tf
import os
import tarfile
import requests

#模型下载地址
inception_pretrain_model_url='http://download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz'

#模型存放地址
inception_pretrain_model_dir="inception_model"
if not os.path.exists(inception_pretrain_model_dir):
    os.makedirs(inception_pretrain_model_dir)

#获取文件名以及文件路径
filename=inception_pretrain_model_url.split('/')[-1]
filepath=os.path.join(inception_pretrain_model_dir, filename)

#下载模型
if not os.path.exists(filepath):
    print("download:", filename)
    r=requests.get(inception_pretrain_model_url, stream=True)
    with open(filepath, 'wb') as f:
        for chunk in r.iter_content(chunk_size=1024):
            if chunk:
                f.write(chunk)
print("finish: ",filename)
#解压文件
tarfile.open(filepath, 'r:gz').extractall(inception_pretrain_model_dir)

#模型结构存放文件
log_dir='inception_log'
if not os.path.exists(log_dir):
    os.makedirs(log_dir)

#classify_image_graph_def.pb为google训练好的模型
inception_graph_def_file=os.path.join(inception_pretrain_model_dir, 'classify_image_graph_def.pb')
with tf.Session() as sess:
    #创建一个图来保存google训练好的模型
    with tf.gfile.FastGFile(inception_graph_def_file, 'rb') as f:
        graph_def=tf.GraphDef()
        graph_def.ParseFromString(f.read())
        tf.import_graph_def(graph_def, name='')
    #保存图的结构
    writer=tf.summary.FileWriter(log_dir, sess.graph)
    writer.close()