下载需要练习的inception模型并看起流程.py

# -*- coding: utf-8 -*-
"""
Created on Tue Jun 26 14:07:39 2018

@author: Administrator
"""

import tensorflow as tf  
import os  
import tarfile  
import requests  
  
#inception_v3模型下载  
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("finishn: ", 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:  
    #创建一个图来存放google训练好的模型，load graph 具体实现方法看下面的链接  
    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()