Tensorflow学习教程------下载图像识别模型inceptionV3

# coding: utf-8
 
import tensorflow as tf
import os
import tarfile
import requests
 

#inception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:
    #创建一个图来存放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()