# coding: UTF-8

#博客链接：https://blog.csdn.net/White_Idiot/article/details/78816850

#https://blog.csdn.net/m0_37870649/article/details/79465917

#下载IInception_V3模型，读取模型，保存模型的图结构

import tensorflow as tf

import os

import tarfile

import requests

import glob

import os.path

import random

import numpy as np

from tensorflow.python.platform import gfile

"""

# 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 = 'D:/tmp/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('D:/tensorflow_models/inception-2015-12-05', 'classify_image_graph_def.pb')

with tf.Session() as sess:

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='Inception_V3')

writer = tf.summary.FileWriter(log_dir, sess.graph) #保存图的结构

#writer = tf.train.SummaryWriter(log_dir, sess.graph)

writer.close()