import tensorflow as tf
import os
import tarfile
import requests

# inception模型下載地址
inception_pretrain_module_url = 'http://download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz'

# 模型儲存地址
inception_pretrain_module_dir = 'inception_model'
if not os.path.exists(inception_pretrain_module_dir):
    os.mkdir(inception_pretrain_module_dir)

# 獲取檔名，以及檔案路徑
 

filename = inception_pretrain_module_url.split('/')[-1]
filepath = os.path.join(inception_pretrain_module_dir, filename)

# 下載模型
if not os.path.exists(filepath):
    print('download', filename)
    r = requests.get(inception_pretrain_module_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)

# 解壓檔案
tarfile.open(filepath, 'r:gz').extractall(inception_pretrain_module_dir)

# 模型結構存放檔案
log_dir = 'inception_log'
if not os.path.exists(log_dir):
    os.mkdir(log_dir)

# classify_image_graph_def.pb為Google訓練好的模型
 

inception_graph_def_file = os.path.join(inception_pretrain_module_dir, 'classify_image_graph_def.pb')
with tf.Session() as sess:
    # 建立一個圖來存放google訓練好的模型
    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='')
        # 儲存圖的結構
        writer = tf.summary.FileWriter(log_dir, sess.graph)
        writer.close()