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# -*- 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()