TensorFlow(十四):谷歌图像识别网络inception-v3下载与查看结构
上代码:
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\' # inception_pretrain_model_url = \'http://download.tensorflow.org/models/inception_v4_2016_09_09.tar.gz\' #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\') # inception_graph_def_file = os.path.join(inception_pretrain_model_dir, \'inception_v4.ckpt\') 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()
结构:
打开cmd,进入inception_log目录:执行:tensorboard –logdir=\’C:\Users\FELIX\Desktop\tensor学习\inception_log\’查看结构。
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