标签：flow html 识别 tar api rem com blank esc
1.环境ubuntu14.04.5
安装TensorFlow
官方文档：https://www.tensorflow.org/install/install_linux
sudo pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.0.1-cp27-none-linux_x86_64.whl
注意：后面的网址根据不同设置而不同：
1 Python 2.7 2 3 CPU only: 4 5 https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.0.1-cp27-none-linux_x86_64.whl 6 GPU support: 7 8 https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.0.1-cp27-none-linux_x86_64.whl 9 Note that GPU support requires the NVIDIA hardware and software described in NVIDIA requirements to run TensorFlow with GPU support. 10 11 Python 3.4 12 13 CPU only: 14 15 https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.0.1-cp34-cp34m-linux_x86_64.whl 16 GPU support: 17 18 https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.0.1-cp34-cp34m-linux_x86_64.whl 19 Note that GPU support requires the NVIDIA hardware and software described in NVIDIA requirements to run TensorFlow with GPU support. 20 21 Python 3.5 22 23 CPU only: 24 25 https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.0.1-cp35-cp35m-linux_x86_64.whl 26 GPU support: 27 28 https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.0.1-cp35-cp35m-linux_x86_64.whl 29 Note that GPU support requires the NVIDIA hardware and software described in NVIDIA requirements to run TensorFlow with GPU support. 30 31 Python 3.6 32 33 CPU only: 34 35 https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.0.1-cp36-cp36m-linux_x86_64.whl 36 GPU support: 37 38 https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.0.1-cp36-cp36m-linux_x86_64.whl
我选择了相当于：python2.7 纯CPU
自动安装无误，若有安装失败，可能是网络问题，重新执行一遍试试。
也有可能是若干依赖没有装好：先把 各种依赖都安一遍
下载神经网络模型：http://download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz
1 mkdir model 2 tar -xf archive_name.tar -C model/
下载代码：https://codeload.github.com/tensorflow/models/zip/master
1 unzip models-master.zip 2 cd models-master/tutorials/image/imagenet/
其中的classify_image.py是我们实现物体识别的主代码
接下来做几个测试
1 classify_image.py --model_dir /home/usr/model --image_file /home/usr/model/cropped_panda.jpg 2 classify_image.py --model_dir /home/usr/model --image_file /home/usr/model/testkb.jpg 3 classify_image.py --model_dir /home/usr/model --image_file /home/usr/model/testmous.jpg
1 giant panda, panda, panda bear, coon bear, ailuropoda melanoleuca (score = 0.89107) 2 computer keyboard, keypad (score = 0.64016) 3 mouse, computer mouse(score = 0.89453)
标签：flow html 识别 tar api rem com blank esc
原文地址：http://www.cnblogs.com/pandaroll/p/6881613.html
