1.TensorFlow安裝

安裝教程在CSDN上有很多文章，但最好依據官方教程，因為TensorFlow不斷更新，需要的CUDA、cudnn等版本也在變化。官方地址在GITHUB裡TensorFlow專案下可以找到安裝指南，https://www.tensorflow.org/install/。這裡我選擇的是Anaconda安裝，方便統一管理。
考慮到翻牆的原因，打不開官方網站的看這裡：

(1)Requirements to run TensorFlow with GPU support

• If you are installing TensorFlow with GPU support using one of the mechanisms described in this guide, then the following NVIDIA software must be installed on your system:

• CUDA® Toolkit 8.0. For details, see NVIDIA’s documentation Ensure that you append the relevant Cuda pathnames to the %PATH% environment variable as described in the NVIDIA documentation.
  The NVIDIA drivers associated with CUDA Toolkit 8.0.

• cuDNN v6.1. For details, see NVIDIA’s documentation. Note that cuDNN is typically installed in a different location from the other CUDA DLLs. Ensure that you add the directory where you installed the cuDNN DLL to your %PATH% environment variable.
  GPU card with CUDA Compute Capability 3.0 or higher. See

  NVIDIA documentation for a list of supported GPU cards.

• If you have a different version of one of the preceding packages, please change to the specified versions. In particular, the cuDNN version must match exactly: TensorFlow will not load if it cannot find cuDNN64_6.dll. To use a different version of cuDNN, you must build from source.

(2)Requirements to run TensorFlow with GPU support

• The Anaconda installation is community supported, not officially supported.
  Take the following steps to install TensorFlow in an Anaconda environment:
  Follow the instructions on the Anaconda download site to download and install Anaconda.
  Create a conda environment named tensorflow by invoking the following command:

C:> conda create -n tensorflow python=3.5 

• Activate the conda environment by issuing the following command:

C:> activate tensorflow
 (tensorflow)C:>  # Your prompt should change 

• Issue the appropriate command to install TensorFlow inside your conda environment. To install the CPU-only version of TensorFlow, enter the following command:

(tensorflow)C:> pip install --ignore-installed --upgrade tensorflow

• To install the GPU version of TensorFlow, enter the following command (on a single line):

(tensorflow)C:> pip install --ignore-installed --upgrade tensorflow-gpu

（3)安裝後日常使用時開啟shell視窗，我用的conEmu，啟用TensorFlow環境再執行。

activate tensorflow

2.下載 TensorFlow models

3.配置依賴庫

• 利用Anaconda安裝protobuf:

conda install protobuf

• 編譯Protobuf庫，在object_detection同級目錄開啟終端執行：

cd E:\TensorFlow\GitHub\models\research
protoc object_detection\protos\*.proto --python_out=.

• 在research目錄下執行：

python setup.py install

• 進入slim目錄執行：

python setup.py install

• 新增環境變數：

• 返回research目錄測試環境是否準備完畢：

python object_detection/builders/model_builder_test.py

若出現缺乏相關庫的提示，根據提示利用conda install安裝，若仍然失敗，重複(3)(4)

4.程式配置和執行

# What model to download.  
MODEL_NAME = 'ssd_mobilenet_v1_coco_11_06_2017'  
#MODEL_NAME = 'faster_rcnn_resnet101_coco_11_06_2017'
#MODEL_NAME = 'ssd_inception_v2_coco_11_06_2017'
MODEL_FILE = MODEL_NAME + '.tar.gz'  
DOWNLOAD_BASE = 'http://download.tensorflow.org/models/object_detection/'  

python --version

我的是3.5.4，所以我選擇：opencv_python-3.3.1-cp35-cp35m-win_amd64.whl
安裝：

pip install opencv_python-3.3.0-cp35-cp35m-win_amd64.whl

• 編寫視訊採集及目標檢測程式碼，執行

python webcamdetect.py

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