win10环境搭建OpenVINO Toolkit并编译运行例程----（2）例程运行

运行例程是进行开发的第一步，本篇分享一下如何运行行人追踪的demo。
官网文档link
运行环境：
Windows10系统

关于工具包安装和例程编译参考上篇：

win10环境搭建OpenVINO Toolkit并编译运行例程----（1）openvino简介和win10环境搭建

Run Pedestrian Tracker C++ Demo

1. 进入annaconda环境 或者CMD

activate env_name
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2. 初始化openvino环境

cd C:\Program Files (x86)\IntelSWTools\openvino\bin
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setupvars.bat
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3. 进入编译生成的例程exe文件夹下

C:\Users\hp\Documents\Intel\OpenVINO\inference_engine_demos_build\intel64\Release
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4. 设置exe输入参数，文件下载。

./pedestrian_tracker_demo -h
InferenceEngine:
    API version ............ <version>
    Build .................. <number>
pedestrian_tracker_demo [OPTION]
Options:
    -h                           Print a usage message.
    -i "<path>"                  Required. Path to a video file or a folder with images (all images should have names 0000000001.jpg, 0000000002.jpg, etc).
    -m_det "<path>"              Required. Path to the Pedestrian Detection Retail model (.xml) file.
    -m_reid "<path>"             Required. Path to the Pedestrian Reidentification Retail model (.xml) file.
    -l "<absolute_path>"         Optional. For CPU custom layers, if any. Absolute path to a shared library with the kernels implementation.
          Or
    -c "<absolute_path>"         Optional. For GPU custom kernels, if any. Absolute path to the .xml file with the kernels description.
    -d_det "<device>"            Optional. Specify the target device for pedestrian detection (the list of available devices is shown below). Default value is CPU. Use "-d HETERO:<comma-separated_devices_list>" format to specify HETERO plugin.
    -d_reid "<device>"           Optional. Specify the target device for pedestrian reidentification (the list of available devices is shown below). Default value is CPU. Use "-d HETERO:<comma-separated_devices_list>" format to specify HETERO plugin.
    -r                           Optional. Output pedestrian tracking results in a raw format (compatible with MOTChallenge format).
    -pc                          Optional. Enable per-layer performance statistics.
    -no_show                     Optional. Do not show processed video.
    -delay                       Optional. Delay between frames used for visualization. If negative, the visualization is turned off (like with the option 'no_show'). If zero, the visualization is made frame-by-frame.
    -out "<path>"                Optional. The file name to write output log file with results of pedestrian tracking. The format of the log file is compatible with MOTChallenge format.
    -first                       Optional. The index of the first frame of video sequence to process. This has effect only if it is positive and the source video sequence is an image folder.
    -last                        Optional. The index of the last frame of video sequence to process. This has effect only if it is positive and the source video sequence is an image folder.
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根据上述输入参数，有3个必须输入的文件：

• -i 输入图像或视频地址
• -m_det Pedestrian Detection Retail model (.xml) 文件的地址
• -m_reid Pedestrian Reidentification Retail model (.xml) file.文件的地址

后两个的下载可以从open model zoo中下载对应openVINO工具包版本文件夹下的xml和bin文件。下载link

其中VPU的设备必须使用FP16版本的文件。

另外，使用chrome浏览器直接点击下载只能下载bin文件，对于xml文件只能浏览的情况我使用了wget命令获取下载：
下载FP32/person-detection-retail-0013.xml 命令行示例：

wget --no-check-certificate https://download.01.org/opencv/2019/open_model_zoo/R3/20190905_163000_models_bin/person-detection-retail-0013/FP32/person-detection-retail-0013.bin
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5. 运行
   根据最终参数的选择在exe所在路径下执行以下命令：

./pedestrian_tracker_demo -i <路径视频文件> \
                          -m_det <模型路径> /person-detection-retail-0013.xml \
                          -m_reid <模型路径> /person-reidentification-retail-0031.xml \
                          -d_det GPU
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该演示使用OpenCV来显示结果帧，并将检测结果渲染为边界框，曲线（用于显示轨迹）和文本。

运行截图后期补充。