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README
Apache-2.0

中文|English

该案例仅仅用于学习,打通流程,不对效果负责,不支持商用。

车辆检测

开发者将本Application部署至Atlas 200 DK上实现对本地mp4文件或者RTSP视频流进行解码,对视频帧中的车辆及其属性进行预测,生成结构化信息发送至Server端进行保存、展示的功能。

当前分支中的应用适配1.32.0.0及以上版本的DDK&RunTime

前提条件

部署此Sample前,需要准备好以下环境:

  • 已完成Mind Studio的安装。
  • 已完成Atlas 200 DK开发者板与Mind Studio的连接,交叉编译器的安装,SD卡的制作及基本信息的配置等。

部署

可以选择如下快速部署或者常规方法部署,二选一即可:

  1. 快速部署,请参考: https://gitee.com/Atlas200DK/faster-deploy

    说明:

    • 该快速部署脚本可以快速部署多个案例,请选择videoanalysiscar案例部署即可。
    • 该快速部署脚本自动完成了代码下载、模型转换、环境变量配置等流程,如果需要了解详细的部署过程请选择常规部署方式。转 2. 常规部署
  2. 常规部署,请参考: https://gitee.com/Atlas200DK/sample-README/tree/master/sample-videoanalysiscar

    说明:

    • 该部署方式,需要手动完成代码下载、模型转换、环境变量配置等过程。完成后,会对其中的过程更加了解。

编译

  1. 打开对应的工程。

    以Mind Studio安装用户在命令行中进入安装包解压后的“MindStudio-ubuntu/bin”目录,如:$HOME/MindStudio-ubuntu/bin。执行如下命令启动Mind Studio

    ./MindStudio.sh

    启动成功后,打开sample-videoanalysiscar工程,如图1所示。

    图 1 打开sample-videoanalysisperson工程

  2. 在src/param_configure.conf文件中配置相关工程信息。

    图 2 配置文件路径

    该配置文件默认配置内容如下:

    remote_host=192.168.1.2
    presenter_view_app_name=video
    video_path_of_host=/home/HwHiAiUser/car.mp4
    rtsp_video_stream=
    • remote_host:配置为Atlas 200 DK开发者板的IP地址。
    • presenter_view_app_name: 用户自定义的在PresenterServer界面展示的View Name,此View Name需要在Presenter Server展示界面唯一,只能为大小写字母、数字、“_”的组合,位数3~20。
    • video_path_of_host:配置为HOST侧的视频文件的绝对路径。
    • rtsp_video_stream:配置为RTSP视频流的URL。

    视频文件配置示例如下:

    remote_host=192.168.1.2
    presenter_view_app_name=video
    video_path_of_host=/home/HwHiAiUser/car.mp4
    rtsp_video_stream=

    Rtsp视频流配置示例如下:

    remote_host=192.168.1.2
    presenter_view_app_name=video
    video_path_of_host=
    rtsp_video_stream=rtsp://192.168.2.37:554/cam/realmonitor?channel=1&subtype=0

    说明:

    • 参数remote_host和presenter_view_app_name必须全部填写,否则无法通过build。
    • 注意所填参数不用使用“”。
    • 参数video_path_of_host和rtsp_video_stream必须至少填写一项。
    • 当前RTSP视频流只支持rtsp://ip:port/path格式,如果需要使用其它格式的url,需要把video_decode.cpp中的IsValidRtsp函数去除,或者直接返回true,跳过正则表达式匹配。
    • 本样例中提供的RTSP流地址不可以直接使用。如果需要使用RTSP,请在本地使用live555或其它方式制作RTSP视频流,并且可以在VLC中播放。然后将本地制作好的RTSP视频流的URL填入配置文件的相应参数中,即可运行。
    • 当前已经按照配置示例配置默认值,请按照配置情况自行修改。
  3. 执行deploy脚本, 进行配置参数调整及第三方库下载编译 打开Mind Studio工具的Terminal,此时默认在代码主目录下,执行如下命令在后台指执行deploy脚本,进行环境部署。如图 执行deploy脚本所示。

    图 3 执行deploy脚本

    说明:

    • 首次deploy时,没有部署第三方库时会自动下载并编译,耗时可能比较久,请耐心等待。后续再重新编译时,不会重复下载编译,部署如上图所示。
    • deploy时,需要选择与开发板通信的主机侧ip,一般为虚拟网卡配置的ip。如果此ip和开发板ip属于同网段,则会自动选择并部署。如果非同网段,则需要手动输入与开发板通信的主机侧ip才能完成deploy。
  4. 开始编译,打开Mind Studio工具,在工具栏中点击Build > Build > Build-Configuration。如图4所示,会在目录下生成build和run文件夹。

    图 4 编译操作及生成文件

    须知:
    首次编译工程时,Build > Build为灰色不可点击状态。需要点击Build > Edit Build Configuration,配置编译参数后再进行编译。

  5. 启动Presenter Server。

    打开Mindstudio工具的Terminal,在应用代码存放路径下,执行如下命令在后台启动Video Analysiscar应用的Presenter Server主程序。如图 启动PresenterServer所示。

    bash run_present_server.sh

    图 5 启动PresenterServer

    • 当提示“Please choose one to show the presenter in browser(default: 127.0.0.1):“时,请输入在浏览器中访问Presenter Server服务所使用的IP地址(一般为访问Mind Studio的IP地址)。

      图6所示,请在“Current environment valid ip list“中选择通过浏览器访问Presenter Server服务使用的IP地址,并输入存储视频解析数据的路径。

      图 6 工程部署示意图

    • 当提示“Please input a absolute path to storage video analysis data:“时,请输入Mind Studio中的绝对路径用于存储视频解析数据,此路径Mind Studio用户需要有读写权限,若此路径不存在,脚本会自动创建。

    图7所示,表示presenter_server的服务启动成功。

    图 7 Presenter Server进程启动

    使用上图提示的URL登录Presenter Server,IP地址为图6中输入的IP地址,端口号默为7005,如下图所示,表示Presenter Server启动成功。

    图 8 主页显示

    Presenter Server、Mind Studio与Atlas 200 DK之间通信使用的IP地址示例如下图所示:

    图 9 IP地址示例

    • Atlas 200 DK开发者板使用的IP地址为192.168.1.2(USB方式连接)。
    • Presenter Server与Atlas 200 DK通信的IP地址为UI Host服务器中与Atlas 200 DK在同一网段的IP地址,例如:192.168.1.223。
    • 通过浏览器访问Presenter Server的IP地址本示例为:10.10.0.1,由于Presenter Server与Mind Studio部署在同一服务器,此IP地址也为通过浏览器访问Mind Studio的IP。
  6. 车辆检测应用支持解析本地视频和RTSP视频流。

    • 如果需要解析本地视频,需要将视频文件传到Host侧。

      例如将视频文件car.mp4上传到Host侧的“/home/HwHiAiUser/“目录下。

      说明:
      支持H264与H265格式的MP4文件,如果MP4文件需要剪辑,建议使用开源工具ffmpeg,使用其他工具剪辑的视频文件ffmpeg工具可能不支持解析。

    • 如果仅解析RTSP视频流,本步骤可跳过。

运行

  1. 运行车辆检测应用程序

    在Mind Studio工具的工具栏中找到Run按钮,点击Run > Run 'sample-videoanalysiscar',如图10所示,可执行程序已经在开发板执行。

    图 10 程序运行示意图

  2. 使用启动Presenter Server服务时提示的URL登录 Presenter Server 网站。

    说明:
    车辆检测应用的Presenter Server最多支持2个 presenter_view_app_name 同时显示。

    页面左侧树结构列出了视频所属app name以及通道名,中间列出了抽取的视频帧大图以及检测出的目标小图,点击下方小图后会在右侧列出详细的推理结果、评分。

    本应用支持车辆属性检测,包括车辆品牌、车辆颜色的识别和车牌号码识别。

    说明:
    车牌号码识别的网络模型,是通过程序自动生成的车牌作为训练集图片训练的,不是使用真实车牌图片训练的。所以该模型在识别真实车牌号码时准确度比较低,如果需要较高的准确度的模型,请自己搜集真实车牌图片作为训练集并训练。

后续处理

  • 停止车辆检测应用

    视频程序分析完之后会自动退出,如图11所示。

    图 11 Video Analysiscar应用程序运行结束

  • 停止Presenter Server服务

    Presenter Server服务启动后会一直处于运行状态,若想停止车辆检测应用对应的Presenter Server服务,可执行如下操作。

    以Mind Studio安装用户在Mind Studio所在服务器的命令行中执行如下命令查看车辆检测应用对应的Presenter Server服务的进程。

    ps -ef | grep presenter | grep video_analysis_car

    ascend@ascend-HP-ProDesk-600-G4-PCI-MT:~/sample-videoanalysiscar$ ps -ef | grep presenter | grep video_analysis_car
    ascend 3655 20313 0 15:10 pts/24?? 00:00:00 python3 presenterserver/presenter_server.py --app video_analysis_car

    如上所示 3655 即为车辆检测应用对应的Presenter Server服务的进程ID。

    若想停止此服务,执行如下命令:

    kill -9 3655

  • 重启车辆检测应用时注意点

    重新启动车辆检测应用时请确保以下条件满足任意一个,否则会报错:

    1. 请确保视频解析数据存储路径中内容已经清空。

      例如:视频解析数据存储路径为:\$HOME/videocar_storage/video,其中:$HOME/videocar_storage是启动Presenter Server时配置的“Please input a absolute path to storage video analysis data”的值,video为param_configure.conf配置文件中参数presenter_view_app_name的值。

      满足此条件情况下,无需重启Presenter Server,直接重新执行**Run > Run 'sample-videoanalysiscar'**运行应用程序即可。

    2. 视频解析数据存储路径中如果已有数据且不想删除,可以修改param_configure.conf配置文件中presenter_view_app_name参数的值,然后在Mind Studio界面中重新执行Build > Rebuild,再执行**Run > Run 'sample-videoanalysiscar'**即可。

      param_configure.conf配置文件中参数presenter_view_app_name的值如下所示。

      满足此条件情况下,无需重启Presenter Server。

    3. 若重新启动Presenter Server,再运行车辆检测应用,在启动Presenter Server时请修改存储视频解析的数据的路径(不与之前存储路径重复)。

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简介

开发者将本Application部署至Atlas 200 DK或者AI加速云服务器上实现对本地mp4文件或者RTSP视频流进行解码,对视频帧中的车辆并对其属性进行预测,生成结构化信息发送至Server端进行保存、展示的功能 展开 收起
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