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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。

人脸检测

开发者可以将本application部署至Atlas 200DK上实现对摄像头数据的实时采集、并对视频中的人脸信息进行预测的功能。

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,请选择人脸检测案例部署即可。
    • 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-facedetection

    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-facedetection工程,如图 打开facedetection工程所示。

    图 1 打开facedetection工程

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

    图 配置文件路径所示。

    图 2 配置文件

    该配置文件默认配置内容如下:

    remote_host=192.168.1.2
    data_source=Channel-1
    presenter_view_app_name=video
    • remote_host:配置为Atlas 200 DK开发者板的IP地址。
    • data_source : 配置摄像头所属Channel,取值为Channel-1或者Channel-2,查询摄像头所属Channel的方法请参考Atlas 200 DK用户手册中的“如何查看摄像头所属Channel”。
    • 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,位数至少1位。

    说明:

    • 三个参数必须全部填写,否则无法通过编译。
    • 注意参数填写时不需要使用“”符号。
    • 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Mindstudio工具,在工具栏中点击Build > Build > Build-Configuration。如图 编译操作及生成文件所示,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Mind Studio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Face Detection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 工程部署示意图所示,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。

    图 6 工程部署示意图

    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 工程部署示意图操作时输入的IP地址,端口号默为7007,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

    其中:

    • 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。

运行

  1. 运行Face Detection程序。

    在Mind Studio工具的工具栏中找到Run按钮,点击Run > Run 'sample-facedetection',如图 程序已执行示意图所示,可执行程序已经在开发者板运行。

    图 10 程序运行示例

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

    等待Presenter Agent传输数据给服务端,单击“Refresh“刷新,当有数据时相应的Channel 的Status变成绿色,如下图所示。

    图 11 Presenter Server界面

    说明:

    • Face Detection的Presenter Server最多支持10路Channel同时显示,每个 presenter_view_app_name 对应一路Channel。
    • 由于硬件的限制,每一路支持的最大帧率是20fps,受限于网络带宽的影响,帧率会自动适配为较低的帧率进行展示。
  3. 单击右侧对应的View Name链接,比如上图的“video”,查看结果,对于检测到的人脸,会给出置信度的标注。

后续处理

  • 停止Face Detection应用

    Face Detection应用执行后会处于持续运行状态,若要停止Face Detection应用程序,可执行如下操作。

    单击图 停止Face Detection应用所示的停止按钮停止Face Detection应用程序。

    图 12 停止Face Detection应用

    图 Face Detection应用已停止所示应用程序已停止运行

    图 13 Face Detection应用已停止

  • 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Face Detection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所在服务器中的命令行中执行如下命令查看Face Detection应用对应的Presenter Server服务的进程。

    ps -ef | grep presenter | grep face_detection

    ascend@ascend-HP-ProDesk-600-G4-PCI-MT:~/sample-facedetection$ ps -ef | grep presenter | grep face_detection
    ascend    7701  1615  0 14:21 pts/8    00:00:00 python3 presenterserver/presenter_server.py --app face_detection

    如上所示 7701 即为face_detection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 7701

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简介

开发者可以将本application部署至Atlas 200DK上实现对摄像头数据的实时采集、并对视频中的人脸信息进行预测的功能。 展开 收起
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