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This application can run on the Atlas 200 DK or the AI acceleration cloud server to decode local MP4 files or RTSP video streams, predict the head poses in the face images in video frames, and send the results to the Presenter Server for storage and display.

The current application adapts to DDK&RunTime of 1.3.0.0 as well as 1.32.0.0 and later versions.

Before deploying this sample, ensure that:

• Mind Studio has been installed.
• The Atlas 200 DK developer board has been connected to Mind Studio, the cross compiler has been installed, the SD card has been prepared, and basic information has been configured.

You can use either of the following methods:

1. Quick deployment: visit https://github.com/Atlas200dk/faster-deploy.

   NOTE:

   • The quick deployment script can be used to quickly deploy multiple cases. Select sample-headposeestimation-python.
   • The quick deployment script automatically completes code download, model conversion, and environment variable configuration. To learn about the detailed deployment process, select the common deployment mode. Go to 2. Common deployment.

2. Common deployment: visit https://github.com/Atlas200dk/sample-README/tree/master/sample-headposeestimation-python.

   NOTE:

   • In this deployment mode, you need to manually download code, convert models, and configure environment variables. After that, you will have a better understanding of the process.

Note: If the HiAI library, OpenCV library, and related dependencies have been installed on the developer board, skip this step.

1. Configure the network connection of the developer board.

   Configure the network connection of the Atlas DK developer board by referring to https://github.com/Atlas200dk/sample-README/tree/master/DK_NetworkConnect.

2. Install the environment dependencies.

   Configure the environment dependency by referring to https://github.com/Atlas200dk/sample-README/tree/master/DK_Environment.

1. Go to the root directory where the headposeestimation-python application code is located as the Mind Studio installation user, for example, $HOME/sample-headposeestimation-python.

2. Run the deployment script to prepare the project environment, including configuring Presenter Server. Presenter Server is used to receive the data sent by the application and display the result through the browser.

   bash deploy.sh host_ip

   • host_ip: indicates the IP address of the Atlas 200 DK developer board.

   Command example:

   bash deploy.sh 192.168.1.2

   When the message Please choose one to show the presenter in browser(default: 127.0.0.1): is displayed, enter the IP address used for accessing the Presenter Server service in the browser. Generally, the IP address is that configured for the virtual NIC.

   Select the IP address used by the browser to access the Presenter Server service in Current environment valid ip list.

3. Start Presenter Server.

   Run the following command to start the Presenter Server program of the head pose estimation application in the background:

   bash start_presenter_server.sh

   NOTE:

   • Running this script will kill other Presenter Server processes on the server. If no process is running on the background, the message "presenter server not in process" is displayed. If a process is running in the background, the message "presenter server stop success" is displayed.
   • After the application is stopped, you can run the bash stop_present_server.sh command to stop Presenter Server.

   If the information shown in Figure 1 is displayed, the Presenter Server service has been started successfully.

   Figure 1 Starting the Presenter Server process
   

   Use the URL shown in the preceding figure to log in to Presenter Server. The IP address is that typed in Step 2 and the default port number is 7007. The following figure indicates that Presenter Server has been started successfully.

   Figure 2 Home page
   

   The following figure shows the IP address used by Presenter Server and Mind Studio to communicate with the Atlas 200 DK.

   Figure 3 IP address example
   

   In the figure:

   • The IP address of the Atlas 200 DK developer board is 192.168.1.2 (connected in USB mode).
   • The IP address used by Presenter Server to communicate with the Atlas 200 DK is in the same network segment as the IP address of the Atlas 200 DK on the UI Host server, for example, 192.168.1.223.
   • The following describes how to access the IP address (such as 10.10.0.1) of Presenter Server using a browser. Because Presenter Server and Mind Studio are deployed on the same server, you can access Mind Studio through the browser using the same IP address.

4. Parse local videos and RTSP video streams using the headposeestimation-python application.

   • To parse a local video, upload the video file to the host.

     For example, upload the video file headpose.mp4 to the /home/HwHiAiUser/sample directory on the host.

     NOTE:
     H.264 and H.265 MP4 files are supported. If an MP4 file needs to be edited, you are advised to use FFmpeg. If a video file is edited by other tools, FFmpeg may fail to parse the file.

   • If only RTSP video streams need to be parsed, skip this step.

1. Log in to the host side as the HwHiAiUser user in SSH mode on Ubuntu Server where Mind Studio is located.

   ssh HwHiAiUser@192.168.1.2

2. Go to the directory where the application code is stored as the HwHiAiUser user.

   cd ~/HIAI_PROJECTS/headposeestimationapp

3. Run the application.

   python main.py channel

   • channel: input video file name or RTSP stream address

   The following is a command example for running video files:

   python main.py /home/HwHiAiUser/sample/crowd.mp4

   The following is a command example for running RTSP video streams:

   python main.py rtsp://192.168.2.37:554/cam/realmonitor?channel=1&subtype=0

   NOTE:
   You can press Ctrl+C to stop the application.

4. Use the URL displayed upon the start of the Presenter Server service to log in to Presenter Server.

   Wait for Presenter Agent to transmit data to the server. Click Refresh. When there is data, the icon in the Status column for the corresponding channel changes to green, as shown in Figure 4.

   Figure 4 Presenter Server page
   

   NOTE:

   • The Presenter Server supports a maximum of 10 channels at the same time (each presenter_view_app_name parameter corresponds to a channel).
   • Due to hardware limitations, each channel supports a maximum frame rate of 20 fps. A lower frame rate is automatically used when the network bandwidth is low.

5. Click a link in the View Name column, for example, video in the preceding figure, and view the result.