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Tutorial: Continuous video recording and playback

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Alternatively, check out topics under Create video applications in the service.

Note

Azure Video Analyzer has been retired and is no longer available.

Azure Video Analyzer for Media is not affected by this retirement. It is now rebranded to Azure Video Indexer. Click here to read more.

In this tutorial, you'll learn how to use Azure Video Analyzer to perform continuous video recording (CVR) to the cloud and play back that recording. This capability is useful for scenarios such as safety and compliance where there is a need to maintain an archive of the footage from a camera for days, weeks, months or even years or alternatively you could specify the retention period for the video being recorded. Retention policy defines how many days of video should be stored (for example, the last 7 days), you can learn more about it in the Manage retention policy article.

In this tutorial you will:

  • Set up the relevant resources.
  • Examine the code that performs CVR.
  • Run the sample code.
  • Examine the results, and view the video.

If you don't have an Azure subscription, create an Azure free account before you begin.

Suggested pre-reading

Read these articles before you begin:

Prerequisites

Prerequisites for this tutorial are:

  • An Azure account that includes an active subscription. Create an account for free if you don't already have one.

    Note

    You will need an Azure subscription where you have access to both Contributor role, and User Access Administrator role. If you do not have the right permissions, please reach out to your account administrator to grant you those permissions.

  • Visual Studio Code, with the following extensions:

    Tip

    When you're installing the Azure IoT Tools extension, you might be prompted to install Docker. Feel free to ignore the prompt.

  • .NET Core 3.1 SDK.

Set up Azure resources

Deploy to Azure

The deployment process will take about 20 minutes. Upon completion, you will have certain Azure resources deployed in the Azure subscription, including:

  1. Video Analyzer account - This cloud service is used to register the Video Analyzer edge module, and for playing back recorded video and video analytics.
  2. Storage account - For storing recorded video and video analytics.
  3. Managed Identity - This is the user assigned managed identity used to manage access to the above storage account.
  4. Virtual machine - This is a virtual machine that will serve as your simulated edge device.
  5. IoT Hub - This acts as a central message hub for bi-directional communication between your IoT application, IoT Edge modules and the devices it manages.

In addition to the resources mentioned above, following items are also created in the 'deployment-output' file share in your storage account, for use in quickstarts and tutorials:

  • appsettings.json - This file contains the device connection string and other properties needed to run the sample application in Visual Studio Code.
  • env.txt - This file contains the environment variables that you will need to generate deployment manifests using Visual Studio Code.
  • deployment.json - This is the deployment manifest used by the template to deploy edge modules to the simulated edge device.

Tip

If you run into issues creating all of the required Azure resources, please use the manual steps in this quickstart.

Concepts

As explained in this article, a video analyzer pipeline lets you define:

  • Where media should be captured from.
  • How it should be processed.
  • Where the results should be delivered.

To accomplish CVR, you need to capture the video from an RTSP-capable camera and continuously record it to a video resource. This diagram shows a graphical representation of that pipeline.

Video Analyzer pipeline for CVR

In this tutorial, you'll use an edge module built using the Live555 Media Server to simulate an RTSP camera. Inside the pipeline, you'll use an RTSP source node to get the live feed and send that video to the video sink node, which records the video to your Video Analyzer account. The video that will be used in this tutorial is a highway intersection sample video.

In this tutorial, you will:

  1. Setup your development environment.
  2. Deploy the required edge modules.
  3. Create and deploy the live pipeline.
  4. Interpret the results.
  5. Clean up resources.

Set up your development environment

Get the sample code

  1. Clone the AVA C# samples repository.

  2. Start Visual Studio Code, and open the folder where the repo has been downloaded.

  3. In Visual Studio Code, browse to the src/cloud-to-device-console-app folder and create a file named appsettings.json. This file contains the settings needed to run the program.

  4. Browse to the file share in the storage account created in the setup step above, and locate the appsettings.json file under the "deployment-output" file share. Click on the file, and then hit the "Download" button. The contents should open in a new browser tab, which should look like:

    {
    "IoThubConnectionString" : "HostName=xxx.azure-devices.net;SharedAccessKeyName=iothubowner;SharedAccessKey=XXX",
    "deviceId" : "avasample-iot-edge-device",
    "moduleId" : "avaedge"
}

    The IoT Hub connection string lets you use Visual Studio Code to send commands to the edge modules via Azure IoT Hub. Copy the above JSON into the src/cloud-to-device-console-app/appsettings.json file.

Connect to the IoT Hub

  1. In Visual Studio Code, set the IoT Hub connection string by selecting the More actions icon next to the AZURE IOT HUB pane in the lower-left corner. Copy the string from the src/cloud-to-device-console-app/appsettings.json file.

    Note

    You might be asked to provide Built-in endpoint information for the IoT Hub. To get that information, in Azure portal, navigate to your IoT Hub and look for Built-in endpoints option in the left navigation pane. Click there and look for the Event Hub-compatible endpoint under Event Hub compatible endpoint section. Copy and use the text in the box. The endpoint will look something like this: Endpoint=sb://iothub-ns-xxx.servicebus.windows.net/;SharedAccessKeyName=iothubowner;SharedAccessKey=XXX;EntityPath=<IoT Hub name>

  2. In about 30 seconds, refresh Azure IoT Hub in the lower-left section. You should see the edge device avasample-iot-edge-device, which should have the following modules deployed:

    • Edge Hub (module name edgeHub)
    • Edge Agent (module name edgeAgent)
    • Video Analyzer (module name avaedge)
    • RTSP simulator (module name rtspsim)

Prepare to monitor the modules

When you use run this quickstart or tutorial, events will be sent to the IoT Hub. To see these events, follow these steps:

  1. Open the Explorer pane in Visual Studio Code, and look for Azure IoT Hub in the lower-left corner.

  2. Expand the Devices node.

  3. Right-click on avasample-iot-edge-device, and select Start Monitoring Built-in Event Endpoint.

    Note

    You might be asked to provide Built-in endpoint information for the IoT Hub. To get that information, in Azure portal, navigate to your IoT Hub and look for Built-in endpoints option in the left navigation pane. Click there and look for the Event Hub-compatible endpoint under Event Hub compatible endpoint section. Copy and use the text in the box. The endpoint will look something like this: Endpoint=sb://iothub-ns-xxx.servicebus.windows.net/;SharedAccessKeyName=iothubowner;SharedAccessKey=XXX;EntityPath=<IoT Hub name>

Examine the sample files

In Visual Studio Code, browse to the src/cloud-to-device-console-app folder. Here you'll see the appsettings.json file that you created along with a few other files:

  • c2d-console-app.csproj: The project file for Visual Studio Code.
  • operations.json: This file lists the different operations that you would run.
  • Program.cs: The sample program code, which:
    • Loads the app settings.
    • Invokes direct methods exposed by Video Analyzer edge module. You can use the module to analyze live video streams by invoking its direct methods.
    • Pauses for you to examine the output from the program in the TERMINAL window and the events generated by the module in the OUTPUT window.
    • Invokes direct methods to clean up resources.

Run the program

  1. In Visual Studio Code, go to src/cloud-to-device-console-app/operations.json.

  2. Under the pipelineTopologySet node, edit the following:

    "pipelineTopologyUrl" : "https://raw.githubusercontent.com/Azure/video-analyzer/main/pipelines/live/topologies/cvr-video-sink/topology.json"

  3. Next, under the livePipelineSet and pipelineTopologyDelete nodes, ensure that the value of topologyName matches the value of the name property in the above pipeline topology:

    "topologyName" : "CVRToVideoSink"

  4. Open the pipeline topology in a browser, and look at videoName - it is hard-coded to sample-cvr-video. This is acceptable for a tutorial. In production, you would take care to ensure that each unique RTSP camera is recorded to a video resource with a unique name.

  5. Start a debugging session by selecting F5. You'll see some messages printed in the TERMINAL window.

  6. The operations.json file starts off with calls to pipelineTopologyList and livePipelineList. If you've cleaned up resources after previous quickstarts or tutorials, this action returns empty lists as shown:

    --------------------------------------------------------------------------
Executing operation pipelineTopologyList
-----------------------  Request: pipelineTopologyList  --------------------------------------------------
{
  "@apiVersion": "1.1"
}
---------------  Response: pipelineTopologyList - Status: 200  ---------------
{
  "value": []
}
--------------------------------------------------------------------------

  7. After that the next set of direct method calls is made:

    • A call to pipelineTopologySet by using the previous topologyUrl

    • A call to livePipelineSet by using the following body

      {
  "@apiVersion": "1.1",
  "name": "Sample-Pipeline-1",
  "properties": {
    "topologyName": "CVRToVideoSink",
    "description": "Sample pipeline description",
    "parameters": [
      {
        "name": "rtspUrl",
        "value": "rtsp://rtspsim:554/media/camera-300s.mkv"
      },
      {
        "name": "rtspUserName",
        "value": "testuser"
      },
      {
        "name": "rtspPassword",
        "value": "testpassword"
      }
    ]
  }
}

    • A call to livePipelineActivate to start the live pipeline and to start the flow of video and then pauses for you to select Enter in the Terminal window

  8. The output in the TERMINAL window pauses now at a Press Enter to continue prompt. Do not select Enter at this time. Scroll up to see the JSON response payloads for the direct methods you invoked.

  9. If you now switch over to the OUTPUT window in Visual Studio Code, you'll see messages being sent to IoT Hub by the Video Analyzer edge module. These messages are discussed in the following section.

  10. The live pipeline continues to run and record the video. The RTSP simulator keeps looping the source video. To stop recording, go back to the TERMINAL window and select Enter. The next series of calls are made to clean up resources by using:

    • A call to livePipelineDeactivate to deactivate the live pipeline.
    • A call to livePipelineDelete to delete the live pipeline.
    • A second call to livePipelineList to show that the live pipeline is in the running state.
    • A call to pipelineTopologyDelete to delete the topology.
    • A final call to pipelineTopologyList to show that the list is now empty.

Interpret the results

When you run the live pipeline, the Video Analyzer edge module sends certain diagnostic and operational events to the IoT Edge hub. These events are the messages you see in the OUTPUT window of Visual Studio Code. They contain a body section and an applicationProperties section. To understand what these sections represent, see Create and read IoT Hub messages.

In the following messages, the application properties and the content of the body are defined by the Video Analyzer edge module.

Diagnostics events

MediaSession Established event

When the live pipeline is activated, the RTSP source node attempts to connect to the RTSP server running in the rtspsim module. If successful, it prints this event:

[IoTHubMonitor] [9:42:18 AM] Message received from [avasample-iot-edge-device/avaedge]:
{
  "body": {
    "sdp": "SDP:\nv=0\r\no=- 1586450538111534 1 IN IP4 XXX.XX.XX.XX\r\ns=Matroska video+audio+(optional)subtitles, streamed by the LIVE555 Media Server\r\ni=media/camera-300s.mkv\r\nt=0 0\r\na=tool:LIVE555 Streaming Media v2020.03.06\r\na=type:broadcast\r\na=control:*\r\na=range:npt=0-300.000\r\na=x-qt-text-nam:Matroska video+audio+(optional)subtitles, streamed by the LIVE555 Media Server\r\na=x-qt-text-inf:media/camera-300s.mkv\r\nm=video 0 RTP/AVP 96\r\nc=IN IP4 0.0.0.0\r\nb=AS:500\r\na=rtpmap:96 H264/90000\r\na=fmtp:96 packetization-mode=1;profile-level-id=4D0029;sprop-parameter-sets=XXXXXXXXXXXXXXXXXXXXXX\r\na=control:track1\r\n"
  },
  "applicationProperties": {
    "dataVersion": "1.0",
    "topic": "/subscriptions/{subscriptionID}/resourceGroups/{name}/providers/microsoft.media/videoanalyzers/{ava-account-name}",
    "subject": "/edgeModules/avaedge/livePipelines/Sample-Pipeline-1/sources/rtspSource",
    "eventType": "Microsoft.VideoAnalyzers.Diagnostics.MediaSessionEstablished",
    "eventTime": "2021-04-09T09:42:18.1280000Z"
  }
}
  • The message is a Diagnostics event (Microsoft.VideoAnalyzers.Diagnostics.MediaSessionEstablished). It indicates that the RTSP source node (the subject) established a connection with the RTSP simulator and began to receive a (simulated) live feed.
  • The subject section in applicationProperties references the node in the pipeline topology from which the message was generated. In this case, the message originates from the RTSP source node.
  • The eventType section in applicationProperties indicates that this is a Diagnostics event.
  • The eventTime section indicates the time when the event occurred.
  • The body section contains data about the Diagnostics event, which in this case is the SDP details.

Operational events

RecordingStarted event

When the video sink node starts to record media, it emits this event of type Microsoft.VideoAnalyzers.Pipeline.OperationalRecordingStarted:

[IoTHubMonitor] [9:42:38 AM] Message received from [avasample-iot-edge-device/avaedge]:
{
  "body": {
    "outputType": "videoName",
    "outputLocation": "sample-cvr-video"
  },
  "applicationProperties": {
    "topic": "/subscriptions/{subscriptionID}/resourceGroups/{resource-group-name}/providers/microsoft.media/videoAnalyzers/{ava-account-name}",
    "subject": "/edgeModules/avaedge/livePipelines/Sample-Pipeline-1/sinks/videoSink",
    "eventType": "Microsoft.VideoAnalyzers.Pipeline.Operational.RecordingStarted",
    "eventTime": "2021-04-09T09:42:38.1280000Z",
    "dataVersion": "1.0"
  }
}

The subject section in applicationProperties references the video sink node in the live pipeline, which generated this message.

The body section contains information about the output location. In this case, it's the name of the Video Analyzer resource into which video is recorded.

RecordingAvailable event

As the name suggests, the RecordingStarted event is sent when recording has started, but media data might not have been uploaded to the video resource yet. When the video sink node has uploaded media, it emits an event of type Microsoft.VideoAnalyzers.Pipeline.Operational.RecordingAvailable:

[IoTHubMonitor] [[9:43:38 AM] Message received from [ava-sample-device/avaedge]:
{
  "body": {
    "outputType": "videoName",
    "outputLocation": "sample-cvr-video"
  },
  "applicationProperties": {
    "topic": "/subscriptions/{subscriptionID}/resourceGroups/{resource-group-name}/providers/microsoft.media/videoAnalyzers/{ava-account-name}",
    "subject": "/edgeModules/avaedge/livePipelines/Sample-Pipeline-1/sinks/videoSink",
    "eventType": "Microsoft.VideoAnalyzers.Pipeline.Operational.RecordingAvailable",
    "eventTime": "2021-04-09T09:43:38.1280000Z",
    "dataVersion": "1.0"
  }
}

This event indicates that enough data was written to the video resource for players or clients to start playback of the video.

The subject section in applicationProperties references the video sink node in the live pipeline, which generated this message.

The body section contains information about the output location. In this case, it's the name of the Video Analyzer resource into which video is recorded.

RecordingStopped event

When you deactivate the live pipeline, the video sink node stops recording media. It emits this event of type Microsoft.VideoAnalyzers.Pipeline.Operational.RecordingStopped:

[IoTHubMonitor] [11:33:31 PM] Message received from [avasample-iot-edge-device/avaedge]:
{
  "body": {
    "outputType": "videoName",
    "outputLocation": "sample-cvr-video"
  },
  "applicationProperties": {
    "topic": "/subscriptions/{subscriptionID}/resourceGroups/{resource-group-name}/providers/microsoft.media/videoAnalyzers/{ava-account-name}",
    "subject": "/edgeModules/avaedge/livePipelines/Sample-Pipeline-1/sinks/videoSink",
    "eventType": "Microsoft.VideoAnalyzers.Pipeline.Operational.RecordingStopped",
    "eventTime": "2021-04-10T11:33:31.051Z",
    "dataVersion": "1.0"
  }
}

This event indicates that recording has stopped.

The subject section in applicationProperties references the video sink node in the live pipeline, which generated this message.

The body section contains information about the output location, which in this case is the name of the Video Analyzer resource into which video is recorded.

Playing back the recording

You can examine the Video Analyzer video resource that was created by the live pipeline by logging in to the Azure portal and viewing the video.

  1. Open your web browser, and go to the Azure portal. Enter your credentials to sign in to the portal. The default view is your service dashboard.
  2. Locate your Video Analyzers account among the resources you have in your subscription, and open the account pane.
  3. Select Videos in the Video Analyzer section.
  4. You'll find a video listed with the name sample-cvr-video. This is the name chosen in your pipeline topology file.
  5. Select the video.
  6. The video details page will open and the playback should start automatically.

Note

Because the source of the video was a container simulating a camera feed, the time stamps in the video are related to when you activated the live pipeline and when you deactivated it.

Clean up resources

If you want to try other quickstarts or tutorials, keep the resources that you created. Otherwise, go to the Azure portal, go to your resource groups, select the resource group where you ran this quickstart, and delete all the resources.

Next steps