Video moderation

Today, online viewers generate billions of video views across popular and regional social media web sites and increasing. By applying machine-learning based services to predict potential adult and racy content, you lower the cost of your moderation efforts.

Sign up for the Content Moderator media processor (preview)

Create a free Azure account

Start here to create a free Azure account if you don't have one already.

Create an Azure Media Services account

The Content Moderator's video capability is available as a public preview media processor in Azure Media Services (AMS) at no charge.

Create an Azure Media Services account in your Azure subscription.

Get Azure Active Directory credentials

  1. Read the Azure Media Services portal article to learn how to use the Azure portal to get your Azure AD authentication credentials.
  2. Read the Azure Media Services .NET article to learn how to use your Azure Active Directory credentials with the .NET SDK.


    The sample code in this quickstart uses the service principal authentication method described in both the articles.

Once you get your AMS credentials, there are two ways to try the Content Moderator media processor.

Use Azure Media Services Explorer

Use the interactive Azure Media Services (AMS) explorer to browse your AMS account, upload videos, and scan with the Content Moderator media processor. Download and install it from GitHub, and browse the source code to dive into using the AMS SDK.

Azure Media Services explorer with Content Moderator

.NET QuickStart with Visual Studio and C#

  1. Add a new Console app (.NET Framework) project to your solution.

    In the sample code, name the project VideoModeration.

  2. Select this project as the single startup project for the solution.

Install required packages

Install the following NuGet packages available on NuGet.

  • windowsazure.mediaservices
  • windowsazure.mediaservices.extensions

Update the program's using statements

Modify the program's using statements.

using System;
using System.Linq;
using System.Threading.Tasks;
using Microsoft.WindowsAzure.MediaServices.Client;
using System.IO;
using System.Threading;
using Microsoft.WindowsAzure.Storage.Blob;
using Microsoft.WindowsAzure.Storage;
using Microsoft.WindowsAzure.Storage.Auth;
using System.Collections.Generic;

Initialize application-specific settings

Add the following static fields to the Program class in Program.cs.

// declare constants and globals
private static CloudMediaContext _context = null;
private static CloudStorageAccount _StorageAccount = null;

// Azure Media Services (AMS) associated Storage Account, Key, and the Container that has 
// a list of Blobs to be processed.

private static StorageCredentials _StorageCredentials = null;

// Azure Media Services authentication. See the quickstart for how to get these.
private const string AZURE_AD_TENANT_NAME = "";
private const string CLIENT_ID = "YOUR CLIENT ID"
private const string CLIENT_SECRET = "YOUR CLIENT SECRET";

// REST API endpoint, for example "".      
private const string REST_API_ENDPOINT = "YOUR API ENDPOINT";

// Content Moderator Media Processor Nam
private const string MEDIA_PROCESSOR = "Azure Media Content Moderator";

// Input and Output files in the current directory of the executable
private const string INPUT_FILE = "VIDEO FILE NAME";
private const string OUTPUT_FOLDER = "";

Create a preset file (json)

Create a JSON file in the current directory with the version number.

private static readonly string CONTENT_MODERATOR_PRESET_FILE = "preset.json";
//Example file content:
//        {
//             "version": "2.0"
//        }
private static readonly string CONTENT_MODERATOR_PRESET_FILE = "preset.json";

Add the following code to the main method

The main method first creates an Azure Media Context and then an Azure Storage Context in case your videos are in blob storage. The remaining code scans a video from a local folder, blob, or multiple blobs within an Azure storage container. You can try all options by commenting out the other lines of code.

// Create Azure Media Context

// Create Storage Context

// Use a file as the input.
// IAsset asset = CreateAssetfromFile();

// -- OR ---

// Or a blob as the input
// IAsset asset = CreateAssetfromBlob((CloudBlockBlob)GetBlobsList().First());

// Then submit the asset to Content Moderator
// RunContentModeratorJob(asset);

//-- OR ----

// Just run the content moderator on all blobs in a list (from a Blob Container)

Add the code to create an Azure Media Context

/// <summary>
/// Creates a media context from azure credentials
/// </summary>
static void CreateMediaContext()
    // Get Azure AD credentials
    var tokenCredentials = new AzureAdTokenCredentials(AZURE_AD_TENANT_NAME,
        new AzureAdClientSymmetricKey(CLIENT_ID, CLIENT_SECRET),

    // Initialize an Azure AD token
    var tokenProvider = new AzureAdTokenProvider(tokenCredentials);

    // Create a media context
    _context = new CloudMediaContext(new Uri(REST_API_ENDPOINT), tokenProvider);

Add the code to create an Azure Storage Context

You use the Storage Context, created from your Storage credentials, to access your blob storage.

/// <summary>
/// Creates a storage context from the AMS associated storage name and key
/// </summary>
static void CreateStorageContext()
    // Get a reference to the storage account associated with a Media Services account. 
    if (_StorageCredentials == null)
        _StorageCredentials = new StorageCredentials(STORAGE_NAME, STORAGE_KEY);
    _StorageAccount = new CloudStorageAccount(_StorageCredentials, false);

Add the code to create Azure Media Assets from local file and blob

The Content Moderator media processor runs jobs on Assets within the Azure Media Services platform. These methods create the Assets from a local file or an associated blob.

/// <summary>
/// Creates an Azure Media Services Asset from the video file
/// </summary>
/// <returns>Asset</returns>
static IAsset CreateAssetfromFile()
    return _context.Assets.CreateFromFile(INPUT_FILE, AssetCreationOptions.None); ;

/// <summary>
/// Creates an Azure Media Services asset from your blog storage
/// </summary>
/// <param name="Blob"></param>
/// <returns>Asset</returns>
static IAsset CreateAssetfromBlob(CloudBlockBlob Blob)
    // Create asset from the FIRST blob in the list and return it
    return _context.Assets.CreateFromBlob(Blob, _StorageCredentials, AssetCreationOptions.None);

Add the code to scan a collection of videos (as blobs) within a container

/// <summary>
/// Runs the Content Moderator Job on all Blobs in a given container name
/// </summary>
static void RunContentModeratorJobOnBlobs()
    // Get the reference to the list of Blobs. See the following method.
    var blobList = GetBlobsList();

    // Iterate over the Blob list items or work on specific ones as needed
    foreach (var sourceBlob in blobList)
        // Create an Asset
        IAsset asset = _context.Assets.CreateFromBlob((CloudBlockBlob)sourceBlob,
                           _StorageCredentials, AssetCreationOptions.None);

        // Submit to Content Moderator

/// <summary>
/// Get all blobs in your container
/// </summary>
/// <returns></returns>
static IEnumerable<IListBlobItem> GetBlobsList()
    // Get a reference to the Container within the Storage Account
    // that has the files (blobs) for moderation
    CloudBlobClient CloudBlobClient = _StorageAccount.CreateCloudBlobClient();
    CloudBlobContainer MediaBlobContainer = CloudBlobClient.GetContainerReference(STORAGE_CONTAINER_NAME);

    // Get the reference to the list of Blobs 
    var blobList = MediaBlobContainer.ListBlobs();
    return blobList;

Add the method to run the Content Moderator Job

/// <summary>
/// Run the Content Moderator job on the designated Asset from local file or blob storage
/// </summary>
/// <param name="asset"></param>
static void RunContentModeratorJob(IAsset asset)
    // Grab the presets
    string configuration = File.ReadAllText(CONTENT_MODERATOR_PRESET_FILE);

    // grab instance of Azure Media Content Moderator MP
    IMediaProcessor mp = _context.MediaProcessors.GetLatestMediaProcessorByName(MEDIA_PROCESSOR);

    // create Job with Content Moderator task
    IJob job = _context.Jobs.Create(String.Format("Content Moderator {0}",
            asset.AssetFiles.First() + "_" + Guid.NewGuid()));

    ITask contentModeratorTask = job.Tasks.AddNew("Adult and racy classifier task",
            mp, configuration,
    contentModeratorTask.OutputAssets.AddNew("Adult and racy classifier output",


    // Create progress printing and querying tasks
    Task progressPrintTask = new Task(() =>
        IJob jobQuery = null;
            var progressContext = _context;
            jobQuery = progressContext.Jobs
            .Where(j => j.Id == job.Id)
         while (jobQuery.State != JobState.Finished &&
         jobQuery.State != JobState.Error &&
         jobQuery.State != JobState.Canceled);

    Task progressJobTask = job.GetExecutionProgressTask(

    // If job state is Error, the event handling 
    // method for job progress should log errors.  Here we check 
    // for error state and exit if needed.
    if (job.State == JobState.Error)
        ErrorDetail error = job.Tasks.First().ErrorDetails.First();
        Console.WriteLine(string.Format("Error: {0}. {1}",

    DownloadAsset(job.OutputMediaAssets.First(), OUTPUT_FOLDER);

Add a couple of helper functions

These methods download the Content Moderator output file (JSON) from the Azure Media Services asset, and help track the status of the moderation job so that the program can log a running status to the console.

static void DownloadAsset(IAsset asset, string outputDirectory)
    foreach (IAssetFile file in asset.AssetFiles)
        file.Download(Path.Combine(outputDirectory, file.Name));

// event handler for Job State
static void StateChanged(object sender, JobStateChangedEventArgs e)
    Console.WriteLine("Job state changed event:");
    Console.WriteLine("  Previous state: " + e.PreviousState);
    Console.WriteLine("  Current state: " + e.CurrentState);
    switch (e.CurrentState)
        case JobState.Finished:
            Console.WriteLine("Job finished.");
        case JobState.Canceling:
        case JobState.Queued:
        case JobState.Scheduled:
        case JobState.Processing:
            Console.WriteLine("Please wait...\n");
        case JobState.Canceled:
            Console.WriteLine("Job is canceled.\n");
        case JobState.Error:
            Console.WriteLine("Job failed.\n");

Run the program and review the output

After the Content Moderation job is completed, analyze the JSON response. It consists of these elements:

  • Video information summary
  • Shots as "fragments"
  • Key frames as "events" with a reviewRecommended" (= true or false)" flag based on Adult and Racy scores
  • start, duration, totalDuration, and timestamp are in "ticks". Divide by timescale to get the number in seconds.


  • adultScore represents the potential presence and prediction score of content that may be considered sexually explicit or adult in certain situations.
  • racyScore represents the potential presence and prediction score of content that may be considered sexually suggestive or mature in certain situations.
  • adultScore and racyScore are between 0 and 1. The higher the score, the higher the model is predicting that the category may be applicable. This preview relies on a statistical model rather than manually coded outcomes. We recommend testing with your own content to determine how each category aligns to your requirements.
  • reviewRecommended is either true or false depending on the internal score thresholds. Customers should assess whether to use this value or decide on custom thresholds based on their content policies.
"version": 2,
"timescale": 90000,
"offset": 0,
"framerate": 50,
"width": 1280,
"height": 720,
"totalDuration": 18696321,
"fragments": [
  "start": 0,
  "duration": 18000
  "start": 18000,
  "duration": 3600,
  "interval": 3600,
  "events": [
        "reviewRecommended": false,
        "adultScore": 0.00001,
        "racyScore": 0.03077,
        "index": 5,
        "timestamp": 18000,
        "shotIndex": 0
  "start": 18386372,
  "duration": 119149,
  "interval": 119149,
  "events": [
        "reviewRecommended": true,
        "adultScore": 0.00000,
        "racyScore": 0.91902,
        "index": 5085,
        "timestamp": 18386372,
        "shotIndex": 62

Next steps

Learn how to generate video reviews from your moderation output.

Add transcript moderation to your video reviews.

Check out the detailed tutorial on how to build a complete video and transcript moderation solution.

Download the Visual Studio solution for this and other Content Moderator quickstarts for .NET.