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Add faces to a PersonGroup

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Caution

Face service access is limited based on eligibility and usage criteria in order to support our Responsible AI principles. Face service is only available to Microsoft managed customers and partners. Use the Face Recognition intake form to apply for access. For more information, see the Face limited access page.

This guide demonstrates how to add a large number of persons and faces to a PersonGroup object. The same strategy also applies to LargePersonGroup, FaceList, and LargeFaceList objects. This sample is written in C#.

Initialization

The following code declares several variables and implements a helper function to schedule the face add requests:

  • PersonCount is the total number of persons.
  • CallLimitPerSecond is the maximum calls per second according to the subscription tier.
  • _timeStampQueue is a Queue to record the request timestamps.
  • await WaitCallLimitPerSecondAsync() waits until it's valid to send the next request.
const int PersonCount = 10000;
const int CallLimitPerSecond = 10;
static Queue<DateTime> _timeStampQueue = new Queue<DateTime>(CallLimitPerSecond);

static async Task WaitCallLimitPerSecondAsync()
{
    Monitor.Enter(_timeStampQueue);
    try
    {
        if (_timeStampQueue.Count >= CallLimitPerSecond)
        {
            TimeSpan timeInterval = DateTime.UtcNow - _timeStampQueue.Peek();
            if (timeInterval < TimeSpan.FromSeconds(1))
            {
                await Task.Delay(TimeSpan.FromSeconds(1) - timeInterval);
            }
            _timeStampQueue.Dequeue();
        }
        _timeStampQueue.Enqueue(DateTime.UtcNow);
    }
    finally
    {
        Monitor.Exit(_timeStampQueue);
    }
}

Create the PersonGroup

This code creates a PersonGroup named "MyPersonGroup" to save the persons. The request time is enqueued to _timeStampQueue to ensure the overall validation.

const string personGroupId = "mypersongroupid";
const string personGroupName = "MyPersonGroup";
_timeStampQueue.Enqueue(DateTime.UtcNow);
using (var content = new ByteArrayContent(Encoding.UTF8.GetBytes(JsonConvert.SerializeObject(new Dictionary<string, object> { ["name"] = personGroupName, ["recognitionModel"] = "recognition_04" }))))
{
    content.Headers.ContentType = new MediaTypeHeaderValue("application/json");
    await httpClient.PutAsync($"{ENDPOINT}/face/v1.0/persongroups/{personGroupId}", content);
}

Create the persons for the PersonGroup

This code creates Persons concurrently, and uses await WaitCallLimitPerSecondAsync() to avoid exceeding the call rate limit.

string?[] persons = new string?[PersonCount];
Parallel.For(0, PersonCount, async i =>
{
    await WaitCallLimitPerSecondAsync();

    string personName = $"PersonName#{i}";
    using (var content = new ByteArrayContent(Encoding.UTF8.GetBytes(JsonConvert.SerializeObject(new Dictionary<string, object> { ["name"] = personName }))))
    {
        content.Headers.ContentType = new MediaTypeHeaderValue("application/json");
        using (var response = await httpClient.PostAsync($"{ENDPOINT}/face/v1.0/persongroups/{personGroupId}/persons", content))
        {
            string contentString = await response.Content.ReadAsStringAsync();
            persons[i] = (string?)(JsonConvert.DeserializeObject<Dictionary<string, object>>(contentString)?["personId"]);
        }
    }
});

Add faces to the persons

Faces added to different persons are processed concurrently. Faces added for one specific person are processed sequentially. Again, await WaitCallLimitPerSecondAsync() is invoked to ensure that the request frequency is within the scope of limitation.

Parallel.For(0, PersonCount, async i =>
{
    string personImageDir = @"/path/to/person/i/images";

    foreach (string imagePath in Directory.GetFiles(personImageDir, "*.jpg"))
    {
        await WaitCallLimitPerSecondAsync();

        using (Stream stream = File.OpenRead(imagePath))
        {
            using (var content = new StreamContent(stream))
            {
                content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream");
                await httpClient.PostAsync($"{ENDPOINT}/face/v1.0/persongroups/{personGroupId}/persons/{persons[i]}/persistedfaces?detectionModel=detection_03", content);
            }
        }
    }
});

Summary

In this guide, you learned the process of creating a PersonGroup with a massive number of persons and faces. Several reminders:

  • This strategy also applies to FaceLists and LargePersonGroups.
  • Adding or deleting faces to different FaceLists or persons in LargePersonGroups are processed concurrently.
  • Adding or deleting faces to one specific FaceList or persons in a LargePersonGroup is done sequentially.

Next steps

Next, learn how to use the enhanced data structure PersonDirectory to do more with your face data.