The Face API which
is a part of the Microsoft Cognitive Services helps you to identify and detect
faces. It is also used to find similar faces, verify images to see if it’s of
same persons .In this blog post, I’ll just use the detect service which detects
faces and shows the gender , age, emotions and other data of the face.
Prerequisites:
Create the Face API Service in Azure
As all Microsoft
cognitive services, you can also create the face API service in Azure via the
portal. It is part of the “Cognitive
Services APIs”, so just search for it and create it.
Select the Face API as
the type of the cognitive service and check the pricing options:
Now, we need to
note down the API key and the API endpoint url. Navigate to the service in the
Azure portal and you will see the endpoint url in the overview. It’s currently
only available in west-us, so the endpoint url will be: https://westus.api.cognitive.microsoft.com/face/v1.0
The keys can be found in “Keys” – just copy one of them and you can use it later in the application:
The keys can be found in “Keys” – just copy one of them and you can use it later in the application:
Using the Face API
with C#.Net
The face API can be
accessed via C# with a simple HttpClient or
with the NuGet package Microsoft.ProjectOxford.Face. My
first sample will use the HttpClient just to show how it works. It also returns
by sure all data that is currently available. The NuGet package is not fully up
to date, so it for example does not contain the emotions.
Access Face API
with C# and HttpClient
In the following sample,
I’ll just send an image to the face API and show the JSON output in the
console. If you want to work with the data, then you can use Newtonsoft.Json
with JObject.Parse, or as already stated, the NuGet package which is described
later in this post
using System;using System.Net.Http;using System.Net.Http.Headers;using System.Threading.Tasks;namespace MyAzureCognitiveService.Face{ class Program { private static string APIKEY = "[APIKEY]"; static void Main(string[] args) { Console.WriteLine("Welcome to the Azure Cognitive Services - Face API"); Console.WriteLine("Please enter image url:"); string path = Console.ReadLine(); Task.Run(async () => { var image = System.IO.File.ReadAllBytes(path); var output = await DetectFaces(image); Console.WriteLine(output); }).Wait(); Console.WriteLine("Press key to exit!"); Console.ReadKey(); } public static async Task<string> DetectFaces(byte[] image) { var client = new HttpClient(); client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", APIKEY); string requestParams = "returnFaceId=true&returnFaceLandmarks=true&returnFaceAttributes=age,gender,headPose,smile,facialHair,glasses,emotion"; using (var content = new ByteArrayContent(image)) { content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream"); var response = await client.PostAsync(uri, content); var jsonText = await response.Content.ReadAsStringAsync(); return jsonText; } } }}
For testing, I have used the below image and output given below.
output.json
[{ "faceId": "c41cd9de-76c8-4f10-b6f5-d01bb08ec616", "faceRectangle": { "top": 332, "left": 709, "width": 48, "height": 48 }, "faceLandmarks": { "pupilLeft": { "x": 723.6, "y": 344.7 }, "pupilRight": { "x": 744.2, "y": 346.3 }, "noseTip": { "x": 732.8, "y": 357.6 }, "mouthLeft": { "x": 720.7, "y": 365.6 }, "mouthRight": { "x": 743.7, "y": 367.1 }, "eyebrowLeftOuter": { "x": 715.8, "y": 341.8 }, "eyebrowLeftInner": { "x": 728.3, "y": 341.2 }, "eyeLeftOuter": { "x": 720.4, "y": 345.1 }, "eyeLeftTop": { "x": 723.3, "y": 344.5 }, "eyeLeftBottom": { "x": 723.3, "y": 345.8 }, "eyeLeftInner": { "x": 726.3, "y": 345.5 }, "eyebrowRightInner": { "x": 738.2, "y": 342.2 }, "eyebrowRightOuter": { "x": 752.0, "y": 342.8 }, "eyeRightInner": { "x": 740.5, "y": 346.3 }, "eyeRightTop": { "x": 743.6, "y": 345.7 }, "eyeRightBottom": { "x": 743.3, "y": 347.1 }, "eyeRightOuter": { "x": 746.4, "y": 347.0 }, "noseRootLeft": { "x": 730.5, "y": 346.3 }, "noseRootRight": { "x": 736.4, "y": 346.5 }, "noseLeftAlarTop": { "x": 728.3, "y": 353.3 }, "noseRightAlarTop": { "x": 738.3, "y": 353.7 }, "noseLeftAlarOutTip": { "x": 726.2, "y": 356.6 }, "noseRightAlarOutTip": { "x": 739.8, "y": 357.7 }, "upperLipTop": { "x": 733.0, "y": 365.1 }, "upperLipBottom": { "x": 732.7, "y": 366.4 }, "underLipTop": { "x": 731.7, "y": 370.6 }, "underLipBottom": { "x": 731.4, "y": 373.1 } }, "faceAttributes": { "smile": 1.0, "headPose": { "pitch": 0.0, "roll": 3.2, "yaw": -0.5 }, "gender": "male", "age": 33.6, "facialHair": { "moustache": 0.0, "beard": 0.2, "sideburns": 0.2 }, "glasses": "ReadingGlasses", "emotion": { "anger": 0.0, "contempt": 0.0, "disgust": 0.0, "fear": 0.0, "happiness": 1.0, "neutral": 0.0, "sadness": 0.0, "surprise": 0.0 } } }]
It seems I look like a 33-year-old man and that my face on the image is the pure
happiness (100%). All other emotions are non-existent (0%).
Access Face API
with C# and the NuGet package
using Microsoft.ProjectOxford.Face;
using System;
using System.Collections.Generic;
using System.Net.Http;
using System.Net.Http.Headers;
using System.Threading.Tasks;
namespace MyAzureCognitiveService.Face
{
class Program
{
private static string APIKEY = "[APIKEY]";
static void Main(string[] args)
{
Console.WriteLine("Welcome to the Azure Cognitive Services - Face API");
Console.WriteLine("Please enter image url:");
string path = Console.ReadLine();
Task.Run(async () =>
{
var faces = await DetectFaces(path);
foreach(var face in faces)
{
Console.WriteLine($"{face.FaceAttributes.Gender},
{face.FaceAttributes.Age}: Smile: {face.FaceAttributes.Smile}");
}
}).Wait();
Console.WriteLine("Press key to exit!");
Console.ReadKey();
}
public static async Task<Microsoft.ProjectOxford.Face.Contract.Face[]> DetectFaces(string path)
{
var client = new FaceServiceClient(APIKEY);
using (System.IO.Stream stream = System.IO.File.OpenRead(path))
{
var data = await client.DetectAsync(stream, true, true, new List<FaceAttributeType>()
{
FaceAttributeType.Age,
FaceAttributeType.Gender,
FaceAttributeType.Glasses,
FaceAttributeType.Smile
});
return data;
}
}
}
}
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