New Face Quickstart Code Samples for C# Python JavaScript

dotnet/Face/Detect.cs

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+using System.Drawing;
+
+using Azure;
+using Azure.AI.Vision.Face;
+
+namespace FaceQuickstart
+{
+    class Program
+    {
+        static string SUBSCRIPTION_KEY = "PASTE_YOUR_FACE_SUBSCRIPTION_KEY_HERE";
+        static string ENDPOINT = "PASTE_YOUR_FACE_ENDPOINT_HERE";
+
+        async static void Quickstart()
+        {
+            FaceClient faceClient = new FaceClient(new Uri(ENDPOINT), new AzureKeyCredential(SUBSCRIPTION_KEY));
+
+            var imageUrl = "https://raw.githubusercontent.com/Azure-Samples/cognitive-services-sample-data-files/master/ComputerVision/Images/faces.jpg";
+
+            // <basic1>
+            var response = await faceClient.DetectAsync(new Uri(imageUrl), FaceDetectionModel.Detection03, FaceRecognitionModel.Recognition04, returnFaceId: false);
+            IReadOnlyList<FaceDetectionResult> faces = response.Value;
+            // </basic1>
+
+            // <basic2>
+            foreach (var face in faces)
+            {
+                string id = face.FaceId.ToString();
+                FaceRectangle rect = face.FaceRectangle;
+            }
+            // </basic2>
+
+            // <landmarks1>
+            // Note DetectionModel.Detection02 cannot be used with returnFaceLandmarks.
+            var response2 = await faceClient.DetectAsync(new Uri(imageUrl), FaceDetectionModel.Detection03, FaceRecognitionModel.Recognition04, returnFaceId: false, returnFaceLandmarks: true);
+            IReadOnlyList<FaceDetectionResult> faces2 = response2.Value;
+            // </landmarks1>
+
+            // <landmarks2>
+            foreach (var face in faces2)
+            {
+                var landmarks = face.FaceLandmarks;
+
+                double noseX = landmarks.NoseTip.X;
+                double noseY = landmarks.NoseTip.Y;
+
+                double leftPupilX = landmarks.PupilLeft.X;
+                double leftPupilY = landmarks.PupilLeft.Y;
+
+                double rightPupilX = landmarks.PupilRight.X;
+                double rightPupilY = landmarks.PupilRight.Y;
+                // </landmarks2>
+
+                // <direction>
+                var upperLipBottom = landmarks.UpperLipBottom;
+                var underLipTop = landmarks.UnderLipTop;
+
+                var centerOfMouth = new Point(
+                    (int)((upperLipBottom.X + underLipTop.X) / 2),
+                    (int)((upperLipBottom.Y + underLipTop.Y) / 2));
+
+                var eyeLeftInner = landmarks.EyeLeftInner;
+                var eyeRightInner = landmarks.EyeRightInner;
+
+                var centerOfTwoEyes = new Point(
+                    (int)((eyeLeftInner.X + eyeRightInner.X) / 2),
+                    (int)((eyeLeftInner.Y + eyeRightInner.Y) / 2));
+
+                var faceDirectionVectorX = centerOfTwoEyes.X - centerOfMouth.X;
+                var faceDirectionVectorY = centerOfTwoEyes.Y - centerOfMouth.Y;
+            }
+            // </direction>
+
+            // <attributes1>
+            var requiredFaceAttributes = new FaceAttributeType[] {
+                FaceAttributeType.Detection03.Blur,
+                FaceAttributeType.Detection03.HeadPose,
+                FaceAttributeType.Detection03.Mask,
+                FaceAttributeType.Recognition04.QualityForRecognition
+            };
+            // Note DetectionModel.Detection02 cannot be used with returnFaceAttributes.
+            var response3 = await faceClient.DetectAsync(new Uri(imageUrl), FaceDetectionModel.Detection03, FaceRecognitionModel.Recognition04, returnFaceId: false, returnFaceAttributes: requiredFaceAttributes);
+            IReadOnlyList<FaceDetectionResult> faces3 = response3.Value;
+            // </attributes1>
+
+            // <attributes2>
+            foreach (var face in faces3)
+            {
+                var attributes = face.FaceAttributes;
+                var blur = attributes.Blur;
+                var headPose = attributes.HeadPose;
+                var mask = attributes.Mask;
+                var qualityForRecognition = attributes.QualityForRecognition;
+            }
+            // </attributes2>
+        }
+
+        static void Main(string[] args)
+        {
+            Quickstart();
+            Console.WriteLine("Press any key to exit.");
+            Console.ReadKey();
+        }
+    }
+}

dotnet/Face/FindSimilar.cs

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+// <snippet_using>
+using Azure;
+using Azure.AI.Vision.Face;
+// </snippet_using>
+
+namespace FaceQuickstart
+{
+    class Program
+    {
+        // <snippet_image_url>
+        const string IMAGE_BASE_URL = "https://raw.githubusercontent.com/Azure-Samples/cognitive-services-sample-data-files/master/Face/images/";
+        // </snippet_image_url>
+
+        // <snippet_creds>
+        static readonly string SUBSCRIPTION_KEY = Environment.GetEnvironmentVariable("FACE_APIKEY") ?? "<apikey>";
+        static readonly string ENDPOINT = Environment.GetEnvironmentVariable("FACE_ENDPOINT") ?? "<endpoint>";
+        // </snippet_creds>
+
+        static void Main(string[] args)
+        {
+
+            // <snippet_detect_models>
+            FaceRecognitionModel RECOGNITION_MODEL4 = FaceRecognitionModel.Recognition04;
+            // </snippet_detect_models>
+
+            // <snippet_maincalls>
+            FaceClient client = Authenticate(ENDPOINT, SUBSCRIPTION_KEY);
+            FindSimilar(client, IMAGE_BASE_URL, RECOGNITION_MODEL4).Wait();
+            // </snippet_maincalls>
+        }
+
+        // <snippet_auth>
+        public static FaceClient Authenticate(string endpoint, string key)
+        {
+            return new FaceClient(new Uri(endpoint), new AzureKeyCredential(key));
+        }
+        // </snippet_auth>
+
+        // <snippet_face_detect_recognize>
+        private static async Task<List<FaceDetectionResult>> DetectFaceRecognize(FaceClient faceClient, string url, FaceRecognitionModel recognition_model)
+        {
+            // Detect faces from image URL.
+            Response<IReadOnlyList<FaceDetectionResult>> response = await faceClient.DetectAsync(new Uri(url), FaceDetectionModel.Detection03, recognition_model, returnFaceId: true, [FaceAttributeType.QualityForRecognition]);
+            IReadOnlyList<FaceDetectionResult> detectedFaces = response.Value;
+            List<FaceDetectionResult> sufficientQualityFaces = new List<FaceDetectionResult>();
+            foreach (FaceDetectionResult detectedFace in detectedFaces)
+            {
+                var faceQualityForRecognition = detectedFace.FaceAttributes.QualityForRecognition;
+                if (faceQualityForRecognition.HasValue && (faceQualityForRecognition.Value != QualityForRecognition.Low))
+                {
+                    sufficientQualityFaces.Add(detectedFace);
+                }
+            }
+            Console.WriteLine($"{detectedFaces.Count} face(s) with {sufficientQualityFaces.Count} having sufficient quality for recognition detected from image `{Path.GetFileName(url)}`");
+
+            return sufficientQualityFaces;
+        }
+        // </snippet_face_detect_recognize>
+
+        public static async Task FindSimilar(FaceClient client, string base_url, FaceRecognitionModel recognition_model)
+        {
+            // <snippet_loadfaces>
+            Console.WriteLine("========FIND SIMILAR========");
+            Console.WriteLine();
+
+            List<string> targetImageFileNames = new List<string>
+                                {
+                                    "Family1-Dad1.jpg",
+                                    "Family1-Daughter1.jpg",
+                                    "Family1-Mom1.jpg",
+                                    "Family1-Son1.jpg",
+                                    "Family2-Lady1.jpg",
+                                    "Family2-Man1.jpg",
+                                    "Family3-Lady1.jpg",
+                                    "Family3-Man1.jpg"
+                                };
+
+            string sourceImageFileName = "findsimilar.jpg";
+            IList<Guid> targetFaceIds = new List<Guid>();
+            foreach (var targetImageFileName in targetImageFileNames)
+            {
+                // Detect faces from target image url.
+                var faces = await DetectFaceRecognize(client, $"{base_url}{targetImageFileName}", recognition_model);
+                // Add detected faceId to list of GUIDs.
+                targetFaceIds.Add(faces[0].FaceId.Value);
+            }
+
+            // Detect faces from source image url.
+            IList<FaceDetectionResult> detectedFaces = await DetectFaceRecognize(client, $"{base_url}{sourceImageFileName}", recognition_model);
+            Console.WriteLine();
+            // </snippet_loadfaces>
+
+            // <snippet_find_similar>
+            // Find a similar face(s) in the list of IDs. Comapring only the first in list for testing purposes.
+            Response<IReadOnlyList<FaceFindSimilarResult>> response = await client.FindSimilarAsync(detectedFaces[0].FaceId.Value, targetFaceIds);
+            IList<FaceFindSimilarResult> similarResults = response.Value.ToList();
+            // </snippet_find_similar>
+            // <snippet_find_similar_print>
+            foreach (var similarResult in similarResults)
+            {
+                Console.WriteLine($"Faces from {sourceImageFileName} & ID:{similarResult.FaceId} are similar with confidence: {similarResult.Confidence}.");
+            }
+            Console.WriteLine();
+            // </snippet_find_similar_print>
+        }
+    }
+}