Amazon Rekognition Rekognition-Beispiele mit AWS SDK for .NET

    using System;
    using System.IO;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Uses the Amazon Rekognition Service to compare faces in two images.
    /// </summary>
    public class CompareFaces
    {
        public static async Task Main()
        {
            float similarityThreshold = 70F;
            string sourceImage = "source.jpg";
            string targetImage = "target.jpg";

            var rekognitionClient = new AmazonRekognitionClient();

            Amazon.Rekognition.Model.Image imageSource = new Amazon.Rekognition.Model.Image();

            try
            {
                using FileStream fs = new FileStream(sourceImage, FileMode.Open, FileAccess.Read);
                byte[] data = new byte[fs.Length];
                fs.Read(data, 0, (int)fs.Length);
                imageSource.Bytes = new MemoryStream(data);
            }
            catch (Exception)
            {
                Console.WriteLine($"Failed to load source image: {sourceImage}");
                return;
            }

            Amazon.Rekognition.Model.Image imageTarget = new Amazon.Rekognition.Model.Image();

            try
            {
                using FileStream fs = new FileStream(targetImage, FileMode.Open, FileAccess.Read);
                byte[] data = new byte[fs.Length];
                data = new byte[fs.Length];
                fs.Read(data, 0, (int)fs.Length);
                imageTarget.Bytes = new MemoryStream(data);
            }
            catch (Exception ex)
            {
                Console.WriteLine($"Failed to load target image: {targetImage}");
                Console.WriteLine(ex.Message);
                return;
            }

            var compareFacesRequest = new CompareFacesRequest
            {
                SourceImage = imageSource,
                TargetImage = imageTarget,
                SimilarityThreshold = similarityThreshold,
            };

            // Call operation
            var compareFacesResponse = await rekognitionClient.CompareFacesAsync(compareFacesRequest);

            // Display results
            compareFacesResponse.FaceMatches.ForEach(match =>
            {
                ComparedFace face = match.Face;
                BoundingBox position = face.BoundingBox;
                Console.WriteLine($"Face at {position.Left} {position.Top} matches with {match.Similarity}% confidence.");
            });

            Console.WriteLine($"Found {compareFacesResponse.UnmatchedFaces.Count} face(s) that did not match.");
        }
    }

    using System;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Uses Amazon Rekognition to create a collection to which you can add
    /// faces using the IndexFaces operation.
    /// </summary>
    public class CreateCollection
    {
        public static async Task Main()
        {
            var rekognitionClient = new AmazonRekognitionClient();

            string collectionId = "MyCollection";
            Console.WriteLine("Creating collection: " + collectionId);

            var createCollectionRequest = new CreateCollectionRequest
            {
                CollectionId = collectionId,
            };

            CreateCollectionResponse createCollectionResponse = await rekognitionClient.CreateCollectionAsync(createCollectionRequest);
            Console.WriteLine($"CollectionArn : {createCollectionResponse.CollectionArn}");
            Console.WriteLine($"Status code : {createCollectionResponse.StatusCode}");
        }
    }

    using System;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Uses the Amazon Rekognition Service to delete an existing collection.
    /// </summary>
    public class DeleteCollection
    {
        public static async Task Main()
        {
            var rekognitionClient = new AmazonRekognitionClient();

            string collectionId = "MyCollection";
            Console.WriteLine("Deleting collection: " + collectionId);

            var deleteCollectionRequest = new DeleteCollectionRequest()
            {
                CollectionId = collectionId,
            };

            var deleteCollectionResponse = await rekognitionClient.DeleteCollectionAsync(deleteCollectionRequest);
            Console.WriteLine($"{collectionId}: {deleteCollectionResponse.StatusCode}");
        }
    }

    using System;
    using System.Collections.Generic;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Uses the Amazon Rekognition Service to delete one or more faces from
    /// a Rekognition collection.
    /// </summary>
    public class DeleteFaces
    {
        public static async Task Main()
        {
            string collectionId = "MyCollection";
            var faces = new List<string> { "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" };

            var rekognitionClient = new AmazonRekognitionClient();

            var deleteFacesRequest = new DeleteFacesRequest()
            {
                CollectionId = collectionId,
                FaceIds = faces,
            };

            DeleteFacesResponse deleteFacesResponse = await rekognitionClient.DeleteFacesAsync(deleteFacesRequest);
            deleteFacesResponse.DeletedFaces.ForEach(face =>
            {
                Console.WriteLine($"FaceID: {face}");
            });
        }
    }

    using System;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Uses the Amazon Rekognition Service to describe the contents of a
    /// collection.
    /// </summary>
    public class DescribeCollection
    {
        public static async Task Main()
        {
            var rekognitionClient = new AmazonRekognitionClient();

            string collectionId = "MyCollection";
            Console.WriteLine($"Describing collection: {collectionId}");

            var describeCollectionRequest = new DescribeCollectionRequest()
            {
                CollectionId = collectionId,
            };

            var describeCollectionResponse = await rekognitionClient.DescribeCollectionAsync(describeCollectionRequest);
            Console.WriteLine($"Collection ARN: {describeCollectionResponse.CollectionARN}");
            Console.WriteLine($"Face count: {describeCollectionResponse.FaceCount}");
            Console.WriteLine($"Face model version: {describeCollectionResponse.FaceModelVersion}");
            Console.WriteLine($"Created: {describeCollectionResponse.CreationTimestamp}");
        }
    }

    using System;
    using System.Collections.Generic;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Uses the Amazon Rekognition Service to detect faces within an image
    /// stored in an Amazon Simple Storage Service (Amazon S3) bucket.
    /// </summary>
    public class DetectFaces
    {
        public static async Task Main()
        {
            string photo = "input.jpg";
            string bucket = "bucket";

            var rekognitionClient = new AmazonRekognitionClient();

            var detectFacesRequest = new DetectFacesRequest()
            {
                Image = new Image()
                {
                    S3Object = new S3Object()
                    {
                        Name = photo,
                        Bucket = bucket,
                    },
                },

                // Attributes can be "ALL" or "DEFAULT".
                // "DEFAULT": BoundingBox, Confidence, Landmarks, Pose, and Quality.
                // "ALL": See https://docs.aws.amazon.com/sdkfornet/v3/apidocs/items/Rekognition/TFaceDetail.html
                Attributes = new List<string>() { "ALL" },
            };

            try
            {
                DetectFacesResponse detectFacesResponse = await rekognitionClient.DetectFacesAsync(detectFacesRequest);
                bool hasAll = detectFacesRequest.Attributes.Contains("ALL");
                foreach (FaceDetail face in detectFacesResponse.FaceDetails)
                {
                    Console.WriteLine($"BoundingBox: top={face.BoundingBox.Left} left={face.BoundingBox.Top} width={face.BoundingBox.Width} height={face.BoundingBox.Height}");
                    Console.WriteLine($"Confidence: {face.Confidence}");
                    Console.WriteLine($"Landmarks: {face.Landmarks.Count}");
                    Console.WriteLine($"Pose: pitch={face.Pose.Pitch} roll={face.Pose.Roll} yaw={face.Pose.Yaw}");
                    Console.WriteLine($"Brightness: {face.Quality.Brightness}\tSharpness: {face.Quality.Sharpness}");

                    if (hasAll)
                    {
                        Console.WriteLine($"Estimated age is between {face.AgeRange.Low} and {face.AgeRange.High} years old.");
                    }
                }
            }
            catch (Exception ex)
            {
                Console.WriteLine(ex.Message);
            }
        }
    }

Zeigt Informationen zum Begrenzungsrahmen für alle Gesichter in einem Bild an.

    using System;
    using System.Collections.Generic;
    using System.Drawing;
    using System.IO;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Uses the Amazon Rekognition Service to display the details of the
    /// bounding boxes around the faces detected in an image.
    /// </summary>
    public class ImageOrientationBoundingBox
    {
        public static async Task Main()
        {
            string photo = @"D:\Development\AWS-Examples\Rekognition\target.jpg"; // "photo.jpg";

            var rekognitionClient = new AmazonRekognitionClient();

            var image = new Amazon.Rekognition.Model.Image();
            try
            {
                using var fs = new FileStream(photo, FileMode.Open, FileAccess.Read);
                byte[] data = null;
                data = new byte[fs.Length];
                fs.Read(data, 0, (int)fs.Length);
                image.Bytes = new MemoryStream(data);
            }
            catch (Exception)
            {
                Console.WriteLine("Failed to load file " + photo);
                return;
            }

            int height;
            int width;

            // Used to extract original photo width/height
            using (var imageBitmap = new Bitmap(photo))
            {
                height = imageBitmap.Height;
                width = imageBitmap.Width;
            }

            Console.WriteLine("Image Information:");
            Console.WriteLine(photo);
            Console.WriteLine("Image Height: " + height);
            Console.WriteLine("Image Width: " + width);

            try
            {
                var detectFacesRequest = new DetectFacesRequest()
                {
                    Image = image,
                    Attributes = new List<string>() { "ALL" },
                };

                DetectFacesResponse detectFacesResponse = await rekognitionClient.DetectFacesAsync(detectFacesRequest);
                detectFacesResponse.FaceDetails.ForEach(face =>
                {
                    Console.WriteLine("Face:");
                    ShowBoundingBoxPositions(
                        height,
                        width,
                        face.BoundingBox,
                        detectFacesResponse.OrientationCorrection);

                    Console.WriteLine($"BoundingBox: top={face.BoundingBox.Left} left={face.BoundingBox.Top} width={face.BoundingBox.Width} height={face.BoundingBox.Height}");
                    Console.WriteLine($"The detected face is estimated to be between {face.AgeRange.Low} and {face.AgeRange.High} years old.\n");
                });
            }
            catch (Exception ex)
            {
                Console.WriteLine(ex.Message);
            }
        }

        /// <summary>
        /// Display the bounding box information for an image.
        /// </summary>
        /// <param name="imageHeight">The height of the image.</param>
        /// <param name="imageWidth">The width of the image.</param>
        /// <param name="box">The bounding box for a face found within the image.</param>
        /// <param name="rotation">The rotation of the face's bounding box.</param>
        public static void ShowBoundingBoxPositions(int imageHeight, int imageWidth, BoundingBox box, string rotation)
        {
            float left;
            float top;

            if (rotation == null)
            {
                Console.WriteLine("No estimated orientation. Check Exif data.");
                return;
            }

            // Calculate face position based on image orientation.
            switch (rotation)
            {
                case "ROTATE_0":
                    left = imageWidth * box.Left;
                    top = imageHeight * box.Top;
                    break;
                case "ROTATE_90":
                    left = imageHeight * (1 - (box.Top + box.Height));
                    top = imageWidth * box.Left;
                    break;
                case "ROTATE_180":
                    left = imageWidth - (imageWidth * (box.Left + box.Width));
                    top = imageHeight * (1 - (box.Top + box.Height));
                    break;
                case "ROTATE_270":
                    left = imageHeight * box.Top;
                    top = imageWidth * (1 - box.Left - box.Width);
                    break;
                default:
                    Console.WriteLine("No estimated orientation information. Check Exif data.");
                    return;
            }

            // Display face location information.
            Console.WriteLine($"Left: {left}");
            Console.WriteLine($"Top: {top}");
            Console.WriteLine($"Face Width: {imageWidth * box.Width}");
            Console.WriteLine($"Face Height: {imageHeight * box.Height}");
        }
    }

    using System;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Uses the Amazon Rekognition Service to detect labels within an image
    /// stored in an Amazon Simple Storage Service (Amazon S3) bucket.
    /// </summary>
    public class DetectLabels
    {
        public static async Task Main()
        {
            string photo = "del_river_02092020_01.jpg"; // "input.jpg";
            string bucket = "igsmiths3photos"; // "bucket";

            var rekognitionClient = new AmazonRekognitionClient();

            var detectlabelsRequest = new DetectLabelsRequest
            {
                Image = new Image()
                {
                    S3Object = new S3Object()
                    {
                        Name = photo,
                        Bucket = bucket,
                    },
                },
                MaxLabels = 10,
                MinConfidence = 75F,
            };

            try
            {
                DetectLabelsResponse detectLabelsResponse = await rekognitionClient.DetectLabelsAsync(detectlabelsRequest);
                Console.WriteLine("Detected labels for " + photo);
                foreach (Label label in detectLabelsResponse.Labels)
                {
                    Console.WriteLine($"Name: {label.Name} Confidence: {label.Confidence}");
                }
            }
            catch (Exception ex)
            {
                Console.WriteLine(ex.Message);
            }
        }
    }

Erkennen Sie Labels in einer Bilddatei, die auf Ihrem Computer gespeichert ist.

    using System;
    using System.IO;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Uses the Amazon Rekognition Service to detect labels within an image
    /// stored locally.
    /// </summary>
    public class DetectLabelsLocalFile
    {
        public static async Task Main()
        {
            string photo = "input.jpg";

            var image = new Amazon.Rekognition.Model.Image();
            try
            {
                using var fs = new FileStream(photo, FileMode.Open, FileAccess.Read);
                byte[] data = null;
                data = new byte[fs.Length];
                fs.Read(data, 0, (int)fs.Length);
                image.Bytes = new MemoryStream(data);
            }
            catch (Exception)
            {
                Console.WriteLine("Failed to load file " + photo);
                return;
            }

            var rekognitionClient = new AmazonRekognitionClient();

            var detectlabelsRequest = new DetectLabelsRequest
            {
                Image = image,
                MaxLabels = 10,
                MinConfidence = 77F,
            };

            try
            {
                DetectLabelsResponse detectLabelsResponse = await rekognitionClient.DetectLabelsAsync(detectlabelsRequest);
                Console.WriteLine($"Detected labels for {photo}");
                foreach (Label label in detectLabelsResponse.Labels)
                {
                    Console.WriteLine($"{label.Name}: {label.Confidence}");
                }
            }
            catch (Exception ex)
            {
                Console.WriteLine(ex.Message);
            }
        }
    }

    using System;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Uses the Amazon Rekognition Service to detect unsafe content in a
    /// JPEG or PNG format image.
    /// </summary>
    public class DetectModerationLabels
    {
        public static async Task Main(string[] args)
        {
            string photo = "input.jpg";
            string bucket = "bucket";

            var rekognitionClient = new AmazonRekognitionClient();

            var detectModerationLabelsRequest = new DetectModerationLabelsRequest()
            {
                Image = new Image()
                {
                    S3Object = new S3Object()
                    {
                        Name = photo,
                        Bucket = bucket,
                    },
                },
                MinConfidence = 60F,
            };

            try
            {
                var detectModerationLabelsResponse = await rekognitionClient.DetectModerationLabelsAsync(detectModerationLabelsRequest);
                Console.WriteLine("Detected labels for " + photo);
                foreach (ModerationLabel label in detectModerationLabelsResponse.ModerationLabels)
                {
                    Console.WriteLine($"Label: {label.Name}");
                    Console.WriteLine($"Confidence: {label.Confidence}");
                    Console.WriteLine($"Parent: {label.ParentName}");
                }
            }
            catch (Exception ex)
            {
                Console.WriteLine(ex.Message);
            }
        }
    }

    using System;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Uses the Amazon Rekognition Service to detect text in an image. The
    /// example was created using the AWS SDK for .NET version 3.7 and .NET
    /// Core 5.0.
    /// </summary>
    public class DetectText
    {
        public static async Task Main()
        {
            string photo = "Dad_photographer.jpg"; // "input.jpg";
            string bucket = "igsmiths3photos"; // "bucket";

            var rekognitionClient = new AmazonRekognitionClient();

            var detectTextRequest = new DetectTextRequest()
            {
                Image = new Image()
                {
                    S3Object = new S3Object()
                    {
                        Name = photo,
                        Bucket = bucket,
                    },
                },
            };

            try
            {
                DetectTextResponse detectTextResponse = await rekognitionClient.DetectTextAsync(detectTextRequest);
                Console.WriteLine($"Detected lines and words for {photo}");
                detectTextResponse.TextDetections.ForEach(text =>
                {
                    Console.WriteLine($"Detected: {text.DetectedText}");
                    Console.WriteLine($"Confidence: {text.Confidence}");
                    Console.WriteLine($"Id : {text.Id}");
                    Console.WriteLine($"Parent Id: {text.ParentId}");
                    Console.WriteLine($"Type: {text.Type}");
                });
            }
            catch (Exception e)
            {
                Console.WriteLine(e.Message);
            }
        }
    }

    using System;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Shows how to use Amazon Rekognition to retrieve information about the
    /// celebrity identified by the supplied celebrity Id.
    /// </summary>
    public class CelebrityInfo
    {
        public static async Task Main()
        {
            string celebId = "nnnnnnnn";

            var rekognitionClient = new AmazonRekognitionClient();

            var celebrityInfoRequest = new GetCelebrityInfoRequest
            {
                Id = celebId,
            };

            Console.WriteLine($"Getting information for celebrity: {celebId}");

            var celebrityInfoResponse = await rekognitionClient.GetCelebrityInfoAsync(celebrityInfoRequest);

            // Display celebrity information.
            Console.WriteLine($"celebrity name: {celebrityInfoResponse.Name}");
            Console.WriteLine("Further information (if available):");
            celebrityInfoResponse.Urls.ForEach(url =>
            {
                Console.WriteLine(url);
            });
        }
    }

    using System;
    using System.Collections.Generic;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Uses the Amazon Rekognition Service to detect faces in an image
    /// that has been uploaded to an Amazon Simple Storage Service (Amazon S3)
    /// bucket and then adds the information to a collection.
    /// </summary>
    public class AddFaces
    {
        public static async Task Main()
        {
            string collectionId = "MyCollection2";
            string bucket = "doc-example-bucket";
            string photo = "input.jpg";

            var rekognitionClient = new AmazonRekognitionClient();

            var image = new Image
            {
                S3Object = new S3Object
                {
                    Bucket = bucket,
                    Name = photo,
                },
            };

            var indexFacesRequest = new IndexFacesRequest
            {
                Image = image,
                CollectionId = collectionId,
                ExternalImageId = photo,
                DetectionAttributes = new List<string>() { "ALL" },
            };

            IndexFacesResponse indexFacesResponse = await rekognitionClient.IndexFacesAsync(indexFacesRequest);

            Console.WriteLine($"{photo} added");
            foreach (FaceRecord faceRecord in indexFacesResponse.FaceRecords)
            {
                Console.WriteLine($"Face detected: Faceid is {faceRecord.Face.FaceId}");
            }
        }
    }

    using System;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Uses Amazon Rekognition to list the collection IDs in the
    /// current account.
    /// </summary>
    public class ListCollections
    {
        public static async Task Main()
        {
            var rekognitionClient = new AmazonRekognitionClient();

            Console.WriteLine("Listing collections");
            int limit = 10;

            var listCollectionsRequest = new ListCollectionsRequest
            {
                MaxResults = limit,
            };

            var listCollectionsResponse = new ListCollectionsResponse();

            do
            {
                if (listCollectionsResponse is not null)
                {
                    listCollectionsRequest.NextToken = listCollectionsResponse.NextToken;
                }

                listCollectionsResponse = await rekognitionClient.ListCollectionsAsync(listCollectionsRequest);

                listCollectionsResponse.CollectionIds.ForEach(id =>
                {
                    Console.WriteLine(id);
                });
            }
            while (listCollectionsResponse.NextToken is not null);
        }
    }

    using System;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Uses the Amazon Rekognition Service to retrieve the list of faces
    /// stored in a collection.
    /// </summary>
    public class ListFaces
    {
        public static async Task Main()
        {
            string collectionId = "MyCollection2";

            var rekognitionClient = new AmazonRekognitionClient();

            var listFacesResponse = new ListFacesResponse();
            Console.WriteLine($"Faces in collection {collectionId}");

            var listFacesRequest = new ListFacesRequest
            {
                CollectionId = collectionId,
                MaxResults = 1,
            };

            do
            {
                listFacesResponse = await rekognitionClient.ListFacesAsync(listFacesRequest);
                listFacesResponse.Faces.ForEach(face =>
                {
                    Console.WriteLine(face.FaceId);
                });

                listFacesRequest.NextToken = listFacesResponse.NextToken;
            }
            while (!string.IsNullOrEmpty(listFacesResponse.NextToken));
        }
    }

    using System;
    using System.IO;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Shows how to use Amazon Rekognition to identify celebrities in a photo.
    /// </summary>
    public class CelebritiesInImage
    {
        public static async Task Main(string[] args)
        {
            string photo = "moviestars.jpg";

            var rekognitionClient = new AmazonRekognitionClient();

            var recognizeCelebritiesRequest = new RecognizeCelebritiesRequest();

            var img = new Amazon.Rekognition.Model.Image();
            byte[] data = null;
            try
            {
                using var fs = new FileStream(photo, FileMode.Open, FileAccess.Read);
                data = new byte[fs.Length];
                fs.Read(data, 0, (int)fs.Length);
            }
            catch (Exception)
            {
                Console.WriteLine($"Failed to load file {photo}");
                return;
            }

            img.Bytes = new MemoryStream(data);
            recognizeCelebritiesRequest.Image = img;

            Console.WriteLine($"Looking for celebrities in image {photo}\n");

            var recognizeCelebritiesResponse = await rekognitionClient.RecognizeCelebritiesAsync(recognizeCelebritiesRequest);

            Console.WriteLine($"{recognizeCelebritiesResponse.CelebrityFaces.Count} celebrity(s) were recognized.\n");
            recognizeCelebritiesResponse.CelebrityFaces.ForEach(celeb =>
            {
                Console.WriteLine($"Celebrity recognized: {celeb.Name}");
                Console.WriteLine($"Celebrity ID: {celeb.Id}");
                BoundingBox boundingBox = celeb.Face.BoundingBox;
                Console.WriteLine($"position: {boundingBox.Left} {boundingBox.Top}");
                Console.WriteLine("Further information (if available):");
                celeb.Urls.ForEach(url =>
                {
                    Console.WriteLine(url);
                });
            });

            Console.WriteLine($"{recognizeCelebritiesResponse.UnrecognizedFaces.Count} face(s) were unrecognized.");
        }
    }

    using System;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Uses the Amazon Rekognition Service to find faces in an image that
    /// match the face Id provided in the method request.
    /// </summary>
    public class SearchFacesMatchingId
    {
        public static async Task Main()
        {
            string collectionId = "MyCollection";
            string faceId = "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx";

            var rekognitionClient = new AmazonRekognitionClient();

            // Search collection for faces matching the face id.
            var searchFacesRequest = new SearchFacesRequest
            {
                CollectionId = collectionId,
                FaceId = faceId,
                FaceMatchThreshold = 70F,
                MaxFaces = 2,
            };

            SearchFacesResponse searchFacesResponse = await rekognitionClient.SearchFacesAsync(searchFacesRequest);

            Console.WriteLine("Face matching faceId " + faceId);

            Console.WriteLine("Matche(s): ");
            searchFacesResponse.FaceMatches.ForEach(face =>
            {
                Console.WriteLine($"FaceId: {face.Face.FaceId} Similarity: {face.Similarity}");
            });
        }
    }

    using System;
    using System.Threading.Tasks;
    using Amazon.Rekognition;
    using Amazon.Rekognition.Model;

    /// <summary>
    /// Uses the Amazon Rekognition Service to search for images matching those
    /// in a collection.
    /// </summary>
    public class SearchFacesMatchingImage
    {
        public static async Task Main()
        {
            string collectionId = "MyCollection";
            string bucket = "bucket";
            string photo = "input.jpg";

            var rekognitionClient = new AmazonRekognitionClient();

            // Get an image object from S3 bucket.
            var image = new Image()
            {
                S3Object = new S3Object()
                {
                    Bucket = bucket,
                    Name = photo,
                },
            };

            var searchFacesByImageRequest = new SearchFacesByImageRequest()
            {
                CollectionId = collectionId,
                Image = image,
                FaceMatchThreshold = 70F,
                MaxFaces = 2,
            };

            SearchFacesByImageResponse searchFacesByImageResponse = await rekognitionClient.SearchFacesByImageAsync(searchFacesByImageRequest);

            Console.WriteLine("Faces matching largest face in image from " + photo);
            searchFacesByImageResponse.FaceMatches.ForEach(face =>
            {
                Console.WriteLine($"FaceId: {face.Face.FaceId}, Similarity: {face.Similarity}");
            });
        }
    }

Zeigt, wie eine Anwendung zur Verwaltung von Fotobeständen entwickelt wird, die mithilfe von Amazon Rekognition Labels in Bildern erkennt und sie für einen späteren Abruf speichert.

Den vollständigen Quellcode und Anweisungen zur Einrichtung und Ausführung finden Sie im vollständigen Beispiel unter GitHub.

Einen tiefen Einblick in den Ursprung dieses Beispiels finden Sie im Beitrag in der AWS -Community.

Zeigt, wie Amazon Rekognition verwendet wird. NETAPIum eine App zu erstellen, die Amazon Rekognition verwendet, um Objekte in Bildern, die sich in einem Amazon Simple Storage Service (Amazon S3) -Bucket befinden, nach Kategorien zu identifizieren. Die App sendet dem Administrator mithilfe von Amazon Simple Email Service (AmazonSES) eine E-Mail-Benachrichtigung mit den Ergebnissen.

Den vollständigen Quellcode und Anweisungen zur Einrichtung und Ausführung finden Sie im vollständigen Beispiel unter GitHub.