Amazon Rekognition 示例使用 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);
            }
        }
    }

顯示映像中所有人臉的邊界框資訊。

    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);
            }
        }
    }

偵測儲存於您計算機的映像檔案中的標籤。

    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}");
            });
        }
    }

顯示如何開發照片資產管理應用程式，以便使用 Amazon Rekognition 偵測圖片中的標籤，並將其儲存以供日後擷取。

有關如何設置和運行的完整源代碼和說明，請參閱中的完整示例 GitHub。

如要深入探索此範例的來源，請參閱 AWS  社群上的文章。

說明如何使用 Amazon Rekognition。 NETAPI建立一個應用程式，該應用程式使用 Amazon Rekognition 在位於亞馬遜簡單儲存服務 (Amazon S3) 儲存貯體中的映像檔中按類別識別物件。該應用程序向管理員發送電子郵件通知，其中包含使用 Amazon 簡單電子郵件服務（AmazonSES）的結果

有關如何設置和運行的完整源代碼和說明，請參閱中的完整示例GitHub。