Amazon Rekognition examples using AWS SDK for .NET - AWS SDK Code Examples

There are more AWS SDK examples available in the AWS Doc SDK Examples GitHub repo.

Amazon Rekognition examples using AWS SDK for .NET

The following code examples show you how to perform actions and implement common scenarios by using the AWS SDK for .NET with Amazon Rekognition.

Actions are code excerpts from larger programs and must be run in context. While actions show you how to call individual service functions, you can see actions in context in their related scenarios.

Scenarios are code examples that show you how to accomplish specific tasks by calling multiple functions within a service or combined with other AWS services.

Each example includes a link to the complete source code, where you can find instructions on how to set up and run the code in context.

Actions

The following code example shows how to use CompareFaces.

For more information, see Comparing faces in images.

AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

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."); } }
  • For API details, see CompareFaces in AWS SDK for .NET API Reference.

The following code example shows how to use CreateCollection.

For more information, see Creating a collection.

AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

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}"); } }

The following code example shows how to use DeleteCollection.

For more information, see Deleting a collection.

AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

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}"); } }

The following code example shows how to use DeleteFaces.

For more information, see Deleting faces from a collection.

AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

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}"); }); } }
  • For API details, see DeleteFaces in AWS SDK for .NET API Reference.

The following code example shows how to use DescribeCollection.

For more information, see Describing a collection.

AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

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}"); } }

The following code example shows how to use DetectFaces.

For more information, see Detecting faces in an image.

AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

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 = "amzn-s3-demo-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); } } }

Display bounding box information for all faces in an image.

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}"); } }
  • For API details, see DetectFaces in AWS SDK for .NET API Reference.

The following code example shows how to use DetectLabels.

For more information, see Detecting labels in an image.

AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

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 = "amzn-s3-demo-bucket"; // "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); } } }

Detect labels in an image file stored on your computer.

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); } } }
  • For API details, see DetectLabels in AWS SDK for .NET API Reference.

The following code example shows how to use DetectModerationLabels.

For more information, see Detecting inappropriate images.

AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

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 = "amzn-s3-demo-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); } } }

The following code example shows how to use DetectText.

For more information, see Detecting text in an image.

AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

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 = "amzn-s3-demo-bucket"; // "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); } } }
  • For API details, see DetectText in AWS SDK for .NET API Reference.

The following code example shows how to use GetCelebrityInfo.

AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

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); }); } }

The following code example shows how to use IndexFaces.

For more information, see Adding faces to a collection.

AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

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 = "amzn-s3-demo-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}"); } } }
  • For API details, see IndexFaces in AWS SDK for .NET API Reference.

The following code example shows how to use ListCollections.

For more information, see Listing collections.

AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

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); } }

The following code example shows how to use ListFaces.

For more information, see Listing faces in a collection.

AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

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)); } }
  • For API details, see ListFaces in AWS SDK for .NET API Reference.

The following code example shows how to use RecognizeCelebrities.

For more information, see Recognizing celebrities in an image.

AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

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."); } }

The following code example shows how to use SearchFaces.

For more information, see Searching for a face (face ID).

AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

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}"); }); } }
  • For API details, see SearchFaces in AWS SDK for .NET API Reference.

The following code example shows how to use SearchFacesByImage.

For more information, see Searching for a face (image).

AWS SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

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 = "amzn-s3-demo-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}"); }); } }

Scenarios

The following code example shows how to create a serverless application that lets users manage photos using labels.

AWS SDK for .NET

Shows how to develop a photo asset management application that detects labels in images using Amazon Rekognition and stores them for later retrieval.

For complete source code and instructions on how to set up and run, see the full example on GitHub.

For a deep dive into the origin of this example see the post on AWS Community.

Services used in this example
  • API Gateway

  • DynamoDB

  • Lambda

  • Amazon Rekognition

  • Amazon S3

  • Amazon SNS

The following code example shows how to build an app that uses Amazon Rekognition to detect objects by category in images.

AWS SDK for .NET

Shows how to use Amazon Rekognition .NET API to create an app that uses Amazon Rekognition to identify objects by category in images located in an Amazon Simple Storage Service (Amazon S3) bucket. The app sends the admin an email notification with the results using Amazon Simple Email Service (Amazon SES).

For complete source code and instructions on how to set up and run, see the full example on GitHub.

Services used in this example
  • Amazon Rekognition

  • Amazon S3

  • Amazon SES