Index faces to an Amazon Rekognition collection using an AWS SDK - AWS SDK Code Examples

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

Index faces to an Amazon Rekognition collection using an AWS SDK

The following code examples show how to index faces in an image and add them to an Amazon Rekognition collection.

For more information, see Adding faces to a collection.

.NET
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. The example was /// created using the AWS SDK for .NET and .NET Core 5.0. /// </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}"); } } }
  • For API details, see IndexFaces in AWS SDK for .NET API Reference.

Java
SDK for Java 2.x
Note

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

public static void addToCollection(RekognitionClient rekClient, String collectionId, String sourceImage) { try { InputStream sourceStream = new FileInputStream(sourceImage); SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream); Image souImage = Image.builder() .bytes(sourceBytes) .build(); IndexFacesRequest facesRequest = IndexFacesRequest.builder() .collectionId(collectionId) .image(souImage) .maxFaces(1) .qualityFilter(QualityFilter.AUTO) .detectionAttributes(Attribute.DEFAULT) .build(); IndexFacesResponse facesResponse = rekClient.indexFaces(facesRequest); System.out.println("Results for the image"); System.out.println("\n Faces indexed:"); List<FaceRecord> faceRecords = facesResponse.faceRecords(); for (FaceRecord faceRecord : faceRecords) { System.out.println(" Face ID: " + faceRecord.face().faceId()); System.out.println(" Location:" + faceRecord.faceDetail().boundingBox().toString()); } List<UnindexedFace> unindexedFaces = facesResponse.unindexedFaces(); System.out.println("Faces not indexed:"); for (UnindexedFace unindexedFace : unindexedFaces) { System.out.println(" Location:" + unindexedFace.faceDetail().boundingBox().toString()); System.out.println(" Reasons:"); for (Reason reason : unindexedFace.reasons()) { System.out.println("Reason: " + reason); } } } catch (RekognitionException | FileNotFoundException e) { System.out.println(e.getMessage()); System.exit(1); } }
  • For API details, see IndexFaces in AWS SDK for Java 2.x API Reference.

Kotlin
SDK for Kotlin
Note

This is prerelease documentation for a feature in preview release. It is subject to change.

Note

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

suspend fun addToCollection(collectionIdVal: String?, sourceImage: String) { val souImage = Image { bytes = (File(sourceImage).readBytes()) } val request = IndexFacesRequest { collectionId = collectionIdVal image = souImage maxFaces = 1 qualityFilter = QualityFilter.Auto detectionAttributes = listOf(Attribute.Default) } RekognitionClient { region = "us-east-1" }.use { rekClient -> val facesResponse = rekClient.indexFaces(request) // Display the results. println("Results for the image") println("\n Faces indexed:") facesResponse.faceRecords?.forEach { faceRecord -> println("Face ID: ${faceRecord.face?.faceId}") println("Location: ${faceRecord.faceDetail?.boundingBox}") } println("Faces not indexed:") facesResponse.unindexedFaces?.forEach { unindexedFace -> println("Location: ${unindexedFace.faceDetail?.boundingBox}") println("Reasons:") unindexedFace.reasons?.forEach { reason -> println("Reason: $reason") } } } }
  • For API details, see IndexFaces in AWS SDK for Kotlin API reference.

Python
SDK for Python (Boto3)
Note

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

class RekognitionCollection: """ Encapsulates an Amazon Rekognition collection. This class is a thin wrapper around parts of the Boto3 Amazon Rekognition API. """ def __init__(self, collection, rekognition_client): """ Initializes a collection object. :param collection: Collection data in the format returned by a call to create_collection. :param rekognition_client: A Boto3 Rekognition client. """ self.collection_id = collection['CollectionId'] self.collection_arn, self.face_count, self.created = self._unpack_collection( collection) self.rekognition_client = rekognition_client @staticmethod def _unpack_collection(collection): """ Unpacks optional parts of a collection that can be returned by describe_collection. :param collection: The collection data. :return: A tuple of the data in the collection. """ return ( collection.get('CollectionArn'), collection.get('FaceCount', 0), collection.get('CreationTimestamp')) def index_faces(self, image, max_faces): """ Finds faces in the specified image, indexes them, and stores them in the collection. :param image: The image to index. :param max_faces: The maximum number of faces to index. :return: A tuple. The first element is a list of indexed faces. The second element is a list of faces that couldn't be indexed. """ try: response = self.rekognition_client.index_faces( CollectionId=self.collection_id, Image=image.image, ExternalImageId=image.image_name, MaxFaces=max_faces, DetectionAttributes=['ALL']) indexed_faces = [ RekognitionFace({**face['Face'], **face['FaceDetail']}) for face in response['FaceRecords']] unindexed_faces = [ RekognitionFace(face['FaceDetail']) for face in response['UnindexedFaces']] logger.info( "Indexed %s faces in %s. Could not index %s faces.", len(indexed_faces), image.image_name, len(unindexed_faces)) except ClientError: logger.exception("Couldn't index faces in image %s.", image.image_name) raise else: return indexed_faces, unindexed_faces
  • For API details, see IndexFaces in AWS SDK for Python (Boto3) API Reference.