Utilizzare IndexFaces con un SDK AWS o una CLI - Esempi di codice per SDK AWS

Sono disponibili altri esempi per SDK AWS nel repository GitHub della documentazione degli esempi per SDK AWS.

Utilizzare IndexFaces con un SDK AWS o una CLI

Gli esempi di codice seguenti mostrano come utilizzare IndexFaces.

Per ulteriori informazioni, consulta Indicizzazione dei volti in una raccolta.

.NET
SDK per .NET
Nota

Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS.

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}"); } } }
  • Per informazioni dettagliate sull’API, consulta IndexFaces nella documentazione di riferimento dell’API AWS SDK per .NET.

CLI
AWS CLI

Come aggiungere volti a una raccolta

Il comando index-faces seguente aggiunge i volti trovati in un’immagine alla raccolta specificata.

aws rekognition index-faces \ --image '{"S3Object":{"Bucket":"MyVideoS3Bucket","Name":"MyPicture.jpg"}}' \ --collection-id MyCollection \ --max-faces 1 \ --quality-filter "AUTO" \ --detection-attributes "ALL" \ --external-image-id "MyPicture.jpg"

Output:

{ "FaceRecords": [ { "FaceDetail": { "Confidence": 99.993408203125, "Eyeglasses": { "Confidence": 99.11750030517578, "Value": false }, "Sunglasses": { "Confidence": 99.98249053955078, "Value": false }, "Gender": { "Confidence": 99.92769622802734, "Value": "Male" }, "Landmarks": [ { "Y": 0.26750367879867554, "X": 0.6202793717384338, "Type": "eyeLeft" }, { "Y": 0.26642778515815735, "X": 0.6787431836128235, "Type": "eyeRight" }, { "Y": 0.31361380219459534, "X": 0.6421601176261902, "Type": "nose" }, { "Y": 0.3495299220085144, "X": 0.6216195225715637, "Type": "mouthLeft" }, { "Y": 0.35194727778434753, "X": 0.669899046421051, "Type": "mouthRight" }, { "Y": 0.26844894886016846, "X": 0.6210268139839172, "Type": "leftPupil" }, { "Y": 0.26707562804222107, "X": 0.6817160844802856, "Type": "rightPupil" }, { "Y": 0.24834522604942322, "X": 0.6018546223640442, "Type": "leftEyeBrowLeft" }, { "Y": 0.24397172033786774, "X": 0.6172008514404297, "Type": "leftEyeBrowUp" }, { "Y": 0.24677404761314392, "X": 0.6339119076728821, "Type": "leftEyeBrowRight" }, { "Y": 0.24582654237747192, "X": 0.6619398593902588, "Type": "rightEyeBrowLeft" }, { "Y": 0.23973053693771362, "X": 0.6804757118225098, "Type": "rightEyeBrowUp" }, { "Y": 0.24441994726657867, "X": 0.6978968977928162, "Type": "rightEyeBrowRight" }, { "Y": 0.2695908546447754, "X": 0.6085202693939209, "Type": "leftEyeLeft" }, { "Y": 0.26716896891593933, "X": 0.6315826177597046, "Type": "leftEyeRight" }, { "Y": 0.26289820671081543, "X": 0.6202316880226135, "Type": "leftEyeUp" }, { "Y": 0.27123287320137024, "X": 0.6205548048019409, "Type": "leftEyeDown" }, { "Y": 0.2668408751487732, "X": 0.6663622260093689, "Type": "rightEyeLeft" }, { "Y": 0.26741549372673035, "X": 0.6910083889961243, "Type": "rightEyeRight" }, { "Y": 0.2614026665687561, "X": 0.6785826086997986, "Type": "rightEyeUp" }, { "Y": 0.27075251936912537, "X": 0.6789616942405701, "Type": "rightEyeDown" }, { "Y": 0.3211299479007721, "X": 0.6324167847633362, "Type": "noseLeft" }, { "Y": 0.32276326417922974, "X": 0.6558475494384766, "Type": "noseRight" }, { "Y": 0.34385165572166443, "X": 0.6444970965385437, "Type": "mouthUp" }, { "Y": 0.3671635091304779, "X": 0.6459195017814636, "Type": "mouthDown" } ], "Pose": { "Yaw": -9.54541015625, "Roll": -0.5709401965141296, "Pitch": 0.6045494675636292 }, "Emotions": [ { "Confidence": 39.90074157714844, "Type": "HAPPY" }, { "Confidence": 23.38753890991211, "Type": "CALM" }, { "Confidence": 5.840933322906494, "Type": "CONFUSED" } ], "AgeRange": { "High": 63, "Low": 45 }, "EyesOpen": { "Confidence": 99.80887603759766, "Value": true }, "BoundingBox": { "Width": 0.18562500178813934, "Top": 0.1618015021085739, "Left": 0.5575000047683716, "Height": 0.24770642817020416 }, "Smile": { "Confidence": 99.69740295410156, "Value": false }, "MouthOpen": { "Confidence": 99.97393798828125, "Value": false }, "Quality": { "Sharpness": 95.54405975341797, "Brightness": 63.867706298828125 }, "Mustache": { "Confidence": 97.05007934570312, "Value": false }, "Beard": { "Confidence": 87.34505462646484, "Value": false } }, "Face": { "BoundingBox": { "Width": 0.18562500178813934, "Top": 0.1618015021085739, "Left": 0.5575000047683716, "Height": 0.24770642817020416 }, "FaceId": "ce7ed422-2132-4a11-ab14-06c5c410f29f", "ExternalImageId": "example-image.jpg", "Confidence": 99.993408203125, "ImageId": "8d67061e-90d2-598f-9fbd-29c8497039c0" } } ], "UnindexedFaces": [], "FaceModelVersion": "3.0", "OrientationCorrection": "ROTATE_0" }

Per ulteriori informazioni, consulta Aggiunta di volti a una raccolta nella Guida per gli sviluppatori di Amazon Rekognition.

  • Per informazioni dettagliate sull’API, consulta IndexFaces nella documentazione di riferimento dei comandi della AWS CLI.

Java
SDK per Java 2.x
Nota

Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS.

import software.amazon.awssdk.regions.Region; import software.amazon.awssdk.services.rekognition.RekognitionClient; import software.amazon.awssdk.services.rekognition.model.*; import java.util.List; /** * Before running this Java V2 code example, set up your development * environment, including your credentials. * * For more information, see the following documentation topic: * * https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html */ public class AddFacesToCollection { public static void main(String[] args) { final String usage = """ Usage: <collectionId> <sourceImage> <bucketName> Where: collectionName - The name of the collection. sourceImage - The name of the image (for example, pic1.png). bucketName - The name of the S3 bucket. """; if (args.length != 3) { System.out.println(usage); System.exit(1); } String collectionId = args[0]; String sourceImage = args[1]; String bucketName = args[2];; Region region = Region.US_EAST_1; RekognitionClient rekClient = RekognitionClient.builder() .region(region) .build(); addToCollection(rekClient, collectionId, bucketName, sourceImage); rekClient.close(); } /** * Adds a face from an image to an Amazon Rekognition collection. * * @param rekClient the Amazon Rekognition client * @param collectionId the ID of the collection to add the face to * @param bucketName the name of the Amazon S3 bucket containing the image * @param sourceImage the name of the image file to add to the collection * @throws RekognitionException if there is an error while interacting with the Amazon Rekognition service */ public static void addToCollection(RekognitionClient rekClient, String collectionId, String bucketName, String sourceImage) { try { S3Object s3ObjectTarget = S3Object.builder() .bucket(bucketName) .name(sourceImage) .build(); Image targetImage = Image.builder() .s3Object(s3ObjectTarget) .build(); IndexFacesRequest facesRequest = IndexFacesRequest.builder() .collectionId(collectionId) .image(targetImage) .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 e) { System.out.println(e.getMessage()); System.exit(1); } } }
  • Per informazioni dettagliate sull’API, consulta IndexFaces nella documentazione di riferimento dell’API AWS SDK for Java 2.x.

Kotlin
SDK per Kotlin
Nota

Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS.

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.fromEnvironment { 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") } } } }
  • Per informazioni dettagliate sull’API, consulta IndexFaces nella documentazione di riferimento dell’API AWS SDK per Kotlin.

Python
SDK per Python (Boto3)
Nota

Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS.

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
  • Per informazioni dettagliate sull’API, consulta IndexFaces nella documentazione di riferimento delle API AWS SDK per Python (Boto3).