Utilizzare IndexFaces con un AWS SDK o CLI - Esempi di codice dell'AWS SDK

Ci sono altri AWS SDK esempi disponibili nel repository AWS Doc SDK Examples GitHub .

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Utilizzare IndexFaces con un AWS SDK o CLI

I seguenti esempi di codice mostrano come utilizzareIndexFaces.

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

.NET
AWS SDK for .NET
Nota

C'è altro da fare 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}"); } } }
CLI
AWS CLI

Per aggiungere volti a una raccolta

Il index-faces comando seguente aggiunge le facce trovate 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 Adding Faces to a Collection nella Amazon Rekognition Developer Guide.

  • Per API i dettagli, consulta Command IndexFacesReference AWS CLI .

Java
SDKper Java 2.x
Nota

C'è altro 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.core.SdkBytes; import software.amazon.awssdk.regions.Region; import software.amazon.awssdk.services.rekognition.RekognitionClient; import software.amazon.awssdk.services.rekognition.model.IndexFacesResponse; import software.amazon.awssdk.services.rekognition.model.IndexFacesRequest; import software.amazon.awssdk.services.rekognition.model.Image; import software.amazon.awssdk.services.rekognition.model.QualityFilter; import software.amazon.awssdk.services.rekognition.model.Attribute; import software.amazon.awssdk.services.rekognition.model.FaceRecord; import software.amazon.awssdk.services.rekognition.model.UnindexedFace; import software.amazon.awssdk.services.rekognition.model.RekognitionException; import software.amazon.awssdk.services.rekognition.model.Reason; import java.io.FileInputStream; import java.io.FileNotFoundException; import java.io.InputStream; 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> Where: collectionName - The name of the collection. sourceImage - The path to the image (for example, C:\\AWS\\pic1.png).\s """; if (args.length != 2) { System.out.println(usage); System.exit(1); } String collectionId = args[0]; String sourceImage = args[1]; Region region = Region.US_EAST_1; RekognitionClient rekClient = RekognitionClient.builder() .region(region) .build(); addToCollection(rekClient, collectionId, sourceImage); rekClient.close(); } 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); } } }
Kotlin
SDKper Kotlin
Nota

c'è altro da fare. 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 { 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 API i dettagli, vedi il riferimento IndexFaces AWSSDKa Kotlin API.

Python
SDKper Python (Boto3)
Nota

C'è di più 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 API i dettagli, vedere IndexFacesPython (Boto3) Reference.AWS SDK API