Use IndexFaces with an AWS SDK or command line tool

The following code examples show how to use IndexFaces.

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.
    /// </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.

CLI

AWS CLI

To add faces to a collection

The following index-faces command adds the faces found in an image to the specified collection.

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"
}

For more information, see Adding Faces to a Collection in the Amazon Rekognition Developer Guide.

• For API details, see IndexFaces in AWS CLI Command 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.

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);
        }
    }
}

• For API details, see IndexFaces in AWS SDK for Java 2.x API Reference.

Kotlin

SDK for Kotlin

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.