Comparaison de visages dans les images

Pour comparer des visages

1. Si vous ne l’avez pas déjà fait :

   1. Créez ou mettez à jour un utilisateur doté d'autorisations AmazonRekognitionFullAccess et AmazonS3ReadOnlyAccess (à titre d'AWS CLI exemple uniquement). Pour de plus amples informations, veuillez consulter Étape 1 : configurer un compte AWS et créer un utilisateur.

   2. Installez et configurez le AWS CLI et le AWS SDKs. Pour de plus amples informations, veuillez consulter Étape 2 : configurer le AWS CLI et AWS SDKs.

2. Utilisez l'exemple de code suivant pour appeler l'opération CompareFaces.

   Java

   Cet exemple affiche des informations sur des visages correspondants dans les images source et cible, qui sont chargées à partir du système de fichiers local.

   Remplacez la valeur de sourceImage et de targetImage par le chemin et le nom de fichier des images source et cible.

   //Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
   //PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-developer-guide/blob/master/LICENSE-SAMPLECODE.)
   
   package aws.example.rekognition.image;
   import com.amazonaws.services.rekognition.AmazonRekognition;
   import com.amazonaws.services.rekognition.AmazonRekognitionClientBuilder;
   import com.amazonaws.services.rekognition.model.Image;
   import com.amazonaws.services.rekognition.model.BoundingBox;
   import com.amazonaws.services.rekognition.model.CompareFacesMatch;
   import com.amazonaws.services.rekognition.model.CompareFacesRequest;
   import com.amazonaws.services.rekognition.model.CompareFacesResult;
   import com.amazonaws.services.rekognition.model.ComparedFace;
   import java.util.List;
   import java.io.File;
   import java.io.FileInputStream;
   import java.io.InputStream;
   import java.nio.ByteBuffer;
   import com.amazonaws.util.IOUtils;
   
   public class CompareFaces {
   
      public static void main(String[] args) throws Exception{
          Float similarityThreshold = 70F;
          String sourceImage = "source.jpg";
          String targetImage = "target.jpg";
          ByteBuffer sourceImageBytes=null;
          ByteBuffer targetImageBytes=null;
   
          AmazonRekognition rekognitionClient = AmazonRekognitionClientBuilder.defaultClient();
   
          //Load source and target images and create input parameters
          try (InputStream inputStream = new FileInputStream(new File(sourceImage))) {
             sourceImageBytes = ByteBuffer.wrap(IOUtils.toByteArray(inputStream));
          }
          catch(Exception e)
          {
              System.out.println("Failed to load source image " + sourceImage);
              System.exit(1);
          }
          try (InputStream inputStream = new FileInputStream(new File(targetImage))) {
              targetImageBytes = ByteBuffer.wrap(IOUtils.toByteArray(inputStream));
          }
          catch(Exception e)
          {
              System.out.println("Failed to load target images: " + targetImage);
              System.exit(1);
          }
   
          Image source=new Image()
               .withBytes(sourceImageBytes);
          Image target=new Image()
               .withBytes(targetImageBytes);
   
          CompareFacesRequest request = new CompareFacesRequest()
                  .withSourceImage(source)
                  .withTargetImage(target)
                  .withSimilarityThreshold(similarityThreshold);
   
          // Call operation
          CompareFacesResult compareFacesResult=rekognitionClient.compareFaces(request);
   
   
          // Display results
          List <CompareFacesMatch> faceDetails = compareFacesResult.getFaceMatches();
          for (CompareFacesMatch match: faceDetails){
            ComparedFace face= match.getFace();
            BoundingBox position = face.getBoundingBox();
            System.out.println("Face at " + position.getLeft().toString()
                  + " " + position.getTop()
                  + " matches with " + match.getSimilarity().toString()
                  + "% confidence.");
   
          }
          List<ComparedFace> uncompared = compareFacesResult.getUnmatchedFaces();
   
          System.out.println("There was " + uncompared.size()
               + " face(s) that did not match");
      }
   }

   Java V2

   Ce code est extrait du GitHub référentiel d'exemples du SDK de AWS documentation. Voir l’exemple complet ici.

   import java.util.List;
   
   import software.amazon.awssdk.auth.credentials.ProfileCredentialsProvider;
   import software.amazon.awssdk.regions.Region;
   import software.amazon.awssdk.services.rekognition.RekognitionClient;
   import software.amazon.awssdk.services.rekognition.model.RekognitionException;
   import software.amazon.awssdk.services.rekognition.model.Image;
   import software.amazon.awssdk.services.rekognition.model.BoundingBox;
   import software.amazon.awssdk.services.rekognition.model.CompareFacesMatch;
   import software.amazon.awssdk.services.rekognition.model.CompareFacesRequest;
   import software.amazon.awssdk.services.rekognition.model.CompareFacesResponse;
   import software.amazon.awssdk.services.rekognition.model.ComparedFace;
   import software.amazon.awssdk.core.SdkBytes;
   import java.io.FileInputStream;
   import java.io.FileNotFoundException;
   import java.io.InputStream;
   
   // snippet-end:[rekognition.java2.detect_faces.import]
   
   /**
    * 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 CompareFaces {
   
       public static void main(String[] args) {
   
           final String usage = "\n" +
               "Usage: " +
               "   <pathSource> <pathTarget>\n\n" +
               "Where:\n" +
               "   pathSource - The path to the source image (for example, C:\\AWS\\pic1.png). \n " +
               "   pathTarget - The path to the target image (for example, C:\\AWS\\pic2.png). \n\n";
   
           if (args.length != 2) {
               System.out.println(usage);
               System.exit(1);
           }
   
           Float similarityThreshold = 70F;
           String sourceImage = args[0];
           String targetImage = args[1];
           Region region = Region.US_EAST_1;
           RekognitionClient rekClient = RekognitionClient.builder()
               .region(region)
               .credentialsProvider(ProfileCredentialsProvider.create("profile-name"))
               .build();
   
           compareTwoFaces(rekClient, similarityThreshold, sourceImage, targetImage);
           rekClient.close();
      }
   
       // snippet-start:[rekognition.java2.compare_faces.main]
       public static void compareTwoFaces(RekognitionClient rekClient, Float similarityThreshold, String sourceImage, String targetImage) {
           try {
               InputStream sourceStream = new FileInputStream(sourceImage);
               InputStream tarStream = new FileInputStream(targetImage);
               SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream);
               SdkBytes targetBytes = SdkBytes.fromInputStream(tarStream);
   
               // Create an Image object for the source image.
               Image souImage = Image.builder()
                   .bytes(sourceBytes)
                   .build();
   
               Image tarImage = Image.builder()
                   .bytes(targetBytes)
                   .build();
   
               CompareFacesRequest facesRequest = CompareFacesRequest.builder()
                   .sourceImage(souImage)
                   .targetImage(tarImage)
                   .similarityThreshold(similarityThreshold)
                   .build();
   
               // Compare the two images.
               CompareFacesResponse compareFacesResult = rekClient.compareFaces(facesRequest);
               List<CompareFacesMatch> faceDetails = compareFacesResult.faceMatches();
               for (CompareFacesMatch match: faceDetails){
                   ComparedFace face= match.face();
                   BoundingBox position = face.boundingBox();
                   System.out.println("Face at " + position.left().toString()
                           + " " + position.top()
                           + " matches with " + face.confidence().toString()
                           + "% confidence.");
   
               }
               List<ComparedFace> uncompared = compareFacesResult.unmatchedFaces();
               System.out.println("There was " + uncompared.size() + " face(s) that did not match");
               System.out.println("Source image rotation: " + compareFacesResult.sourceImageOrientationCorrection());
               System.out.println("target image rotation: " + compareFacesResult.targetImageOrientationCorrection());
   
           } catch(RekognitionException | FileNotFoundException e) {
               System.out.println("Failed to load source image " + sourceImage);
               System.exit(1);
           }
       }
       // snippet-end:[rekognition.java2.compare_faces.main]
   }

   AWS CLI

   Cet exemple affiche le résultat JSON de l'compare-faces AWS CLI opération.

   Remplacez amzn-s3-demo-bucket par le nom du compartiment Amazon S3 qui contient les images source et cible. Remplacez la valeur de source.jpg et de target.jpg par le nom de fichier de l'image source et le nom de fichier de l'image cible.

   aws rekognition compare-faces --target-image \
   "{"S3Object":{"Bucket":"amzn-s3-demo-bucket","Name":"image-name"}}" \
   --source-image "{"S3Object":{"Bucket":"amzn-s3-demo-bucket","Name":"image-name"}}" 
   --profile profile-name  
                           

   Si vous accédez à la CLI sur un périphérique Windows, utilisez des guillemets doubles au lieu de guillemets simples et évitez les guillemets doubles internes par une barre oblique inverse (c’est-à-dire \) pour corriger les erreurs d’analyse que vous pourriez rencontrer. Par exemple, consultez ce qui suit :

   aws rekognition compare-faces --target-image "{\"S3Object\":{\"Bucket\":\"amzn-s3-demo-bucket\",\"Name\":\"image-name\"}}" \ 
   --source-image "{\"S3Object\":{\"Bucket\":\"amzn-s3-demo-bucket\",\"Name\":\"image-name\"}}" --profile profile-name
                               

   Python

   Cet exemple affiche des informations sur des visages correspondants dans les images source et cible, qui sont chargées à partir du système de fichiers local.

   Remplacez la valeur de source_file et de target_file par le chemin et le nom de fichier des images source et cible. Remplacez la valeur de profile_name dans la ligne qui crée la session de Rekognition par le nom de votre profil de développeur.

   # Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
   # PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-developer-guide/blob/master/LICENSE-SAMPLECODE.)
   
   import boto3
   
   def compare_faces(sourceFile, targetFile):
   
       session = boto3.Session(profile_name='profile-name')
       client = session.client('rekognition')
   
       imageSource = open(sourceFile, 'rb')
       imageTarget = open(targetFile, 'rb')
   
       response = client.compare_faces(SimilarityThreshold=80,
                                       SourceImage={'Bytes': imageSource.read()},
                                       TargetImage={'Bytes': imageTarget.read()})
   
       for faceMatch in response['FaceMatches']:
           position = faceMatch['Face']['BoundingBox']
           similarity = str(faceMatch['Similarity'])
           print('The face at ' +
                 str(position['Left']) + ' ' +
                 str(position['Top']) +
                 ' matches with ' + similarity + '% confidence')
   
       imageSource.close()
       imageTarget.close()
       return len(response['FaceMatches'])
   
   def main():
       source_file = 'source-file-name'
       target_file = 'target-file-name'
       face_matches = compare_faces(source_file, target_file)
       print("Face matches: " + str(face_matches))
   
   if __name__ == "__main__":
       main()

   .NET

   Cet exemple affiche des informations sur des visages correspondants dans les images source et cible, qui sont chargées à partir du système de fichiers local.

   Remplacez la valeur de sourceImage et de targetImage par le chemin et le nom de fichier des images source et cible.

   //Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
   //PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-developer-guide/blob/master/LICENSE-SAMPLECODE.)
   
   using System;
   using System.IO;
   using Amazon.Rekognition;
   using Amazon.Rekognition.Model;
   
   public class CompareFaces
   {
       public static void Example()
       {
           float similarityThreshold = 70F;
           String sourceImage = "source.jpg";
           String targetImage = "target.jpg";
   
           AmazonRekognitionClient 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)
           {
               Console.WriteLine("Failed to load target image: " + targetImage);
               return;
           }
   
           CompareFacesRequest compareFacesRequest = new CompareFacesRequest()
           {
               SourceImage = imageSource,
               TargetImage = imageTarget,
               SimilarityThreshold = similarityThreshold
           };
   
           // Call operation
           CompareFacesResponse compareFacesResponse = rekognitionClient.CompareFaces(compareFacesRequest);
   
           // Display results
           foreach(CompareFacesMatch match in compareFacesResponse.FaceMatches)
           {
               ComparedFace face = match.Face;
               BoundingBox position = face.BoundingBox;
               Console.WriteLine("Face at " + position.Left
                     + " " + position.Top
                     + " matches with " + match.Similarity
                     + "% confidence.");
           }
   
           Console.WriteLine("There was " + compareFacesResponse.UnmatchedFaces.Count + " face(s) that did not match");
   
       }
   }

   Ruby

   Cet exemple affiche des informations sur des visages correspondants dans les images source et cible, qui sont chargées à partir du système de fichiers local.

   Remplacez la valeur de photo_source et de photo_target par le chemin et le nom de fichier des images source et cible.

     # Add to your Gemfile
      # gem 'aws-sdk-rekognition'
      require 'aws-sdk-rekognition'
      credentials = Aws::Credentials.new(
         ENV['AWS_ACCESS_KEY_ID'],
         ENV['AWS_SECRET_ACCESS_KEY']
      )
      bucket        = 'bucket' # the bucketname without s3://
      photo_source  = 'source.jpg'
      photo_target  = 'target.jpg'
      client   = Aws::Rekognition::Client.new credentials: credentials
      attrs = {
        source_image: {
          s3_object: {
            bucket: bucket,
            name: photo_source
          },
        },
        target_image: {
          s3_object: {
            bucket: bucket,
            name: photo_target
          },
        },
        similarity_threshold: 70
      }
      response = client.compare_faces attrs
      response.face_matches.each do |face_match|
        position   = face_match.face.bounding_box
        similarity = face_match.similarity
        puts "The face at: #{position.left}, #{position.top} matches with #{similarity} % confidence"
      end

   Node.js

   Cet exemple affiche des informations sur des visages correspondants dans les images source et cible, qui sont chargées à partir du système de fichiers local.

   Remplacez la valeur de photo_source et de photo_target par le chemin et le nom de fichier des images source et cible. Remplacez la valeur de profile_name dans la ligne qui crée la session de Rekognition par le nom de votre profil de développeur.

   // Load the SDK
   var AWS = require('aws-sdk');
   const bucket = 'bucket-name' // the bucket name without s3://
   const photo_source  = 'photo-source-name' // path and the name of file
   const photo_target = 'photo-target-name'
   
   var credentials = new AWS.SharedIniFileCredentials({profile: 'profile-name'});
   AWS.config.credentials = credentials;
   AWS.config.update({region:'region-name'});
   
   const client = new AWS.Rekognition();
      const params = {
        SourceImage: {
          S3Object: {
            Bucket: bucket,
            Name: photo_source
          },
        },
        TargetImage: {
          S3Object: {
            Bucket: bucket,
            Name: photo_target
          },
        },
        SimilarityThreshold: 70
      }
      client.compareFaces(params, function(err, response) {
        if (err) {
          console.log(err, err.stack); // an error occurred
        } else {
          response.FaceMatches.forEach(data => {
            let position   = data.Face.BoundingBox
            let similarity = data.Similarity
            console.log(`The face at: ${position.Left}, ${position.Top} matches with ${similarity} % confidence`)
          }) // for response.faceDetails
        } // if
      });