比较图像中的人脸

比较人脸

1. 如果您尚未执行以下操作，请：

   1. 创建或更新具有AmazonRekognitionFullAccess和AmazonS3ReadOnlyAccess（仅限AWS CLI 示例）权限的用户。有关更多信息，请参阅 步骤 1：设置AWS账户并创建用户。

   2. 安装和配置 AWS CLI 和 AWS SDK。有关更多信息，请参阅 第 2 步：设置 AWS CLI 以及 AWS SDKs。

2. 使用以下示例代码调用 CompareFaces 操作。

   Java

   此示例显示有关与从本地文件系统加载的源和目标图像中的人脸进行匹配的信息。

   将 sourceImage 和 targetImage 的值分别替换为源和目标图像的路径和文件名。

   //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

   此代码取自 AWS 文档 SDK 示例 GitHub 存储库。请在此处查看完整示例。

   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

   此示例显示compare-faces AWS CLI 操作的 JSON 输出。

   将bucket-name替换为包含源和目标图像的 Amazon S3 存储桶的名称。将 source.jpg 和 target.jpg 替换为源和目标图像的文件名。

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

   如果您在 Windows 设备上访问 CLI，请使用双引号代替单引号，并用反斜杠（即 \）对内部双引号进行转义，以解决可能遇到的任何解析器错误。例如，请参阅以下内容：

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

   Python

   此示例显示有关与从本地文件系统加载的源和目标图像中的人脸进行匹配的信息。

   将 source_file 和 target_file 的值分别替换为源和目标图像的路径和文件名。将创建 Rekognition 会话的行中的profile_name值替换为您的开发人员资料的名称。

   # 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

   此示例显示有关与从本地文件系统加载的源和目标图像中的人脸进行匹配的信息。

   将 sourceImage 和 targetImage 的值分别替换为源和目标图像的路径和文件名。

   //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

   此示例显示有关与从本地文件系统加载的源和目标图像中的人脸进行匹配的信息。

   将 photo_source 和 photo_target 的值分别替换为源和目标图像的路径和文件名。

     # 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

   此示例显示有关与从本地文件系统加载的源和目标图像中的人脸进行匹配的信息。

   将 photo_source 和 photo_target 的值分别替换为源和目标图像的路径和文件名。将创建 Rekognition 会话的行中的profile_name值替换为您的开发人员资料的名称。

   // 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
      });