比較映像中的人臉

比較臉部

1. 如果您尚未執行：

   1. 建立或更新具有AmazonRekognitionFullAccess和 AmazonS3ReadOnlyAccess (僅限AWS CLI 範例) 權限的使用者。如需詳細資訊，請參閱 步驟 1：設定AWS帳戶並建立使用者。

   2. 安裝和設定 AWS CLI AWS 軟體開發套件。如需詳細資訊，請參閱 步驟 2：設定 AWS CLI 以及 AWS SDKs。

2. 使用下列程式碼範例來呼叫 CompareFaces 操作。

   Java

   此範例顯示有關來源和目標映像 (從本機檔案系統載入) 中相符臉孔的資訊。

   將 sourceImage 與 targetImage 的值取代為來源和目標映像的路徑和檔案名稱。

   //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

   此代碼取自 AWS 文檔 SDK 示例 GitHub 存儲庫。請參閱此處的完整範例。

   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

   此範例會顯示compare-faces AWS CLI 作業的 JSON 輸出。

   將 bucket-name 取代為 Amazon S3 儲存貯體的名稱，其中包含來源和目標映像。將 source.jpg 和 target.jpg 取代為來源和目標映像的檔案名稱。

   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 裝置上存取 CLI，請使用雙引號而非單引號，並以反斜線 (即\) 替代內部雙引號，以解決您可能遇到的任何剖析器錯誤。例如，請參閱下列內容：

   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

   此範例顯示有關來源和目標映像 (從本機檔案系統載入) 中相符臉孔的資訊，表面載入在從本機檔案系統。

   將 source_file 與 target_file 的值取代為來源和目標映像的路徑和檔案名稱。將建立 Rekognition 工作階段的行中 profile_name 值取代為您開發人員設定檔的名稱。

   # 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

   此範例顯示有關來源和目標映像 (從本機檔案系統載入) 中相符臉孔的資訊。

   將 sourceImage 與 targetImage 的值取代為來源和目標映像的路徑和檔案名稱。

   //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

   此範例顯示有關來源和目標映像 (從本機檔案系統載入) 中相符臉孔的資訊，表面載入在從本機檔案系統。

   將 photo_source 與 photo_target 的值取代為來源和目標映像的路徑和檔案名稱。

     # 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

   此範例顯示有關來源和目標映像 (從本機檔案系統載入) 中相符臉孔的資訊，表面載入在從本機檔案系統。

   將 photo_source 與 photo_target 的值取代為來源和目標映像的路徑和檔案名稱。將建立 Rekognition 工作階段的行中 profile_name 值取代為您開發人員設定檔的名稱。

   // 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
      });