保存したビデオでの顔の検索

ビデオ内で一致する顔を検索するには (SDK)

1. コレクションを作成します。

2. 顔にインデックスを付けてコレクションに追加します。

3. 「Java または Python を使用した、Amazon S3 バケットに保存されたビデオの分析 (SDK)」を実行します。

4. ステップ 3 で作成したクラス VideoDetect に次のコードを追加します。

   Java

      //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.)
   
          //Face collection search in video ==================================================================
          private static void StartFaceSearchCollection(String bucket, String video, String collection) throws Exception{
   
           NotificationChannel channel= new NotificationChannel()
                   .withSNSTopicArn(snsTopicArn)
                   .withRoleArn(roleArn);
   
           StartFaceSearchRequest req = new StartFaceSearchRequest()
                   .withCollectionId(collection)
                   .withVideo(new Video()
                           .withS3Object(new S3Object()
                                   .withBucket(bucket)
                                   .withName(video)))
                   .withNotificationChannel(channel);
   
   
   
           StartFaceSearchResult startPersonCollectionSearchResult = rek.startFaceSearch(req);
           startJobId=startPersonCollectionSearchResult.getJobId();
   
       } 
   
       //Face collection search in video ==================================================================
       private static void GetFaceSearchCollectionResults() throws Exception{
   
          GetFaceSearchResult faceSearchResult=null;
          int maxResults=10;
          String paginationToken=null;
   
          do {
   
              if (faceSearchResult !=null){
                  paginationToken = faceSearchResult.getNextToken();
              }
   
   
              faceSearchResult  = rek.getFaceSearch(
                      new GetFaceSearchRequest()
                      .withJobId(startJobId)
                      .withMaxResults(maxResults)
                      .withNextToken(paginationToken)
                      .withSortBy(FaceSearchSortBy.TIMESTAMP)
                      );
   
   
              VideoMetadata videoMetaData=faceSearchResult.getVideoMetadata();
   
              System.out.println("Format: " + videoMetaData.getFormat());
              System.out.println("Codec: " + videoMetaData.getCodec());
              System.out.println("Duration: " + videoMetaData.getDurationMillis());
              System.out.println("FrameRate: " + videoMetaData.getFrameRate());
              System.out.println();      
   
   
              //Show search results
              List<PersonMatch> matches= 
                      faceSearchResult.getPersons();
   
              for (PersonMatch match: matches) { 
                  long milliSeconds=match.getTimestamp();
                  System.out.print("Timestamp: " + Long.toString(milliSeconds));
                  System.out.println(" Person number: " + match.getPerson().getIndex());
                  List <FaceMatch> faceMatches = match.getFaceMatches();
                  if (faceMatches != null) {
                      System.out.println("Matches in collection...");
                      for (FaceMatch faceMatch: faceMatches){
                          Face face=faceMatch.getFace();
                          System.out.println("Face Id: "+ face.getFaceId());
                          System.out.println("Similarity: " + faceMatch.getSimilarity().toString());
                          System.out.println();
                      }
                  }
                  System.out.println();           
              } 
   
              System.out.println(); 
   
          } while (faceSearchResult !=null && faceSearchResult.getNextToken() != null);
   
      }
   

   関数 main で、以下の行を置き換えます。

           StartLabelDetection(bucket, video);
   
           if (GetSQSMessageSuccess()==true)
           	GetLabelDetectionResults();

   を:

           String collection="collection";
           StartFaceSearchCollection(bucket, video, collection);
   
           if (GetSQSMessageSuccess()==true)
           	GetFaceSearchCollectionResults();

   Java V2

   このコードは AWS Documentation SDK サンプル GitHub リポジトリから取得されます。詳しい事例は [こちら] です。

   import software.amazon.awssdk.regions.Region;
   import software.amazon.awssdk.services.rekognition.RekognitionClient;
   import software.amazon.awssdk.services.rekognition.model.*;
   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 VideoDetectFaces {
       private static String startJobId = "";
   
       public static void main(String[] args) {
           final String usage = """
   
                   Usage:    <bucket> <video> <topicArn> <roleArn>
   
                   Where:
                      bucket - The name of the bucket in which the video is located (for example, (for example, myBucket).\s
                      video - The name of video (for example, people.mp4).\s
                      topicArn - The ARN of the Amazon Simple Notification Service (Amazon SNS) topic.\s
                      roleArn - The ARN of the AWS Identity and Access Management (IAM) role to use.\s
                   """;
   
           if (args.length != 4) {
               System.out.println(usage);
               System.exit(1);
           }
   
           String bucket = args[0];
           String video = args[1];
           String topicArn = args[2];
           String roleArn = args[3];
   
           Region region = Region.US_EAST_1;
           RekognitionClient rekClient = RekognitionClient.builder()
                   .region(region)
                   .build();
   
           NotificationChannel channel = NotificationChannel.builder()
                   .snsTopicArn(topicArn)
                   .roleArn(roleArn)
                   .build();
   
           startFaceDetection(rekClient, channel, bucket, video);
           getFaceResults(rekClient);
           System.out.println("This example is done!");
           rekClient.close();
       }
   
       public static void startFaceDetection(RekognitionClient rekClient,
               NotificationChannel channel,
               String bucket,
               String video) {
           try {
               S3Object s3Obj = S3Object.builder()
                       .bucket(bucket)
                       .name(video)
                       .build();
   
               Video vidOb = Video.builder()
                       .s3Object(s3Obj)
                       .build();
   
               StartFaceDetectionRequest faceDetectionRequest = StartFaceDetectionRequest.builder()
                       .jobTag("Faces")
                       .faceAttributes(FaceAttributes.ALL)
                       .notificationChannel(channel)
                       .video(vidOb)
                       .build();
   
               StartFaceDetectionResponse startLabelDetectionResult = rekClient.startFaceDetection(faceDetectionRequest);
               startJobId = startLabelDetectionResult.jobId();
   
           } catch (RekognitionException e) {
               System.out.println(e.getMessage());
               System.exit(1);
           }
       }
   
       public static void getFaceResults(RekognitionClient rekClient) {
           try {
               String paginationToken = null;
               GetFaceDetectionResponse faceDetectionResponse = null;
               boolean finished = false;
               String status;
               int yy = 0;
   
               do {
                   if (faceDetectionResponse != null)
                       paginationToken = faceDetectionResponse.nextToken();
   
                   GetFaceDetectionRequest recognitionRequest = GetFaceDetectionRequest.builder()
                           .jobId(startJobId)
                           .nextToken(paginationToken)
                           .maxResults(10)
                           .build();
   
                   // Wait until the job succeeds.
                   while (!finished) {
   
                       faceDetectionResponse = rekClient.getFaceDetection(recognitionRequest);
                       status = faceDetectionResponse.jobStatusAsString();
   
                       if (status.compareTo("SUCCEEDED") == 0)
                           finished = true;
                       else {
                           System.out.println(yy + " status is: " + status);
                           Thread.sleep(1000);
                       }
                       yy++;
                   }
   
                   finished = false;
   
                   // Proceed when the job is done - otherwise VideoMetadata is null.
                   VideoMetadata videoMetaData = faceDetectionResponse.videoMetadata();
                   System.out.println("Format: " + videoMetaData.format());
                   System.out.println("Codec: " + videoMetaData.codec());
                   System.out.println("Duration: " + videoMetaData.durationMillis());
                   System.out.println("FrameRate: " + videoMetaData.frameRate());
                   System.out.println("Job");
   
                   // Show face information.
                   List<FaceDetection> faces = faceDetectionResponse.faces();
                   for (FaceDetection face : faces) {
                       String age = face.face().ageRange().toString();
                       String smile = face.face().smile().toString();
                       System.out.println("The detected face is estimated to be"
                               + age + " years old.");
                       System.out.println("There is a smile : " + smile);
                   }
   
               } while (faceDetectionResponse != null && faceDetectionResponse.nextToken() != null);
   
           } catch (RekognitionException | InterruptedException e) {
               System.out.println(e.getMessage());
               System.exit(1);
           }
       }
   }
   

   Python

   #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.)
   
       # ============== Face Search ===============
       def StartFaceSearchCollection(self,collection):
           response = self.rek.start_face_search(Video={'S3Object':{'Bucket':self.bucket,'Name':self.video}},
               CollectionId=collection,
               NotificationChannel={'RoleArn':self.roleArn, 'SNSTopicArn':self.snsTopicArn})
           
           self.startJobId=response['JobId']
           
           print('Start Job Id: ' + self.startJobId)
   
   
       def GetFaceSearchCollectionResults(self):
           maxResults = 10
           paginationToken = ''
   
           finished = False
   
           while finished == False:
               response = self.rek.get_face_search(JobId=self.startJobId,
                                           MaxResults=maxResults,
                                           NextToken=paginationToken)
   
               print(response['VideoMetadata']['Codec'])
               print(str(response['VideoMetadata']['DurationMillis']))
               print(response['VideoMetadata']['Format'])
               print(response['VideoMetadata']['FrameRate'])
   
               for personMatch in response['Persons']:
                   print('Person Index: ' + str(personMatch['Person']['Index']))
                   print('Timestamp: ' + str(personMatch['Timestamp']))
   
                   if ('FaceMatches' in personMatch):
                       for faceMatch in personMatch['FaceMatches']:
                           print('Face ID: ' + faceMatch['Face']['FaceId'])
                           print('Similarity: ' + str(faceMatch['Similarity']))
                   print()
               if 'NextToken' in response:
                   paginationToken = response['NextToken']
               else:
                   finished = True
               print()

   関数 main で、以下の行を置き換えます。

       analyzer.StartLabelDetection()
       if analyzer.GetSQSMessageSuccess()==True:
           analyzer.GetLabelDetectionResults()

   を:

       collection='tests'
       analyzer.StartFaceSearchCollection(collection)
       
       if analyzer.GetSQSMessageSuccess()==True:
           analyzer.GetFaceSearchCollectionResults()

   Java または Python を使用した、Amazon S3 バケットに保存されたビデオの分析 (SDK) 以外のビデオ例をすでに実行している場合、置き換えるコードは異なる可能性があります。

5. collection の値は、ステップ 1 で作成したコレクションの名前に変更します。

6. コードを実行します。入力コレクション内の顔と一致するビデオ内の顔の人物が一覧表示されます。一致した人物ごとの追跡データも表示されます。