Mencari video yang disimpan untuk wajah

Untuk mencari video untuk pencocokan wajah (SDK)

1. Buat koleksi.

2. Indeks wajah ke dalam koleksi.

3. Lakukan Menganalisis video yang disimpan dalam bucket Amazon S3 dengan Java atau Python () SDK.

4. Tambahkan kode berikut ke kelas VideoDetect yang Anda buat di langkah 3.

   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);
   
      }
   

   Di fungsi main, ganti baris:

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

   dengan:

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

   Java V2

   Kode ini diambil dari GitHub repositori SDK contoh AWS Dokumentasi. Lihat contoh lengkapnya di sini.

   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()

   Dalam fungsi main, ganti baris:

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

   dengan:

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

   Jika Anda sudah menjalankan contoh video selain Menganalisis video yang disimpan dalam bucket Amazon S3 dengan Java atau Python () SDK, kode yang akan diganti mungkin berbeda.

5. Ubah nilai collection pada nama koleksi yang Anda buat pada langkah 1.

6. Jalankan kode tersebut. Daftar orang dalam video yang wajahnya cocok dengan yang ada di koleksi input akan ditampilkan. Data pelacakan untuk setiap orang yang cocok juga ditampilkan.