Detectando vídeos armazenados inapropriados

Para detectar conteúdo impróprio ou ofensivo em um vídeo armazenado em um bucket do Amazon S3 () SDK

1. Execute Análise de um vídeo armazenado em um bucket do Amazon S3 com Java ou Python () SDK.

2. Adicione o código a seguir à classe VideoDetect criada por você na etapa 1.

   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.)
   
           //Content moderation ==================================================================
           private static void StartUnsafeContentDetection(String bucket, String video) throws Exception{
           
               NotificationChannel channel= new NotificationChannel()
                       .withSNSTopicArn(snsTopicArn)
                       .withRoleArn(roleArn);
               
               StartContentModerationRequest req = new StartContentModerationRequest()
                       .withVideo(new Video()
                               .withS3Object(new S3Object()
                                   .withBucket(bucket)
                                   .withName(video)))
                       .withNotificationChannel(channel);
                                    
                                    
                
                StartContentModerationResult startModerationLabelDetectionResult = rek.startContentModeration(req);
                startJobId=startModerationLabelDetectionResult.getJobId();
                
            } 
            
            private static void GetUnsafeContentDetectionResults() throws Exception{
                
                int maxResults=10;
                String paginationToken=null;
                GetContentModerationResult moderationLabelDetectionResult =null;
                
                do{
                    if (moderationLabelDetectionResult !=null){
                        paginationToken = moderationLabelDetectionResult.getNextToken();
                    }
                    
                    moderationLabelDetectionResult = rek.getContentModeration(
                            new GetContentModerationRequest()
                                .withJobId(startJobId)
                                .withNextToken(paginationToken)
                                .withSortBy(ContentModerationSortBy.TIMESTAMP)
                                .withMaxResults(maxResults));
                            
                    
           
                    VideoMetadata videoMetaData=moderationLabelDetectionResult.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());
                        
                        
                    //Show moderated content labels, confidence and detection times
                    List<ContentModerationDetection> moderationLabelsInFrames= 
                            moderationLabelDetectionResult.getModerationLabels();
                 
                    for (ContentModerationDetection label: moderationLabelsInFrames) { 
                        long seconds=label.getTimestamp()/1000;
                        System.out.print("Sec: " + Long.toString(seconds));
                        System.out.println(label.getModerationLabel().toString());
                        System.out.println();           
                    }  
                } while (moderationLabelDetectionResult !=null && moderationLabelDetectionResult.getNextToken() != null);
                
            }  
         

   Na função main, substitua as linhas:

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

   por:

           StartUnsafeContentDetection(bucket, video);
   
           if (GetSQSMessageSuccess()==true)
           	GetUnsafeContentDetectionResults();

   Java V2

   Esse código foi retirado do GitHub repositório de SDK exemplos de AWS documentação. Veja o exemplo completo aqui.

   import software.amazon.awssdk.regions.Region;
   import software.amazon.awssdk.services.rekognition.RekognitionClient;
   import software.amazon.awssdk.services.rekognition.model.NotificationChannel;
   import software.amazon.awssdk.services.rekognition.model.S3Object;
   import software.amazon.awssdk.services.rekognition.model.Video;
   import software.amazon.awssdk.services.rekognition.model.StartContentModerationRequest;
   import software.amazon.awssdk.services.rekognition.model.StartContentModerationResponse;
   import software.amazon.awssdk.services.rekognition.model.RekognitionException;
   import software.amazon.awssdk.services.rekognition.model.GetContentModerationResponse;
   import software.amazon.awssdk.services.rekognition.model.GetContentModerationRequest;
   import software.amazon.awssdk.services.rekognition.model.VideoMetadata;
   import software.amazon.awssdk.services.rekognition.model.ContentModerationDetection;
   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 VideoDetectInappropriate {
       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();
   
           startModerationDetection(rekClient, channel, bucket, video);
           getModResults(rekClient);
           System.out.println("This example is done!");
           rekClient.close();
       }
   
       public static void startModerationDetection(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();
   
               StartContentModerationRequest modDetectionRequest = StartContentModerationRequest.builder()
                       .jobTag("Moderation")
                       .notificationChannel(channel)
                       .video(vidOb)
                       .build();
   
               StartContentModerationResponse startModDetectionResult = rekClient
                       .startContentModeration(modDetectionRequest);
               startJobId = startModDetectionResult.jobId();
   
           } catch (RekognitionException e) {
               System.out.println(e.getMessage());
               System.exit(1);
           }
       }
   
       public static void getModResults(RekognitionClient rekClient) {
           try {
               String paginationToken = null;
               GetContentModerationResponse modDetectionResponse = null;
               boolean finished = false;
               String status;
               int yy = 0;
   
               do {
                   if (modDetectionResponse != null)
                       paginationToken = modDetectionResponse.nextToken();
   
                   GetContentModerationRequest modRequest = GetContentModerationRequest.builder()
                           .jobId(startJobId)
                           .nextToken(paginationToken)
                           .maxResults(10)
                           .build();
   
                   // Wait until the job succeeds.
                   while (!finished) {
                       modDetectionResponse = rekClient.getContentModeration(modRequest);
                       status = modDetectionResponse.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 = modDetectionResponse.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");
   
                   List<ContentModerationDetection> mods = modDetectionResponse.moderationLabels();
                   for (ContentModerationDetection mod : mods) {
                       long seconds = mod.timestamp() / 1000;
                       System.out.print("Mod label: " + seconds + " ");
                       System.out.println(mod.moderationLabel().toString());
                       System.out.println();
                   }
   
               } while (modDetectionResponse != null && modDetectionResponse.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.)
   
       # ============== Unsafe content =============== 
       def StartUnsafeContent(self):
           response=self.rek.start_content_moderation(Video={'S3Object': {'Bucket': self.bucket, 'Name': self.video}},
               NotificationChannel={'RoleArn': self.roleArn, 'SNSTopicArn': self.snsTopicArn})
   
           self.startJobId=response['JobId']
           print('Start Job Id: ' + self.startJobId)
   
       def GetUnsafeContentResults(self):
           maxResults = 10
           paginationToken = ''
           finished = False
   
           while finished == False:
               response = self.rek.get_content_moderation(JobId=self.startJobId,
                                                   MaxResults=maxResults,
                                                   NextToken=paginationToken,
                                                   SortBy="NAME",
                                                   AggregateBy="TIMESTAMPS")
   
               print('Codec: ' + response['VideoMetadata']['Codec'])
               print('Duration: ' + str(response['VideoMetadata']['DurationMillis']))
               print('Format: ' + response['VideoMetadata']['Format'])
               print('Frame rate: ' + str(response['VideoMetadata']['FrameRate']))
               print()
   
               for contentModerationDetection in response['ModerationLabels']:
                   print('Label: ' +
                       str(contentModerationDetection['ModerationLabel']['Name']))
                   print('Confidence: ' +
                       str(contentModerationDetection['ModerationLabel']['Confidence']))
                   print('Parent category: ' +
                       str(contentModerationDetection['ModerationLabel']['ParentName']))
                   print('Timestamp: ' + str(contentModerationDetection['Timestamp']))
                   print()
   
               if 'NextToken' in response:
                   paginationToken = response['NextToken']
               else:
                   finished = True

   Na função main, substitua as linhas:

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

   por:

       analyzer.StartUnsafeContent()
       if analyzer.GetSQSMessageSuccess()==True:
           analyzer.GetUnsafeContentResults()

   nota

   Se você já tiver executado um exemplo de vídeo diferente de Análise de um vídeo armazenado em um bucket do Amazon S3 com Java ou Python () SDK, o código a ser substituído poderá ser diferente.

3. Execute o código. É exibida uma lista de rótulos de conteúdo impróprio detectados no vídeo.