不適切な保存動画の検出

Amazon S3 バケットに保存されているビデオ内の不適切または不快なコンテンツを検出するには (SDK）

1. 「Java または Python を使用して Amazon S3 バケットに保存されている動画を分析する (SDK）」を実行します。

2. ステップ 1 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.)
   
           //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);
                
            }  
         

   関数 main で、以下の行を置き換えます。

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

   を:

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

   Java V2

   このコードは、 AWS ドキュメント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.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

   関数 main で、以下の行を置き換えます。

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

   を:

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

   注記

   Java または Python を使用して Amazon S3 バケットに保存されている動画を分析する (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。

3. コードを実行します。ビデオで検出された、安全でないコンテンツのラベルのリストが表示されます。