기계 번역으로 제공되는 번역입니다. 제공된 번역과 원본 영어의 내용이 상충하는 경우에는 영어 버전이 우선합니다.

# 부적절한 저장된 동영상 탐지
<a name="procedure-moderate-videos"></a>

Amazon Rekognition Video의 저장된 비디오 속 부적절하거나 불쾌감을 주는 콘텐츠 탐지는 비동기 작업입니다. 부적절하거나 불쾌감을 주는 콘텐츠 탐지를 시작하려면 [StartContentModeration](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_StartContentModeration.html)을 직접 호출하세요. Amazon Rekognition Video는 비디오 분석의 완료 상태를 Amazon Simple Notification Service 주제에 게시합니다. 비디오 분석이 성공적으로 완료되면, [GetContentModeration](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_GetContentModeration.html) 직접 호출을 통해 분석 결과를 가져옵니다. 비디오 분석 시작 및 결과 가져오기에 대한 자세한 내용은 [Amazon Rekognition Video 작업 직접 호출](api-video.md) 단원을 참조하십시오. Amazon Rekognition의 조절 레이블 목록은 [이미지 및 비디오 조절 API 사용](https://docs.aws.amazon.com/rekognition/latest/dg/moderation.html#moderation-api)을 참조하세요.

 이 절차는 동영상 분석 요청의 완료 상태를 가져오기 위해 Amazon Simple Queue Service 대기열을 사용하는 [Java 또는 Python으로 Amazon S3 버킷에 저장된 비디오 분석(SDK)](video-analyzing-with-sqs.md)의 코드를 확장합니다.

**Amazon S3 버킷(SDK)에 저장된 비디오에서 부적절하거나 불쾌감을 주는 콘텐츠를 탐지하려면**

1. [Java 또는 Python으로 Amazon S3 버킷에 저장된 비디오 분석(SDK)](video-analyzing-with-sqs.md)을 수행합니다.

1. 1단계에서 만든 클래스 `VideoDetect`에 다음 코드를 추가합니다.

------
#### [ 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);
                
            }
   ```

   `main` 함수에서 다음 줄을 바꿉니다.

   ```
           StartLabelDetection(amzn-s3-demo-bucket, video);
   
           if (GetSQSMessageSuccess()==true)
           	GetLabelDetectionResults();
   ```

   다음으로 바꿉니다.

   ```
           StartUnsafeContentDetection(amzn-s3-demo-bucket, video);
   
           if (GetSQSMessageSuccess()==true)
           	GetUnsafeContentDetectionResults();
   ```

------
#### [ Java V2 ]

   이 코드는 AWS 설명서 SDK 예제 GitHub 리포지토리에서 가져온 것입니다. 전체 예제는 [여기](https://github.com/awsdocs/aws-doc-sdk-examples/blob/master/javav2/example_code/rekognition/src/main/java/com/example/rekognition/VideoDetectInappropriate.java)에서 확인하세요.

   ```
   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
   ```

   `main` 함수에서 다음 줄을 바꿉니다.

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

   다음으로 바꿉니다.

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

------
**참고**  
[Java 또는 Python으로 Amazon S3 버킷에 저장된 비디오 분석(SDK)](video-analyzing-with-sqs.md) 이외에 비디오 예제를 이미 실행한 경우, 바꿀 코드가 다를 수 있습니다.

1. 코드를 실행합니다. 비디오에서 감지된 부적절한 콘텐츠 레이블 목록이 표시됩니다.

## GetContentModeration 작업 응답
<a name="getcontentmoderation-operationresponse"></a>

`GetContentModeration`의 응답은 [ContentModerationDetection](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_ContentModerationDetection.html) 객체로 구성된 `ModerationLabels` 배열입니다. 부적절한 콘텐츠 레이블이 감지될 때마다 배열에 요소가 포함됩니다. `ContentModerationDetectionObject` 객체 내에 있는 [ModerationLabel](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_ModerationLabel.html)에는 부적절하거나 불쾌감을 주는 콘텐츠가 감지된 항목에 대한 정보가 포함되어 있습니다. `Timestamp`는 비디오 시작부터 레이블이 감지된 때까지 지난 시간(밀리초 단위)입니다. 레이블은 부적절한 콘텐츠 이미지 분석을 통해 감지된 레이블과 동일한 방식의 계층적 구조로 구성됩니다. 자세한 내용은 [콘텐츠 조절](moderation.md) 단원을 참조하십시오.

다음은 `NAME` 기준으로 정렬하고 `TIMESTAMPS` 기준으로 집계한 `GetContentModeration`로부터의 예제 응답입니다.

```
{
    "JobStatus": "SUCCEEDED",
    "VideoMetadata": {
        "Codec": "h264",
        "DurationMillis": 54100,
        "Format": "QuickTime / MOV",
        "FrameRate": 30.0,
        "FrameHeight": 462,
        "FrameWidth": 884,
        "ColorRange": "LIMITED"
    },
    "ModerationLabels": [
        {
            "Timestamp": 36000,
            "ModerationLabel": {
                "Confidence": 52.451576232910156,
                "Name": "Alcohol",
                "ParentName": "",
                "TaxonomyLevel": 1
            },
            "ContentTypes": [
                {
                    "Confidence": 99.9999008178711,
                    "Name": "Animated"
                }
            ]
        },
        {
            "Timestamp": 36000,
            "ModerationLabel": {
                "Confidence": 52.451576232910156,
                "Name": "Alcoholic Beverages",
                "ParentName": "Alcohol",
                "TaxonomyLevel": 2
            },
            "ContentTypes": [
                {
                    "Confidence": 99.9999008178711,
                    "Name": "Animated"
                }
            ]
        }
    ],
    "ModerationModelVersion": "7.0",
    "JobId": "a1b2c3d4...",
    "Video": {
        "S3Object": {
            "Bucket": "amzn-s3-demo-bucket",
            "Name": "video-name.mp4"
        }
    },
    "GetRequestMetadata": {
        "SortBy": "TIMESTAMP",
        "AggregateBy": "TIMESTAMPS"
    }
}
```

 다음은 `NAME` 기준으로 정렬하고 `SEGMENTS` 기준으로 집계한 `GetContentModeration`로부터의 예제 응답입니다.

```
{
    "JobStatus": "SUCCEEDED",
    "VideoMetadata": {
        "Codec": "h264",
        "DurationMillis": 54100,
        "Format": "QuickTime / MOV",
        "FrameRate": 30.0,
        "FrameHeight": 462,
        "FrameWidth": 884,
        "ColorRange": "LIMITED"
    },
    "ModerationLabels": [
        {
            "Timestamp": 0,
            "ModerationLabel": {
                "Confidence": 0.0003000000142492354,
                "Name": "Alcohol Use",
                "ParentName": "Alcohol",
                "TaxonomyLevel": 2
            },
            "StartTimestampMillis": 0,
            "EndTimestampMillis": 29520,
            "DurationMillis": 29520,
            "ContentTypes": [
                {
                    "Confidence": 99.9999008178711,
                    "Name": "Illustrated"
                },
                {
                    "Confidence": 99.9999008178711,
                    "Name": "Animated"
                }
            ]
        }
    ],
    "ModerationModelVersion": "7.0",
    "JobId": "a1b2c3d4...",
    "Video": {
        "S3Object": {
            "Bucket": "amzn-s3-demo-bucket",
            "Name": "video-name.mp4"
        }
    },
    "GetRequestMetadata": {
        "SortBy": "TIMESTAMP",
        "AggregateBy": "SEGMENTS"
    }
}
```