Contoh: Mendeteksi segmen dalam video yang tersimpan

Untuk mendeteksi segmen dalam video yang disimpan dalam bucket Amazon S3 (SDK)

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

2. Tambahkan berikut ke kode yang Anda gunakan pada langkah 1.

   Java

   1. Tambahkan impor berikut.

      import com.amazonaws.services.rekognition.model.GetSegmentDetectionRequest;
      import com.amazonaws.services.rekognition.model.GetSegmentDetectionResult;
      import com.amazonaws.services.rekognition.model.SegmentDetection;
      import com.amazonaws.services.rekognition.model.SegmentType;
      import com.amazonaws.services.rekognition.model.SegmentTypeInfo;
      import com.amazonaws.services.rekognition.model.ShotSegment;
      import com.amazonaws.services.rekognition.model.StartSegmentDetectionFilters;
      import com.amazonaws.services.rekognition.model.StartSegmentDetectionRequest;
      import com.amazonaws.services.rekognition.model.StartSegmentDetectionResult;
      import com.amazonaws.services.rekognition.model.StartShotDetectionFilter;
      import com.amazonaws.services.rekognition.model.StartTechnicalCueDetectionFilter;
      import com.amazonaws.services.rekognition.model.TechnicalCueSegment;
      import com.amazonaws.services.rekognition.model.AudioMetadata;
      

   2. Tambahkan kode berikut ke kelas VideoDetect.

          //Copyright 2020 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.)
      
      
          private static void StartSegmentDetection(String bucket, String video) throws Exception{
                  
              NotificationChannel channel= new NotificationChannel()
                      .withSNSTopicArn(snsTopicArn)
                      .withRoleArn(roleArn);
      
              float minTechnicalCueConfidence = 80F; 
              float minShotConfidence = 80F; 
                      
              StartSegmentDetectionRequest req = new StartSegmentDetectionRequest()
                      .withVideo(new Video()
                              .withS3Object(new S3Object()
                                      .withBucket(bucket)
                                      .withName(video)))
                      .withSegmentTypes("TECHNICAL_CUE" , "SHOT")
                      .withFilters(new StartSegmentDetectionFilters()
                              .withTechnicalCueFilter(new StartTechnicalCueDetectionFilter()
                                      .withMinSegmentConfidence(minTechnicalCueConfidence))
                              .withShotFilter(new StartShotDetectionFilter()
                                      .withMinSegmentConfidence(minShotConfidence)))
                      .withJobTag("DetectingVideoSegments")
                      .withNotificationChannel(channel);
      
              StartSegmentDetectionResult startLabelDetectionResult = rek.startSegmentDetection(req);
              startJobId=startLabelDetectionResult.getJobId();
              
          }
      
          private static void GetSegmentDetectionResults() throws Exception{
      
              int maxResults=10;
              String paginationToken=null;
              GetSegmentDetectionResult segmentDetectionResult=null;
              Boolean firstTime=true;
              
      
              do {
                  if (segmentDetectionResult !=null){
                      paginationToken = segmentDetectionResult.getNextToken();
                  }
      
                  GetSegmentDetectionRequest segmentDetectionRequest= new GetSegmentDetectionRequest()
                          .withJobId(startJobId)
                          .withMaxResults(maxResults)
                          .withNextToken(paginationToken);
      
                  segmentDetectionResult = rek.getSegmentDetection(segmentDetectionRequest);
                  
                  if(firstTime) {
                      System.out.println("\nStatus\n------");
                      System.out.println(segmentDetectionResult.getJobStatus());
                      System.out.println("\nRequested features\n------------------");
                       for (SegmentTypeInfo requestedFeatures : segmentDetectionResult.getSelectedSegmentTypes()) {
                          System.out.println(requestedFeatures.getType());
                      }
                       int count=1;
                       List<VideoMetadata> videoMetaDataList = segmentDetectionResult.getVideoMetadata();
                       System.out.println("\nVideo Streams\n-------------");
                       for (VideoMetadata videoMetaData: videoMetaDataList) {
                           System.out.println("Stream: " + count++);
                           System.out.println("\tFormat: " + videoMetaData.getFormat());
                           System.out.println("\tCodec: " + videoMetaData.getCodec());
                           System.out.println("\tDuration: " + videoMetaData.getDurationMillis());
                           System.out.println("\tFrameRate: " + videoMetaData.getFrameRate());
                       } 
      
                       
                       List<AudioMetadata> audioMetaDataList = segmentDetectionResult.getAudioMetadata();
                       System.out.println("\nAudio streams\n-------------");
      
                       count=1;
                       for (AudioMetadata audioMetaData: audioMetaDataList) {
                           System.out.println("Stream: " + count++);
                           System.out.println("\tSample Rate: " + audioMetaData.getSampleRate());
                           System.out.println("\tCodec: " + audioMetaData.getCodec());
                           System.out.println("\tDuration: " + audioMetaData.getDurationMillis());
                           System.out.println("\tNumber of Channels: " + audioMetaData.getNumberOfChannels());
                       }
                       System.out.println("\nSegments\n--------");
      
                      firstTime=false;
                  }
      
      
                  //Show segment information
      
                  List<SegmentDetection> detectedSegments= segmentDetectionResult.getSegments();
                  
                  for (SegmentDetection detectedSegment: detectedSegments) { 
                      
                     if (detectedSegment.getType().contains(SegmentType.TECHNICAL_CUE.toString())) {
                          System.out.println("Technical Cue");
                          TechnicalCueSegment segmentCue=detectedSegment.getTechnicalCueSegment();
                          System.out.println("\tType: " + segmentCue.getType()); 
                          System.out.println("\tConfidence: " + segmentCue.getConfidence().toString());
                      }
                     if (detectedSegment.getType().contains(SegmentType.SHOT.toString())) { 
                          System.out.println("Shot");
                          ShotSegment segmentShot=detectedSegment.getShotSegment();
                          System.out.println("\tIndex " + segmentShot.getIndex()); 
                          System.out.println("\tConfidence: " + segmentShot.getConfidence().toString());
                      }
                      long seconds=detectedSegment.getDurationMillis();
                      System.out.println("\tDuration : " + Long.toString(seconds) + " milliseconds");
                      System.out.println("\tStart time code: " + detectedSegment.getStartTimecodeSMPTE());
                      System.out.println("\tEnd time code: " + detectedSegment.getEndTimecodeSMPTE());
                      System.out.println("\tDuration time code: " + detectedSegment.getDurationSMPTE());
                      System.out.println();
                                      
                   } 
                         
              } while (segmentDetectionResult !=null && segmentDetectionResult.getNextToken() != null);
      
          } 
      

   3. Dalam fungsi main, ganti baris:

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

      dengan:

              StartSegmentDetection(bucket, video);
      
              if (GetSQSMessageSuccess()==true)
              	GetSegmentDetectionResults();

   Java V2

   //snippet-start:[rekognition.java2.recognize_video_text.import]
   import software.amazon.awssdk.auth.credentials.ProfileCredentialsProvider;
   import software.amazon.awssdk.regions.Region;
   import software.amazon.awssdk.services.rekognition.RekognitionClient;
   import software.amazon.awssdk.services.rekognition.model.S3Object;
   import software.amazon.awssdk.services.rekognition.model.NotificationChannel;
   import software.amazon.awssdk.services.rekognition.model.Video;
   import software.amazon.awssdk.services.rekognition.model.StartTextDetectionRequest;
   import software.amazon.awssdk.services.rekognition.model.StartTextDetectionResponse;
   import software.amazon.awssdk.services.rekognition.model.RekognitionException;
   import software.amazon.awssdk.services.rekognition.model.GetTextDetectionResponse;
   import software.amazon.awssdk.services.rekognition.model.GetTextDetectionRequest;
   import software.amazon.awssdk.services.rekognition.model.VideoMetadata;
   import software.amazon.awssdk.services.rekognition.model.TextDetectionResult;
   import java.util.List;
   //snippet-end:[rekognition.java2.recognize_video_text.import]
   
   /**
   * 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 DetectVideoSegments {
   
    private static String startJobId ="";
    public static void main(String[] args) {
   
        final String usage = "\n" +
            "Usage: " +
            "   <bucket> <video> <topicArn> <roleArn>\n\n" +
            "Where:\n" +
            "   bucket - The name of the bucket in which the video is located (for example, (for example, myBucket). \n\n"+
            "   video - The name of video (for example, people.mp4). \n\n" +
            "   topicArn - The ARN of the Amazon Simple Notification Service (Amazon SNS) topic. \n\n" +
            "   roleArn - The ARN of the AWS Identity and Access Management (IAM) role to use. \n\n" ;
   
        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_WEST_2;
        RekognitionClient rekClient = RekognitionClient.builder()
            .region(region)
            .credentialsProvider(ProfileCredentialsProvider.create("profile-name"))
            .build();
   
        NotificationChannel channel = NotificationChannel.builder()
            .snsTopicArn(topicArn)
            .roleArn(roleArn)
            .build();
   
        startTextLabels(rekClient, channel, bucket, video);
        GetTextResults(rekClient);
        System.out.println("This example is done!");
        rekClient.close();
    }
   
    // snippet-start:[rekognition.java2.recognize_video_text.main]
    public static void startTextLabels(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();
   
            StartTextDetectionRequest labelDetectionRequest = StartTextDetectionRequest.builder()
                .jobTag("DetectingLabels")
                .notificationChannel(channel)
                .video(vidOb)
                .build();
   
            StartTextDetectionResponse labelDetectionResponse = rekClient.startTextDetection(labelDetectionRequest);
            startJobId = labelDetectionResponse.jobId();
   
        } catch (RekognitionException e) {
            System.out.println(e.getMessage());
            System.exit(1);
        }
    }
   
    public static void GetTextResults(RekognitionClient rekClient) {
   
        try {
            String paginationToken=null;
            GetTextDetectionResponse textDetectionResponse=null;
            boolean finished = false;
            String status;
            int yy=0 ;
   
            do{
                if (textDetectionResponse !=null)
                    paginationToken = textDetectionResponse.nextToken();
   
                GetTextDetectionRequest recognitionRequest = GetTextDetectionRequest.builder()
                    .jobId(startJobId)
                    .nextToken(paginationToken)
                    .maxResults(10)
                    .build();
   
                // Wait until the job succeeds.
                while (!finished) {
                    textDetectionResponse = rekClient.getTextDetection(recognitionRequest);
                    status = textDetectionResponse.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=textDetectionResponse.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<TextDetectionResult> labels= textDetectionResponse.textDetections();
                for (TextDetectionResult detectedText: labels) {
                    System.out.println("Confidence: " + detectedText.textDetection().confidence().toString());
                    System.out.println("Id : " + detectedText.textDetection().id());
                    System.out.println("Parent Id: " + detectedText.textDetection().parentId());
                    System.out.println("Type: " + detectedText.textDetection().type());
                    System.out.println("Text: " + detectedText.textDetection().detectedText());
                    System.out.println();
                }
   
            } while (textDetectionResponse !=null && textDetectionResponse.nextToken() != null);
   
        } catch(RekognitionException | InterruptedException e) {
            System.out.println(e.getMessage());
            System.exit(1);
        }
    }
    // snippet-end:[rekognition.java2.recognize_video_text.main]
   }

   Python

   1. Tambahkan kode berikut ke kelas VideoDetect yang Anda buat di langkah 1.

      # Copyright 2020 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.)
      
          def StartSegmentDetection(self):
      
              min_Technical_Cue_Confidence = 80.0
              min_Shot_Confidence = 80.0
              max_pixel_threshold = 0.1
              min_coverage_percentage = 60
      
              response = self.rek.start_segment_detection(
                  Video={"S3Object": {"Bucket": self.bucket, "Name": self.video}},
                  NotificationChannel={
                      "RoleArn": self.roleArn,
                      "SNSTopicArn": self.snsTopicArn,
                  },
                  SegmentTypes=["TECHNICAL_CUE", "SHOT"],
                  Filters={
                      "TechnicalCueFilter": {
                          "BlackFrame": {
                              "MaxPixelThreshold": max_pixel_threshold,
                              "MinCoveragePercentage": min_coverage_percentage,
                          },
                          "MinSegmentConfidence": min_Technical_Cue_Confidence,
                      },
                      "ShotFilter": {"MinSegmentConfidence": min_Shot_Confidence},
                  }
              )
      
              self.startJobId = response["JobId"]
              print(f"Start Job Id: {self.startJobId}")
      
          def GetSegmentDetectionResults(self):
              maxResults = 10
              paginationToken = ""
              finished = False
              firstTime = True
      
              while finished == False:
                  response = self.rek.get_segment_detection(
                      JobId=self.startJobId, MaxResults=maxResults, NextToken=paginationToken
                  )
      
                  if firstTime == True:
                      print(f"Status\n------\n{response['JobStatus']}")
                      print("\nRequested Types\n---------------")
                      for selectedSegmentType in response['SelectedSegmentTypes']:
                          print(f"\tType: {selectedSegmentType['Type']}")
                          print(f"\t\tModel Version: {selectedSegmentType['ModelVersion']}")
      
                      print()
                      print("\nAudio metadata\n--------------")
                      for audioMetadata in response['AudioMetadata']:
                          print(f"\tCodec: {audioMetadata['Codec']}")
                          print(f"\tDuration: {audioMetadata['DurationMillis']}")
                          print(f"\tNumber of Channels: {audioMetadata['NumberOfChannels']}")
                          print(f"\tSample rate: {audioMetadata['SampleRate']}")
                      print()
                      print("\nVideo metadata\n--------------")
                      for videoMetadata in response["VideoMetadata"]:
                          print(f"\tCodec: {videoMetadata['Codec']}")
                          print(f"\tColor Range: {videoMetadata['ColorRange']}")
                          print(f"\tDuration: {videoMetadata['DurationMillis']}")
                          print(f"\tFormat: {videoMetadata['Format']}")
                          print(f"\tFrame rate: {videoMetadata['FrameRate']}")
                          print("\nSegments\n--------")
      
                      firstTime = False
      
                  for segment in response['Segments']:
      
                      if segment["Type"] == "TECHNICAL_CUE":
                          print("Technical Cue")
                          print(f"\tConfidence: {segment['TechnicalCueSegment']['Confidence']}")
                          print(f"\tType: {segment['TechnicalCueSegment']['Type']}")
      
                      if segment["Type"] == "SHOT":
                          print("Shot")
                          print(f"\tConfidence: {segment['ShotSegment']['Confidence']}")
                          print(f"\tIndex: " + str(segment["ShotSegment"]["Index"]))
      
                      print(f"\tDuration (milliseconds): {segment['DurationMillis']}")
                      print(f"\tStart Timestamp (milliseconds): {segment['StartTimestampMillis']}")
                      print(f"\tEnd Timestamp (milliseconds): {segment['EndTimestampMillis']}")
                      
                      print(f"\tStart timecode: {segment['StartTimecodeSMPTE']}")
                      print(f"\tEnd timecode: {segment['EndTimecodeSMPTE']}")
                      print(f"\tDuration timecode: {segment['DurationSMPTE']}")
      
                      print(f"\tStart frame number {segment['StartFrameNumber']}")
                      print(f"\tEnd frame number: {segment['EndFrameNumber']}")
                      print(f"\tDuration frames: {segment['DurationFrames']}")
      
                      print()
      
                  if "NextToken" in response:
                      paginationToken = response["NextToken"]
                  else:
                      finished = True

   2. Dalam fungsi main, ganti baris:

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

      dengan:

          analyzer.StartSegmentDetection()
          if analyzer.GetSQSMessageSuccess()==True:
              analyzer.GetSegmentDetectionResults()

   catatan

   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.

3. Jalankan kode tersebut. Informasi tentang segmen yang terdeteksi dalam video input akan ditampilkan.