Exemple : Détection de segments dans une vidéo stockée

La procédure suivante montre comment détecter des segments de repères techniques et des segments de détection de plans dans une vidéo stockée dans un compartiment Amazon S3. La procédure montre également comment filtrer les segments détectés en fonction de la confiance de Vidéo Amazon Rekognition dans la précision de la détection.

L’exemple s’appuie sur le code figurant dans Analyse d’une vidéo stockée dans un compartiment Amazon S3 avec Java or Python (SDK), qui utilise une file d’attente Amazon Simple Queue Service pour obtenir le statut d’achèvement d’une demande d’analyse vidéo.

Pour détecter des segments dans une vidéo stockée dans un compartiment Amazon S3 (SDK)

Effectuez une Analyse d’une vidéo stockée dans un compartiment Amazon S3 avec Java or Python (SDK).

Ajoutez ce qui suit au code que vous avez utilisé à l’étape 1.

Java

Ajoutez les importations suivantes.


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;

Ajoutez le code suivant à la classe 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);

    }

Dans la fonction main, remplacez les lignes :


        StartLabelDetection(bucket, video);

        if (GetSQSMessageSuccess()==true)
        	GetLabelDetectionResults();

avec :


        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

Ajoutez le code suivant à la classe VideoDetect que vous avez créée à l’étape 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

Dans la fonction main, remplacez les lignes :


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

avec :


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

Note

Si vous avez déjà exécuté un exemple vidéo autre que Analyse d’une vidéo stockée dans un compartiment Amazon S3 avec Java or Python (SDK), le code à remplacer peut être différent.

Exécutez le code. Les informations sur les segments détectés dans la vidéo d’entrée sont affichées.

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Conventions de rédaction

Utilisation de l’API de segmentation Amazon Rekognition

Détection de la vivacité faciale