示例：检测存储视频中的分段

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示例：检测存储视频中的分段 - Amazon Rekognition

以下过程说明如何针对存储在 Amazon S3 存储桶中的视频，检测技术提示分段和镜头检测分段。此过程还显示了如何根据 Amazon Rekognition Video 对检测准确性的置信度筛选检测到的分段。

此示例扩展了使用 Java 或 Python 分析存储在 Amazon S3 存储桶中的视频 (SDK)（使用 Amazon Simple Queue Service 队列获取视频分析请求的完成状态）中的代码。

检测存储在 Amazon S3 存储桶的视频中的分段 (SDK)

执行使用 Java 或 Python 分析存储在 Amazon S3 存储桶中的视频 (SDK)。

将以下内容添加到您在步骤 1 中使用的代码。

Java

添加以下导入。


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;

将以下代码添加类 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);

    }

在函数 main 中，将以下行:


        StartLabelDetection(amzn-s3-demo-bucket, video);

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

替换为:


        StartSegmentDetection(amzn-s3-demo-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, amzn-s3-demo-bucket). \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

将以下代码添加到您在步骤 1 中创建的类 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.)

    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

在函数 main 中，将以下行:


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

替换为:


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

anchor anchor anchor

添加以下导入。


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;

将以下代码添加类 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);

    }

在函数 main 中，将以下行:


        StartLabelDetection(amzn-s3-demo-bucket, video);

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

替换为:


        StartSegmentDetection(amzn-s3-demo-bucket, video);

        if (GetSQSMessageSuccess()==true)
        	GetSegmentDetectionResults();

注意

如果您已经运行了除使用 Java 或 Python 分析存储在 Amazon S3 存储桶中的视频 (SDK) 之外的视频示例，则要替换的代码可能会有所不同。

运行该代码。将显示在输入视频中检测到的分段的相关信息。

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示例：检测存储视频中的分段

检测存储在 Amazon S3 存储桶的视频中的分段 (SDK)

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