Esempio: rilevamento di segmenti in un video archiviato - Amazon Rekognition

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Esempio: rilevamento di segmenti in un video archiviato

La procedura seguente illustra come rilevare segmenti di segnali d'azione tecnici e segmenti di rilevamento delle riprese in un video archiviato in un bucket Amazon S3. La procedura illustra anche come filtrare i segmenti rilevati in base alla sicurezza che Video Amazon Rekognition ha nell'accuratezza del rilevamento.

L'esempio si espande nel codice in Analisi di un video archiviato in un bucket Amazon S3 con Java o Python (SDK), che utilizza una coda Amazon Simple Queue Service per ottenere lo stato di completamento di una richiesta di analisi video.

Per rilevare segmenti in un video archiviato in un bucket Amazon S3 (SDK)
  1. Eseguire Analisi di un video archiviato in un bucket Amazon S3 con Java o Python (SDK).

  2. Aggiungere quanto segue al codice utilizzato nella fase 1.

    Java
    1. Aggiungi le seguenti importazioni:

      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. Aggiungere il codice seguente alla 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); }
    3. Nella funzione main, sostituisci le righe:

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

      con:

      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. Aggiungere il seguente codice alla classe VideoDetect creata nella fase 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. Nella funzione main, sostituisci le righe:

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

      con:

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

    Se hai già eseguito un video di esempio diverso da Analisi di un video archiviato in un bucket Amazon S3 con Java o Python (SDK), il codice da sostituire potrebbe essere diverso.

  3. Eseguire il codice. Vengono visualizzate informazioni sui segmenti rilevati nel video di input.