Get Segment Detection

rekognition_get_segment_detection

R Documentation

Gets the segment detection results of a Amazon Rekognition Video analysis started by StartSegmentDetection

Description

Gets the segment detection results of a Amazon Rekognition Video analysis started by start_segment_detection.

Segment detection with Amazon Rekognition Video is an asynchronous operation. You start segment detection by calling start_segment_detection which returns a job identifier (JobId). When the segment detection operation finishes, Amazon Rekognition publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to start_segment_detection. To get the results of the segment detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. if so, call get_segment_detection and pass the job identifier (JobId) from the initial call of start_segment_detection.

get_segment_detection returns detected segments in an array (Segments) of SegmentDetection objects. Segments is sorted by the segment types specified in the SegmentTypes input parameter of start_segment_detection. Each element of the array includes the detected segment, the precentage confidence in the acuracy of the detected segment, the type of the segment, and the frame in which the segment was detected.

Use SelectedSegmentTypes to find out the type of segment detection requested in the call to start_segment_detection.

Use the MaxResults parameter to limit the number of segment detections returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call get_segment_detection and populate the NextToken request parameter with the token value returned from the previous call to get_segment_detection.

For more information, see Detecting video segments in stored video in the Amazon Rekognition Developer Guide.

Usage

rekognition_get_segment_detection(JobId, MaxResults, NextToken)

Arguments

JobId

[required] Job identifier for the text detection operation for which you want results returned. You get the job identifer from an initial call to start_segment_detection.

MaxResults

Maximum number of results to return per paginated call. The largest value you can specify is 1000.

NextToken

If the response is truncated, Amazon Rekognition Video returns this token that you can use in the subsequent request to retrieve the next set of text.

Value

A list with the following syntax:

list(
  JobStatus = "IN_PROGRESS"|"SUCCEEDED"|"FAILED",
  StatusMessage = "string",
  VideoMetadata = list(
    list(
      Codec = "string",
      DurationMillis = 123,
      Format = "string",
      FrameRate = 123.0,
      FrameHeight = 123,
      FrameWidth = 123,
      ColorRange = "FULL"|"LIMITED"
    )
  ),
  AudioMetadata = list(
    list(
      Codec = "string",
      DurationMillis = 123,
      SampleRate = 123,
      NumberOfChannels = 123
    )
  ),
  NextToken = "string",
  Segments = list(
    list(
      Type = "TECHNICAL_CUE"|"SHOT",
      StartTimestampMillis = 123,
      EndTimestampMillis = 123,
      DurationMillis = 123,
      StartTimecodeSMPTE = "string",
      EndTimecodeSMPTE = "string",
      DurationSMPTE = "string",
      TechnicalCueSegment = list(
        Type = "ColorBars"|"EndCredits"|"BlackFrames"|"OpeningCredits"|"StudioLogo"|"Slate"|"Content",
        Confidence = 123.0
      ),
      ShotSegment = list(
        Index = 123,
        Confidence = 123.0
      ),
      StartFrameNumber = 123,
      EndFrameNumber = 123,
      DurationFrames = 123
    )
  ),
  SelectedSegmentTypes = list(
    list(
      Type = "TECHNICAL_CUE"|"SHOT",
      ModelVersion = "string"
    )
  ),
  JobId = "string",
  Video = list(
    S3Object = list(
      Bucket = "string",
      Name = "string",
      Version = "string"
    )
  ),
  JobTag = "string"
)

Request syntax

svc$get_segment_detection(
  JobId = "string",
  MaxResults = 123,
  NextToken = "string"
)