getLabelDetection method

Future<GetLabelDetectionResponse> getLabelDetection({ required String jobId, int? maxResults, String? nextToken, LabelDetectionSortBy? sortBy, })

Gets the label detection results of a Amazon Rekognition Video analysis started by StartLabelDetection.

The label detection operation is started by a call to StartLabelDetection which returns a job identifier (JobId). When the label detection operation finishes, Amazon Rekognition publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartlabelDetection. To get the results of the label detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetLabelDetection and pass the job identifier (JobId) from the initial call to StartLabelDetection.

GetLabelDetection returns an array of detected labels (Labels) sorted by the time the labels were detected. You can also sort by the label name by specifying NAME for the SortBy input parameter.

The labels returned include the label name, the percentage confidence in the accuracy of the detected label, and the time the label was detected in the video.

The returned labels also include bounding box information for common objects, a hierarchical taxonomy of detected labels, and the version of the label model used for detection.

Use MaxResults parameter to limit the number of labels 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 GetlabelDetection and populate the NextToken request parameter with the token value returned from the previous call to GetLabelDetection.

May throw AccessDeniedException. May throw InternalServerError. May throw InvalidParameterException. May throw InvalidPaginationTokenException. May throw ProvisionedThroughputExceededException. May throw ResourceNotFoundException. May throw ThrottlingException.

Parameter jobId : Job identifier for the label detection operation for which you want results returned. You get the job identifer from an initial call to StartlabelDetection.

Parameter maxResults : Maximum number of results to return per paginated call. The largest value you can specify is 1000. If you specify a value greater than 1000, a maximum of 1000 results is returned. The default value is 1000.

Parameter nextToken : If the previous response was incomplete (because there are more labels to retrieve), Amazon Rekognition Video returns a pagination token in the response. You can use this pagination token to retrieve the next set of labels.

Parameter sortBy : Sort to use for elements in the Labels array. Use TIMESTAMP to sort array elements by the time labels are detected. Use NAME to alphabetically group elements for a label together. Within each label group, the array element are sorted by detection confidence. The default sort is by TIMESTAMP.

Implementation

Future<GetLabelDetectionResponse> getLabelDetection({
  required String jobId,
  int? maxResults,
  String? nextToken,
  LabelDetectionSortBy? sortBy,
}) async {
  ArgumentError.checkNotNull(jobId, 'jobId');
  _s.validateStringLength(
    'jobId',
    jobId,
    1,
    64,
    isRequired: true,
  );
  _s.validateNumRange(
    'maxResults',
    maxResults,
    1,
    1152921504606846976,
  );
  _s.validateStringLength(
    'nextToken',
    nextToken,
    0,
    255,
  );
  final headers = <String, String>{
    'Content-Type': 'application/x-amz-json-1.1',
    'X-Amz-Target': 'RekognitionService.GetLabelDetection'
  };
  final jsonResponse = await _protocol.send(
    method: 'POST',
    requestUri: '/',
    exceptionFnMap: _exceptionFns,
    // TODO queryParams
    headers: headers,
    payload: {
      'JobId': jobId,
      if (maxResults != null) 'MaxResults': maxResults,
      if (nextToken != null) 'NextToken': nextToken,
      if (sortBy != null) 'SortBy': sortBy.toValue(),
    },
  );

  return GetLabelDetectionResponse.fromJson(jsonResponse.body);
}