<p>Gets the label detection results of a Amazon Rekognition Video analysis started by <a>StartLabelDetection</a>. </p> <p>The label detection operation is started by a call to <a>StartLabelDetection</a> which returns a job identifier (<code>JobId</code>). 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 <code>StartlabelDetection</code>. </p> <p>To get the results of the label detection operation, first check that the status value published to the Amazon SNS topic is <code>SUCCEEDED</code>. If so, call <a>GetLabelDetection</a> and pass the job identifier (<code>JobId</code>) from the initial call to <code>StartLabelDetection</code>.</p> <p> <code>GetLabelDetection</code> returns an array of detected labels (<code>Labels</code>) sorted by the time the labels were detected. You can also sort by the label name by specifying <code>NAME</code> for the <code>SortBy</code> input parameter. If there is no <code>NAME</code> specified, the default sort is by timestamp.</p> <p>You can select how results are aggregated by using the <code>AggregateBy</code> input parameter. The default aggregation method is <code>TIMESTAMPS</code>. You can also aggregate by <code>SEGMENTS</code>, which aggregates all instances of labels detected in a given segment. </p> <p>The returned Labels array may include the following attributes:</p> <ul> <li> <p>Name - The name of the detected label.</p> </li> <li> <p>Confidence - The level of confidence in the label assigned to a detected object. </p> </li> <li> <p>Parents - The ancestor labels for a detected label. GetLabelDetection returns a hierarchical taxonomy of detected labels. For example, a detected car might be assigned the label car. The label car has two parent labels: Vehicle (its parent) and Transportation (its grandparent). The response includes the all ancestors for a label, where every ancestor is a unique label. In the previous example, Car, Vehicle, and Transportation are returned as unique labels in the response. </p> </li> <li> <p> Aliases - Possible Aliases for the label. </p> </li> <li> <p>Categories - The label categories that the detected label belongs to.</p> </li> <li> <p>BoundingBox — Bounding boxes are described for all instances of detected common object labels, returned in an array of Instance objects. An Instance object contains a BoundingBox object, describing the location of the label on the input image. It also includes the confidence for the accuracy of the detected bounding box.</p> </li> <li> <p>Timestamp - Time, in milliseconds from the start of the video, that the label was detected. For aggregation by <code>SEGMENTS</code>, the <code>StartTimestampMillis</code>, <code>EndTimestampMillis</code>, and <code>DurationMillis</code> structures are what define a segment. Although the “Timestamp” structure is still returned with each label, its value is set to be the same as <code>StartTimestampMillis</code>.</p> </li> </ul> <p>Timestamp and Bounding box information are returned for detected Instances, only if aggregation is done by <code>TIMESTAMPS</code>. If aggregating by <code>SEGMENTS</code>, information about detected instances isn’t returned. </p> <p>The version of the label model used for the detection is also returned.</p> <p> <b>Note <code>DominantColors</code> isn't returned for <code>Instances</code>, although it is shown as part of the response in the sample seen below.</b> </p> <p>Use <code>MaxResults</code> parameter to limit the number of labels returned. If there are more results than specified in <code>MaxResults</code>, the value of <code>NextToken</code> in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call <code>GetlabelDetection</code> and populate the <code>NextToken</code> request parameter with the token value returned from the previous call to <code>GetLabelDetection</code>.</p>

{
  "success": true,
  "data": {
    "id": "abc123",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

{
  "success": false,
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Invalid request parameters"
  }
}