<p>Starts asynchronous detection of labels in a stored video.</p> <p>Amazon Rekognition Video can detect labels in a video. Labels are instances of real-world entities. This includes objects like flower, tree, and table; events like wedding, graduation, and birthday party; concepts like landscape, evening, and nature; and activities like a person getting out of a car or a person skiing.</p> <p>The video must be stored in an Amazon S3 bucket. Use <a>Video</a> to specify the bucket name and the filename of the video. <code>StartLabelDetection</code> returns a job identifier (<code>JobId</code>) which you use to get the results of the operation. When label detection is finished, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic that you specify in <code>NotificationChannel</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> <i>Optional Parameters</i> </p> <p> <code>StartLabelDetection</code> has the <code>GENERAL_LABELS</code> Feature applied by default. This feature allows you to provide filtering criteria to the <code>Settings</code> parameter. You can filter with sets of individual labels or with label categories. You can specify inclusive filters, exclusive filters, or a combination of inclusive and exclusive filters. For more information on filtering, see <a href="https://docs.aws.amazon.com/rekognition/latest/dg/labels-detecting-labels-video.html">Detecting labels in a video</a>.</p> <p>You can specify <code>MinConfidence</code> to control the confidence threshold for the labels returned. The default is 50.</p>

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

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

<p>Starts asynchronous detection of labels in a stored video.</p> <p>Amazon Rekognition Video can detect labels in a video. Labels are instances of real-world entities. This includes objects like flower, tree, and table; events like wedding, graduation, and birthday party; concepts like landscape, evening, and nature; and activities like a person getting out of a car or a person skiing.</p> <p>The video must be stored in an Amazon S3 bucket. Use <a>Video</a> to specify the bucket name and the filename of the video. <code>StartLabelDetection</code> returns a job identifier (<code>JobId</code>) which you use to get the results of the operation. When label detection is finished, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic that you specify in <code>NotificationChannel</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> <i>Optional Parameters</i> </p> <p> <code>StartLabelDetection</code> has the <code>GENERAL_LABELS</code> Feature applied by default. This feature allows you to provide filtering criteria to the <code>Settings</code> parameter. You can filter with sets of individual labels or with label categories. You can specify inclusive filters, exclusive filters, or a combination of inclusive and exclusive filters. For more information on filtering, see <a href="https://docs.aws.amazon.com/rekognition/latest/dg/labels-detecting-labels-video.html">Detecting labels in a video</a>.</p> <p>You can specify <code>MinConfidence</code> to control the confidence threshold for the labels returned. The default is 50.</p>

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

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