startLabelDetection method

Future<StartLabelDetectionResponse> startLabelDetection({ required Video video, String? clientRequestToken, String? jobTag, double? minConfidence, NotificationChannel? notificationChannel, })

Starts asynchronous detection of labels in a stored video.

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.

The video must be stored in an Amazon S3 bucket. Use Video to specify the bucket name and the filename of the video. StartLabelDetection returns a job identifier (JobId) 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 NotificationChannel.

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.

May throw AccessDeniedException. May throw IdempotentParameterMismatchException. May throw InvalidParameterException. May throw InvalidS3ObjectException. May throw InternalServerError. May throw VideoTooLargeException. May throw ProvisionedThroughputExceededException. May throw LimitExceededException. May throw ThrottlingException.

Parameter video : The video in which you want to detect labels. The video must be stored in an Amazon S3 bucket.

Parameter clientRequestToken : Idempotent token used to identify the start request. If you use the same token with multiple StartLabelDetection requests, the same JobId is returned. Use ClientRequestToken to prevent the same job from being accidently started more than once.

Parameter jobTag : An identifier you specify that's returned in the completion notification that's published to your Amazon Simple Notification Service topic. For example, you can use JobTag to group related jobs and identify them in the completion notification.

Parameter minConfidence : Specifies the minimum confidence that Amazon Rekognition Video must have in order to return a detected label. Confidence represents how certain Amazon Rekognition is that a label is correctly identified.0 is the lowest confidence. 100 is the highest confidence. Amazon Rekognition Video doesn't return any labels with a confidence level lower than this specified value.

If you don't specify MinConfidence, the operation returns labels with confidence values greater than or equal to 50 percent.

Parameter notificationChannel : The Amazon SNS topic ARN you want Amazon Rekognition Video to publish the completion status of the label detection operation to.

Implementation

Future<StartLabelDetectionResponse> startLabelDetection({
  required Video video,
  String? clientRequestToken,
  String? jobTag,
  double? minConfidence,
  NotificationChannel? notificationChannel,
}) async {
  ArgumentError.checkNotNull(video, 'video');
  _s.validateStringLength(
    'clientRequestToken',
    clientRequestToken,
    1,
    64,
  );
  _s.validateStringLength(
    'jobTag',
    jobTag,
    1,
    256,
  );
  _s.validateNumRange(
    'minConfidence',
    minConfidence,
    0,
    100,
  );
  final headers = <String, String>{
    'Content-Type': 'application/x-amz-json-1.1',
    'X-Amz-Target': 'RekognitionService.StartLabelDetection'
  };
  final jsonResponse = await _protocol.send(
    method: 'POST',
    requestUri: '/',
    exceptionFnMap: _exceptionFns,
    // TODO queryParams
    headers: headers,
    payload: {
      'Video': video,
      if (clientRequestToken != null)
        'ClientRequestToken': clientRequestToken,
      if (jobTag != null) 'JobTag': jobTag,
      if (minConfidence != null) 'MinConfidence': minConfidence,
      if (notificationChannel != null)
        'NotificationChannel': notificationChannel,
    },
  );

  return StartLabelDetectionResponse.fromJson(jsonResponse.body);
}