Rekognition / Client / start_label_detection
start_label_detection#
- Rekognition.Client.start_label_detection(**kwargs)#
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 inNotificationChannel
.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 toStartLabelDetection
.Optional Parameters
StartLabelDetection
has theGENERAL_LABELS
Feature applied by default. This feature allows you to provide filtering criteria to theSettings
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 Detecting labels in a video.You can specify
MinConfidence
to control the confidence threshold for the labels returned. The default is 50.See also: AWS API Documentation
Request Syntax
response = client.start_label_detection( Video={ 'S3Object': { 'Bucket': 'string', 'Name': 'string', 'Version': 'string' } }, ClientRequestToken='string', MinConfidence=..., NotificationChannel={ 'SNSTopicArn': 'string', 'RoleArn': 'string' }, JobTag='string', Features=[ 'GENERAL_LABELS', ], Settings={ 'GeneralLabels': { 'LabelInclusionFilters': [ 'string', ], 'LabelExclusionFilters': [ 'string', ], 'LabelCategoryInclusionFilters': [ 'string', ], 'LabelCategoryExclusionFilters': [ 'string', ] } } )
- Parameters:
Video (dict) –
[REQUIRED]
The video in which you want to detect labels. The video must be stored in an Amazon S3 bucket.
S3Object (dict) –
The Amazon S3 bucket name and file name for the video.
Bucket (string) –
Name of the S3 bucket.
Name (string) –
S3 object key name.
Version (string) –
If the bucket is versioning enabled, you can specify the object version.
ClientRequestToken (string) – Idempotent token used to identify the start request. If you use the same token with multiple
StartLabelDetection
requests, the sameJobId
is returned. UseClientRequestToken
to prevent the same job from being accidently started more than once.MinConfidence (float) –
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 and bounding boxes (if detected) with confidence values greater than or equal to 50 percent.NotificationChannel (dict) –
The Amazon SNS topic ARN you want Amazon Rekognition Video to publish the completion status of the label detection operation to. The Amazon SNS topic must have a topic name that begins with AmazonRekognition if you are using the AmazonRekognitionServiceRole permissions policy.
SNSTopicArn (string) – [REQUIRED]
The Amazon SNS topic to which Amazon Rekognition posts the completion status.
RoleArn (string) – [REQUIRED]
The ARN of an IAM role that gives Amazon Rekognition publishing permissions to the Amazon SNS topic.
JobTag (string) – 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.Features (list) –
The features to return after video analysis. You can specify that GENERAL_LABELS are returned.
(string) –
Settings (dict) –
The settings for a StartLabelDetection request.Contains the specified parameters for the label detection request of an asynchronous label analysis operation. Settings can include filters for GENERAL_LABELS.
GeneralLabels (dict) –
Contains filters for the object labels returned by DetectLabels. Filters can be inclusive, exclusive, or a combination of both and can be applied to individual l abels or entire label categories.
LabelInclusionFilters (list) –
The labels that should be included in the return from DetectLabels.
(string) –
LabelExclusionFilters (list) –
The labels that should be excluded from the return from DetectLabels.
(string) –
LabelCategoryInclusionFilters (list) –
The label categories that should be included in the return from DetectLabels.
(string) –
LabelCategoryExclusionFilters (list) –
The label categories that should be excluded from the return from DetectLabels.
(string) –
- Return type:
dict
- Returns:
Response Syntax
{ 'JobId': 'string' }
Response Structure
(dict) –
JobId (string) –
The identifier for the label detection job. Use
JobId
to identify the job in a subsequent call toGetLabelDetection
.
Exceptions
Rekognition.Client.exceptions.AccessDeniedException
Rekognition.Client.exceptions.IdempotentParameterMismatchException
Rekognition.Client.exceptions.InvalidParameterException
Rekognition.Client.exceptions.InvalidS3ObjectException
Rekognition.Client.exceptions.InternalServerError
Rekognition.Client.exceptions.VideoTooLargeException
Rekognition.Client.exceptions.ProvisionedThroughputExceededException
Rekognition.Client.exceptions.LimitExceededException
Rekognition.Client.exceptions.ThrottlingException