get_label_detection(**kwargs)¶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 .
GetLabelDetectionreturns an array of detected labels (Labels) sorted by the time the labels were detected. You can also sort by the label name by specifyingNAMEfor theSortByinput parameter. If there is noNAMEspecified, the default sort is by timestamp.
You can select how results are aggregated by using the AggregateBy input parameter. The default aggregation method is TIMESTAMPS . You can also aggregate by SEGMENTS , which aggregates all instances of labels detected in a given segment.
The returned Labels array may include the following attributes:
SEGMENTS , the StartTimestampMillis , EndTimestampMillis , and DurationMillis 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 StartTimestampMillis .Timestamp and Bounding box information are returned for detected Instances, only if aggregation is done by TIMESTAMPS . If aggregating by SEGMENTS , information about detected instances isn’t returned.
The version of the label model used for the detection is also returned.
NoteDominantColorsisn't returned forInstances, although it is shown as part of the response in the sample seen below.
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 .
See also: AWS API Documentation
Request Syntax
response = client.get_label_detection(
JobId='string',
MaxResults=123,
NextToken='string',
SortBy='NAME'|'TIMESTAMP',
AggregateBy='TIMESTAMPS'|'SEGMENTS'
)
[REQUIRED]
Job identifier for the label detection operation for which you want results returned. You get the job identifer from an initial call to StartlabelDetection .
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 .dict
Response Syntax
{
'JobStatus': 'IN_PROGRESS'|'SUCCEEDED'|'FAILED',
'StatusMessage': 'string',
'VideoMetadata': {
'Codec': 'string',
'DurationMillis': 123,
'Format': 'string',
'FrameRate': ...,
'FrameHeight': 123,
'FrameWidth': 123,
'ColorRange': 'FULL'|'LIMITED'
},
'NextToken': 'string',
'Labels': [
{
'Timestamp': 123,
'Label': {
'Name': 'string',
'Confidence': ...,
'Instances': [
{
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'Confidence': ...,
'DominantColors': [
{
'Red': 123,
'Blue': 123,
'Green': 123,
'HexCode': 'string',
'CSSColor': 'string',
'SimplifiedColor': 'string',
'PixelPercent': ...
},
]
},
],
'Parents': [
{
'Name': 'string'
},
],
'Aliases': [
{
'Name': 'string'
},
],
'Categories': [
{
'Name': 'string'
},
]
},
'StartTimestampMillis': 123,
'EndTimestampMillis': 123,
'DurationMillis': 123
},
],
'LabelModelVersion': 'string'
}
Response Structure
(dict) --
JobStatus (string) --
The current status of the label detection job.
StatusMessage (string) --
If the job fails, StatusMessage provides a descriptive error message.
VideoMetadata (dict) --
Information about a video that Amazon Rekognition Video analyzed. Videometadata is returned in every page of paginated responses from a Amazon Rekognition video operation.
Codec (string) --
Type of compression used in the analyzed video.
DurationMillis (integer) --
Length of the video in milliseconds.
Format (string) --
Format of the analyzed video. Possible values are MP4, MOV and AVI.
FrameRate (float) --
Number of frames per second in the video.
FrameHeight (integer) --
Vertical pixel dimension of the video.
FrameWidth (integer) --
Horizontal pixel dimension of the video.
ColorRange (string) --
A description of the range of luminance values in a video, either LIMITED (16 to 235) or FULL (0 to 255).
NextToken (string) --
If the response is truncated, Amazon Rekognition Video returns this token that you can use in the subsequent request to retrieve the next set of labels.
Labels (list) --
An array of labels detected in the video. Each element contains the detected label and the time, in milliseconds from the start of the video, that the label was detected.
(dict) --
Information about a label detected in a video analysis request and the time the label was detected in the video.
Timestamp (integer) --
Time, in milliseconds from the start of the video, that the label was detected. Note that Timestamp is not guaranteed to be accurate to the individual frame where the label first appears.
Label (dict) --
Details about the detected label.
Name (string) --
The name (label) of the object or scene.
Confidence (float) --
Level of confidence.
Instances (list) --
If Label represents an object, Instances contains the bounding boxes for each instance of the detected object. Bounding boxes are returned for common object labels such as people, cars, furniture, apparel or pets.
(dict) --
An instance of a label returned by Amazon Rekognition Image ( DetectLabels ) or by Amazon Rekognition Video ( GetLabelDetection ).
BoundingBox (dict) --
The position of the label instance on the image.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
Confidence (float) --
The confidence that Amazon Rekognition has in the accuracy of the bounding box.
DominantColors (list) --
The dominant colors found in an individual instance of a label.
(dict) --
A description of the dominant colors in an image.
Red (integer) --
The Red RGB value for a dominant color.
Blue (integer) --
The Blue RGB value for a dominant color.
Green (integer) --
The Green RGB value for a dominant color.
HexCode (string) --
The Hex code equivalent of the RGB values for a dominant color.
CSSColor (string) --
The CSS color name of a dominant color.
SimplifiedColor (string) --
One of 12 simplified color names applied to a dominant color.
PixelPercent (float) --
The percentage of image pixels that have a given dominant color.
Parents (list) --
The parent labels for a label. The response includes all ancestor labels.
(dict) --
A parent label for a label. A label can have 0, 1, or more parents.
Name (string) --
The name of the parent label.
Aliases (list) --
A list of potential aliases for a given label.
(dict) --
A potential alias of for a given label.
Name (string) --
The name of an alias for a given label.
Categories (list) --
A list of the categories associated with a given label.
(dict) --
The category that applies to a given label.
Name (string) --
The name of a category that applies to a given label.
StartTimestampMillis (integer) --
The time in milliseconds defining the start of the timeline segment containing a continuously detected label.
EndTimestampMillis (integer) --
The time in milliseconds defining the end of the timeline segment containing a continuously detected label.
DurationMillis (integer) --
The time duration of a segment in milliseconds, I.e. time elapsed from StartTimestampMillis to EndTimestampMillis.
LabelModelVersion (string) --
Version number of the label detection model that was used to detect labels.
Exceptions
Rekognition.Client.exceptions.AccessDeniedExceptionRekognition.Client.exceptions.InternalServerErrorRekognition.Client.exceptions.InvalidParameterExceptionRekognition.Client.exceptions.InvalidPaginationTokenExceptionRekognition.Client.exceptions.ProvisionedThroughputExceededExceptionRekognition.Client.exceptions.ResourceNotFoundExceptionRekognition.Client.exceptions.ThrottlingException