Class: Aws::LookoutforVision::Types::DetectAnomalyResult
- Inherits:
-
Struct
- Object
- Struct
- Aws::LookoutforVision::Types::DetectAnomalyResult
- Defined in:
- gems/aws-sdk-lookoutforvision/lib/aws-sdk-lookoutforvision/types.rb
Overview
The prediction results from a call to DetectAnomalies.
DetectAnomalyResult
includes classification information for the
prediction (IsAnomalous
and Confidence
). If the model you use is
an image segementation model, DetectAnomalyResult
also includes
segmentation information (Anomalies
and AnomalyMask
).
Classification information is calculated separately from segmentation
information and you shouldn't assume a relationship between them.
Constant Summary collapse
- SENSITIVE =
[]
Instance Attribute Summary collapse
-
#anomalies ⇒ Array<Types::Anomaly>
If the model is an image segmentation model,
Anomalies
contains a list of anomaly types found in the image. -
#anomaly_mask ⇒ String
If the model is an image segmentation model,
AnomalyMask
contains pixel masks that covers all anomaly types found on the image. -
#confidence ⇒ Float
The confidence that Lookout for Vision has in the accuracy of the classification in
IsAnomalous
. -
#is_anomalous ⇒ Boolean
True if Amazon Lookout for Vision classifies the image as containing an anomaly, otherwise false.
-
#source ⇒ Types::ImageSource
The source of the image that was analyzed.
Instance Attribute Details
#anomalies ⇒ Array<Types::Anomaly>
If the model is an image segmentation model, Anomalies
contains a
list of anomaly types found in the image. There is one entry for
each type of anomaly found (even if multiple instances of an anomaly
type exist on the image). The first element in the list is always an
anomaly type representing the image background ('background') and
shouldn't be considered an anomaly. Amazon Lookout for Vision
automatically add the background anomaly type to the response, and
you don't need to declare a background anomaly type in your
dataset.
If the list has one entry ('background'), no anomalies were found on the image.
An image classification model doesn't return an Anomalies
list.
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# File 'gems/aws-sdk-lookoutforvision/lib/aws-sdk-lookoutforvision/types.rb', line 752 class DetectAnomalyResult < Struct.new( :source, :is_anomalous, :confidence, :anomalies, :anomaly_mask) SENSITIVE = [] include Aws::Structure end |
#anomaly_mask ⇒ String
If the model is an image segmentation model, AnomalyMask
contains
pixel masks that covers all anomaly types found on the image. Each
anomaly type has a different mask color. To map a color to an
anomaly type, see the color
field of the PixelAnomaly object.
An image classification model doesn't return an Anomalies
list.
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# File 'gems/aws-sdk-lookoutforvision/lib/aws-sdk-lookoutforvision/types.rb', line 752 class DetectAnomalyResult < Struct.new( :source, :is_anomalous, :confidence, :anomalies, :anomaly_mask) SENSITIVE = [] include Aws::Structure end |
#confidence ⇒ Float
The confidence that Lookout for Vision has in the accuracy of the
classification in IsAnomalous
.
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# File 'gems/aws-sdk-lookoutforvision/lib/aws-sdk-lookoutforvision/types.rb', line 752 class DetectAnomalyResult < Struct.new( :source, :is_anomalous, :confidence, :anomalies, :anomaly_mask) SENSITIVE = [] include Aws::Structure end |
#is_anomalous ⇒ Boolean
True if Amazon Lookout for Vision classifies the image as containing an anomaly, otherwise false.
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# File 'gems/aws-sdk-lookoutforvision/lib/aws-sdk-lookoutforvision/types.rb', line 752 class DetectAnomalyResult < Struct.new( :source, :is_anomalous, :confidence, :anomalies, :anomaly_mask) SENSITIVE = [] include Aws::Structure end |
#source ⇒ Types::ImageSource
The source of the image that was analyzed. direct
means that the
images was supplied from the local computer. No other values are
supported.
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# File 'gems/aws-sdk-lookoutforvision/lib/aws-sdk-lookoutforvision/types.rb', line 752 class DetectAnomalyResult < Struct.new( :source, :is_anomalous, :confidence, :anomalies, :anomaly_mask) SENSITIVE = [] include Aws::Structure end |