@Generated(value="software.amazon.awssdk:codegen") public final class DetectAnomalyResult extends Object implements SdkPojo, Serializable, ToCopyableBuilder<DetectAnomalyResult.Builder,DetectAnomalyResult>
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.
| Modifier and Type | Class and Description |
|---|---|
static interface |
DetectAnomalyResult.Builder |
| Modifier and Type | Method and Description |
|---|---|
List<Anomaly> |
anomalies()
If the model is an image segmentation model,
Anomalies contains a list of anomaly types found in the
image. |
SdkBytes |
anomalyMask()
If the model is an image segmentation model,
AnomalyMask contains pixel masks that covers all
anomaly types found on the image. |
static DetectAnomalyResult.Builder |
builder() |
Float |
confidence()
The confidence that Lookout for Vision has in the accuracy of the classification in
IsAnomalous. |
boolean |
equals(Object obj) |
boolean |
equalsBySdkFields(Object obj) |
<T> Optional<T> |
getValueForField(String fieldName,
Class<T> clazz) |
boolean |
hasAnomalies()
For responses, this returns true if the service returned a value for the Anomalies property.
|
int |
hashCode() |
Boolean |
isAnomalous()
True if Amazon Lookout for Vision classifies the image as containing an anomaly, otherwise false.
|
List<SdkField<?>> |
sdkFields() |
static Class<? extends DetectAnomalyResult.Builder> |
serializableBuilderClass() |
ImageSource |
source()
The source of the image that was analyzed.
|
DetectAnomalyResult.Builder |
toBuilder() |
String |
toString()
Returns a string representation of this object.
|
clone, finalize, getClass, notify, notifyAll, wait, wait, waitcopypublic final ImageSource source()
The source of the image that was analyzed. direct means that the images was supplied from the local
computer. No other values are supported.
direct means that the images was supplied from
the local computer. No other values are supported.public final Boolean isAnomalous()
True if Amazon Lookout for Vision classifies the image as containing an anomaly, otherwise false.
public final Float confidence()
The confidence that Lookout for Vision has in the accuracy of the classification in IsAnomalous.
IsAnomalous.public final boolean hasAnomalies()
isEmpty() method on the property). This is
useful because the SDK will never return a null collection or map, but you may need to differentiate between the
service returning nothing (or null) and the service returning an empty collection or map. For requests, this
returns true if a value for the property was specified in the request builder, and false if a value was not
specified.public final List<Anomaly> anomalies()
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.
Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
This method will never return null. If you would like to know whether the service returned this field (so that
you can differentiate between null and empty), you can use the hasAnomalies() method.
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.
public final SdkBytes anomalyMask()
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.
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.
public DetectAnomalyResult.Builder toBuilder()
toBuilder in interface ToCopyableBuilder<DetectAnomalyResult.Builder,DetectAnomalyResult>public static DetectAnomalyResult.Builder builder()
public static Class<? extends DetectAnomalyResult.Builder> serializableBuilderClass()
public final boolean equalsBySdkFields(Object obj)
equalsBySdkFields in interface SdkPojopublic final String toString()
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