Class ExplanationMetadata.InputMetadata.Visualization.Builder (2.4.0)

public static final class ExplanationMetadata.InputMetadata.Visualization.Builder extends GeneratedMessageV3.Builder<ExplanationMetadata.InputMetadata.Visualization.Builder> implements ExplanationMetadata.InputMetadata.VisualizationOrBuilder

Visualization configurations for image explanation.

Protobuf type google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > ExplanationMetadata.InputMetadata.Visualization.Builder

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public ExplanationMetadata.InputMetadata.Visualization.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder
Overrides

build()

public ExplanationMetadata.InputMetadata.Visualization build()
Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization

buildPartial()

public ExplanationMetadata.InputMetadata.Visualization buildPartial()
Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization

clear()

public ExplanationMetadata.InputMetadata.Visualization.Builder clear()
Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder
Overrides

clearClipPercentLowerbound()

public ExplanationMetadata.InputMetadata.Visualization.Builder clearClipPercentLowerbound()

Excludes attributions below the specified percentile, from the highlighted areas. Defaults to 62.

float clip_percent_lowerbound = 5;

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

clearClipPercentUpperbound()

public ExplanationMetadata.InputMetadata.Visualization.Builder clearClipPercentUpperbound()

Excludes attributions above the specified percentile from the highlighted areas. Using the clip_percent_upperbound and clip_percent_lowerbound together can be useful for filtering out noise and making it easier to see areas of strong attribution. Defaults to 99.9.

float clip_percent_upperbound = 4;

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

clearColorMap()

public ExplanationMetadata.InputMetadata.Visualization.Builder clearColorMap()

The color scheme used for the highlighted areas. Defaults to PINK_GREEN for Integrated Gradients attribution, which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which highlights the most influential regions in yellow and the least influential in blue.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public ExplanationMetadata.InputMetadata.Visualization.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
NameDescription
fieldFieldDescriptor
Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder
Overrides

clearOneof(Descriptors.OneofDescriptor oneof)

public ExplanationMetadata.InputMetadata.Visualization.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
NameDescription
oneofOneofDescriptor
Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder
Overrides

clearOverlayType()

public ExplanationMetadata.InputMetadata.Visualization.Builder clearOverlayType()

How the original image is displayed in the visualization. Adjusting the overlay can help increase visual clarity if the original image makes it difficult to view the visualization. Defaults to NONE.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

clearPolarity()

public ExplanationMetadata.InputMetadata.Visualization.Builder clearPolarity()

Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

clearType()

public ExplanationMetadata.InputMetadata.Visualization.Builder clearType()

Type of the image visualization. Only applicable to Integrated Gradients attribution. OUTLINES shows regions of attribution, while PIXELS shows per-pixel attribution. Defaults to OUTLINES.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

clone()

public ExplanationMetadata.InputMetadata.Visualization.Builder clone()
Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder
Overrides

getClipPercentLowerbound()

public float getClipPercentLowerbound()

Excludes attributions below the specified percentile, from the highlighted areas. Defaults to 62.

float clip_percent_lowerbound = 5;

Returns
TypeDescription
float

The clipPercentLowerbound.

getClipPercentUpperbound()

public float getClipPercentUpperbound()

Excludes attributions above the specified percentile from the highlighted areas. Using the clip_percent_upperbound and clip_percent_lowerbound together can be useful for filtering out noise and making it easier to see areas of strong attribution. Defaults to 99.9.

float clip_percent_upperbound = 4;

Returns
TypeDescription
float

The clipPercentUpperbound.

getColorMap()

public ExplanationMetadata.InputMetadata.Visualization.ColorMap getColorMap()

The color scheme used for the highlighted areas. Defaults to PINK_GREEN for Integrated Gradients attribution, which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which highlights the most influential regions in yellow and the least influential in blue.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.ColorMap

The colorMap.

getColorMapValue()

public int getColorMapValue()

The color scheme used for the highlighted areas. Defaults to PINK_GREEN for Integrated Gradients attribution, which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which highlights the most influential regions in yellow and the least influential in blue.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;

Returns
TypeDescription
int

The enum numeric value on the wire for colorMap.

getDefaultInstanceForType()

public ExplanationMetadata.InputMetadata.Visualization getDefaultInstanceForType()
Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
TypeDescription
Descriptor

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
Descriptor
Overrides

getOverlayType()

public ExplanationMetadata.InputMetadata.Visualization.OverlayType getOverlayType()

How the original image is displayed in the visualization. Adjusting the overlay can help increase visual clarity if the original image makes it difficult to view the visualization. Defaults to NONE.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.OverlayType

The overlayType.

getOverlayTypeValue()

public int getOverlayTypeValue()

How the original image is displayed in the visualization. Adjusting the overlay can help increase visual clarity if the original image makes it difficult to view the visualization. Defaults to NONE.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;

Returns
TypeDescription
int

The enum numeric value on the wire for overlayType.

getPolarity()

public ExplanationMetadata.InputMetadata.Visualization.Polarity getPolarity()

Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Polarity

The polarity.

getPolarityValue()

public int getPolarityValue()

Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;

Returns
TypeDescription
int

The enum numeric value on the wire for polarity.

getType()

public ExplanationMetadata.InputMetadata.Visualization.Type getType()

Type of the image visualization. Only applicable to Integrated Gradients attribution. OUTLINES shows regions of attribution, while PIXELS shows per-pixel attribution. Defaults to OUTLINES.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Type

The type.

getTypeValue()

public int getTypeValue()

Type of the image visualization. Only applicable to Integrated Gradients attribution. OUTLINES shows regions of attribution, while PIXELS shows per-pixel attribution. Defaults to OUTLINES.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;

Returns
TypeDescription
int

The enum numeric value on the wire for type.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

mergeFrom(ExplanationMetadata.InputMetadata.Visualization other)

public ExplanationMetadata.InputMetadata.Visualization.Builder mergeFrom(ExplanationMetadata.InputMetadata.Visualization other)
Parameter
NameDescription
otherExplanationMetadata.InputMetadata.Visualization
Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public ExplanationMetadata.InputMetadata.Visualization.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder
Overrides Exceptions
TypeDescription
IOException

mergeFrom(Message other)

public ExplanationMetadata.InputMetadata.Visualization.Builder mergeFrom(Message other)
Parameter
NameDescription
otherMessage
Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder
Overrides

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ExplanationMetadata.InputMetadata.Visualization.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder
Overrides

setClipPercentLowerbound(float value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setClipPercentLowerbound(float value)

Excludes attributions below the specified percentile, from the highlighted areas. Defaults to 62.

float clip_percent_lowerbound = 5;

Parameter
NameDescription
valuefloat

The clipPercentLowerbound to set.

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

setClipPercentUpperbound(float value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setClipPercentUpperbound(float value)

Excludes attributions above the specified percentile from the highlighted areas. Using the clip_percent_upperbound and clip_percent_lowerbound together can be useful for filtering out noise and making it easier to see areas of strong attribution. Defaults to 99.9.

float clip_percent_upperbound = 4;

Parameter
NameDescription
valuefloat

The clipPercentUpperbound to set.

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

setColorMap(ExplanationMetadata.InputMetadata.Visualization.ColorMap value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setColorMap(ExplanationMetadata.InputMetadata.Visualization.ColorMap value)

The color scheme used for the highlighted areas. Defaults to PINK_GREEN for Integrated Gradients attribution, which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which highlights the most influential regions in yellow and the least influential in blue.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;

Parameter
NameDescription
valueExplanationMetadata.InputMetadata.Visualization.ColorMap

The colorMap to set.

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

setColorMapValue(int value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setColorMapValue(int value)

The color scheme used for the highlighted areas. Defaults to PINK_GREEN for Integrated Gradients attribution, which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which highlights the most influential regions in yellow and the least influential in blue.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;

Parameter
NameDescription
valueint

The enum numeric value on the wire for colorMap to set.

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder
Overrides

setOverlayType(ExplanationMetadata.InputMetadata.Visualization.OverlayType value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setOverlayType(ExplanationMetadata.InputMetadata.Visualization.OverlayType value)

How the original image is displayed in the visualization. Adjusting the overlay can help increase visual clarity if the original image makes it difficult to view the visualization. Defaults to NONE.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;

Parameter
NameDescription
valueExplanationMetadata.InputMetadata.Visualization.OverlayType

The overlayType to set.

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

setOverlayTypeValue(int value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setOverlayTypeValue(int value)

How the original image is displayed in the visualization. Adjusting the overlay can help increase visual clarity if the original image makes it difficult to view the visualization. Defaults to NONE.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;

Parameter
NameDescription
valueint

The enum numeric value on the wire for overlayType to set.

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

setPolarity(ExplanationMetadata.InputMetadata.Visualization.Polarity value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setPolarity(ExplanationMetadata.InputMetadata.Visualization.Polarity value)

Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;

Parameter
NameDescription
valueExplanationMetadata.InputMetadata.Visualization.Polarity

The polarity to set.

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

setPolarityValue(int value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setPolarityValue(int value)

Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;

Parameter
NameDescription
valueint

The enum numeric value on the wire for polarity to set.

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
NameDescription
fieldFieldDescriptor
indexint
valueObject
Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder
Overrides

setType(ExplanationMetadata.InputMetadata.Visualization.Type value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setType(ExplanationMetadata.InputMetadata.Visualization.Type value)

Type of the image visualization. Only applicable to Integrated Gradients attribution. OUTLINES shows regions of attribution, while PIXELS shows per-pixel attribution. Defaults to OUTLINES.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;

Parameter
NameDescription
valueExplanationMetadata.InputMetadata.Visualization.Type

The type to set.

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

setTypeValue(int value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setTypeValue(int value)

Type of the image visualization. Only applicable to Integrated Gradients attribution. OUTLINES shows regions of attribution, while PIXELS shows per-pixel attribution. Defaults to OUTLINES.

.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;

Parameter
NameDescription
valueint

The enum numeric value on the wire for type to set.

Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

public final ExplanationMetadata.InputMetadata.Visualization.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
ExplanationMetadata.InputMetadata.Visualization.Builder
Overrides