Class ExplanationMetadata.InputMetadata.Visualization.Builder (3.49.0)

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.v1.ExplanationMetadata.InputMetadata.Visualization

Inheritance

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

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
Type Description
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public ExplanationMetadata.InputMetadata.Visualization.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
Name Description
field FieldDescriptor
value Object
Returns
Type Description
ExplanationMetadata.InputMetadata.Visualization.Builder
Overrides

build()

public ExplanationMetadata.InputMetadata.Visualization build()
Returns
Type Description
ExplanationMetadata.InputMetadata.Visualization

buildPartial()

public ExplanationMetadata.InputMetadata.Visualization buildPartial()
Returns
Type Description
ExplanationMetadata.InputMetadata.Visualization

clear()

public ExplanationMetadata.InputMetadata.Visualization.Builder clear()
Returns
Type Description
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
Type Description
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
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;

Returns
Type Description
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public ExplanationMetadata.InputMetadata.Visualization.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
Name Description
field FieldDescriptor
Returns
Type Description
ExplanationMetadata.InputMetadata.Visualization.Builder
Overrides

clearOneof(Descriptors.OneofDescriptor oneof)

public ExplanationMetadata.InputMetadata.Visualization.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
Name Description
oneof OneofDescriptor
Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;

Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;

Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;

Returns
Type Description
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

clone()

public ExplanationMetadata.InputMetadata.Visualization.Builder clone()
Returns
Type Description
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
Type Description
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
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;

Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;

Returns
Type Description
int

The enum numeric value on the wire for colorMap.

getDefaultInstanceForType()

public ExplanationMetadata.InputMetadata.Visualization getDefaultInstanceForType()
Returns
Type Description
ExplanationMetadata.InputMetadata.Visualization

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;

Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;

Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;

Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;

Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;

Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;

Returns
Type Description
int

The enum numeric value on the wire for type.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Type Description
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
Type Description
boolean
Overrides

mergeFrom(ExplanationMetadata.InputMetadata.Visualization other)

public ExplanationMetadata.InputMetadata.Visualization.Builder mergeFrom(ExplanationMetadata.InputMetadata.Visualization other)
Parameter
Name Description
other ExplanationMetadata.InputMetadata.Visualization
Returns
Type Description
ExplanationMetadata.InputMetadata.Visualization.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public ExplanationMetadata.InputMetadata.Visualization.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input CodedInputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
ExplanationMetadata.InputMetadata.Visualization.Builder
Overrides
Exceptions
Type Description
IOException

mergeFrom(Message other)

public ExplanationMetadata.InputMetadata.Visualization.Builder mergeFrom(Message other)
Parameter
Name Description
other Message
Returns
Type Description
ExplanationMetadata.InputMetadata.Visualization.Builder
Overrides

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ExplanationMetadata.InputMetadata.Visualization.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
Name Description
unknownFields UnknownFieldSet
Returns
Type Description
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
Name Description
value float

The clipPercentLowerbound to set.

Returns
Type Description
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
Name Description
value float

The clipPercentUpperbound to set.

Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;

Parameter
Name Description
value ExplanationMetadata.InputMetadata.Visualization.ColorMap

The colorMap to set.

Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;

Parameter
Name Description
value int

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

Returns
Type Description
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
Name Description
field FieldDescriptor
value Object
Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;

Parameter
Name Description
value ExplanationMetadata.InputMetadata.Visualization.OverlayType

The overlayType to set.

Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;

Parameter
Name Description
value int

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

Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;

Parameter
Name Description
value ExplanationMetadata.InputMetadata.Visualization.Polarity

The polarity to set.

Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;

Parameter
Name Description
value int

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

Returns
Type Description
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
Name Description
field FieldDescriptor
index int
value Object
Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;

Parameter
Name Description
value ExplanationMetadata.InputMetadata.Visualization.Type

The type to set.

Returns
Type Description
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.v1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;

Parameter
Name Description
value int

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

Returns
Type Description
ExplanationMetadata.InputMetadata.Visualization.Builder

This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

public final ExplanationMetadata.InputMetadata.Visualization.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
Name Description
unknownFields UnknownFieldSet
Returns
Type Description
ExplanationMetadata.InputMetadata.Visualization.Builder
Overrides