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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.BuilderMethods
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public ExplanationMetadata.InputMetadata.Visualization.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Name | Description |
field | FieldDescriptor |
value | Object |
Type | Description |
ExplanationMetadata.InputMetadata.Visualization.Builder |
build()
public ExplanationMetadata.InputMetadata.Visualization build()
Type | Description |
ExplanationMetadata.InputMetadata.Visualization |
buildPartial()
public ExplanationMetadata.InputMetadata.Visualization buildPartial()
Type | Description |
ExplanationMetadata.InputMetadata.Visualization |
clear()
public ExplanationMetadata.InputMetadata.Visualization.Builder clear()
Type | Description |
ExplanationMetadata.InputMetadata.Visualization.Builder |
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;
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;
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.v1beta1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;
Type | Description |
ExplanationMetadata.InputMetadata.Visualization.Builder | This builder for chaining. |
clearField(Descriptors.FieldDescriptor field)
public ExplanationMetadata.InputMetadata.Visualization.Builder clearField(Descriptors.FieldDescriptor field)
Name | Description |
field | FieldDescriptor |
Type | Description |
ExplanationMetadata.InputMetadata.Visualization.Builder |
clearOneof(Descriptors.OneofDescriptor oneof)
public ExplanationMetadata.InputMetadata.Visualization.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Name | Description |
oneof | OneofDescriptor |
Type | Description |
ExplanationMetadata.InputMetadata.Visualization.Builder |
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;
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.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;
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.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;
Type | Description |
ExplanationMetadata.InputMetadata.Visualization.Builder | This builder for chaining. |
clone()
public ExplanationMetadata.InputMetadata.Visualization.Builder clone()
Type | Description |
ExplanationMetadata.InputMetadata.Visualization.Builder |
getClipPercentLowerbound()
public float getClipPercentLowerbound()
Excludes attributions below the specified percentile, from the highlighted areas. Defaults to 62.
float clip_percent_lowerbound = 5;
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;
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.v1beta1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;
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.v1beta1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;
Type | Description |
int | The enum numeric value on the wire for colorMap. |
getDefaultInstanceForType()
public ExplanationMetadata.InputMetadata.Visualization getDefaultInstanceForType()
Type | Description |
ExplanationMetadata.InputMetadata.Visualization |
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Type | Description |
Descriptor |
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()
Type | Description |
Descriptor |
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;
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.v1beta1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;
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.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;
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.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;
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.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;
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.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;
Type | Description |
int | The enum numeric value on the wire for type. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Type | Description |
FieldAccessorTable |
isInitialized()
public final boolean isInitialized()
Type | Description |
boolean |
mergeFrom(ExplanationMetadata.InputMetadata.Visualization other)
public ExplanationMetadata.InputMetadata.Visualization.Builder mergeFrom(ExplanationMetadata.InputMetadata.Visualization other)
Name | Description |
other | ExplanationMetadata.InputMetadata.Visualization |
Type | Description |
ExplanationMetadata.InputMetadata.Visualization.Builder |
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public ExplanationMetadata.InputMetadata.Visualization.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Name | Description |
input | CodedInputStream |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
ExplanationMetadata.InputMetadata.Visualization.Builder |
Type | Description |
IOException |
mergeFrom(Message other)
public ExplanationMetadata.InputMetadata.Visualization.Builder mergeFrom(Message other)
Name | Description |
other | Message |
Type | Description |
ExplanationMetadata.InputMetadata.Visualization.Builder |
mergeUnknownFields(UnknownFieldSet unknownFields)
public final ExplanationMetadata.InputMetadata.Visualization.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Name | Description |
unknownFields | UnknownFieldSet |
Type | Description |
ExplanationMetadata.InputMetadata.Visualization.Builder |
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;
Name | Description |
value | float The clipPercentLowerbound to set. |
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;
Name | Description |
value | float The clipPercentUpperbound to set. |
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.v1beta1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;
Name | Description |
value | ExplanationMetadata.InputMetadata.Visualization.ColorMap The colorMap to set. |
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.v1beta1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;
Name | Description |
value | int The enum numeric value on the wire for colorMap to set. |
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)
Name | Description |
field | FieldDescriptor |
value | Object |
Type | Description |
ExplanationMetadata.InputMetadata.Visualization.Builder |
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;
Name | Description |
value | ExplanationMetadata.InputMetadata.Visualization.OverlayType The overlayType to set. |
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.v1beta1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;
Name | Description |
value | int The enum numeric value on the wire for overlayType to set. |
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.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;
Name | Description |
value | ExplanationMetadata.InputMetadata.Visualization.Polarity The polarity to set. |
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.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;
Name | Description |
value | int The enum numeric value on the wire for polarity to set. |
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)
Name | Description |
field | FieldDescriptor |
index | int |
value | Object |
Type | Description |
ExplanationMetadata.InputMetadata.Visualization.Builder |
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;
Name | Description |
value | ExplanationMetadata.InputMetadata.Visualization.Type The type to set. |
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.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;
Name | Description |
value | int The enum numeric value on the wire for type to set. |
Type | Description |
ExplanationMetadata.InputMetadata.Visualization.Builder | This builder for chaining. |
setUnknownFields(UnknownFieldSet unknownFields)
public final ExplanationMetadata.InputMetadata.Visualization.Builder setUnknownFields(UnknownFieldSet unknownFields)
Name | Description |
unknownFields | UnknownFieldSet |
Type | Description |
ExplanationMetadata.InputMetadata.Visualization.Builder |