Package com.google.cloud.aiplatform.v1
Class ExplanationMetadata.InputMetadata.Visualization.Builder
java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<ExplanationMetadata.InputMetadata.Visualization.Builder>
com.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Builder
- All Implemented Interfaces:
ExplanationMetadata.InputMetadata.VisualizationOrBuilder,com.google.protobuf.Message.Builder,com.google.protobuf.MessageLite.Builder,com.google.protobuf.MessageLiteOrBuilder,com.google.protobuf.MessageOrBuilder,Cloneable
- Enclosing class:
- ExplanationMetadata.InputMetadata.Visualization
public static final class ExplanationMetadata.InputMetadata.Visualization.Builder
extends com.google.protobuf.GeneratedMessage.Builder<ExplanationMetadata.InputMetadata.Visualization.Builder>
implements ExplanationMetadata.InputMetadata.VisualizationOrBuilder
Visualization configurations for image explanation.Protobuf type
google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization-
Method Summary
Modifier and TypeMethodDescriptionbuild()clear()Excludes attributions below the specified percentile, from the highlighted areas.Excludes attributions above the specified percentile from the highlighted areas.The color scheme used for the highlighted areas.How the original image is displayed in the visualization.Whether to only highlight pixels with positive contributions, negative or both.Type of the image visualization.floatExcludes attributions below the specified percentile, from the highlighted areas.floatExcludes attributions above the specified percentile from the highlighted areas.The color scheme used for the highlighted areas.intThe color scheme used for the highlighted areas.static final com.google.protobuf.Descriptors.Descriptorcom.google.protobuf.Descriptors.DescriptorHow the original image is displayed in the visualization.intHow the original image is displayed in the visualization.Whether to only highlight pixels with positive contributions, negative or both.intWhether to only highlight pixels with positive contributions, negative or both.getType()Type of the image visualization.intType of the image visualization.protected com.google.protobuf.GeneratedMessage.FieldAccessorTablefinal booleanmergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) mergeFrom(com.google.protobuf.Message other) setClipPercentLowerbound(float value) Excludes attributions below the specified percentile, from the highlighted areas.setClipPercentUpperbound(float value) Excludes attributions above the specified percentile from the highlighted areas.The color scheme used for the highlighted areas.setColorMapValue(int value) The color scheme used for the highlighted areas.How the original image is displayed in the visualization.setOverlayTypeValue(int value) How the original image is displayed in the visualization.Whether to only highlight pixels with positive contributions, negative or both.setPolarityValue(int value) Whether to only highlight pixels with positive contributions, negative or both.Type of the image visualization.setTypeValue(int value) Type of the image visualization.Methods inherited from class com.google.protobuf.GeneratedMessage.Builder
addRepeatedField, clearField, clearOneof, clone, getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, getUnknownFieldSetBuilder, hasField, hasOneof, internalGetMapField, internalGetMapFieldReflection, internalGetMutableMapField, internalGetMutableMapFieldReflection, isClean, markClean, mergeUnknownFields, mergeUnknownLengthDelimitedField, mergeUnknownVarintField, newBuilderForField, onBuilt, onChanged, parseUnknownField, setField, setRepeatedField, setUnknownFields, setUnknownFieldSetBuilder, setUnknownFieldsProto3Methods inherited from class com.google.protobuf.AbstractMessage.Builder
findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toStringMethods inherited from class com.google.protobuf.AbstractMessageLite.Builder
addAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, newUninitializedMessageExceptionMethods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitMethods inherited from interface com.google.protobuf.Message.Builder
mergeDelimitedFrom, mergeDelimitedFromMethods inherited from interface com.google.protobuf.MessageLite.Builder
mergeFromMethods inherited from interface com.google.protobuf.MessageOrBuilder
findInitializationErrors, getAllFields, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof
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Method Details
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getDescriptor
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() -
internalGetFieldAccessorTable
protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()- Specified by:
internalGetFieldAccessorTablein classcom.google.protobuf.GeneratedMessage.Builder<ExplanationMetadata.InputMetadata.Visualization.Builder>
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clear
- Specified by:
clearin interfacecom.google.protobuf.Message.Builder- Specified by:
clearin interfacecom.google.protobuf.MessageLite.Builder- Overrides:
clearin classcom.google.protobuf.GeneratedMessage.Builder<ExplanationMetadata.InputMetadata.Visualization.Builder>
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getDescriptorForType
public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()- Specified by:
getDescriptorForTypein interfacecom.google.protobuf.Message.Builder- Specified by:
getDescriptorForTypein interfacecom.google.protobuf.MessageOrBuilder- Overrides:
getDescriptorForTypein classcom.google.protobuf.GeneratedMessage.Builder<ExplanationMetadata.InputMetadata.Visualization.Builder>
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getDefaultInstanceForType
- Specified by:
getDefaultInstanceForTypein interfacecom.google.protobuf.MessageLiteOrBuilder- Specified by:
getDefaultInstanceForTypein interfacecom.google.protobuf.MessageOrBuilder
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build
- Specified by:
buildin interfacecom.google.protobuf.Message.Builder- Specified by:
buildin interfacecom.google.protobuf.MessageLite.Builder
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buildPartial
- Specified by:
buildPartialin interfacecom.google.protobuf.Message.Builder- Specified by:
buildPartialin interfacecom.google.protobuf.MessageLite.Builder
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mergeFrom
public ExplanationMetadata.InputMetadata.Visualization.Builder mergeFrom(com.google.protobuf.Message other) - Specified by:
mergeFromin interfacecom.google.protobuf.Message.Builder- Overrides:
mergeFromin classcom.google.protobuf.AbstractMessage.Builder<ExplanationMetadata.InputMetadata.Visualization.Builder>
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mergeFrom
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isInitialized
public final boolean isInitialized()- Specified by:
isInitializedin interfacecom.google.protobuf.MessageLiteOrBuilder- Overrides:
isInitializedin classcom.google.protobuf.GeneratedMessage.Builder<ExplanationMetadata.InputMetadata.Visualization.Builder>
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mergeFrom
public ExplanationMetadata.InputMetadata.Visualization.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException - Specified by:
mergeFromin interfacecom.google.protobuf.Message.Builder- Specified by:
mergeFromin interfacecom.google.protobuf.MessageLite.Builder- Overrides:
mergeFromin classcom.google.protobuf.AbstractMessage.Builder<ExplanationMetadata.InputMetadata.Visualization.Builder>- Throws:
IOException
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getTypeValue
public int getTypeValue()Type of the image visualization. Only applicable to [Integrated Gradients attribution][google.cloud.aiplatform.v1.ExplanationParameters.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;- Specified by:
getTypeValuein interfaceExplanationMetadata.InputMetadata.VisualizationOrBuilder- Returns:
- The enum numeric value on the wire for type.
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setTypeValue
Type of the image visualization. Only applicable to [Integrated Gradients attribution][google.cloud.aiplatform.v1.ExplanationParameters.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;- Parameters:
value- The enum numeric value on the wire for type to set.- Returns:
- This builder for chaining.
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getType
Type of the image visualization. Only applicable to [Integrated Gradients attribution][google.cloud.aiplatform.v1.ExplanationParameters.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;- Specified by:
getTypein interfaceExplanationMetadata.InputMetadata.VisualizationOrBuilder- Returns:
- The type.
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setType
public ExplanationMetadata.InputMetadata.Visualization.Builder setType(ExplanationMetadata.InputMetadata.Visualization.Type value) Type of the image visualization. Only applicable to [Integrated Gradients attribution][google.cloud.aiplatform.v1.ExplanationParameters.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;- Parameters:
value- The type to set.- Returns:
- This builder for chaining.
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clearType
Type of the image visualization. Only applicable to [Integrated Gradients attribution][google.cloud.aiplatform.v1.ExplanationParameters.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:
- This builder for chaining.
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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;- Specified by:
getPolarityValuein interfaceExplanationMetadata.InputMetadata.VisualizationOrBuilder- Returns:
- The enum numeric value on the wire for polarity.
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setPolarityValue
Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE.
.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;- Parameters:
value- The enum numeric value on the wire for polarity to set.- Returns:
- This builder for chaining.
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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;- Specified by:
getPolarityin interfaceExplanationMetadata.InputMetadata.VisualizationOrBuilder- Returns:
- The polarity.
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setPolarity
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;- Parameters:
value- The polarity to set.- Returns:
- This builder for chaining.
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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:
- This builder for chaining.
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getColorMapValue
public int getColorMapValue()The color scheme used for the highlighted areas. Defaults to PINK_GREEN for [Integrated Gradients attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution], which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for [XRAI attribution][google.cloud.aiplatform.v1.ExplanationParameters.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;- Specified by:
getColorMapValuein interfaceExplanationMetadata.InputMetadata.VisualizationOrBuilder- Returns:
- The enum numeric value on the wire for colorMap.
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setColorMapValue
The color scheme used for the highlighted areas. Defaults to PINK_GREEN for [Integrated Gradients attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution], which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for [XRAI attribution][google.cloud.aiplatform.v1.ExplanationParameters.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;- Parameters:
value- The enum numeric value on the wire for colorMap to set.- Returns:
- This builder for chaining.
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getColorMap
The color scheme used for the highlighted areas. Defaults to PINK_GREEN for [Integrated Gradients attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution], which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for [XRAI attribution][google.cloud.aiplatform.v1.ExplanationParameters.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;- Specified by:
getColorMapin interfaceExplanationMetadata.InputMetadata.VisualizationOrBuilder- Returns:
- The colorMap.
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setColorMap
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][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution], which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for [XRAI attribution][google.cloud.aiplatform.v1.ExplanationParameters.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;- Parameters:
value- The colorMap to set.- Returns:
- This builder for chaining.
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clearColorMap
The color scheme used for the highlighted areas. Defaults to PINK_GREEN for [Integrated Gradients attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution], which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for [XRAI attribution][google.cloud.aiplatform.v1.ExplanationParameters.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:
- This builder for chaining.
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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;- Specified by:
getClipPercentUpperboundin interfaceExplanationMetadata.InputMetadata.VisualizationOrBuilder- Returns:
- The clipPercentUpperbound.
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setClipPercentUpperbound
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;- Parameters:
value- The clipPercentUpperbound to set.- Returns:
- This builder for chaining.
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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:
- This builder for chaining.
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getClipPercentLowerbound
public float getClipPercentLowerbound()Excludes attributions below the specified percentile, from the highlighted areas. Defaults to 62.
float clip_percent_lowerbound = 5;- Specified by:
getClipPercentLowerboundin interfaceExplanationMetadata.InputMetadata.VisualizationOrBuilder- Returns:
- The clipPercentLowerbound.
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setClipPercentLowerbound
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;- Parameters:
value- The clipPercentLowerbound to set.- Returns:
- This builder for chaining.
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clearClipPercentLowerbound
Excludes attributions below the specified percentile, from the highlighted areas. Defaults to 62.
float clip_percent_lowerbound = 5;- Returns:
- This builder for chaining.
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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;- Specified by:
getOverlayTypeValuein interfaceExplanationMetadata.InputMetadata.VisualizationOrBuilder- Returns:
- The enum numeric value on the wire for overlayType.
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setOverlayTypeValue
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;- Parameters:
value- The enum numeric value on the wire for overlayType to set.- Returns:
- This builder for chaining.
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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;- Specified by:
getOverlayTypein interfaceExplanationMetadata.InputMetadata.VisualizationOrBuilder- Returns:
- The overlayType.
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setOverlayType
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;- Parameters:
value- The overlayType to set.- Returns:
- This builder for chaining.
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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:
- This builder for chaining.
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