Interface PredictResponseOrBuilder (2.17.0)

public interface PredictResponseOrBuilder extends MessageOrBuilder

Implements

MessageOrBuilder

Methods

containsMetadata(String key)

public abstract boolean containsMetadata(String key)

Additional domain-specific prediction response metadata. AutoML Vision Object Detection max_bounding_box_count : (int64) The maximum number of bounding boxes to return per image. AutoML Natural Language Sentiment Analysis sentiment_score : (float, deprecated) A value between -1 and 1, -1 maps to least positive sentiment, while 1 maps to the most positive one and the higher the score, the more positive the sentiment in the document is. Yet these values are relative to the training data, so e.g. if all data was positive then -1 is also positive (though the least). sentiment_score is not the same as "score" and "magnitude" from Sentiment Analysis in the Natural Language API.

map<string, string> metadata = 2;

Parameter
NameDescription
keyString
Returns
TypeDescription
boolean

getMetadata()

public abstract Map<String,String> getMetadata()

Use #getMetadataMap() instead.

Returns
TypeDescription
Map<String,String>

getMetadataCount()

public abstract int getMetadataCount()

Additional domain-specific prediction response metadata. AutoML Vision Object Detection max_bounding_box_count : (int64) The maximum number of bounding boxes to return per image. AutoML Natural Language Sentiment Analysis sentiment_score : (float, deprecated) A value between -1 and 1, -1 maps to least positive sentiment, while 1 maps to the most positive one and the higher the score, the more positive the sentiment in the document is. Yet these values are relative to the training data, so e.g. if all data was positive then -1 is also positive (though the least). sentiment_score is not the same as "score" and "magnitude" from Sentiment Analysis in the Natural Language API.

map<string, string> metadata = 2;

Returns
TypeDescription
int

getMetadataMap()

public abstract Map<String,String> getMetadataMap()

Additional domain-specific prediction response metadata. AutoML Vision Object Detection max_bounding_box_count : (int64) The maximum number of bounding boxes to return per image. AutoML Natural Language Sentiment Analysis sentiment_score : (float, deprecated) A value between -1 and 1, -1 maps to least positive sentiment, while 1 maps to the most positive one and the higher the score, the more positive the sentiment in the document is. Yet these values are relative to the training data, so e.g. if all data was positive then -1 is also positive (though the least). sentiment_score is not the same as "score" and "magnitude" from Sentiment Analysis in the Natural Language API.

map<string, string> metadata = 2;

Returns
TypeDescription
Map<String,String>

getMetadataOrDefault(String key, String defaultValue)

public abstract String getMetadataOrDefault(String key, String defaultValue)

Additional domain-specific prediction response metadata. AutoML Vision Object Detection max_bounding_box_count : (int64) The maximum number of bounding boxes to return per image. AutoML Natural Language Sentiment Analysis sentiment_score : (float, deprecated) A value between -1 and 1, -1 maps to least positive sentiment, while 1 maps to the most positive one and the higher the score, the more positive the sentiment in the document is. Yet these values are relative to the training data, so e.g. if all data was positive then -1 is also positive (though the least). sentiment_score is not the same as "score" and "magnitude" from Sentiment Analysis in the Natural Language API.

map<string, string> metadata = 2;

Parameters
NameDescription
keyString
defaultValueString
Returns
TypeDescription
String

getMetadataOrThrow(String key)

public abstract String getMetadataOrThrow(String key)

Additional domain-specific prediction response metadata. AutoML Vision Object Detection max_bounding_box_count : (int64) The maximum number of bounding boxes to return per image. AutoML Natural Language Sentiment Analysis sentiment_score : (float, deprecated) A value between -1 and 1, -1 maps to least positive sentiment, while 1 maps to the most positive one and the higher the score, the more positive the sentiment in the document is. Yet these values are relative to the training data, so e.g. if all data was positive then -1 is also positive (though the least). sentiment_score is not the same as "score" and "magnitude" from Sentiment Analysis in the Natural Language API.

map<string, string> metadata = 2;

Parameter
NameDescription
keyString
Returns
TypeDescription
String

getPayload(int index)

public abstract AnnotationPayload getPayload(int index)

Prediction result. AutoML Translation and AutoML Natural Language Sentiment Analysis return precisely one payload.

repeated .google.cloud.automl.v1.AnnotationPayload payload = 1;

Parameter
NameDescription
indexint
Returns
TypeDescription
AnnotationPayload

getPayloadCount()

public abstract int getPayloadCount()

Prediction result. AutoML Translation and AutoML Natural Language Sentiment Analysis return precisely one payload.

repeated .google.cloud.automl.v1.AnnotationPayload payload = 1;

Returns
TypeDescription
int

getPayloadList()

public abstract List<AnnotationPayload> getPayloadList()

Prediction result. AutoML Translation and AutoML Natural Language Sentiment Analysis return precisely one payload.

repeated .google.cloud.automl.v1.AnnotationPayload payload = 1;

Returns
TypeDescription
List<AnnotationPayload>

getPayloadOrBuilder(int index)

public abstract AnnotationPayloadOrBuilder getPayloadOrBuilder(int index)

Prediction result. AutoML Translation and AutoML Natural Language Sentiment Analysis return precisely one payload.

repeated .google.cloud.automl.v1.AnnotationPayload payload = 1;

Parameter
NameDescription
indexint
Returns
TypeDescription
AnnotationPayloadOrBuilder

getPayloadOrBuilderList()

public abstract List<? extends AnnotationPayloadOrBuilder> getPayloadOrBuilderList()

Prediction result. AutoML Translation and AutoML Natural Language Sentiment Analysis return precisely one payload.

repeated .google.cloud.automl.v1.AnnotationPayload payload = 1;

Returns
TypeDescription
List<? extends com.google.cloud.automl.v1.AnnotationPayloadOrBuilder>

getPreprocessedInput()

public abstract ExamplePayload getPreprocessedInput()

The preprocessed example that AutoML actually makes prediction on. Empty if AutoML does not preprocess the input example. For AutoML Natural Language (Classification, Entity Extraction, and Sentiment Analysis), if the input is a document, the recognized text is returned in the document_text property.

.google.cloud.automl.v1.ExamplePayload preprocessed_input = 3;

Returns
TypeDescription
ExamplePayload

The preprocessedInput.

getPreprocessedInputOrBuilder()

public abstract ExamplePayloadOrBuilder getPreprocessedInputOrBuilder()

The preprocessed example that AutoML actually makes prediction on. Empty if AutoML does not preprocess the input example. For AutoML Natural Language (Classification, Entity Extraction, and Sentiment Analysis), if the input is a document, the recognized text is returned in the document_text property.

.google.cloud.automl.v1.ExamplePayload preprocessed_input = 3;

Returns
TypeDescription
ExamplePayloadOrBuilder

hasPreprocessedInput()

public abstract boolean hasPreprocessedInput()

The preprocessed example that AutoML actually makes prediction on. Empty if AutoML does not preprocess the input example. For AutoML Natural Language (Classification, Entity Extraction, and Sentiment Analysis), if the input is a document, the recognized text is returned in the document_text property.

.google.cloud.automl.v1.ExamplePayload preprocessed_input = 3;

Returns
TypeDescription
boolean

Whether the preprocessedInput field is set.