public final class PredictResponse extends GeneratedMessageV3 implements PredictResponseOrBuilder
Response message for PredictionService.Predict.
Protobuf type google.cloud.automl.v1beta1.PredictResponse
Static Fields
public static final int METADATA_FIELD_NUMBER
Field Value
PAYLOAD_FIELD_NUMBER
public static final int PAYLOAD_FIELD_NUMBER
Field Value
public static final int PREPROCESSED_INPUT_FIELD_NUMBER
Field Value
Static Methods
getDefaultInstance()
public static PredictResponse getDefaultInstance()
Returns
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Returns
newBuilder()
public static PredictResponse.Builder newBuilder()
Returns
newBuilder(PredictResponse prototype)
public static PredictResponse.Builder newBuilder(PredictResponse prototype)
Parameter
Returns
public static PredictResponse parseDelimitedFrom(InputStream input)
Parameter
Returns
Exceptions
public static PredictResponse parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Returns
Exceptions
parseFrom(byte[] data)
public static PredictResponse parseFrom(byte[] data)
Parameter
| Name | Description |
| data | byte[]
|
Returns
Exceptions
parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static PredictResponse parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
Parameters
Returns
Exceptions
parseFrom(ByteString data)
public static PredictResponse parseFrom(ByteString data)
Parameter
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Exceptions
parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static PredictResponse parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
Parameters
Returns
Exceptions
public static PredictResponse parseFrom(CodedInputStream input)
Parameter
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Exceptions
public static PredictResponse parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
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Exceptions
public static PredictResponse parseFrom(InputStream input)
Parameter
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Exceptions
public static PredictResponse parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Returns
Exceptions
parseFrom(ByteBuffer data)
public static PredictResponse parseFrom(ByteBuffer data)
Parameter
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Exceptions
parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static PredictResponse parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
Parameters
Returns
Exceptions
parser()
public static Parser<PredictResponse> parser()
Returns
Methods
public boolean containsMetadata(String key)
Additional domain-specific prediction response metadata.
- For Image Object Detection:
max_bounding_box_count - (int64) At most that many bounding boxes per
image could have been returned.
- For Text Sentiment:
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 will be also positive (though
the least).
The sentiment_score shouldn't be confused with "score" or "magnitude"
from the previous Natural Language Sentiment Analysis API.
map<string, string> metadata = 2;
equals(Object obj)
public boolean equals(Object obj)
Parameter
Returns
Overrides
getDefaultInstanceForType()
public PredictResponse getDefaultInstanceForType()
Returns
public Map<String,String> getMetadata()
Returns
public int getMetadataCount()
Additional domain-specific prediction response metadata.
- For Image Object Detection:
max_bounding_box_count - (int64) At most that many bounding boxes per
image could have been returned.
- For Text Sentiment:
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 will be also positive (though
the least).
The sentiment_score shouldn't be confused with "score" or "magnitude"
from the previous Natural Language Sentiment Analysis API.
map<string, string> metadata = 2;
public Map<String,String> getMetadataMap()
Additional domain-specific prediction response metadata.
- For Image Object Detection:
max_bounding_box_count - (int64) At most that many bounding boxes per
image could have been returned.
- For Text Sentiment:
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 will be also positive (though
the least).
The sentiment_score shouldn't be confused with "score" or "magnitude"
from the previous Natural Language Sentiment Analysis API.
map<string, string> metadata = 2;
public String getMetadataOrDefault(String key, String defaultValue)
Additional domain-specific prediction response metadata.
- For Image Object Detection:
max_bounding_box_count - (int64) At most that many bounding boxes per
image could have been returned.
- For Text Sentiment:
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 will be also positive (though
the least).
The sentiment_score shouldn't be confused with "score" or "magnitude"
from the previous Natural Language Sentiment Analysis API.
map<string, string> metadata = 2;
public String getMetadataOrThrow(String key)
Additional domain-specific prediction response metadata.
- For Image Object Detection:
max_bounding_box_count - (int64) At most that many bounding boxes per
image could have been returned.
- For Text Sentiment:
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 will be also positive (though
the least).
The sentiment_score shouldn't be confused with "score" or "magnitude"
from the previous Natural Language Sentiment Analysis API.
map<string, string> metadata = 2;
getParserForType()
public Parser<PredictResponse> getParserForType()
Returns
Overrides
getPayload(int index)
public AnnotationPayload getPayload(int index)
Prediction result.
Translation and Text Sentiment will return precisely one payload.
repeated .google.cloud.automl.v1beta1.AnnotationPayload payload = 1;
getPayloadCount()
public int getPayloadCount()
Prediction result.
Translation and Text Sentiment will return precisely one payload.
repeated .google.cloud.automl.v1beta1.AnnotationPayload payload = 1;
getPayloadList()
public List<AnnotationPayload> getPayloadList()
Prediction result.
Translation and Text Sentiment will return precisely one payload.
repeated .google.cloud.automl.v1beta1.AnnotationPayload payload = 1;
getPayloadOrBuilder(int index)
public AnnotationPayloadOrBuilder getPayloadOrBuilder(int index)
Prediction result.
Translation and Text Sentiment will return precisely one payload.
repeated .google.cloud.automl.v1beta1.AnnotationPayload payload = 1;
getPayloadOrBuilderList()
public List<? extends AnnotationPayloadOrBuilder> getPayloadOrBuilderList()
Prediction result.
Translation and Text Sentiment will return precisely one payload.
repeated .google.cloud.automl.v1beta1.AnnotationPayload payload = 1;
| Type | Description |
| List<? extends com.google.cloud.automl.v1beta1.AnnotationPayloadOrBuilder> | |
public ExamplePayload getPreprocessedInput()
The preprocessed example that AutoML actually makes prediction on.
Empty if AutoML does not preprocess the input example.
- For Text Extraction:
If the input is a .pdf file, the OCR'ed text will be provided in
document_text.
.google.cloud.automl.v1beta1.ExamplePayload preprocessed_input = 3;
public ExamplePayloadOrBuilder getPreprocessedInputOrBuilder()
The preprocessed example that AutoML actually makes prediction on.
Empty if AutoML does not preprocess the input example.
- For Text Extraction:
If the input is a .pdf file, the OCR'ed text will be provided in
document_text.
.google.cloud.automl.v1beta1.ExamplePayload preprocessed_input = 3;
getSerializedSize()
public int getSerializedSize()
Returns
Overrides
getUnknownFields()
public final UnknownFieldSet getUnknownFields()
Returns
Overrides
public boolean hasPreprocessedInput()
The preprocessed example that AutoML actually makes prediction on.
Empty if AutoML does not preprocess the input example.
- For Text Extraction:
If the input is a .pdf file, the OCR'ed text will be provided in
document_text.
.google.cloud.automl.v1beta1.ExamplePayload preprocessed_input = 3;
| Type | Description |
| boolean | Whether the preprocessedInput field is set.
|
hashCode()
Returns
Overrides
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Overrides
internalGetMapField(int number)
protected MapField internalGetMapField(int number)
Parameter
Returns
Overrides
isInitialized()
public final boolean isInitialized()
Returns
Overrides
newBuilderForType()
public PredictResponse.Builder newBuilderForType()
Returns
newBuilderForType(GeneratedMessageV3.BuilderParent parent)
protected PredictResponse.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Parameter
Returns
Overrides
newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Parameter
Returns
Overrides
toBuilder()
public PredictResponse.Builder toBuilder()
Returns
writeTo(CodedOutputStream output)
public void writeTo(CodedOutputStream output)
Parameter
Overrides
Exceptions
