Package com.google.cloud.automl.v1beta1

Interface PredictResponseOrBuilder

  • All Superinterfaces:
    com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
    All Known Implementing Classes:
    PredictResponse, PredictResponse.Builder
    public interface PredictResponseOrBuilder
extends com.google.protobuf.MessageOrBuilder

    • Method Detail

      • getPayloadList

        List<AnnotationPayload> getPayloadList()
         Prediction result.
 Translation and Text Sentiment will return precisely one payload.
        repeated .google.cloud.automl.v1beta1.AnnotationPayload payload = 1;

      • getPayload

        AnnotationPayload getPayload​(int index)
         Prediction result.
 Translation and Text Sentiment will return precisely one payload.
        repeated .google.cloud.automl.v1beta1.AnnotationPayload payload = 1;

      • getPayloadCount

        int getPayloadCount()
         Prediction result.
 Translation and Text Sentiment will return precisely one payload.
        repeated .google.cloud.automl.v1beta1.AnnotationPayload payload = 1;

      • getPayloadOrBuilderList

        List<? extends AnnotationPayloadOrBuilder> getPayloadOrBuilderList()
         Prediction result.
 Translation and Text Sentiment will return precisely one payload.
        repeated .google.cloud.automl.v1beta1.AnnotationPayload payload = 1;

      • getPayloadOrBuilder

        AnnotationPayloadOrBuilder getPayloadOrBuilder​(int index)
         Prediction result.
 Translation and Text Sentiment will return precisely one payload.
        repeated .google.cloud.automl.v1beta1.AnnotationPayload payload = 1;

      • hasPreprocessedInput

        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.Document.document_text].
        .google.cloud.automl.v1beta1.ExamplePayload preprocessed_input = 3;
        Returns:
        Whether the preprocessedInput field is set.

      • getPreprocessedInput

        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.Document.document_text].
        .google.cloud.automl.v1beta1.ExamplePayload preprocessed_input = 3;
        Returns:
        The preprocessedInput.

      • getPreprocessedInputOrBuilder

        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.Document.document_text].
        .google.cloud.automl.v1beta1.ExamplePayload preprocessed_input = 3;

      • getMetadataCount

        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;

      • containsMetadata

        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;

      • getMetadataMap

        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;

      • getMetadataOrDefault

        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;

      • getMetadataOrThrow

        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;