Reference documentation and code samples for the Cloud AutoML V1beta1 Client class PredictResponse.
Response message for PredictionService.Predict .
Generated from protobuf message google.cloud.automl.v1beta1.PredictResponse
Methods
__construct
Constructor.
data
array
Optional. Data for populating the Message object.
↳ payload
array< Google\Cloud\AutoMl\V1beta1\AnnotationPayload
>
Prediction result. Translation and Text Sentiment will return precisely one payload.
↳ preprocessed_input
Google\Cloud\AutoMl\V1beta1\ExamplePayload
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 .
↳ metadata
array| Google\Protobuf\Internal\MapField
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.
getPayload
Prediction result.
Translation and Text Sentiment will return precisely one payload.
setPayload
Prediction result.
Translation and Text Sentiment will return precisely one payload.
$this
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 .
hasPreprocessedInput
clearPreprocessedInput
setPreprocessedInput
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 .
$this
getMetadata
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.
setMetadata
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.
$this
