// Copyright 2019 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// Note: this file is purely for documentation. Any contents are not expected
// to be loaded as the JS file.
/**
* Request message for
* PredictionService.Predict.
*
* @property {string} name
* Name of the model requested to serve the prediction.
*
* @property {Object} payload
* Required. Payload to perform a prediction on. The payload must match the
* problem type that the model was trained to solve.
*
* This object should have the same structure as [ExamplePayload]{@link google.cloud.automl.v1beta1.ExamplePayload}
*
* @property {Object.<string, string>} params
* Additional domain-specific parameters, any string must be up to 25000
* characters long.
*
* * For Image Classification:
*
* `score_threshold` - (float) A value from 0.0 to 1.0. When the model
* makes predictions for an image, it will only produce results that have
* at least this confidence score. The default is 0.5.
*
* * For Image Object Detection:
* `score_threshold` - (float) When Model detects objects on the image,
* it will only produce bounding boxes which have at least this
* confidence score. Value in 0 to 1 range, default is 0.5.
* `max_bounding_box_count` - (int64) No more than this number of bounding
* boxes will be returned in the response. Default is 100, the
* requested value may be limited by server.
* * For Tables:
* `feature_importance` - (boolean) Whether
*
* [feature_importance][[google.cloud.automl.v1beta1.TablesModelColumnInfo.feature_importance]
* should be populated in the returned
*
* [TablesAnnotation(-s)][[google.cloud.automl.v1beta1.TablesAnnotation].
* The default is false.
*
* @typedef PredictRequest
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.PredictRequest definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/prediction_service.proto}
*/
const PredictRequest = {
// This is for documentation. Actual contents will be loaded by gRPC.
};
/**
* Response message for
* PredictionService.Predict.
*
* @property {Object[]} payload
* Prediction result.
* Translation and Text Sentiment will return precisely one payload.
*
* This object should have the same structure as [AnnotationPayload]{@link google.cloud.automl.v1beta1.AnnotationPayload}
*
* @property {Object} preprocessedInput
* 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 object should have the same structure as [ExamplePayload]{@link google.cloud.automl.v1beta1.ExamplePayload}
*
* @property {Object.<string, string>} metadata
* 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.
*
* @typedef PredictResponse
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.PredictResponse definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/prediction_service.proto}
*/
const PredictResponse = {
// This is for documentation. Actual contents will be loaded by gRPC.
};
/**
* Request message for
* PredictionService.BatchPredict.
*
* @property {string} name
* Name of the model requested to serve the batch prediction.
*
* @property {Object} inputConfig
* Required. The input configuration for batch prediction.
*
* This object should have the same structure as [BatchPredictInputConfig]{@link google.cloud.automl.v1beta1.BatchPredictInputConfig}
*
* @property {Object} outputConfig
* Required. The Configuration specifying where output predictions should
* be written.
*
* This object should have the same structure as [BatchPredictOutputConfig]{@link google.cloud.automl.v1beta1.BatchPredictOutputConfig}
*
* @property {Object.<string, string>} params
* Additional domain-specific parameters for the predictions, any string must
* be up to 25000 characters long.
*
* * For Text Classification:
*
* `score_threshold` - (float) A value from 0.0 to 1.0. When the model
* makes predictions for a text snippet, it will only produce results
* that have at least this confidence score. The default is 0.5.
*
* * For Image Classification:
*
* `score_threshold` - (float) A value from 0.0 to 1.0. When the model
* makes predictions for an image, it will only produce results that
* have at least this confidence score. The default is 0.5.
*
* * For Image Object Detection:
*
* `score_threshold` - (float) When Model detects objects on the image,
* it will only produce bounding boxes which have at least this
* confidence score. Value in 0 to 1 range, default is 0.5.
* `max_bounding_box_count` - (int64) No more than this number of bounding
* boxes will be produced per image. Default is 100, the
* requested value may be limited by server.
*
* * For Video Classification :
* `score_threshold` - (float) A value from 0.0 to 1.0. When the model
* makes predictions for a video, it will only produce results that
* have at least this confidence score. The default is 0.5.
* `segment_classification` - (boolean) Set to true to request
* segment-level classification. AutoML Video Intelligence returns
* labels and their confidence scores for the entire segment of the
* video that user specified in the request configuration.
* The default is "true".
* `shot_classification` - (boolean) Set to true to request shot-level
* classification. AutoML Video Intelligence determines the boundaries
* for each camera shot in the entire segment of the video that user
* specified in the request configuration. AutoML Video Intelligence
* then returns labels and their confidence scores for each detected
* shot, along with the start and end time of the shot.
* WARNING: Model evaluation is not done for this classification type,
* the quality of it depends on training data, but there are no metrics
* provided to describe that quality. The default is "false".
* `1s_interval_classification` - (boolean) Set to true to request
* classification for a video at one-second intervals. AutoML Video
* Intelligence returns labels and their confidence scores for each
* second of the entire segment of the video that user specified in the
* request configuration.
* WARNING: Model evaluation is not done for this classification
* type, the quality of it depends on training data, but there are no
* metrics provided to describe that quality. The default is
* "false".
*
* * For Video Object Tracking:
* `score_threshold` - (float) When Model detects objects on video frames,
* it will only produce bounding boxes which have at least this
* confidence score. Value in 0 to 1 range, default is 0.5.
* `max_bounding_box_count` - (int64) No more than this number of bounding
* boxes will be returned per frame. Default is 100, the requested
* value may be limited by server.
* `min_bounding_box_size` - (float) Only bounding boxes with shortest edge
* at least that long as a relative value of video frame size will be
* returned. Value in 0 to 1 range. Default is 0.
*
* @typedef BatchPredictRequest
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.BatchPredictRequest definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/prediction_service.proto}
*/
const BatchPredictRequest = {
// This is for documentation. Actual contents will be loaded by gRPC.
};
/**
* Result of the Batch Predict. This message is returned in
* response of the operation returned
* by the
* PredictionService.BatchPredict.
*
* @property {Object.<string, string>} metadata
* 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 Video Object Tracking:
* `max_bounding_box_count` - (int64) At most that many bounding boxes per
* frame could have been returned.
*
* @typedef BatchPredictResult
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.BatchPredictResult definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/prediction_service.proto}
*/
const BatchPredictResult = {
// This is for documentation. Actual contents will be loaded by gRPC.
};