# frozen_string_literal: true # Copyright 2020 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. # Auto-generated by gapic-generator-ruby. DO NOT EDIT! module Google module Cloud module AutoML module V1 # Request message for {::Google::Cloud::AutoML::V1::PredictionService::Client#predict PredictionService.Predict}. # @!attribute [rw] name # @return [::String] # Required. Name of the model requested to serve the prediction. # @!attribute [rw] payload # @return [::Google::Cloud::AutoML::V1::ExamplePayload] # Required. Payload to perform a prediction on. The payload must match the # problem type that the model was trained to solve. # @!attribute [rw] params # @return [::Google::Protobuf::Map{::String => ::String}] # Additional domain-specific parameters, any string must be up to 25000 # characters long. # # AutoML Vision 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. # # AutoML Vision 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) The maximum number of bounding # boxes returned. The default is 100. The # number of returned bounding boxes might be limited by the server. # # AutoML Tables # # `feature_importance` # : (boolean) Whether # [feature_importance][google.cloud.automl.v1.TablesModelColumnInfo.feature_importance] # is populated in the returned list of # [TablesAnnotation][google.cloud.automl.v1.TablesAnnotation] # objects. The default is false. class PredictRequest include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # @!attribute [rw] key # @return [::String] # @!attribute [rw] value # @return [::String] class ParamsEntry include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Response message for {::Google::Cloud::AutoML::V1::PredictionService::Client#predict PredictionService.Predict}. # @!attribute [rw] payload # @return [::Array<::Google::Cloud::AutoML::V1::AnnotationPayload>] # Prediction result. # AutoML Translation and AutoML Natural Language Sentiment Analysis # return precisely one payload. # @!attribute [rw] preprocessed_input # @return [::Google::Cloud::AutoML::V1::ExamplePayload] # 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 # {::Google::Cloud::AutoML::V1::Document#document_text document_text} # property. # @!attribute [rw] metadata # @return [::Google::Protobuf::Map{::String => ::String}] # 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. class PredictResponse include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # @!attribute [rw] key # @return [::String] # @!attribute [rw] value # @return [::String] class MetadataEntry include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Request message for {::Google::Cloud::AutoML::V1::PredictionService::Client#batch_predict PredictionService.BatchPredict}. # @!attribute [rw] name # @return [::String] # Required. Name of the model requested to serve the batch prediction. # @!attribute [rw] input_config # @return [::Google::Cloud::AutoML::V1::BatchPredictInputConfig] # Required. The input configuration for batch prediction. # @!attribute [rw] output_config # @return [::Google::Cloud::AutoML::V1::BatchPredictOutputConfig] # Required. The Configuration specifying where output predictions should # be written. # @!attribute [rw] params # @return [::Google::Protobuf::Map{::String => ::String}] # Additional domain-specific parameters for the predictions, any string must # be up to 25000 characters long. # # AutoML Natural Language 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. # # # AutoML Vision 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. # # AutoML Vision 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) The maximum number of bounding # boxes returned per image. The default is 100, the # number of bounding boxes returned might be limited by the server. # AutoML Video Intelligence 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. # The default is false. # # 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. # # `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. The default is false. # # 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. # # AutoML Video Intelligence 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) The maximum number of bounding # boxes returned per image. The default is 100, the # number of bounding boxes returned might be limited by the server. # # `min_bounding_box_size` # : (float) Only bounding boxes with shortest edge # at least that long as a relative value of video frame size are # returned. Value in 0 to 1 range. Default is 0. class BatchPredictRequest include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # @!attribute [rw] key # @return [::String] # @!attribute [rw] value # @return [::String] class ParamsEntry include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the Batch Predict. This message is returned in # {::Google::Longrunning::Operation#response response} of the operation returned # by the {::Google::Cloud::AutoML::V1::PredictionService::Client#batch_predict PredictionService.BatchPredict}. # @!attribute [rw] metadata # @return [::Google::Protobuf::Map{::String => ::String}] # Additional domain-specific prediction response metadata. # # AutoML Vision Object Detection # # `max_bounding_box_count` # : (int64) The maximum number of bounding boxes returned per image. # # AutoML Video Intelligence Object Tracking # # `max_bounding_box_count` # : (int64) The maximum number of bounding boxes returned per frame. class BatchPredictResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # @!attribute [rw] key # @return [::String] # @!attribute [rw] value # @return [::String] class MetadataEntry include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end end end end end