# 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 V1beta1
        # Request message for {Google::Cloud::AutoML::V1beta1::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::V1beta1::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.
        #
        #     *  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_imp<span>ortan</span>ce - (boolean) Whether feature importance
        #            should be populated in the returned TablesAnnotation.
        #            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::V1beta1::PredictionService::Client#predict PredictionService.Predict}.
        # @!attribute [rw] payload
        #   @return [Array<Google::Cloud::AutoML::V1beta1::AnnotationPayload>]
        #     Prediction result.
        #     Translation and Text Sentiment will return precisely one payload.
        # @!attribute [rw] preprocessed_input
        #   @return [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
        #       {Google::Cloud::AutoML::V1beta1::Document#document_text document_text}.
        # @!attribute [rw] metadata
        #   @return [Google::Protobuf::Map{String => String}]
        #     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.
        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::V1beta1::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::V1beta1::BatchPredictInputConfig]
        #     Required. The input configuration for batch prediction.
        # @!attribute [rw] output_config
        #   @return [Google::Cloud::AutoML::V1beta1::BatchPredictOutputConfig]
        #     Required. The Configuration specifying where output predictions should
        #     be written.
        # @!attribute [rw] params
        #   @return [Google::Protobuf::Map{String => String}]
        #     Required. 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 Tables:
        #
        #        feature_imp<span>ortan</span>ce - (boolean) Whether feature importance
        #            should be populated in the returned TablesAnnotations. 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.
        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::V1beta1::PredictionService::Client#batch_predict PredictionService.BatchPredict}.
        # @!attribute [rw] metadata
        #   @return [Google::Protobuf::Map{String => String}]
        #     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.
        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