// Copyright 2018 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
//
//     http://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.
//

syntax = "proto3";

package google.cloud.automl.v1beta1;

import "google/api/annotations.proto";
import "google/cloud/automl/v1beta1/text_segment.proto";

option go_package = "google.golang.org/genproto/googleapis/cloud/automl/v1beta1;automl";
option java_multiple_files = true;
option java_package = "com.google.cloud.automl.v1beta1";
option php_namespace = "Google\\Cloud\\AutoMl\\V1beta1";


// Annotation for identifying spans of text.
message TextExtractionAnnotation {
  // Output only. A confidence estimate between 0.0 and 1.0. A higher value
  // means greater confidence in correctness of the annotation.
  float score = 1;

  // Required. The part of the original text to which this annotation pertains.
  TextSegment text_segment = 3;
}

// Model evaluation metrics for text extraction problems.
message TextExtractionEvaluationMetrics {
  // Metrics for a single confidence threshold.
  message ConfidenceMetricsEntry {
    // Output only. The confidence threshold value used to compute the metrics.
    // Only annotations with score of at least this threshold are considered to
    // be ones the model would return.
    float confidence_threshold = 1;

    // Output only. Recall under the given confidence threshold.
    float recall = 3;

    // Output only. Precision under the given confidence threshold.
    float precision = 4;

    // Output only. The harmonic mean of recall and precision.
    float f1_score = 5;
  }

  // Output only. The Area under precision recall curve metric.
  float au_prc = 1;

  // Output only. Metrics that have confidence thresholds.
  // Precision-recall curve can be derived from it.
  repeated ConfidenceMetricsEntry confidence_metrics_entries = 2;
}