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PROTO library for proto-google-cloud-automl-v1beta1
// Copyright 2024 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/cloud/automl/v1beta1/text_segment.proto";
option go_package = "cloud.google.com/go/automl/apiv1beta1/automlpb;automlpb";
option java_multiple_files = true;
option java_package = "com.google.cloud.automl.v1beta1";
option php_namespace = "Google\\Cloud\\AutoMl\\V1beta1";
option ruby_package = "Google::Cloud::AutoML::V1beta1";
// Annotation for identifying spans of text.
message TextExtractionAnnotation {
// Required. Text extraction annotations can either be a text segment or a
// text relation.
oneof annotation {
// An entity annotation will set this, which is the part of the original
// text to which the annotation pertains.
TextSegment text_segment = 3;
}
// 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;
}
// 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;
}