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64 lines
2.2 KiB
64 lines
2.2 KiB
// Copyright 2018 Google LLC.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//
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syntax = "proto3";
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package google.cloud.automl.v1beta1;
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import "google/api/annotations.proto";
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import "google/cloud/automl/v1beta1/text_segment.proto";
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option go_package = "google.golang.org/genproto/googleapis/cloud/automl/v1beta1;automl";
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option java_multiple_files = true;
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option java_package = "com.google.cloud.automl.v1beta1";
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option php_namespace = "Google\\Cloud\\AutoMl\\V1beta1";
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// Annotation for identifying spans of text.
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message TextExtractionAnnotation {
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// Output only. A confidence estimate between 0.0 and 1.0. A higher value
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// means greater confidence in correctness of the annotation.
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float score = 1;
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// Required. The part of the original text to which this annotation pertains.
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TextSegment text_segment = 3;
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}
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// Model evaluation metrics for text extraction problems.
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message TextExtractionEvaluationMetrics {
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// Metrics for a single confidence threshold.
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message ConfidenceMetricsEntry {
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// Output only. The confidence threshold value used to compute the metrics.
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// Only annotations with score of at least this threshold are considered to
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// be ones the model would return.
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float confidence_threshold = 1;
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// Output only. Recall under the given confidence threshold.
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float recall = 3;
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// Output only. Precision under the given confidence threshold.
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float precision = 4;
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// Output only. The harmonic mean of recall and precision.
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float f1_score = 5;
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}
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// Output only. The Area under precision recall curve metric.
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float au_prc = 1;
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// Output only. Metrics that have confidence thresholds.
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// Precision-recall curve can be derived from it.
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repeated ConfidenceMetricsEntry confidence_metrics_entries = 2;
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}
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