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87 lines
3.4 KiB
87 lines
3.4 KiB
// Copyright 2020 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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syntax = "proto3"; |
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package google.cloud.automl.v1; |
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import "google/cloud/automl/v1/geometry.proto"; |
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import "google/protobuf/duration.proto"; |
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import "google/api/annotations.proto"; |
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option csharp_namespace = "Google.Cloud.AutoML.V1"; |
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option go_package = "google.golang.org/genproto/googleapis/cloud/automl/v1;automl"; |
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option java_multiple_files = true; |
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option java_package = "com.google.cloud.automl.v1"; |
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option php_namespace = "Google\\Cloud\\AutoMl\\V1"; |
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option ruby_package = "Google::Cloud::AutoML::V1"; |
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// Annotation details for image object detection. |
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message ImageObjectDetectionAnnotation { |
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// Output only. The rectangle representing the object location. |
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BoundingPoly bounding_box = 1; |
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// Output only. The confidence that this annotation is positive for the parent example, |
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// value in [0, 1], higher means higher positivity confidence. |
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float score = 2; |
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} |
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// Bounding box matching model metrics for a single intersection-over-union |
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// threshold and multiple label match confidence thresholds. |
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message BoundingBoxMetricsEntry { |
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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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float confidence_threshold = 1; |
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// Output only. Recall under the given confidence threshold. |
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float recall = 2; |
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// Output only. Precision under the given confidence threshold. |
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float precision = 3; |
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// Output only. The harmonic mean of recall and precision. |
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float f1_score = 4; |
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} |
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// Output only. The intersection-over-union threshold value used to compute |
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// this metrics entry. |
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float iou_threshold = 1; |
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// Output only. The mean average precision, most often close to au_prc. |
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float mean_average_precision = 2; |
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// Output only. Metrics for each label-match confidence_threshold from |
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// 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is |
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// derived from them. |
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repeated ConfidenceMetricsEntry confidence_metrics_entries = 3; |
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} |
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// Model evaluation metrics for image object detection problems. |
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// Evaluates prediction quality of labeled bounding boxes. |
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message ImageObjectDetectionEvaluationMetrics { |
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// Output only. The total number of bounding boxes (i.e. summed over all |
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// images) the ground truth used to create this evaluation had. |
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int32 evaluated_bounding_box_count = 1; |
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// Output only. The bounding boxes match metrics for each |
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// Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 |
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// and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 |
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// pair. |
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repeated BoundingBoxMetricsEntry bounding_box_metrics_entries = 2; |
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// Output only. The single metric for bounding boxes evaluation: |
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// the mean_average_precision averaged over all bounding_box_metrics_entries. |
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float bounding_box_mean_average_precision = 3; |
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}
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