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89 lines
3.3 KiB
89 lines
3.3 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/geometry.proto";
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import "google/protobuf/duration.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 details for image object detection.
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message ImageObjectDetectionAnnotation {
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// Output only.
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// The rectangle representing the object location.
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BoundingPoly bounding_box = 1;
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// Output only.
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// 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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