# frozen_string_literal: true # Copyright 2020 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 # # https://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. # Auto-generated by gapic-generator-ruby. DO NOT EDIT! module Google module Cloud module AutoML module V1 # Annotation details for image object detection. # @!attribute [rw] bounding_box # @return [::Google::Cloud::AutoML::V1::BoundingPoly] # Output only. The rectangle representing the object location. # @!attribute [rw] score # @return [::Float] # Output only. The confidence that this annotation is positive for the parent example, # value in [0, 1], higher means higher positivity confidence. class ImageObjectDetectionAnnotation include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Bounding box matching model metrics for a single intersection-over-union # threshold and multiple label match confidence thresholds. # @!attribute [rw] iou_threshold # @return [::Float] # Output only. The intersection-over-union threshold value used to compute # this metrics entry. # @!attribute [rw] mean_average_precision # @return [::Float] # Output only. The mean average precision, most often close to au_prc. # @!attribute [rw] confidence_metrics_entries # @return [::Array<::Google::Cloud::AutoML::V1::BoundingBoxMetricsEntry::ConfidenceMetricsEntry>] # Output only. Metrics for each label-match confidence_threshold from # 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is # derived from them. class BoundingBoxMetricsEntry include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Metrics for a single confidence threshold. # @!attribute [rw] confidence_threshold # @return [::Float] # Output only. The confidence threshold value used to compute the metrics. # @!attribute [rw] recall # @return [::Float] # Output only. Recall under the given confidence threshold. # @!attribute [rw] precision # @return [::Float] # Output only. Precision under the given confidence threshold. # @!attribute [rw] f1_score # @return [::Float] # Output only. The harmonic mean of recall and precision. class ConfidenceMetricsEntry include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Model evaluation metrics for image object detection problems. # Evaluates prediction quality of labeled bounding boxes. # @!attribute [rw] evaluated_bounding_box_count # @return [::Integer] # Output only. The total number of bounding boxes (i.e. summed over all # images) the ground truth used to create this evaluation had. # @!attribute [rw] bounding_box_metrics_entries # @return [::Array<::Google::Cloud::AutoML::V1::BoundingBoxMetricsEntry>] # Output only. The bounding boxes match metrics for each # Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 # and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 # pair. # @!attribute [rw] bounding_box_mean_average_precision # @return [::Float] # Output only. The single metric for bounding boxes evaluation: # the mean_average_precision averaged over all bounding_box_metrics_entries. class ImageObjectDetectionEvaluationMetrics include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end end end end