// Copyright 2019 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.v1;

import "google/api/annotations.proto";
import "google/cloud/automl/v1/geometry.proto";
import "google/protobuf/duration.proto";

option csharp_namespace = "Google.Cloud.AutoML.V1";
option go_package = "google.golang.org/genproto/googleapis/cloud/automl/v1;automl";
option java_multiple_files = true;
option java_package = "com.google.cloud.automl.v1";
option php_namespace = "Google\\Cloud\\AutoML\\V1";
option ruby_package = "Google::Cloud::AutoML::V1";

// Annotation details for image object detection.
message ImageObjectDetectionAnnotation {
  // Output only. The rectangle representing the object location.
  BoundingPoly bounding_box = 1;

  // Output only. The confidence that this annotation is positive for the parent
  // example, value in [0, 1], higher means higher positivity confidence.
  float score = 2;
}

// Bounding box matching model metrics for a single intersection-over-union
// threshold and multiple label match confidence thresholds.
message BoundingBoxMetricsEntry {
  // Metrics for a single confidence threshold.
  message ConfidenceMetricsEntry {
    // Output only. The confidence threshold value used to compute the metrics.
    float confidence_threshold = 1;

    // Output only. Recall under the given confidence threshold.
    float recall = 2;

    // Output only. Precision under the given confidence threshold.
    float precision = 3;

    // Output only. The harmonic mean of recall and precision.
    float f1_score = 4;
  }

  // Output only. The intersection-over-union threshold value used to compute
  // this metrics entry.
  float iou_threshold = 1;

  // Output only. The mean average precision, most often close to au_prc.
  float mean_average_precision = 2;

  // 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.
  repeated ConfidenceMetricsEntry confidence_metrics_entries = 3;
}

// Model evaluation metrics for image object detection problems.
// Evaluates prediction quality of labeled bounding boxes.
message ImageObjectDetectionEvaluationMetrics {
  // Output only. The total number of bounding boxes (i.e. summed over all
  // images) the ground truth used to create this evaluation had.
  int32 evaluated_bounding_box_count = 1;

  // 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.
  repeated BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

  // Output only. The single metric for bounding boxes evaluation:
  // the mean_average_precision averaged over all bounding_box_metrics_entries.
  float bounding_box_mean_average_precision = 3;
}