// 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
//
// 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.
// Note: this file is purely for documentation. Any contents are not expected
// to be loaded as the JS file.
/**
* Annotation details for image object detection.
*
* @property {Object} boundingBox
* Output only. The rectangle representing the object location.
*
* This object should have the same structure as [BoundingPoly]{@link google.cloud.automl.v1beta1.BoundingPoly}
*
* @property {number} score
* Output only. The confidence that this annotation is positive for the parent example,
* value in [0, 1], higher means higher positivity confidence.
*
* @typedef ImageObjectDetectionAnnotation
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.ImageObjectDetectionAnnotation definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/detection.proto}
*/
const ImageObjectDetectionAnnotation = {
// This is for documentation. Actual contents will be loaded by gRPC.
};
/**
* Annotation details for video object tracking.
*
* @property {string} instanceId
* Optional. The instance of the object, expressed as a positive integer. Used to tell
* apart objects of the same type (i.e. AnnotationSpec) when multiple are
* present on a single example.
* NOTE: Instance ID prediction quality is not a part of model evaluation and
* is done as best effort. Especially in cases when an entity goes
* off-screen for a longer time (minutes), when it comes back it may be given
* a new instance ID.
*
* @property {Object} timeOffset
* Required. A time (frame) of a video to which this annotation pertains.
* Represented as the duration since the video's start.
*
* This object should have the same structure as [Duration]{@link google.protobuf.Duration}
*
* @property {Object} boundingBox
* Required. The rectangle representing the object location on the frame (i.e.
* at the time_offset of the video).
*
* This object should have the same structure as [BoundingPoly]{@link google.cloud.automl.v1beta1.BoundingPoly}
*
* @property {number} score
* Output only. The confidence that this annotation is positive for the video at
* the time_offset, value in [0, 1], higher means higher positivity
* confidence. For annotations created by the user the score is 1. When
* user approves an annotation, the original float score is kept (and not
* changed to 1).
*
* @typedef VideoObjectTrackingAnnotation
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.VideoObjectTrackingAnnotation definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/detection.proto}
*/
const VideoObjectTrackingAnnotation = {
// This is for documentation. Actual contents will be loaded by gRPC.
};
/**
* Bounding box matching model metrics for a single intersection-over-union
* threshold and multiple label match confidence thresholds.
*
* @property {number} iouThreshold
* Output only. The intersection-over-union threshold value used to compute
* this metrics entry.
*
* @property {number} meanAveragePrecision
* Output only. The mean average precision, most often close to au_prc.
*
* @property {Object[]} confidenceMetricsEntries
* 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.
*
* This object should have the same structure as [ConfidenceMetricsEntry]{@link google.cloud.automl.v1beta1.ConfidenceMetricsEntry}
*
* @typedef BoundingBoxMetricsEntry
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.BoundingBoxMetricsEntry definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/detection.proto}
*/
const BoundingBoxMetricsEntry = {
// This is for documentation. Actual contents will be loaded by gRPC.
/**
* Metrics for a single confidence threshold.
*
* @property {number} confidenceThreshold
* Output only. The confidence threshold value used to compute the metrics.
*
* @property {number} recall
* Output only. Recall under the given confidence threshold.
*
* @property {number} precision
* Output only. Precision under the given confidence threshold.
*
* @property {number} f1Score
* Output only. The harmonic mean of recall and precision.
*
* @typedef ConfidenceMetricsEntry
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/detection.proto}
*/
ConfidenceMetricsEntry: {
// This is for documentation. Actual contents will be loaded by gRPC.
}
};
/**
* Model evaluation metrics for image object detection problems.
* Evaluates prediction quality of labeled bounding boxes.
*
* @property {number} evaluatedBoundingBoxCount
* Output only. The total number of bounding boxes (i.e. summed over all
* images) the ground truth used to create this evaluation had.
*
* @property {Object[]} boundingBoxMetricsEntries
* 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.
*
* This object should have the same structure as [BoundingBoxMetricsEntry]{@link google.cloud.automl.v1beta1.BoundingBoxMetricsEntry}
*
* @property {number} boundingBoxMeanAveragePrecision
* Output only. The single metric for bounding boxes evaluation:
* the mean_average_precision averaged over all bounding_box_metrics_entries.
*
* @typedef ImageObjectDetectionEvaluationMetrics
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.ImageObjectDetectionEvaluationMetrics definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/detection.proto}
*/
const ImageObjectDetectionEvaluationMetrics = {
// This is for documentation. Actual contents will be loaded by gRPC.
};
/**
* Model evaluation metrics for video object tracking problems.
* Evaluates prediction quality of both labeled bounding boxes and labeled
* tracks (i.e. series of bounding boxes sharing same label and instance ID).
*
* @property {number} evaluatedFrameCount
* Output only. The number of video frames used to create this evaluation.
*
* @property {number} evaluatedBoundingBoxCount
* Output only. The total number of bounding boxes (i.e. summed over all
* frames) the ground truth used to create this evaluation had.
*
* @property {Object[]} boundingBoxMetricsEntries
* 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.
*
* This object should have the same structure as [BoundingBoxMetricsEntry]{@link google.cloud.automl.v1beta1.BoundingBoxMetricsEntry}
*
* @property {number} boundingBoxMeanAveragePrecision
* Output only. The single metric for bounding boxes evaluation:
* the mean_average_precision averaged over all bounding_box_metrics_entries.
*
* @typedef VideoObjectTrackingEvaluationMetrics
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.VideoObjectTrackingEvaluationMetrics definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/detection.proto}
*/
const VideoObjectTrackingEvaluationMetrics = {
// This is for documentation. Actual contents will be loaded by gRPC.
};