Data Labeling v1beta1 API - Class EvaluationJobConfig (2.0.0-beta03)

public sealed class EvaluationJobConfig : IMessage<EvaluationJobConfig>, IEquatable<EvaluationJobConfig>, IDeepCloneable<EvaluationJobConfig>, IBufferMessage, IMessage

Reference documentation and code samples for the Data Labeling v1beta1 API class EvaluationJobConfig.

Configures specific details of how a continuous evaluation job works. Provide this configuration when you create an EvaluationJob.

Inheritance

object > EvaluationJobConfig

Implements

IMessage EvaluationJobConfig, IEquatable EvaluationJobConfig, IDeepCloneable EvaluationJobConfig, IBufferMessage, IMessage

Inherited Members

object.GetHashCode()

object.GetType()

object.ToString()

Namespace

Google.Cloud.DataLabeling.V1Beta1

Assembly

Google.Cloud.DataLabeling.V1Beta1.dll

Constructors

EvaluationJobConfig()

public EvaluationJobConfig()

EvaluationJobConfig(EvaluationJobConfig)

public EvaluationJobConfig(EvaluationJobConfig other)

Parameter
Name	Description
`other`	`EvaluationJobConfig`

Properties

BigqueryImportKeys

public MapField<string, string> BigqueryImportKeys { get; }

Required. Prediction keys that tell Data Labeling Service where to find the data for evaluation in your BigQuery table. When the service samples prediction input and output from your model version and saves it to BigQuery, the data gets stored as JSON strings in the BigQuery table. These keys tell Data Labeling Service how to parse the JSON.

You can provide the following entries in this field:

data_json_key: the data key for prediction input. You must provide either this key or reference_json_key.
reference_json_key: the data reference key for prediction input. You must provide either this key or data_json_key.
label_json_key: the label key for prediction output. Required.
label_score_json_key: the score key for prediction output. Required.
bounding_box_json_key: the bounding box key for prediction output. Required if your model version perform image object detection.

Learn how to configure prediction keys.

Property Value
Type	Description
`MapFieldstringstring`

BoundingPolyConfig

public BoundingPolyConfig BoundingPolyConfig { get; set; }

Specify this field if your model version performs image object detection (bounding box detection).

annotationSpecSet in this configuration must match [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].

Property Value
Type	Description
`BoundingPolyConfig`

EvaluationConfig

public EvaluationConfig EvaluationConfig { get; set; }

Required. Details for calculating evaluation metrics and creating [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. If your model version performs image object detection, you must specify the boundingBoxEvaluationOptions field within this configuration. Otherwise, provide an empty object for this configuration.

Property Value
Type	Description
`EvaluationConfig`

EvaluationJobAlertConfig

public EvaluationJobAlertConfig EvaluationJobAlertConfig { get; set; }

Optional. Configuration details for evaluation job alerts. Specify this field if you want to receive email alerts if the evaluation job finds that your predictions have low mean average precision during a run.

Property Value
Type	Description
`EvaluationJobAlertConfig`

ExampleCount

public int ExampleCount { get; set; }

Required. The maximum number of predictions to sample and save to BigQuery during each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. This limit overrides example_sample_percentage: even if the service has not sampled enough predictions to fulfill example_sample_perecentage during an interval, it stops sampling predictions when it meets this limit.

Property Value
Type	Description
`int`

ExampleSamplePercentage

public double ExampleSamplePercentage { get; set; }

Required. Fraction of predictions to sample and save to BigQuery during each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. For example, 0.1 means 10% of predictions served by your model version get saved to BigQuery.

Property Value
Type	Description
`double`

HumanAnnotationConfig

public HumanAnnotationConfig HumanAnnotationConfig { get; set; }

Optional. Details for human annotation of your data. If you set [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] to true for this evaluation job, then you must specify this field. If you plan to provide your own ground truth labels, then omit this field.

Note that you must create an [Instruction][google.cloud.datalabeling.v1beta1.Instruction] resource before you can specify this field. Provide the name of the instruction resource in the instruction field within this configuration.

Property Value
Type	Description
`HumanAnnotationConfig`

HumanAnnotationRequestConfigCase

public EvaluationJobConfig.HumanAnnotationRequestConfigOneofCase HumanAnnotationRequestConfigCase { get; }

Property Value
Type	Description
`EvaluationJobConfigHumanAnnotationRequestConfigOneofCase`

ImageClassificationConfig

public ImageClassificationConfig ImageClassificationConfig { get; set; }

Specify this field if your model version performs image classification or general classification.

annotationSpecSet in this configuration must match [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set]. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].

Property Value
Type	Description
`ImageClassificationConfig`

InputConfig

public InputConfig InputConfig { get; set; }

Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:

dataType must be one of IMAGE, TEXT, or GENERAL_DATA.
annotationType must be one of IMAGE_CLASSIFICATION_ANNOTATION, TEXT_CLASSIFICATION_ANNOTATION, GENERAL_CLASSIFICATION_ANNOTATION, or IMAGE_BOUNDING_BOX_ANNOTATION (image object detection).
If your machine learning model performs classification, you must specify classificationMetadata.isMultiLabel.
You must specify bigquerySource (not gcsSource).

Property Value
Type	Description
`InputConfig`

TextClassificationConfig

public TextClassificationConfig TextClassificationConfig { get; set; }

Specify this field if your model version performs text classification.

Property Value
Type	Description
`TextClassificationConfig`