View Source API Reference google_api_data_labeling v0.3.1
Modules
API client metadata for GoogleApi.DataLabeling.V1beta1.
API calls for all endpoints tagged Projects
.
Handle Tesla connections for GoogleApi.DataLabeling.V1beta1.
Metadata of a CreateInstruction operation.
Metadata of an ExportData operation.
Response used for ExportDataset longrunning operation.
Export destination of the data.Only gcs path is allowed in output_uri.
Export folder destination of the data.
Configuration for how human labeling task should be done.
Metadata of an ImportData operation.
Response used for ImportData longrunning operation.
Details of a LabelImageBoundingBox operation metadata.
Details of LabelImageBoundingPoly operation metadata.
Metadata of a LabelImageClassification operation.
Details of a LabelImageOrientedBoundingBox operation metadata.
Details of LabelImagePolyline operation metadata.
Details of a LabelImageSegmentation operation metadata.
Metadata of a labeling operation, such as LabelImage or LabelVideo. Next tag: 23
Statistics about annotation specs.
Details of a LabelTextClassification operation metadata.
Details of a LabelTextEntityExtraction operation metadata.
Details of a LabelVideoClassification operation metadata.
Details of a LabelVideoEvent operation metadata.
Details of a LabelVideoObjectDetection operation metadata.
Details of a LabelVideoObjectTracking operation metadata.
The configuration of output data.
AnnotatedDataset is a set holding annotations for data in a Dataset. Each labeling task will generate an AnnotatedDataset under the Dataset that the task is requested for.
Metadata on AnnotatedDataset.
Annotation for Example. Each example may have one or more annotations. For example in image classification problem, each image might have one or more labels. We call labels binded with this image an Annotation.
Additional information associated with the annotation.
Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as dog
or cat
must reference an AnnotationSpec for dog
and an AnnotationSpec for cat
.
An AnnotationSpecSet is a collection of label definitions. For example, in image classification tasks, you define a set of possible labels for images as an AnnotationSpecSet. An AnnotationSpecSet is immutable upon creation.
Annotation spec set with the setting of allowing multi labels or not.
Annotation value for an example.
Records a failed evaluation job run.
The BigQuery location for input data. If used in an EvaluationJob, this is where the service saves the prediction input and output sampled from the model version.
Options regarding evaluation between bounding boxes.
A bounding polygon in the image.
Config for image bounding poly (and bounding box) human labeling task.
Metadata for classification annotations.
Metrics calculated for a classification model.
Attributes
-
confidenceThreshold
(type:number()
, default:nil
) - Threshold used for this entry. For classification tasks, this is a classification threshold: a predicted label is categorized as positive or negative (in the context of this point on the PR curve) based on whether the label's score meets this threshold. For image object detection (bounding box) tasks, this is the intersection-over-union (IOU) threshold for the context of this point on the PR curve. -
f1Score
(type:number()
, default:nil
) - Harmonic mean of recall and precision. -
f1ScoreAt1
(type:number()
, default:nil
) - The harmonic mean of recall_at1 and precision_at1. -
f1ScoreAt5
(type:number()
, default:nil
) - The harmonic mean of recall_at5 and precision_at5. -
precision
(type:number()
, default:nil
) - Precision value. -
precisionAt1
(type:number()
, default:nil
) - Precision value for entries with label that has highest score. -
precisionAt5
(type:number()
, default:nil
) - Precision value for entries with label that has highest 5 scores. -
recall
(type:number()
, default:nil
) - Recall value. -
recallAt1
(type:number()
, default:nil
) - Recall value for entries with label that has highest score. -
recallAt5
(type:number()
, default:nil
) - Recall value for entries with label that has highest 5 scores.
Confusion matrix of the model running the classification. Only applicable when the metrics entry aggregates multiple labels. Not applicable when the entry is for a single label.
Attributes
-
annotationSpec
(type:GoogleApi.DataLabeling.V1beta1.Model.GoogleCloudDatalabelingV1beta1AnnotationSpec.t
, default:nil
) - The annotation spec of a predicted label. -
itemCount
(type:integer()
, default:nil
) - Number of items predicted to have this label. (The ground truth label for these items is theRow.annotationSpec
of this entry's parent.)
Request message for CreateAnnotationSpecSet.
Request message for CreateDataset.
Request message for CreateEvaluationJob.
Metadata of a CreateInstruction operation.
Request message for CreateInstruction.
Deprecated: this instruction format is not supported any more. Instruction from a CSV file.
DataItem is a piece of data, without annotation. For example, an image.
Dataset is the resource to hold your data. You can request multiple labeling tasks for a dataset while each one will generate an AnnotatedDataset.
Describes an evaluation between a machine learning model's predictions and ground truth labels. Created when an EvaluationJob runs successfully.
Configuration details used for calculating evaluation metrics and creating an Evaluation.
Defines an evaluation job that runs periodically to generate Evaluations. Creating an evaluation job is the starting point for using continuous evaluation.
Provides details for how an evaluation job sends email alerts based on the results of a run.
Configures specific details of how a continuous evaluation job works. Provide this configuration when you create an EvaluationJob.
Config for video event human labeling task.
An Example is a piece of data and its annotation. For example, an image with label "house".
Example comparisons comparing ground truth output and predictions for a specific input.
Metadata of an ExportData operation.
Response used for ExportDataset longrunning operation.
Request message for ExportData API.
A feedback message inside a feedback thread.
A feedback thread of a certain labeling task on a certain annotated dataset.
Export destination of the data.Only gcs path is allowed in output_uri.
Export folder destination of the data.
Source of the Cloud Storage file to be imported.
Configuration for how human labeling task should be done.
Image bounding poly annotation. It represents a polygon including bounding box in the image.
Image classification annotation definition.
Config for image classification human labeling task.
Container of information about an image.
A polyline for the image annotation.
Image segmentation annotation.
Metadata of an ImportData operation.
Response used for ImportData longrunning operation.
Request message for ImportData API.
The configuration of input data, including data type, location, etc.
Instruction of how to perform the labeling task for human operators. Currently only PDF instruction is supported.
Details of a LabelImageBoundingBox operation metadata.
Details of LabelImageBoundingPoly operation metadata.
Metadata of a LabelImageClassification operation.
Details of a LabelImageOrientedBoundingBox operation metadata.
Details of LabelImagePolyline operation metadata.
Request message for starting an image labeling task.
Details of a LabelImageSegmentation operation metadata.
Metadata of a labeling operation, such as LabelImage or LabelVideo. Next tag: 23
Statistics about annotation specs.
Details of a LabelTextClassification operation metadata.
Details of a LabelTextEntityExtraction operation metadata.
Request message for LabelText.
Details of a LabelVideoClassification operation metadata.
Details of a LabelVideoEvent operation metadata.
Details of a LabelVideoObjectDetection operation metadata.
Details of a LabelVideoObjectTracking operation metadata.
Request message for LabelVideo.
Results of listing annotated datasets for a dataset.
Results of listing annotation spec set under a project.
Results of listing data items in a dataset.
Results of listing datasets within a project.
Results for listing evaluation jobs.
Results of listing Examples in and annotated dataset.
Results for listing FeedbackMessages.
Results for listing FeedbackThreads.
Results of listing instructions under a project.
Normalized bounding polygon.
Normalized polyline.
A vertex represents a 2D point in the image. NOTE: the normalized vertex coordinates are relative to the original image and range from 0 to 1.
Config for video object detection human labeling task. Object detection will be conducted on the images extracted from the video, and those objects will be labeled with bounding boxes. User need to specify the number of images to be extracted per second as the extraction frame rate.
Metrics calculated for an image object detection (bounding box) model.
Config for video object tracking human labeling task.
Video frame level annotation for object detection and tracking.
Metadata describing the feedback from the operator.
General information useful for labels coming from contributors.
The configuration of output data.
Request message for PauseEvaluationJob.
Instruction from a PDF file.
A line with multiple line segments.
Config for image polyline human labeling task.
Attributes
-
annotationSpec
(type:GoogleApi.DataLabeling.V1beta1.Model.GoogleCloudDatalabelingV1beta1AnnotationSpec.t
, default:nil
) - The annotation spec of the label for which the precision-recall curve calculated. If this field is empty, that means the precision-recall curve is an aggregate curve for all labels. -
areaUnderCurve
(type:number()
, default:nil
) - Area under the precision-recall curve. Not to be confused with area under a receiver operating characteristic (ROC) curve. -
confidenceMetricsEntries
(type:list(GoogleApi.DataLabeling.V1beta1.Model.GoogleCloudDatalabelingV1beta1ConfidenceMetricsEntry.t)
, default:nil
) - Entries that make up the precision-recall graph. Each entry is a "point" on the graph drawn for a differentconfidence_threshold
. -
meanAveragePrecision
(type:number()
, default:nil
) - Mean average prcision of this curve.
Metadata describing the feedback from the labeling task requester.
Request message ResumeEvaluationJob.
A row in the confusion matrix. Each entry in this row has the same ground truth label.
Results of searching evaluations.
Request message of SearchExampleComparisons.
Results of searching example comparisons.
Config for image segmentation
Config for setting up sentiments.
Start and end position in a sequence (e.g. text segment).
Text classification annotation.
Config for text classification human labeling task.
Text entity extraction annotation.
Config for text entity extraction human labeling task.
Metadata for the text.
Container of information about a piece of text.
A time period inside of an example that has a time dimension (e.g. video).
A vertex represents a 2D point in the image. NOTE: the vertex coordinates are in the same scale as the original image.
Video classification annotation.
Config for video classification human labeling task. Currently two types of video classification are supported: 1. Assign labels on the entire video. 2. Split the video into multiple video clips based on camera shot, and assign labels on each video clip.
Video event annotation.
Video object tracking annotation.
Container of information of a video.
Container of information of a video thumbnail.
Metadata of a CreateInstruction operation.
Metadata of an ExportData operation.
Response used for ExportDataset longrunning operation.
Export destination of the data.Only gcs path is allowed in output_uri.
Export folder destination of the data.
Metadata of an GenerateAnalysisReport operation.
Configuration for how human labeling task should be done.
Metadata of an ImportData operation.
Response used for ImportData longrunning operation.
Details of a LabelImageBoundingBox operation metadata.
Details of LabelImageBoundingPoly operation metadata.
Metadata of a LabelImageClassification operation.
Details of a LabelImageOrientedBoundingBox operation metadata.
Details of LabelImagePolyline operation metadata.
Details of a LabelImageSegmentation operation metadata.
Metadata of a labeling operation, such as LabelImage or LabelVideo. Next tag: 23
Statistics about annotation specs.
Details of a LabelTextClassification operation metadata.
Details of a LabelTextEntityExtraction operation metadata.
Details of a LabelVideoClassification operation metadata.
Details of a LabelVideoEvent operation metadata.
Details of a LabelVideoObjectDetection operation metadata.
Details of a LabelVideoObjectTracking operation metadata.
The configuration of output data.
Metadata of a CreateInstruction operation.
Metadata of an ExportData operation.
Response used for ExportDataset longrunning operation.
Export destination of the data.Only gcs path is allowed in output_uri.
Export folder destination of the data.
Configuration for how human labeling task should be done.
Metadata of an ImportData operation.
Response used for ImportData longrunning operation.
Details of a LabelImageBoundingBox operation metadata.
Details of LabelImageBoundingPoly operation metadata.
Metadata of a LabelImageClassification operation.
Details of a LabelImageOrientedBoundingBox operation metadata.
Details of LabelImagePolyline operation metadata.
Details of a LabelImageSegmentation operation metadata.
Metadata of a labeling operation, such as LabelImage or LabelVideo. Next tag: 23
Statistics about annotation specs.
Details of a LabelTextClassification operation metadata.
Details of a LabelTextEntityExtraction operation metadata.
Details of a LabelVideoClassification operation metadata.
Details of a LabelVideoEvent operation metadata.
Details of a LabelVideoObjectDetection operation metadata.
Details of a LabelVideoObjectTracking operation metadata.
The configuration of output data.
The response message for Operations.ListOperations.
This resource represents a long-running operation that is the result of a network API call.
A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
The Status
type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by gRPC. Each Status
message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the API Design Guide.