Package Classes (1.11.1)

Service for the AI Platform Data Labeling API.

Service for the AI Platform Data Labeling API.

A pager for iterating through list_annotated_datasets requests.

This class thinly wraps an initial ListAnnotatedDatasetsResponse object, and provides an __aiter__ method to iterate through its annotated_datasets field.

If there are more pages, the __aiter__ method will make additional ListAnnotatedDatasets requests and continue to iterate through the annotated_datasets field on the corresponding responses.

All the usual ListAnnotatedDatasetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_annotated_datasets requests.

This class thinly wraps an initial ListAnnotatedDatasetsResponse object, and provides an __iter__ method to iterate through its annotated_datasets field.

If there are more pages, the __iter__ method will make additional ListAnnotatedDatasets requests and continue to iterate through the annotated_datasets field on the corresponding responses.

All the usual ListAnnotatedDatasetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_annotation_spec_sets requests.

This class thinly wraps an initial ListAnnotationSpecSetsResponse object, and provides an __aiter__ method to iterate through its annotation_spec_sets field.

If there are more pages, the __aiter__ method will make additional ListAnnotationSpecSets requests and continue to iterate through the annotation_spec_sets field on the corresponding responses.

All the usual ListAnnotationSpecSetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_annotation_spec_sets requests.

This class thinly wraps an initial ListAnnotationSpecSetsResponse object, and provides an __iter__ method to iterate through its annotation_spec_sets field.

If there are more pages, the __iter__ method will make additional ListAnnotationSpecSets requests and continue to iterate through the annotation_spec_sets field on the corresponding responses.

All the usual ListAnnotationSpecSetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_data_items requests.

This class thinly wraps an initial ListDataItemsResponse object, and provides an __aiter__ method to iterate through its data_items field.

If there are more pages, the __aiter__ method will make additional ListDataItems requests and continue to iterate through the data_items field on the corresponding responses.

All the usual ListDataItemsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_data_items requests.

This class thinly wraps an initial ListDataItemsResponse object, and provides an __iter__ method to iterate through its data_items field.

If there are more pages, the __iter__ method will make additional ListDataItems requests and continue to iterate through the data_items field on the corresponding responses.

All the usual ListDataItemsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_datasets requests.

This class thinly wraps an initial ListDatasetsResponse object, and provides an __aiter__ method to iterate through its datasets field.

If there are more pages, the __aiter__ method will make additional ListDatasets requests and continue to iterate through the datasets field on the corresponding responses.

All the usual ListDatasetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_datasets requests.

This class thinly wraps an initial ListDatasetsResponse object, and provides an __iter__ method to iterate through its datasets field.

If there are more pages, the __iter__ method will make additional ListDatasets requests and continue to iterate through the datasets field on the corresponding responses.

All the usual ListDatasetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_evaluation_jobs requests.

This class thinly wraps an initial ListEvaluationJobsResponse object, and provides an __aiter__ method to iterate through its evaluation_jobs field.

If there are more pages, the __aiter__ method will make additional ListEvaluationJobs requests and continue to iterate through the evaluation_jobs field on the corresponding responses.

All the usual ListEvaluationJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_evaluation_jobs requests.

This class thinly wraps an initial ListEvaluationJobsResponse object, and provides an __iter__ method to iterate through its evaluation_jobs field.

If there are more pages, the __iter__ method will make additional ListEvaluationJobs requests and continue to iterate through the evaluation_jobs field on the corresponding responses.

All the usual ListEvaluationJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_examples requests.

This class thinly wraps an initial ListExamplesResponse object, and provides an __aiter__ method to iterate through its examples field.

If there are more pages, the __aiter__ method will make additional ListExamples requests and continue to iterate through the examples field on the corresponding responses.

All the usual ListExamplesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_examples requests.

This class thinly wraps an initial ListExamplesResponse object, and provides an __iter__ method to iterate through its examples field.

If there are more pages, the __iter__ method will make additional ListExamples requests and continue to iterate through the examples field on the corresponding responses.

All the usual ListExamplesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_instructions requests.

This class thinly wraps an initial ListInstructionsResponse object, and provides an __aiter__ method to iterate through its instructions field.

If there are more pages, the __aiter__ method will make additional ListInstructions requests and continue to iterate through the instructions field on the corresponding responses.

All the usual ListInstructionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_instructions requests.

This class thinly wraps an initial ListInstructionsResponse object, and provides an __iter__ method to iterate through its instructions field.

If there are more pages, the __iter__ method will make additional ListInstructions requests and continue to iterate through the instructions field on the corresponding responses.

All the usual ListInstructionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through search_evaluations requests.

This class thinly wraps an initial SearchEvaluationsResponse object, and provides an __aiter__ method to iterate through its evaluations field.

If there are more pages, the __aiter__ method will make additional SearchEvaluations requests and continue to iterate through the evaluations field on the corresponding responses.

All the usual SearchEvaluationsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through search_evaluations requests.

This class thinly wraps an initial SearchEvaluationsResponse object, and provides an __iter__ method to iterate through its evaluations field.

If there are more pages, the __iter__ method will make additional SearchEvaluations requests and continue to iterate through the evaluations field on the corresponding responses.

All the usual SearchEvaluationsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through search_example_comparisons requests.

This class thinly wraps an initial SearchExampleComparisonsResponse object, and provides an __aiter__ method to iterate through its example_comparisons field.

If there are more pages, the __aiter__ method will make additional SearchExampleComparisons requests and continue to iterate through the example_comparisons field on the corresponding responses.

All the usual SearchExampleComparisonsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through search_example_comparisons requests.

This class thinly wraps an initial SearchExampleComparisonsResponse object, and provides an __iter__ method to iterate through its example_comparisons field.

If there are more pages, the __iter__ method will make additional SearchExampleComparisons requests and continue to iterate through the example_comparisons field on the corresponding responses.

All the usual SearchExampleComparisonsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

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.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

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.

Specifies where the annotation comes from (whether it was provided by a human labeler or a different source).

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 value for an example.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

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.

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.

A row in the confusion matrix. Each entry in this row has the same ground truth label.

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.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

Dataset is the resource to hold your data. You can request multiple labeling tasks for a dataset while each one will generate an AnnotatedDataset.

Request message for DeleteAnnotatedDataset.

Request message for DeleteAnnotationSpecSet.

Request message for DeleteDataset.

Request message DeleteEvaluationJob.

Request message for DeleteInstruction.

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.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

Defines an evaluation job that runs periodically to generate Evaluations. Creating an evaluation job </ml-engine/docs/continuous-evaluation/create-job>__ is the starting point for using continuous evaluation.

State of the job.

    When the job is in this state, it samples prediction input
    and output from your model version into your BigQuery table
    as predictions occur.
RUNNING (2):
    The job is currently running. When the job runs, Data
    Labeling Service does several things:

    1. If you have configured your job to use Data Labeling
       Service for ground truth labeling, the service creates a
       <xref uid="google.cloud.datalabeling.v1beta1.Dataset">Dataset</xref> and
       a labeling task for all data sampled since the last time
       the job ran. Human labelers provide ground truth labels
       for your data. Human labeling may take hours, or even
       days, depending on how much data has been sampled. The
       job remains in the `RUNNING` state during this time,
       and it can even be running multiple times in parallel if
       it gets triggered again (for example 24 hours later)
       before the earlier run has completed. When human labelers
       have finished labeling the data, the next step occurs. If
       you have configured your job to provide your own ground
       truth labels, Data Labeling Service still creates a
       <xref uid="google.cloud.datalabeling.v1beta1.Dataset">Dataset</xref> for
       newly sampled data, but it expects that you have already
       added ground truth labels to the BigQuery table by this
       time. The next step occurs immediately.

    2. Data Labeling Service creates an
       <xref uid="google.cloud.datalabeling.v1beta1.Evaluation">Evaluation</xref>
       by comparing your model version's predictions with the
       ground truth labels.

    If the job remains in this state for a long time, it
    continues to sample prediction data into your BigQuery table
    and will run again at the next interval, even if it causes
    the job to run multiple times in parallel.
PAUSED (3):
    The job is not sampling prediction input and output into
    your BigQuery table and it will not run according to its
    schedule. You can
    <xref uid="google.cloud.datalabeling.v1beta1.DataLabelingService.ResumeEvaluationJob">resume</xref>
    the job.
STOPPED (4):
    The job has this state right before it is
    deleted.

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.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

The abstract base class for a message.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

Config for video event human labeling task.

An Example is a piece of data and its annotation. For example, an image with label "house".

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

Metadata of an ExportData operation.

Response used for ExportDataset longrunning operation.

Request message for ExportData API.

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.

Request message for GetAnnotatedDataset.

Request message for GetAnnotationSpecSet.

Request message for GetDataItem.

Request message for GetDataSet.

Request message for GetEvaluationJob.

Request message for GetEvaluation.

Request message for GetExample

Request message for GetInstruction.

Configuration for how human labeling task should be done.

Image bounding poly annotation. It represents a polygon including bounding box in the image.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

Image classification annotation definition.

Config for image classification human labeling task.

Container of information about an image.

A polyline for the image annotation.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

Image segmentation annotation.

The abstract base class for a message.

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.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

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.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

Image labeling task feature.

Details of a LabelImageSegmentation operation metadata.

Metadata of a labeling operation, such as LabelImage or LabelVideo. Next tag: 20

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

Statistics about annotation specs.

The abstract base class for a message.

Details of a LabelTextClassification operation metadata.

Details of a LabelTextEntityExtraction operation metadata.

Request message for LabelText.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

Text labeling task feature.

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.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

Video labeling task feature.

Request message for ListAnnotatedDatasets.

Results of listing annotated datasets for a dataset.

Request message for ListAnnotationSpecSets.

Results of listing annotation spec set under a project.

Request message for ListDataItems.

Results of listing data items in a dataset.

Request message for ListDataset.

Results of listing datasets within a project.

Request message for ListEvaluationJobs.

Results for listing evaluation jobs.

Request message for ListExamples.

Results of listing Examples in and annotated dataset.

Request message for ListInstructions.

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.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

General information useful for labels coming from contributors.

The configuration of output data.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

Request message for PauseEvaluationJob.

Instruction from a PDF file.

A line with multiple line segments.

Config for image polyline human labeling task.

Request message ResumeEvaluationJob.

Request message for SearchEvaluation.

Results of searching evaluations.

Request message of SearchExampleComparisons.

Results of searching example comparisons.

Example comparisons comparing ground truth output and predictions for a specific input.

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).

Request message for UpdateEvaluationJob.

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.

Annotation spec set with the setting of allowing multi labels or not.

Video event annotation.

Video object tracking annotation.

Container of information of a video.

Container of information of a video thumbnail.

API documentation for datalabeling_v1beta1.services.data_labeling_service.pagers module.