DataLabelingServiceAsyncClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Union[str, google.cloud.datalabeling_v1beta1.services.data_labeling_service.transports.base.DataLabelingServiceTransport] = 'grpc_asyncio', client_options: typing.Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)
Service for the AI Platform Data Labeling API.
Properties
api_endpoint
Return the API endpoint used by the client instance.
Returns | |
---|---|
Type | Description |
str | The API endpoint used by the client instance. |
transport
Returns the transport used by the client instance.
Returns | |
---|---|
Type | Description |
DataLabelingServiceTransport | The transport used by the client instance. |
universe_domain
Return the universe domain used by the client instance.
Returns | |
---|---|
Type | Description |
str | The universe domain used by the client instance. |
Methods
DataLabelingServiceAsyncClient
DataLabelingServiceAsyncClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Union[str, google.cloud.datalabeling_v1beta1.services.data_labeling_service.transports.base.DataLabelingServiceTransport] = 'grpc_asyncio', client_options: typing.Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)
Instantiates the data labeling service async client.
Parameters | |
---|---|
Name | Description |
credentials |
Optional[google.auth.credentials.Credentials]
The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment. |
transport |
Union[str,
The transport to use. If set to None, a transport is chosen automatically. |
client_options |
Optional[Union[google.api_core.client_options.ClientOptions, dict]]
Custom options for the client. 1. The |
client_info |
google.api_core.gapic_v1.client_info.ClientInfo
The client info used to send a user-agent string along with API requests. If |
Exceptions | |
---|---|
Type | Description |
google.auth.exceptions.MutualTlsChannelError | If mutual TLS transport creation failed for any reason. |
annotated_dataset_path
annotated_dataset_path(project: str, dataset: str, annotated_dataset: str) -> str
Returns a fully-qualified annotated_dataset string.
annotation_spec_set_path
annotation_spec_set_path(project: str, annotation_spec_set: str) -> str
Returns a fully-qualified annotation_spec_set string.
common_billing_account_path
common_billing_account_path(billing_account: str) -> str
Returns a fully-qualified billing_account string.
common_folder_path
common_folder_path(folder: str) -> str
Returns a fully-qualified folder string.
common_location_path
common_location_path(project: str, location: str) -> str
Returns a fully-qualified location string.
common_organization_path
common_organization_path(organization: str) -> str
Returns a fully-qualified organization string.
common_project_path
common_project_path(project: str) -> str
Returns a fully-qualified project string.
create_annotation_spec_set
create_annotation_spec_set(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.CreateAnnotationSpecSetRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
annotation_spec_set: typing.Optional[
google.cloud.datalabeling_v1beta1.types.annotation_spec_set.AnnotationSpecSet
] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.datalabeling_v1beta1.types.annotation_spec_set.AnnotationSpecSet
Creates an annotation spec set by providing a set of labels.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_create_annotation_spec_set():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.CreateAnnotationSpecSetRequest(
parent="parent_value",
)
# Make the request
response = await client.create_annotation_spec_set(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.CreateAnnotationSpecSetRequest, dict]]
The request object. Request message for CreateAnnotationSpecSet. |
parent |
Required. AnnotationSpecSet resource parent, format: projects/{project_id} This corresponds to the |
annotation_spec_set |
AnnotationSpecSet
Required. Annotation spec set to create. Annotation specs must be included. Only one annotation spec will be accepted for annotation specs with same display_name. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.types.AnnotationSpecSet | 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. |
create_dataset
create_dataset(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.CreateDatasetRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
dataset: typing.Optional[
google.cloud.datalabeling_v1beta1.types.dataset.Dataset
] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.datalabeling_v1beta1.types.dataset.Dataset
Creates dataset. If success return a Dataset resource.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_create_dataset():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.CreateDatasetRequest(
parent="parent_value",
)
# Make the request
response = await client.create_dataset(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.CreateDatasetRequest, dict]]
The request object. Request message for CreateDataset. |
parent |
Required. Dataset resource parent, format: projects/{project_id} This corresponds to the |
dataset |
Dataset
Required. The dataset to be created. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.types.Dataset | Dataset is the resource to hold your data. You can request multiple labeling tasks for a dataset while each one will generate an AnnotatedDataset. |
create_evaluation_job
create_evaluation_job(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.CreateEvaluationJobRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
job: typing.Optional[
google.cloud.datalabeling_v1beta1.types.evaluation_job.EvaluationJob
] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.datalabeling_v1beta1.types.evaluation_job.EvaluationJob
Creates an evaluation job.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_create_evaluation_job():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.CreateEvaluationJobRequest(
parent="parent_value",
)
# Make the request
response = await client.create_evaluation_job(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.CreateEvaluationJobRequest, dict]]
The request object. Request message for CreateEvaluationJob. |
parent |
Required. Evaluation job resource parent. Format: "projects/{project_id}" This corresponds to the |
job |
EvaluationJob
Required. The evaluation job to create. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.types.EvaluationJob | 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. |
create_instruction
create_instruction(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.CreateInstructionRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
instruction: typing.Optional[
google.cloud.datalabeling_v1beta1.types.instruction.Instruction
] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Creates an instruction for how data should be labeled.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_create_instruction():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.CreateInstructionRequest(
parent="parent_value",
)
# Make the request
operation = client.create_instruction(request=request)
print("Waiting for operation to complete...")
response = (await operation).result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.CreateInstructionRequest, dict]]
The request object. Request message for CreateInstruction. |
parent |
Required. Instruction resource parent, format: projects/{project_id} This corresponds to the |
instruction |
Instruction
Required. Instruction of how to perform the labeling task. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be Instruction Instruction of how to perform the labeling task for human operators. Currently only PDF instruction is supported. |
data_item_path
data_item_path(project: str, dataset: str, data_item: str) -> str
Returns a fully-qualified data_item string.
dataset_path
dataset_path(project: str, dataset: str) -> str
Returns a fully-qualified dataset string.
delete_annotated_dataset
delete_annotated_dataset(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.DeleteAnnotatedDatasetRequest,
dict,
]
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None
Deletes an annotated dataset by resource name.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_delete_annotated_dataset():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.DeleteAnnotatedDatasetRequest(
name="name_value",
)
# Make the request
await client.delete_annotated_dataset(request=request)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.DeleteAnnotatedDatasetRequest, dict]]
The request object. Request message for DeleteAnnotatedDataset. |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
delete_annotation_spec_set
delete_annotation_spec_set(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.DeleteAnnotationSpecSetRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None
Deletes an annotation spec set by resource name.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_delete_annotation_spec_set():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.DeleteAnnotationSpecSetRequest(
name="name_value",
)
# Make the request
await client.delete_annotation_spec_set(request=request)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.DeleteAnnotationSpecSetRequest, dict]]
The request object. Request message for DeleteAnnotationSpecSet. |
name |
Required. AnnotationSpec resource name, format: |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
delete_dataset
delete_dataset(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.DeleteDatasetRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None
Deletes a dataset by resource name.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_delete_dataset():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.DeleteDatasetRequest(
name="name_value",
)
# Make the request
await client.delete_dataset(request=request)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.DeleteDatasetRequest, dict]]
The request object. Request message for DeleteDataset. |
name |
Required. Dataset resource name, format: projects/{project_id}/datasets/{dataset_id} This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
delete_evaluation_job
delete_evaluation_job(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.DeleteEvaluationJobRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None
Stops and deletes an evaluation job.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_delete_evaluation_job():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.DeleteEvaluationJobRequest(
name="name_value",
)
# Make the request
await client.delete_evaluation_job(request=request)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.DeleteEvaluationJobRequest, dict]]
The request object. Request message DeleteEvaluationJob. |
name |
Required. Name of the evaluation job that is going to be deleted. Format: "projects/{project_id}/evaluationJobs/{evaluation_job_id}" This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
delete_instruction
delete_instruction(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.DeleteInstructionRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None
Deletes an instruction object by resource name.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_delete_instruction():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.DeleteInstructionRequest(
name="name_value",
)
# Make the request
await client.delete_instruction(request=request)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.DeleteInstructionRequest, dict]]
The request object. Request message for DeleteInstruction. |
name |
Required. Instruction resource name, format: projects/{project_id}/instructions/{instruction_id} This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
evaluation_job_path
evaluation_job_path(project: str, evaluation_job: str) -> str
Returns a fully-qualified evaluation_job string.
evaluation_path
evaluation_path(project: str, dataset: str, evaluation: str) -> str
Returns a fully-qualified evaluation string.
example_path
example_path(
project: str, dataset: str, annotated_dataset: str, example: str
) -> str
Returns a fully-qualified example string.
export_data
export_data(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.ExportDataRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
annotated_dataset: typing.Optional[str] = None,
filter: typing.Optional[str] = None,
output_config: typing.Optional[
google.cloud.datalabeling_v1beta1.types.dataset.OutputConfig
] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Exports data and annotations from dataset.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_export_data():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.ExportDataRequest(
name="name_value",
annotated_dataset="annotated_dataset_value",
)
# Make the request
operation = client.export_data(request=request)
print("Waiting for operation to complete...")
response = (await operation).result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.ExportDataRequest, dict]]
The request object. Request message for ExportData API. |
name |
Required. Dataset resource name, format: projects/{project_id}/datasets/{dataset_id} This corresponds to the |
annotated_dataset |
Required. Annotated dataset resource name. DataItem in Dataset and their annotations in specified annotated dataset will be exported. It's in format of projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id} This corresponds to the |
filter |
Optional. Filter is not supported at this moment. This corresponds to the |
output_config |
OutputConfig
Required. Specify the output destination. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be ExportDataOperationResponse Response used for ExportDataset longrunning operation. |
from_service_account_file
from_service_account_file(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Parameter | |
---|---|
Name | Description |
filename |
str
The path to the service account private key json file. |
Returns | |
---|---|
Type | Description |
DataLabelingServiceAsyncClient | The constructed client. |
from_service_account_info
from_service_account_info(info: dict, *args, **kwargs)
Creates an instance of this client using the provided credentials info.
Parameter | |
---|---|
Name | Description |
info |
dict
The service account private key info. |
Returns | |
---|---|
Type | Description |
DataLabelingServiceAsyncClient | The constructed client. |
from_service_account_json
from_service_account_json(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Parameter | |
---|---|
Name | Description |
filename |
str
The path to the service account private key json file. |
Returns | |
---|---|
Type | Description |
DataLabelingServiceAsyncClient | The constructed client. |
get_annotated_dataset
get_annotated_dataset(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetAnnotatedDatasetRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.datalabeling_v1beta1.types.dataset.AnnotatedDataset
Gets an annotated dataset by resource name.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_get_annotated_dataset():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.GetAnnotatedDatasetRequest(
name="name_value",
)
# Make the request
response = await client.get_annotated_dataset(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.GetAnnotatedDatasetRequest, dict]]
The request object. Request message for GetAnnotatedDataset. |
name |
Required. Name of the annotated dataset to get, format: projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id} This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.types.AnnotatedDataset | 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. |
get_annotation_spec_set
get_annotation_spec_set(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetAnnotationSpecSetRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.datalabeling_v1beta1.types.annotation_spec_set.AnnotationSpecSet
Gets an annotation spec set by resource name.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_get_annotation_spec_set():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.GetAnnotationSpecSetRequest(
name="name_value",
)
# Make the request
response = await client.get_annotation_spec_set(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.GetAnnotationSpecSetRequest, dict]]
The request object. Request message for GetAnnotationSpecSet. |
name |
Required. AnnotationSpecSet resource name, format: projects/{project_id}/annotationSpecSets/{annotation_spec_set_id} This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.types.AnnotationSpecSet | 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. |
get_data_item
get_data_item(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetDataItemRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.datalabeling_v1beta1.types.dataset.DataItem
Gets a data item in a dataset by resource name. This API can be called after data are imported into dataset.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_get_data_item():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.GetDataItemRequest(
name="name_value",
)
# Make the request
response = await client.get_data_item(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.GetDataItemRequest, dict]]
The request object. Request message for GetDataItem. |
name |
Required. The name of the data item to get, format: projects/{project_id}/datasets/{dataset_id}/dataItems/{data_item_id} This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.types.DataItem | DataItem is a piece of data, without annotation. For example, an image. |
get_dataset
get_dataset(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetDatasetRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.datalabeling_v1beta1.types.dataset.Dataset
Gets dataset by resource name.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_get_dataset():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.GetDatasetRequest(
name="name_value",
)
# Make the request
response = await client.get_dataset(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.GetDatasetRequest, dict]]
The request object. Request message for GetDataSet. |
name |
Required. Dataset resource name, format: projects/{project_id}/datasets/{dataset_id} This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.types.Dataset | Dataset is the resource to hold your data. You can request multiple labeling tasks for a dataset while each one will generate an AnnotatedDataset. |
get_evaluation
get_evaluation(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetEvaluationRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.datalabeling_v1beta1.types.evaluation.Evaluation
Gets an evaluation by resource name (to search, use xref_projects.evaluations.search).
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_get_evaluation():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.GetEvaluationRequest(
name="name_value",
)
# Make the request
response = await client.get_evaluation(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.GetEvaluationRequest, dict]]
The request object. Request message for GetEvaluation. |
name |
Required. Name of the evaluation. Format: "projects/{project_id}/datasets/{dataset_id}/evaluations/{evaluation_id}' This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.types.Evaluation | Describes an evaluation between a machine learning model's predictions and ground truth labels. Created when an EvaluationJob runs successfully. |
get_evaluation_job
get_evaluation_job(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetEvaluationJobRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.datalabeling_v1beta1.types.evaluation_job.EvaluationJob
Gets an evaluation job by resource name.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_get_evaluation_job():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.GetEvaluationJobRequest(
name="name_value",
)
# Make the request
response = await client.get_evaluation_job(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.GetEvaluationJobRequest, dict]]
The request object. Request message for GetEvaluationJob. |
name |
Required. Name of the evaluation job. Format: "projects/{project_id}/evaluationJobs/{evaluation_job_id}" This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.types.EvaluationJob | 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. |
get_example
get_example(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetExampleRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
filter: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.datalabeling_v1beta1.types.dataset.Example
Gets an example by resource name, including both data and annotation.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_get_example():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.GetExampleRequest(
name="name_value",
)
# Make the request
response = await client.get_example(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.GetExampleRequest, dict]]
The request object. Request message for GetExample |
name |
Required. Name of example, format: projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id}/examples/{example_id} This corresponds to the |
filter |
Optional. An expression for filtering Examples. Filter by annotation_spec.display_name is supported. Format "annotation_spec.display_name = {display_name}" This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.types.Example | An Example is a piece of data and its annotation. For example, an image with label "house". |
get_instruction
get_instruction(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetInstructionRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.datalabeling_v1beta1.types.instruction.Instruction
Gets an instruction by resource name.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_get_instruction():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.GetInstructionRequest(
name="name_value",
)
# Make the request
response = await client.get_instruction(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.GetInstructionRequest, dict]]
The request object. Request message for GetInstruction. |
name |
Required. Instruction resource name, format: projects/{project_id}/instructions/{instruction_id} This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.types.Instruction | Instruction of how to perform the labeling task for human operators. Currently only PDF instruction is supported. |
get_mtls_endpoint_and_cert_source
get_mtls_endpoint_and_cert_source(
client_options: typing.Optional[
google.api_core.client_options.ClientOptions
] = None,
)
Return the API endpoint and client cert source for mutual TLS.
The client cert source is determined in the following order:
(1) if GOOGLE_API_USE_CLIENT_CERTIFICATE
environment variable is not "true", the
client cert source is None.
(2) if client_options.client_cert_source
is provided, use the provided one; if the
default client cert source exists, use the default one; otherwise the client cert
source is None.
The API endpoint is determined in the following order:
(1) if client_options.api_endpoint
if provided, use the provided one.
(2) if GOOGLE_API_USE_CLIENT_CERTIFICATE
environment variable is "always", use the
default mTLS endpoint; if the environment variable is "never", use the default API
endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise
use the default API endpoint.
More details can be found at https://google.aip.dev/auth/4114.
Parameter | |
---|---|
Name | Description |
client_options |
google.api_core.client_options.ClientOptions
Custom options for the client. Only the |
Exceptions | |
---|---|
Type | Description |
google.auth.exceptions.MutualTLSChannelError | If any errors happen. |
Returns | |
---|---|
Type | Description |
Tuple[str, Callable[[], Tuple[bytes, bytes]]] | returns the API endpoint and the client cert source to use. |
get_transport_class
get_transport_class() -> (
typing.Type[
google.cloud.datalabeling_v1beta1.services.data_labeling_service.transports.base.DataLabelingServiceTransport
]
)
Returns an appropriate transport class.
Parameter | |
---|---|
Name | Description |
label |
typing.Optional[str]
The name of the desired transport. If none is provided, then the first transport in the registry is used. |
import_data
import_data(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.ImportDataRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
input_config: typing.Optional[
google.cloud.datalabeling_v1beta1.types.dataset.InputConfig
] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Imports data into dataset based on source locations defined in request. It can be called multiple times for the same dataset. Each dataset can only have one long running operation running on it. For example, no labeling task (also long running operation) can be started while importing is still ongoing. Vice versa.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_import_data():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.ImportDataRequest(
name="name_value",
)
# Make the request
operation = client.import_data(request=request)
print("Waiting for operation to complete...")
response = (await operation).result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.ImportDataRequest, dict]]
The request object. Request message for ImportData API. |
name |
Required. Dataset resource name, format: projects/{project_id}/datasets/{dataset_id} This corresponds to the |
input_config |
InputConfig
Required. Specify the input source of the data. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be ImportDataOperationResponse Response used for ImportData longrunning operation. |
instruction_path
instruction_path(project: str, instruction: str) -> str
Returns a fully-qualified instruction string.
label_image
label_image(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelImageRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
basic_config: typing.Optional[
google.cloud.datalabeling_v1beta1.types.human_annotation_config.HumanAnnotationConfig
] = None,
feature: typing.Optional[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelImageRequest.Feature
] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Starts a labeling task for image. The type of image labeling task is configured by feature in the request.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_label_image():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
image_classification_config = datalabeling_v1beta1.ImageClassificationConfig()
image_classification_config.annotation_spec_set = "annotation_spec_set_value"
basic_config = datalabeling_v1beta1.HumanAnnotationConfig()
basic_config.instruction = "instruction_value"
basic_config.annotated_dataset_display_name = "annotated_dataset_display_name_value"
request = datalabeling_v1beta1.LabelImageRequest(
image_classification_config=image_classification_config,
parent="parent_value",
basic_config=basic_config,
feature="SEGMENTATION",
)
# Make the request
operation = client.label_image(request=request)
print("Waiting for operation to complete...")
response = (await operation).result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.LabelImageRequest, dict]]
The request object. Request message for starting an image labeling task. |
parent |
Required. Name of the dataset to request labeling task, format: projects/{project_id}/datasets/{dataset_id} This corresponds to the |
basic_config |
HumanAnnotationConfig
Required. Basic human annotation config. This corresponds to the |
feature |
Feature
Required. The type of image labeling task. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be AnnotatedDataset 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. |
label_text
label_text(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelTextRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
basic_config: typing.Optional[
google.cloud.datalabeling_v1beta1.types.human_annotation_config.HumanAnnotationConfig
] = None,
feature: typing.Optional[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelTextRequest.Feature
] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Starts a labeling task for text. The type of text labeling task is configured by feature in the request.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_label_text():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
text_classification_config = datalabeling_v1beta1.TextClassificationConfig()
text_classification_config.annotation_spec_set = "annotation_spec_set_value"
basic_config = datalabeling_v1beta1.HumanAnnotationConfig()
basic_config.instruction = "instruction_value"
basic_config.annotated_dataset_display_name = "annotated_dataset_display_name_value"
request = datalabeling_v1beta1.LabelTextRequest(
text_classification_config=text_classification_config,
parent="parent_value",
basic_config=basic_config,
feature="TEXT_ENTITY_EXTRACTION",
)
# Make the request
operation = client.label_text(request=request)
print("Waiting for operation to complete...")
response = (await operation).result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.LabelTextRequest, dict]]
The request object. Request message for LabelText. |
parent |
Required. Name of the data set to request labeling task, format: projects/{project_id}/datasets/{dataset_id} This corresponds to the |
basic_config |
HumanAnnotationConfig
Required. Basic human annotation config. This corresponds to the |
feature |
Feature
Required. The type of text labeling task. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be AnnotatedDataset 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. |
label_video
label_video(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelVideoRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
basic_config: typing.Optional[
google.cloud.datalabeling_v1beta1.types.human_annotation_config.HumanAnnotationConfig
] = None,
feature: typing.Optional[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelVideoRequest.Feature
] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Starts a labeling task for video. The type of video labeling task is configured by feature in the request.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_label_video():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
video_classification_config = datalabeling_v1beta1.VideoClassificationConfig()
video_classification_config.annotation_spec_set_configs.annotation_spec_set = "annotation_spec_set_value"
basic_config = datalabeling_v1beta1.HumanAnnotationConfig()
basic_config.instruction = "instruction_value"
basic_config.annotated_dataset_display_name = "annotated_dataset_display_name_value"
request = datalabeling_v1beta1.LabelVideoRequest(
video_classification_config=video_classification_config,
parent="parent_value",
basic_config=basic_config,
feature="EVENT",
)
# Make the request
operation = client.label_video(request=request)
print("Waiting for operation to complete...")
response = (await operation).result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.LabelVideoRequest, dict]]
The request object. Request message for LabelVideo. |
parent |
Required. Name of the dataset to request labeling task, format: projects/{project_id}/datasets/{dataset_id} This corresponds to the |
basic_config |
HumanAnnotationConfig
Required. Basic human annotation config. This corresponds to the |
feature |
Feature
Required. The type of video labeling task. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be AnnotatedDataset 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. |
list_annotated_datasets
list_annotated_datasets(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotatedDatasetsRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
filter: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListAnnotatedDatasetsAsyncPager
)
Lists annotated datasets for a dataset. Pagination is supported.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_list_annotated_datasets():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.ListAnnotatedDatasetsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_annotated_datasets(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.ListAnnotatedDatasetsRequest, dict]]
The request object. Request message for ListAnnotatedDatasets. |
parent |
Required. Name of the dataset to list annotated datasets, format: projects/{project_id}/datasets/{dataset_id} This corresponds to the |
filter |
Optional. Filter is not supported at this moment. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListAnnotatedDatasetsAsyncPager | Results of listing annotated datasets for a dataset. Iterating over this object will yield results and resolve additional pages automatically. |
list_annotation_spec_sets
list_annotation_spec_sets(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotationSpecSetsRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
filter: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListAnnotationSpecSetsAsyncPager
)
Lists annotation spec sets for a project. Pagination is supported.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_list_annotation_spec_sets():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.ListAnnotationSpecSetsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_annotation_spec_sets(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.ListAnnotationSpecSetsRequest, dict]]
The request object. Request message for ListAnnotationSpecSets. |
parent |
Required. Parent of AnnotationSpecSet resource, format: projects/{project_id} This corresponds to the |
filter |
Optional. Filter is not supported at this moment. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListAnnotationSpecSetsAsyncPager | Results of listing annotation spec set under a project. Iterating over this object will yield results and resolve additional pages automatically. |
list_data_items
list_data_items(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDataItemsRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
filter: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListDataItemsAsyncPager
)
Lists data items in a dataset. This API can be called after data are imported into dataset. Pagination is supported.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_list_data_items():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.ListDataItemsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_data_items(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.ListDataItemsRequest, dict]]
The request object. Request message for ListDataItems. |
parent |
Required. Name of the dataset to list data items, format: projects/{project_id}/datasets/{dataset_id} This corresponds to the |
filter |
Optional. Filter is not supported at this moment. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListDataItemsAsyncPager | Results of listing data items in a dataset. Iterating over this object will yield results and resolve additional pages automatically. |
list_datasets
list_datasets(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDatasetsRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
filter: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListDatasetsAsyncPager
)
Lists datasets under a project. Pagination is supported.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_list_datasets():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.ListDatasetsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_datasets(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.ListDatasetsRequest, dict]]
The request object. Request message for ListDataset. |
parent |
Required. Dataset resource parent, format: projects/{project_id} This corresponds to the |
filter |
Optional. Filter on dataset is not supported at this moment. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListDatasetsAsyncPager | Results of listing datasets within a project. Iterating over this object will yield results and resolve additional pages automatically. |
list_evaluation_jobs
list_evaluation_jobs(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListEvaluationJobsRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
filter: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListEvaluationJobsAsyncPager
)
Lists all evaluation jobs within a project with possible filters. Pagination is supported.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_list_evaluation_jobs():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.ListEvaluationJobsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_evaluation_jobs(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.ListEvaluationJobsRequest, dict]]
The request object. Request message for ListEvaluationJobs. |
parent |
Required. Evaluation job resource parent. Format: "projects/{project_id}" This corresponds to the |
filter |
Optional. You can filter the jobs to list by model_id (also known as model_name, as described in EvaluationJob.modelVersion) or by evaluation job state (as described in EvaluationJob.state). To filter by both criteria, use the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListEvaluationJobsAsyncPager | Results for listing evaluation jobs. Iterating over this object will yield results and resolve additional pages automatically. |
list_examples
list_examples(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListExamplesRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
filter: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListExamplesAsyncPager
)
Lists examples in an annotated dataset. Pagination is supported.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_list_examples():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.ListExamplesRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_examples(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.ListExamplesRequest, dict]]
The request object. Request message for ListExamples. |
parent |
Required. Example resource parent. This corresponds to the |
filter |
Optional. An expression for filtering Examples. For annotated datasets that have annotation spec set, filter by annotation_spec.display_name is supported. Format "annotation_spec.display_name = {display_name}" This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListExamplesAsyncPager | Results of listing Examples in and annotated dataset. Iterating over this object will yield results and resolve additional pages automatically. |
list_instructions
list_instructions(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListInstructionsRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
filter: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListInstructionsAsyncPager
)
Lists instructions for a project. Pagination is supported.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_list_instructions():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.ListInstructionsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_instructions(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.ListInstructionsRequest, dict]]
The request object. Request message for ListInstructions. |
parent |
Required. Instruction resource parent, format: projects/{project_id} This corresponds to the |
filter |
Optional. Filter is not supported at this moment. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListInstructionsAsyncPager | Results of listing instructions under a project. Iterating over this object will yield results and resolve additional pages automatically. |
parse_annotated_dataset_path
parse_annotated_dataset_path(path: str) -> typing.Dict[str, str]
Parses a annotated_dataset path into its component segments.
parse_annotation_spec_set_path
parse_annotation_spec_set_path(path: str) -> typing.Dict[str, str]
Parses a annotation_spec_set path into its component segments.
parse_common_billing_account_path
parse_common_billing_account_path(path: str) -> typing.Dict[str, str]
Parse a billing_account path into its component segments.
parse_common_folder_path
parse_common_folder_path(path: str) -> typing.Dict[str, str]
Parse a folder path into its component segments.
parse_common_location_path
parse_common_location_path(path: str) -> typing.Dict[str, str]
Parse a location path into its component segments.
parse_common_organization_path
parse_common_organization_path(path: str) -> typing.Dict[str, str]
Parse a organization path into its component segments.
parse_common_project_path
parse_common_project_path(path: str) -> typing.Dict[str, str]
Parse a project path into its component segments.
parse_data_item_path
parse_data_item_path(path: str) -> typing.Dict[str, str]
Parses a data_item path into its component segments.
parse_dataset_path
parse_dataset_path(path: str) -> typing.Dict[str, str]
Parses a dataset path into its component segments.
parse_evaluation_job_path
parse_evaluation_job_path(path: str) -> typing.Dict[str, str]
Parses a evaluation_job path into its component segments.
parse_evaluation_path
parse_evaluation_path(path: str) -> typing.Dict[str, str]
Parses a evaluation path into its component segments.
parse_example_path
parse_example_path(path: str) -> typing.Dict[str, str]
Parses a example path into its component segments.
parse_instruction_path
parse_instruction_path(path: str) -> typing.Dict[str, str]
Parses a instruction path into its component segments.
pause_evaluation_job
pause_evaluation_job(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.PauseEvaluationJobRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None
Pauses an evaluation job. Pausing an evaluation job that is
already in a PAUSED
state is a no-op.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_pause_evaluation_job():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.PauseEvaluationJobRequest(
name="name_value",
)
# Make the request
await client.pause_evaluation_job(request=request)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.PauseEvaluationJobRequest, dict]]
The request object. Request message for PauseEvaluationJob. |
name |
Required. Name of the evaluation job that is going to be paused. Format: "projects/{project_id}/evaluationJobs/{evaluation_job_id}" This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
resume_evaluation_job
resume_evaluation_job(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.ResumeEvaluationJobRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None
Resumes a paused evaluation job. A deleted evaluation job can't be resumed. Resuming a running or scheduled evaluation job is a no-op.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_resume_evaluation_job():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.ResumeEvaluationJobRequest(
name="name_value",
)
# Make the request
await client.resume_evaluation_job(request=request)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.ResumeEvaluationJobRequest, dict]]
The request object. Request message ResumeEvaluationJob. |
name |
Required. Name of the evaluation job that is going to be resumed. Format: "projects/{project_id}/evaluationJobs/{evaluation_job_id}" This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
search_evaluations
search_evaluations(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchEvaluationsRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
filter: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.SearchEvaluationsAsyncPager
)
Searches xref_evaluations within a project.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_search_evaluations():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.SearchEvaluationsRequest(
parent="parent_value",
)
# Make the request
page_result = client.search_evaluations(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.SearchEvaluationsRequest, dict]]
The request object. Request message for SearchEvaluation. |
parent |
Required. Evaluation search parent (project ID). Format: "projects/{project_id}" This corresponds to the |
filter |
Optional. To search evaluations, you can filter by the following: - evaluation_job.evaluation_job_id (the last part of EvaluationJob.name) - evaluation_job.model_id (the {model_name} portion of EvaluationJob.modelVersion) - evaluation_job.evaluation_job_run_time_start (Minimum threshold for the evaluationJobRunTime that created the evaluation) - evaluation_job.evaluation_job_run_time_end (Maximum threshold for the evaluationJobRunTime that created the evaluation) - evaluation_job.job_state (EvaluationJob.state) - annotation_spec.display_name (the Evaluation contains a metric for the annotation spec with this displayName) To filter by multiple critiera, use the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.SearchEvaluationsAsyncPager | Results of searching evaluations. Iterating over this object will yield results and resolve additional pages automatically. |
search_example_comparisons
search_example_comparisons(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchExampleComparisonsRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.SearchExampleComparisonsAsyncPager
)
Searches example comparisons from an evaluation. The return format is a list of example comparisons that show ground truth and prediction(s) for a single input. Search by providing an evaluation ID.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_search_example_comparisons():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.SearchExampleComparisonsRequest(
parent="parent_value",
)
# Make the request
page_result = client.search_example_comparisons(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.SearchExampleComparisonsRequest, dict]]
The request object. Request message of SearchExampleComparisons. |
parent |
Required. Name of the Evaluation resource to search for example comparisons from. Format: "projects/{project_id}/datasets/{dataset_id}/evaluations/{evaluation_id}" This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.SearchExampleComparisonsAsyncPager | Results of searching example comparisons. Iterating over this object will yield results and resolve additional pages automatically. |
update_evaluation_job
update_evaluation_job(
request: typing.Optional[
typing.Union[
google.cloud.datalabeling_v1beta1.types.data_labeling_service.UpdateEvaluationJobRequest,
dict,
]
] = None,
*,
evaluation_job: typing.Optional[
google.cloud.datalabeling_v1beta1.types.evaluation_job.EvaluationJob
] = None,
update_mask: typing.Optional[google.protobuf.field_mask_pb2.FieldMask] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.datalabeling_v1beta1.types.evaluation_job.EvaluationJob
Updates an evaluation job. You can only update certain fields of
the job's
xref_EvaluationJobConfig:
humanAnnotationConfig.instruction
, exampleCount
, and
exampleSamplePercentage
.
If you want to change any other aspect of the evaluation job, you must delete the job and create a new one.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1
async def sample_update_evaluation_job():
# Create a client
client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()
# Initialize request argument(s)
request = datalabeling_v1beta1.UpdateEvaluationJobRequest(
)
# Make the request
response = await client.update_evaluation_job(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.datalabeling_v1beta1.types.UpdateEvaluationJobRequest, dict]]
The request object. Request message for UpdateEvaluationJob. |
evaluation_job |
EvaluationJob
Required. Evaluation job that is going to be updated. This corresponds to the |
update_mask |
Optional. Mask for which fields to update. You can only provide the following fields: - |
retry |
google.api_core.retry_async.AsyncRetry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.datalabeling_v1beta1.types.EvaluationJob | 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. |