You can request labeling service for your Annotate projects and manage the requested labeling workforce using the Labelbox Python SDK.

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Experimental feature

This is an experimental feature that requires you to enable experimental features before using its methods.

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Methods

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Get and request labeling service

Use project.labeling_service = project.get_labeling_service() to get the labeling service associated with the project. Then use labeling_service.request() to request a workforce of trained labelers for your data. 
# Enable experimental features
client.enable_experimental = True

# Get labeling service
labeling_service = project.get_labeling_service()

# Validate all project requirements and request labeling service
labeling_service.request()

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Get labeling service status

Use project.get_labeling_service_status() to check the status of your requested labeling service. 
# Enable experimental features
client.enable_experimental = True

# Get status of requested labeling service
project.get_labeling_service_status()
This method returns the following value defined in the LabelingServiceStatus enum, corresponding to the statuses of your requested labeling service:
  • SET_UP: Your request has been submitted, but you need to set up your request by adding data rows, ontologies, and labeling instructions to proceed the request.
  • REQUESTED: Your request has been validated and is pending approval for connecting to labeling workforce.
  • ACCEPTED: Your request has satisfied the prerequisite and been accepted.
  • CALIBRATION: Labelers are labeling a sample of your data rows that you can review and confirm alignment on the expectation.
  • PRODUCTION: Labelers are labeling all data rows.
  • COMPLETE: Labelers have finished adding labels to your projects.

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Get labeling service details

Use project.get_labeling_service_dashboard() to retrieve the following attributes of the project for which you requested labeling service:
  • id: The project ID
  • name: The project name status: The status of the labeling service
  • data_rows_count: The total number of data rows batched in the project
  • tasks_completed_count: The number of completed tasks (with the COMPLETE status)
  • tasks_remaining_count: The number of incomplete tasks (queued data rows with statuses other than COMPLETE)
  • tags: Project tags associated with the project
  • media_type: The media type of the project
  • client: The Labelbox client
If you are an admin, you can also use client.get_labeling_service_dashboard() to retrieve details of all projects with labeling service requested in your workspace. 
# Enable experimental features
client.enable_experimental = True

# Get details of a project with labeling service requested
project.get_labeling_service_dashboard()

# Get details of all projects with labeling service requested
client.get_labeling_service_dashboard()