To get started, create and configure a data labeling project.
To create a project via the Labelbox UI, follow these steps:
Under the Projects tab, select New project.
Add a project name and an optional description for your project.
Attach a dataset to your project and click Next to proceed to the next step.
Choose a label editor. Editor is the native labeling interface and has the most robust labeling and QA tools. If you are using a custom editor, select the Custom Editor.
Set up quality assurance tools for your project. In this step, you can turn on Benchmarks or Consensus as well as the Review step.
Click Finish to complete the setup process.
# Create a new project project = client.create_project(name="my-test-project", description="a description") # Get the Labelbox editor editor = next(client.get_labeling_frontends(where = LabelingFrontend.name == 'editor')) # Get exsiting ontology (you can share an ontology across projects) ontology = client.get_ontology("ONTOLOGY_ID") # Get dataset dataset = client.get_dataset("DATASET_ID") # Setup project with editor and normalized ontology project.setup(editor, ontology.normalized) # Upload labeling instructions project.upsert_instructions("LOCAL_FILE_PATH (PDF or HTML)") #Attach the dataset to the project project.datasets.connect(dataset) #Detach the dataset from the project project.datasets.disconnect(dataset)
For a lot of use cases, chances are that you may want to use a dedicated external data labeling team. Labelbox offers a premium data labeling service integrated tightly into the Labelbox Annotate platform.
Internal data labeling team
Inviting, onboard, and manage your own data labeling team using this guide: Manage members
Collaboration & rapid iteration is critical for achieving outstanding outcome with data quality.
Our very best customers run their data labeling operations through real-time collaboration with the data labeling workforce, data engineers, and ML engineers. In Labelbox, you can easily augment your internal domain experts with external data labeling service providers.
Any time during the life of a data labeling project, you can easily update key project settings. Below are the most common things you will likely need to update:
A project can be deleted by Admin. To delete a project, go to Danger zone under project settings.
Deleting a project will also delete all the labels that have been submitted for a project.
Updated about 2 months ago