You can attach one or more datasets to a labeling project. When you attach a dataset to a project, Labelbox will add all of the data rows in that dataset to the labeling queue.
If you have a large dataset (over 100k data rows), we recommend dividing the large dataset into smaller datasets. This will keep the queue size small and maintain high queue performance, especially if you are working with a large labeling team.
When you detach a dataset from a project, Labelbox will remove all its data rows from the project. However, you'll still be able to view the labels in the project. If the dataset is detached during a live labeling session, some of its data rows may remain reserved in the queue (depending upon the number of active labelers).
Once a dataset is attached to one or more projects, you can continuously append new data rows to the label queue for those projects by adding them to the attached dataset. You can add more data rows via the app or you can use the Python SDK (recommended).
The batch queue allows you to individually select any number of data rows and submit them to a project for labeling - allowing you to use Catalog to engage in Active learning.
For more information, see our batch queue docs.
Updated about 1 month ago