Use batch queue instead
Dataset-based queueing (attaching an entire dataset to a project for labeling) is a legacy feature that is being replaced by batch-based queueing. We are making batch queue the default queueing mode for customers on a rolling basis. To learn more about migrating your old projects to batch queue, visit our migration guide.
Dataset based queues are useful when you intend to label all the data rows in a data set.
Attach / Detach
Dataset limit per project
Please note that you can add at most 1500 datasets to a single project.
You can attach up to 1500 dataset 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.
You can attach a dataset via the app or you can do it via the Python SDK.
Appending to a Dataset
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).
Updated 4 months ago