Labelbox allows users to send data rows, from Model to a labeling project in Annotate using a batch. Queueing data rows via a batch gives you flexibility and control of the data rows to label.

Create a batch from a Model Run

To send a batch of data to a project for labeling, use the following steps:

1. Go to Model and filter for the relevant data rows you want to label.

2. Once you have the desired data rows in the result, either choose Select all or manually select data rows to include in your batch. Once you have the data rows selected, hit the blue button at the top of the screen and select Send to > Project as batch project

3. From the batch creation modal, choose a project, give the batch a name, and select a priority for the data rows. When setting data row priority, 1 is the highest and 5 is the lowest. You may see a warning that some of the data rows have already been submitted to the labeling project. Data rows that have already been submitted will be excluded from the batch when you click submit.
4. Optionally, include predictions as pre-labels in the batch.
   If you want to speed up labeling, you can send predictions that are stored in a Model Run, as pre-labels in the labeling project. Learn more about How to include predictions as pre-labels in a batch
5. Click Submit batch. Then, navigate to the project to begin labeling.

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Data row distribution

Newly queued data rows will be distributed after any data rows in the label queue have already been reserved.

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Batches enforce data type

Only assets that matches the project data type will be added to your batches.

How to include predictions as pre-labels in a batch

It is not always efficient to label data from scratch. Indeed, it is sometimes recommended to start labeling based on your model predictions. Labelbox allows users to send predictions that are stored in a Model Run, as pre-labels in the labeling project.

Decide if you want to send predictions as pre-labels

A toggle allows you to include or exclude predictions from the batch. Labelbox shows you how many predictions could be sent as pre-labels.

Pick which predictions to send as pre-labels

You decide which model run to use thanks to a drop-down. The predictions from the selected model run will be sent to the labeling project, as pre-labels.

Besides, you can send predictions corresponding to all features - or to a subset of features - by toggling on/off each feature. For example, you might want to use predictions from specific features on which your model is doing well, but exclude predictions from other features on which the model is struggling.

Pick a model run that is compatible with the labeling project

In order to send predictions from a model run, as pre-labels in a labeling project, the feature must be present in both the model run ontology and in the labeling project ontology.

The model run and the labeling project do not need to share the exact same ontology. However, they must share at least some features in common. You can only send predictions as pre-labels, for these features that are shared between the model run and the labeling project.

If no predictions from the model run are compatible with the labeling project, you will see a warning message.

FAQs

Can I submit the same data row multiple times?

A data row can only be sent once to a labeling project. Hence, it cannot be part of more than one batch in a project.

Can a batch be shared between projects?

A batch lives inside a project. Hence, a batch cannot be shared between projects. However, you can create a new batch using the same data rows.

Can I append data rows to a batch?

Once a batch has been submitted you cannot add more data rows. We are considering adding this functionality in the future.

How many data rows can be in a batch?

100,000 data rows. See Limits for more information.

How many batches can be added to a project?

There is no limit to batches that have been labeled on a project. But there is a limit of 1,500 batches on a project. See Limits for more information