Label Studio terminology
The following table describes some terms you might encounter as you use Label Studio:
|The output of a labeling task. Previously called “completions”. The terms “annotations” and “labels” are frequently used interchangeably.
|Region within an image.
|What you import into Label Studio, comprised of individual items, or labeling tasks.
|What you add to each region while labeling a task in Label Studio.
|When you click Label All Tasks from the Data Manager, you are working within the label stream.
|The labeling configuration determines what annotators and reviewers will see. It is configured in the project settings.
|Annotations in Label Studio format that machine learning models create for an unlabeled dataset. See import pre-annotations
|A defined relationship between two labeled regions.
|A label applied to a specific region as stored in an annotation or prediction. See Label Studio JSON format of annotated tasks.
|The “quick view” is what you see when you click an individual item in the Data Manager to open it (different than viewing it in the “label stream”).
|Item in a dataset.
|The portion of the task identified for labeling. For example, when working with text, this might be a specific span of text or field. For images, an example region is a bounding box. For text, an example region is a span of text. Often has a label assigned to it.
|When you upload data to Label Studio, each item in the dataset becomes a labeling task. A task is a distinct item from a dataset that is ready to be labeled, pre-annotated, or has already been annotated. For example: a text snippet, an image, or a video clip.
|Configuration options to customize the labeling interface. See more about tags.
|Example labeling configurations that you can use to specify the type of labeling that you’re performing with your dataset. See all available templates