eatures integrations with label_studio and pigeon.Annotator Flavor Integration Notes ArgillaAnnotator argilla argilla Connect ZenML with Argilla LabelStudioAnnotator label_studio label_studio Connect ZenML with Label Studio PigeonAnnotator pigeon pigeon Connect ZenML with Pigeon. Notebook only & for image and text classification tasks. ProdigyAnnotator prodigy prodigy Connect ZenML with Prodigy Custom Implementation custom Extend the annotator abstraction and provide your own implementation

If you would like to see the available flavors for annotators, you can use the command:

zenml annotator flavor list

How to use it

The available implementation of the annotator is built on top of the Label Studio integration, which means that using an annotator currently is no different from what's described on the Label Studio page: How to use it?. (Pigeon is also supported, but has a very limited functionality and only works within Jupyter notebooks.)

A note on names

The various annotation tools have mostly standardized around the naming of key concepts as part of how they build their tools. Unfortunately, this hasn't been completely unified so ZenML takes an opinion on which names we use for our stack components and integrations. Key differences to note:

Label Studio refers to the grouping of a set of annotations/tasks as a 'Project', whereas most other tools use the term 'Dataset', so ZenML also calls this grouping a 'Dataset'.

The individual meta-unit for 'an annotation + the source data' is referred to in different ways, but at ZenML (and with Label Studio) we refer to them as 'tasks'.

The remaining core concepts ('annotation' and 'prediction', in particular) are broadly used among annotation tools.

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Last updated 15 days ago