An attribute adds more information to a class. So, if you’re annotating apples, you could create the class
An attribute group is a subcategory of a class that provides more detailed information regarding the instance. So, if you’re annotating apples, you could create the class
A class is a label that gives information about your instance. So, if you’re annotating images of apples, you would annotate the apples and assign each of them the class
A collection of items.
A dataset is an environment that houses the images of your Vector Project where you can check the quality of your annotations.
An editor is an interface where you can annotate items. Currently, SuperAnnotate has 4 editors: Pixel Editor (images), Vector Editor (images and video frames), Video Editor, and Text Editor.
An instance is a single annotation.
An item is a file you upload to your project to annotate it. Currently, you can upload the following items to SuperAnnotate: images, videos, and documents.
The neural network is an environment to create and train models.
Priority values help you determine the images that you need to annotate first to improve your model training. It's a key active learning feature that speeds up your annotation time.
A project contributor is a user who works on a project. They can be a Project Admin, an Annotator, or a QA.
Smart Prediction allows you to predict instances on your items using available models or your own models.
Smart Segmentation allows you to divide your images into multiple segments and create pixel-accurate annotations fast.
A team is a group of users who work on projects. A team member can be a Team Owner, a Team Admin, or a Contributor.
Token for Python SDK
A token for Python SDK is an authentication key that grants you access to various API calls within the platform.
A workflow is a feature that allows you to distribute annotation steps to your Annotators, helping your team save time by avoiding mistakes.
Updated 2 months ago