Plainsight's annotation tool supports several types of labels to choose from. Choosing a label type depends on the model being used and the intended outcome of the model.
Rectangles: Object detection
Polygons: Semantic and instance segmentation
Feature Points: Key point detection for a group
Text: image captioning (not supported for SmartML model training)
Classification: Image classification (not supported for SmartML model training)
Multi Classification: multi-label image classification (not supported for SmartML model training)
Navigate to "Label Definitions" tab within a project
Enter the name of the new label
Select the type of new label
Finish setup for label type selected (Setup will vary on label type)
Click "Save" button
Rectangles, Polygons, and Feature Point labels have the option of adding sub-labels into the label definitions.
This is useful for having classes associated with higher level instances. Example: drawing rectangles around birds for object detection, but having a class for types of bird within the rectangle (Duck, Geese, etc...).
Click "Add Sublabel"
Type a sub-label name
Choose sub-label type
Fill out label options
Click on the edit icon
Make desired changes to the label options
Click on the trash-bin icon
Click "Yes" or "Confirm" to confirm deletion