Labelling for Object Detection

When training an object detection model, you will often need to do some labelling first. This guide covers some of the features common to labelling for object detection.

• Navigate To The Assessment Editor
• Draw A Bounding Box
• Use Best Practices
• Avoid Common Issues
• Tips and Tricks

Navigate To The Assessment Editor

When you first log in to Highlighter, you should see your assessment dashboard. If not, click the 'Assess' link in the top navigation. Click the button in the main pane that says 'Start Task' or 'Continue Task'. This will take you to the Assessment Editor to start work. You will see this button if you have been assigned a work queue. If you don't see it, please contact your Highlighter project manager.

Draw a Bounding Box

Select the Bounding Box tool.

Use Best Practices

• Consistency: Use the same criteria for labeling across all images (e.g., include only fully visible objects).
• Accuracy: Ensure bounding boxes are precise and labels are correct.
• Clarity: If an object is ambiguous, consult the provided guidelines or a supervisor.
• Efficiency: Work systematically, but prioritize quality over speed.

Avoid Common Issues

• Loose Bounding Boxes: Boxes should be snug, not oversized.
• Incorrect Labels: Verify the class before saving.
• Missing Objects: Ensure no objects from the class list are overlooked.
• Duplicate Boxes: Avoid labeling the same object twice.

Tips and Tricks

Quickly Label Multiple Annotations With The Same Attributes

Label multiple annotations with the same attributes by selecting your first annotation, then holding down shift and selecting more annotations. Then open the attributes form in the bottom left by clicking Edit, set your attributes, then click Update. The selected attributes will be applied to all the annotations you selected.