Choose an App to Label Ground Truth Data

You can use Computer Vision Toolbox™ and Automated Driving Toolbox™ apps to label ground truth data. Use this labeled data to validate or train algorithms such as image classifiers, object detectors, and semantic segmentation networks. The choice of labeling app depends on several factors, including the supported data sources, labels, and types of automation.

One key consideration is the type of data that you want to label.

• If your data is an image collection, use the Image Labeler app. An image collection is an unordered set of images that can vary in size. For example, you can use the app to label images of books for training a classifier.

• If your data is a single video or image sequence, use the Video Labeler app. An image sequence is an ordered set of images that resembles a video. For example, you can use this app to label a video or image sequence of cars driving on a highway for training an object detector.

• If your data includes multiple time-overlapped signals, such as videos, image sequences, or lidar signals, use the Ground Truth Labeler app. For example, you can label data for a single scene captured by multiple sensors mounted on a vehicle.

The table summarizes the key features of these labeling apps.

Labeling App	Data Sources	Label Support	Automation	Additional Features
Image Labeler (Computer Vision Toolbox)	Image collections	Rectangle regions of interest (ROIs) Line ROIs Pixel ROIs Sublabels Attributes Scenes	Built-in automation algorithms Custom automation algorithms	View visual summary of labeled data
Video Labeler (Computer Vision Toolbox)	Videos Image sequences Custom image data sources	Rectangle ROIs Line ROIs Pixel ROIs Sublabels Attributes Scenes	Built-in automation algorithms Custom automation algorithms Temporal automation algorithms	View visual summary of labeled data
Ground Truth Labeler (Automated Driving Toolbox)	Videos Image sequences Custom image data sources Point cloud sequences (PCD or PLY files) Velodyne® lidar files Rosbags (requires ROS Toolbox)	Rectangle ROIs Cuboid ROIs Line ROIs Pixel ROIs Sublabels Attributes Scenes	Built-in automation algorithms, including vehicle and lane detection algorithms and a point cloud temporal interpolation algorithm Custom automation algorithms Temporal automation algorithms	View visual summary of labeled data Connect external tool to app for displaying time-synchronized signals, such as lidar or CAN bus data Customize loading interface to support additional data sources

Related Topics

• Get Started with the Image Labeler
• Get Started with the Video Labeler
• Get Started with the Ground Truth Labeler (Automated Driving Toolbox)