Choose an App to Label Ground Truth Data
You can use Computer Vision Toolbox™, Automated Driving Toolbox™, Lidar Toolbox™, Audio Toolbox™, Signal Processing Toolbox™, and Medical Imaging Toolbox™ apps to label ground truth data. Use this labeled data to validate or train algorithms such as image classifiers, object detectors, semantic segmentation networks, instance segmentation networks, and deep learning applications. 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. The Image Labeler can also handle very large images (at least one dimension >8K).
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 (Automated Driving Toolbox) app. For example, you can label data for a single scene captured by multiple sensors mounted on a vehicle.
If your data is only a lidar signal, use the Lidar Labeler (Lidar Toolbox). For example, you can use this app to label data captured from a point cloud sensor.
If your data consists of single-channel or multichannel one-dimensional signals, use the Signal Labeler (Signal Processing Toolbox). For example, you can label biomedical, speech, communications, or vibration data. You can also use Signal Labeler to perform audio-specific tasks, such as speech detection and speech-to-text transcription.
If your data is a 2-D medical image or image series, or a 3-D medical image volume, use the Medical Image Labeler (Medical Imaging Toolbox). For example, you can label computed tomography (CT) image volumes of the chest to train a semantic segmentation network.
This table summarizes the key features of the labeling apps.
Labeling App | Data Sources | Label Support | Automation | Additional Features |
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Image Labeler |
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Video Labeler |
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Ground Truth Labeler (Automated Driving Toolbox) |
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Lidar Labeler (Lidar Toolbox) |
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Signal Labeler (Signal Processing Toolbox) |
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Medical Image Labeler (Medical Imaging Toolbox) |
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Related Topics
- Get Started with the Image Labeler
- Get Started with the Video Labeler
- Get Started with Ground Truth Labelling (Automated Driving Toolbox)
- Get Started with the Lidar Labeler (Lidar Toolbox)
- Using Signal Labeler App (Signal Processing Toolbox)
- Label Spoken Words in Audio Signals (Signal Processing Toolbox)
- Get Started with Medical Image Labeler (Medical Imaging Toolbox)