Computer Vision Toolbox™ and Automated Driving Toolbox™ provide several apps for labeling ground truth data. You can use this labeled data to validate algorithms or to 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 to train a classifier.
If your data is a video or image sequence, use the Video Labeler or Ground Truth Labeler app. An image sequence is an ordered set of images that resemble a video. For example, you can use these apps to label a video or image sequence of cars driving on a highway to train an object detector.
The table summarizes the key features of all three labeling apps.
Labeling App | Data Sources | Label Support | Automation | Additional Features |
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Image Labeler (Computer Vision Toolbox) |
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Video Labeler (Computer Vision Toolbox) |
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Ground Truth Labeler (Automated Driving Toolbox) |
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