Image and Video Ground Truth Labeling

Interactive image and video labeling, create training data for deep learning with object detection, semantic segmentation, instance segmentation, and image classification

Use the Image Labeler and Video Labeler apps to interactively label a collection of images, a video, or a sequence of images to create training data for deep learning. You can label rectangular regions of interest (ROIs) or polylines, pixels for semantic segmentation, polygons for instance segmentation, and scenes for image classification. The apps also include computer vision algorithms to automate the labeling of ground truth data for use with detection and tracking algorithms. They also provide an API and workflow that enables you to import your own algorithms to automate the labeling of ground truth data.

Image Labeler app also provides an interface for a collaborative multi-user team labeling workflow. You can distribute images for labeling between team members. You can also review the labeled images, provide feedback and track progress for all labeling and review tasks.

Featured Examples

New

Automatically Label Ground Truth Using Segment Anything Model

Produce pixel labels for semantic segmentation using the Segment Anything Model (SAM) in the Image Labeler app. The SAM is an automatic segmentation technique that you can use to segment object regions to label with just a few clicks, or automatically segment the entire image and instantaneously create labels for selected regions. In this example, you interactively label pixels for semantic segmentation in two ways.

Since R2024b
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Export Ground Truth Object to Custom and COCO JSON Files

Export a ground truth object to a custom data format JavaScript Object Notation (JSON) file and to a COCO data format JSON file.

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Automate Ground Truth Labeling for Semantic Segmentation

Use a pretrained semantic segmentation algorithm to segment the sky and a road in an image.

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Convert Image Labeler Polygons to Labeled Blocked Image for Semantic Segmentation

Convert polygon labels stored in a groundTruth object into a labeled blocked image for semantic segmentation workflows.

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New

Automate Labeling of Objects in Video Using RAFT Optical Flow

Use a pretrained RAFT optical flow estimation network to propagate a predefined object mask from one frame to the next in a video sequence.

Since R2024b
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Automate Ground Truth Labeling for Object Detection

Create an automation algorithm to automatically label data for object detection using a pretrained object detector.

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