Label images for computer vision applications
The Image Labeler app enables you to label ground truth data in a collection of images. Using the app, you can:
Define rectangular regions of interest (ROI) labels, polyline ROI labels, pixel ROI labels, polygon ROI labels, and scene labels. Use these labels to interactively label your ground truth data.
Use built-in detection or tracking algorithms to label your ground truth data.
Write, import, and use your own custom automation algorithm to automatically label ground truth. See Create Automation Algorithm for Labeling.
Evaluate the performance of your label automation algorithms using a visual summary. See View Summary of Ground Truth Labels.
Export the labeled ground truth as a groundTruth
object. You can use
this object for system verification or for training an object detector or
semantic segmentation network. See Training Data for Object Detection and Semantic Segmentation.
The Image Labeler app supports all image file formats supported by
imread
. To read additional file
formats, you can create an imageDatastore
and use the
ReadFcn
property.
When loading images, if an image has a dimension larger than 8000 pixels or is a multiresolution image, the Image Labeler app offers you the option to convert the image into a blocked image. A blocked image consists of a large image that has been divided into smaller blocks that can fit in memory. Once the Image Labeler converts the large image into a blocked, you can process it in the app as you would any other image. While using blocked images enables you to process images in the app that you might not otherwise be able to, there are some limitations. For more information, see Label Large Images in Image Labeler.
To learn more about this app, see Get Started with the Image Labeler.
MATLAB® Toolstrip: On the Apps tab, under Image Processing and Computer Vision, click the app icon.
MATLAB command prompt: Enter imageLabeler
.