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, pixel ROI labels, and scene labels, and 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 Train Object Detector or Semantic Segmentation Network from Ground Truth Data.
MATLAB® Toolstrip: On the Apps tab, under Image Processing and Computer Vision, click the app icon.
MATLAB command prompt: Enter
imageLabeler opens a new session of the app, enabling you to
label ground truth data in images.
imageLabeler(imageFolder) opens the app and loads all the
images from the folder named
imageLabeler(imageDatastore) opens the app and reads all of
the images from an
imageDatastore object. The
imageDatastore files are read using
imread. For example, to open the
app with a collection of stop sign
stopSignsFolder = fullfile(toolboxdir('vision'),'visiondata','stopSignImages'); imds = imageDatastore(stopSignsFolder) imageLabeler(imds)
imageLabeler(sessionFile) opens the app and loads a saved
Image Labeler session,
sessionFile input contains the path and file name. The
sessionFile points to contains the saved
The Image Labeler app provides built-in algorithms that you can use to automate labeling. From the app toolstrip, click Select Algorithm and then select an automation algorithm.
|Built-In Automation Algorithm||Description|
ACF People Detector
|Detect and label people using a pretrained detector based on aggregate channel features (ACF). With this algorithm, you do not need to draw any ROI labels.|
ACF Vehicle Detector (requires Automated Driving System Toolbox™)
|Detect and label vehicles using a pretrained detector based on ACF. With this algorithm, you do not need to draw any ROI labels.|