You should follow this example: https://www.mathworks.com/help/vision/examples/semantic-segmentation-using-deep-learning.html
After labeling, you should have two sets of images. The first set will be the original images and the second set will be the categorial images with labels.
For semantic segmentation you should create datastores:
imds = imageDatastore(imgDir); %corresponding to the original images
pxds = pixelLabelDatastore(labelDir,classes,labelIDs); %corresponding to labeled images
The example link above explains this in more detail.
Note that imgDir and labelDir can simply be a cell array of the filepaths to the images, in corresponding order
For instance:
imgDir = {"~/Users/awz/img1.tif", "~/Users/awz/img2.tif", "~/Users/awz/img3.tif"};
labelDir = {"~/Users/awz/label1.tif", "~/Users/awz/label2.tif", "~/Users/awz/label3.tif"};
classes = ["class1", "class2", "class3"];
labelIDs = [1 2 3];
imds = imageDatastore(imgDir);
pxds = pixelLabelDatastore(labelDir,classes,labelIDs);
