I am following this tutorial on image segmentation on the TensorFlow website.

The website uses its own labeled images for the tutorial, so the images have data that says which pixels are a part of the object, which ones border the object, and which pixels aren't part of the object.

This tutorial uses the Oxford-IIIT Pet Dataset, created by Parkhi et al. The dataset consists of images of 37 pet breeds, with 200 images per breed (~100 each in the train and test split). Each image includes the corresponding labels, and pixel-wise masks. The masks are class-labels for each pixel. Each pixel is given one of three categories :

  • Class 1: Pixel belonging to the pet.
  • Class 2: Pixel bordering the pet.
  • Class 3: None of the above/ Surrounding pixel.

In my case, I have unlabelled images, so I cannot currently perform image segmentation with my images. Which approach should I use to label my images for image segmentation?


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