title: PascalVOC `trainaug` and `test` dataset
body: <p>In the <a href="https://arxiv.org/pdf/1802.02611v3.pdf" rel="nofollow noreferrer">DeepLabv3+ paper</a> the authors state the following:</p>
  <blockquote>
  <p>The proposed models are evaluated on the PASCAL VOC 2012 semantic
  segmentation benchmark [1] which contains 20 foreground object classes and one
  background class. The original dataset contains 1, 464 (train), 1, 449 (val), and
  1, 456 (test) pixel-level annotated images. We augment the dataset by the extra
  annotations provided by [76], resulting in 10, 582 (trainaug) training images.</p>
  </blockquote>
  <ol>
  <li>What's the exact PyTorch code to retrieve the trainaug dataset?</li>
  <li>The size of trainaug considers also the 1464 images of the PASCAL VOC 2012 dataset?</li>
  <li>What's the exact code to retrieve the test dataset?</li>
  </ol>