code: def load_label(self, idx):
          
          label = scipy.io.loadmat('{}/segmentation/img_{}.mat'.format(self.nyud_dir, idx))['segmentation'].astype(np.uint8)
          label -= 1  # rotate labels
          label = label[np.newaxis, ...]
          return label
docs: Load label image as 1 x height x width integer array of label indices.
          Shift labels so that classes are 0-39 and void is 255 (to ignore it).
          The leading singleton dimension is required by the loss.