NB!!!! Dataset Class during Brats Challenge validation or testing

[AlyssaAmod]

UNN_BraTS23/scripts/data_class.py

**lines: 41-69**

Should this section not account for when mask does not exist?

see code change suggestion in docstring at end

[AlyssaAmod]

@Alexandra-Smith I see you already discovered this during inference --> can you check if you happy with my suggested code replace from line 41

As in script under Ask Alex:

image = np.load(self.imgs[idx])
image = torch.from_numpy(image) # 4, 240, 240, 155
if self.mode == "labels":
  mask = np.load(self.lbls[idx])
  mask = torch.from_numpy(mask) # 240, 240, 155           
if self.transform is not None:
  if self.mode == "labels":
    subject = tio.Subject(
        image=tio.ScalarImage(tensor=image),
        mask=tio.LabelMap(tensor=mask)
        )
    tranformed_subject = self.transform(subject)
    if self.SSA == False and self.SSAtransform is not None:
      tranformed_subject = self.SSAtransform(tranformed_subject) 
      print("Tranformed_subject: ", tranformed_subject)
      image = tranformed_subject["image"].data
      mask = tranformed_subject["mask"].data
      return image, mask, self.imgs[idx]
    else:
      subject = tio.Subject(
          image=tio.ScalarImage(tensor=image),
          )
      tranformed_subject = self.transform(subject)           
      print("Tranformed_subject: ", tranformed_subject)
      image = tranformed_subject["image"].data
      return image, self.imgs[idx]