Yes, target_type is set to instance. What should I be using. I don’t know the background of these.
The cityscapes class is as below:

torchvision.datasets. Cityscapes ( root ,  split=‘train’ ,  mode=‘fine’ ,  target_type=‘instance’ ,  transform=None ,  target_transform=None ,  transforms=None )[SOURCE]
Cityscapes Dataset.
Parameters


root  ( string ) – Root directory of dataset where directory  leftImg8bit  and  gtFine  or  gtCoarse  are located.

split  ( string ,  optional ) – The image split to use,  train ,  test  or  val  if mode=”fine” otherwise  train ,  train_extra  or  val


mode  ( string ,  optional ) – The quality mode to use,  fine  or  coarse


target_type  ( string  or   list  ,  optional ) – Type of target to use,  instance ,  semantic ,  polygon  or  color . Can also be a list to output a tuple with all specified target types.

transform  ( callable ,  optional ) – A function/transform that takes in a PIL image and returns a transformed version. E.g,  transforms.RandomCrop


target_transform  ( callable ,  optional ) – A function/transform that takes in the target and transforms it.

transforms  ( callable ,  optional ) – A function/transform that takes input sample and its target as entry and returns a transformed version.


Edit: I just saw that we have a target_type called semantic. I’ll try using it.