cppe5["train"] = cppe5["train"].with_transform(transform_aug_ann)
cppe5["train"][15]
{'pixel_values': tensor([[[ 0.9132,  0.9132,  0.9132,  , -1.9809, -1.9809, -1.9809],
          [ 0.9132,  0.9132,  0.9132,  , -1.9809, -1.9809, -1.9809],
          [ 0.9132,  0.9132,  0.9132,  , -1.9638, -1.9638, -1.9638],
          ,
          [-1.5699, -1.5699, -1.5699,  , -1.9980, -1.9980, -1.9980],
          [-1.5528, -1.5528, -1.5528,  , -1.9980, -1.9809, -1.9809],
          [-1.5528, -1.5528, -1.5528,  , -1.9980, -1.9809, -1.9809]],

     [[ 1.3081,  1.3081,  1.3081,  , -1.8431, -1.8431, -1.8431],
      [ 1.3081,  1.3081,  1.3081,  , -1.8431, -1.8431, -1.8431],
      [ 1.3081,  1.3081,  1.3081,  , -1.8256, -1.8256, -1.8256],
      ,
      [-1.3179, -1.3179, -1.3179,  , -1.8606, -1.8606, -1.8606],
      [-1.3004, -1.3004, -1.3004,  , -1.8606, -1.8431, -1.8431],
      [-1.3004, -1.3004, -1.3004,  , -1.8606, -1.8431, -1.8431]],

     [[ 1.4200,  1.4200,  1.4200,  , -1.6476, -1.6476, -1.6476],
      [ 1.4200,  1.4200,  1.4200,  , -1.6476, -1.6476, -1.6476],
      [ 1.4200,  1.4200,  1.4200,  , -1.6302, -1.6302, -1.6302],
      ,
      [-1.0201, -1.0201, -1.0201,  , -1.5604, -1.5604, -1.5604],
      [-1.0027, -1.0027, -1.0027,  , -1.5604, -1.5430, -1.5430],
      [-1.0027, -1.0027, -1.0027,  , -1.5604, -1.5430, -1.5430]]]),

'pixel_mask': tensor([[1, 1, 1,  , 1, 1, 1],
         [1, 1, 1,  , 1, 1, 1],
         [1, 1, 1,  , 1, 1, 1],
         ,
         [1, 1, 1,  , 1, 1, 1],
         [1, 1, 1,  , 1, 1, 1],
         [1, 1, 1,  , 1, 1, 1]]),
 'labels': {'size': tensor([800, 800]), 'image_id': tensor([756]), 'class_labels': tensor([4]), 'boxes': tensor([[0.7340, 0.6986, 0.3414, 0.5944]]), 'area': tensor([519544.4375]), 'iscrowd': tensor([0]), 'orig_size': tensor([480, 480])}}

You have successfully augmented the individual images and prepared their annotations.