Quick typing fix for datasets

biogtr/datasets/cell_tracking_dataset.py

@@ -28,7 +28,7 @@ def __init__(
         clip_length: int = 10,
         mode: str = "train",
         augmentations: Optional[dict] = None,
-        gt_list: str = None,
+        gt_list: Optional[str] = None,
     ):
         """Initialize CellTrackingDataset.
 

biogtr/datasets/microscopy_dataset.py

@@ -4,6 +4,7 @@
 from biogtr.datasets.base_dataset import BaseDataset
 from torch.utils.data import Dataset
 from torchvision.transforms import functional as tvf
+from typing import Optional
 import albumentations as A
 import numpy as np
 import random
@@ -23,7 +24,7 @@ def __init__(
         chunk: bool = False,
         clip_length: int = 10,
         mode: str = "Train",
-        augmentations: dict = None,
+        augmentations: Optional[dict] = None,
     ):
         """Initialize MicroscopyDataset.
 

biogtr/datasets/sleap_dataset.py

@@ -1,14 +1,14 @@
 """Module containing logic for loading sleap datasets."""
+from biogtr.datasets import data_utils
+from biogtr.datasets.base_dataset import BaseDataset
+from torchvision.transforms import functional as tvf
+from typing import List, Optional
 import albumentations as A
-import torch
 import imageio
 import numpy as np
-import sleap_io as sio
 import random
-from biogtr.datasets import data_utils
-from biogtr.datasets.base_dataset import BaseDataset
-from torchvision.transforms import functional as tvf
-from typing import List
+import sleap_io as sio
+import torch
 
 
 class SleapDataset(BaseDataset):
@@ -23,7 +23,7 @@ def __init__(
         chunk: bool = True,
         clip_length: int = 500,
         mode: str = "train",
-        augmentations: dict = None,
+        augmentations: Optional[dict] = None,
     ):
         """Initialize SleapDataset.
 
@@ -137,6 +137,7 @@ def get_instances(self, label_idx: List[int], frame_idx: List[int]) -> list[dict
             gt_track_ids, bboxes, crops, poses, shown_poses = [], [], [], [], []
 
             i = int(i)
+            print(i)
 
             lf = video[i]
             img = vid_reader.get_data(i)