ultralytics 8.0.72 faster Windows trainings and corrupt cache fix (#1912)

Co-authored-by: andreaswimmer <53872150+andreaswimmer@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

ultralytics/yolo/engine/model.py

@@ -253,10 +253,10 @@ class YOLO:
             source (str, optional): The input source for object tracking. Can be a file path or a video stream.
             stream (bool, optional): Whether the input source is a video stream. Defaults to False.
             persist (bool, optional): Whether to persist the trackers if they already exist. Defaults to False.
-            **kwargs: Additional keyword arguments for the tracking process.
+            **kwargs (optional): Additional keyword arguments for the tracking process.
 
         Returns:
-            object: The tracking results.
+            (List[ultralytics.yolo.engine.results.Results]): The tracking results.
 
         """
         if not hasattr(self.predictor, 'trackers'):

ultralytics/yolo/engine/results.py

@@ -244,8 +244,7 @@ class Boxes(BaseTensor):
         orig_shape (tuple): Original image size, in the format (height, width).
 
     Attributes:
-        boxes (torch.Tensor) or (numpy.ndarray): A tensor or numpy array containing the detection boxes,
-            with shape (num_boxes, 6).
+        boxes (torch.Tensor) or (numpy.ndarray): The detection boxes with shape (num_boxes, 6).
         orig_shape (torch.Tensor) or (numpy.ndarray): Original image size, in the format (height, width).
         is_track (bool): True if the boxes also include track IDs, False otherwise.
 
@@ -272,7 +271,6 @@ class Boxes(BaseTensor):
             boxes = boxes[None, :]
         n = boxes.shape[-1]
         assert n in (6, 7), f'expected `n` in [6, 7], but got {n}'  # xyxy, (track_id), conf, cls
-        # TODO
         self.is_track = n == 7
         self.boxes = boxes
         self.orig_shape = torch.as_tensor(orig_shape, device=boxes.device) if isinstance(boxes, torch.Tensor) \