Add docformatter to pre-commit (#5279)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Burhan <62214284+Burhan-Q@users.noreply.github.com>

ultralytics/data/dataset.py

@@ -33,6 +33,7 @@ class YOLODataset(BaseDataset):
     """
 
     def __init__(self, *args, data=None, use_segments=False, use_keypoints=False, **kwargs):
+        """Initializes the YOLODataset with optional configurations for segments and keypoints."""
         self.use_segments = use_segments
         self.use_keypoints = use_keypoints
         self.data = data
@@ -40,7 +41,9 @@ class YOLODataset(BaseDataset):
         super().__init__(*args, **kwargs)
 
     def cache_labels(self, path=Path('./labels.cache')):
-        """Cache dataset labels, check images and read shapes.
+        """
+        Cache dataset labels, check images and read shapes.
+
         Args:
             path (Path): path where to save the cache file (default: Path('./labels.cache')).
         Returns:
@@ -157,7 +160,7 @@ class YOLODataset(BaseDataset):
         self.transforms = self.build_transforms(hyp)
 
     def update_labels_info(self, label):
-        """custom your label format here."""
+        """Custom your label format here."""
         # NOTE: cls is not with bboxes now, classification and semantic segmentation need an independent cls label
         # we can make it also support classification and semantic segmentation by add or remove some dict keys there.
         bboxes = label.pop('bboxes')
@@ -254,6 +257,7 @@ class ClassificationDataset(torchvision.datasets.ImageFolder):
         return {'img': sample, 'cls': j}
 
     def __len__(self) -> int:
+        """Return the total number of samples in the dataset."""
         return len(self.samples)
 
     def verify_images(self):
@@ -320,6 +324,16 @@ def save_dataset_cache_file(prefix, path, x):
 
 # TODO: support semantic segmentation
 class SemanticDataset(BaseDataset):
+    """
+    Semantic Segmentation Dataset.
+
+    This class is responsible for handling datasets used for semantic segmentation tasks. It inherits functionalities
+    from the BaseDataset class.
+
+    Note:
+        This class is currently a placeholder and needs to be populated with methods and attributes for supporting
+        semantic segmentation tasks.
+    """
 
     def __init__(self):
         """Initialize a SemanticDataset object."""