FIX: formatting

Author: gdj0nes

labelbox/data/annotation_types/data/raster.py

@@ -23,7 +23,8 @@ class RasterData(BaseModel, ABC):
     arr: Optional[TypedArray[Literal['uint8']]] = None
 
     @classmethod
-    def from_2D_arr(cls, arr: Union[TypedArray[Literal['uint8']], TypedArray[Literal['int']]], **kwargs):
+    def from_2D_arr(cls, arr: Union[TypedArray[Literal['uint8']],
+                                    TypedArray[Literal['int']]], **kwargs):
         """Construct from a 2D numpy array
 
         Args:
@@ -44,7 +45,9 @@ def from_2D_arr(cls, arr: Union[TypedArray[Literal['uint8']], TypedArray[Literal
         if np.can_cast(arr, np.uint8):
             arr = arr.astype(np.uint8)
         else:
-            raise ValueError("Could not cast array to uint8, check that values are between 0 and 255")
+            raise ValueError(
+                "Could not cast array to uint8, check that values are between 0 and 255"
+            )
 
         arr = np.stack((arr,) * 3, axis=-1)
         return cls(arr=arr, **kwargs)

labelbox/data/annotation_types/label.py

@@ -5,12 +5,8 @@
 
 from labelbox.orm.model import Entity
 from labelbox.schema import ontology
-from .annotation import (
-    ClassificationAnnotation,
-    ObjectAnnotation,
-    VideoClassificationAnnotation,
-    VideoObjectAnnotation
-)
+from .annotation import (ClassificationAnnotation, ObjectAnnotation,
+                         VideoClassificationAnnotation, VideoObjectAnnotation)
 from .classification import ClassificationAnswer
 from .data import VideoData, TextData, ImageData, BaseData
 from .geometry import Mask
@@ -40,14 +36,10 @@ class Label(BaseModel):
     """
     uid: Optional[Cuid] = None
     data: Union[BaseData]
-    annotations: List[Union[
-        ClassificationAnnotation,
-        ObjectAnnotation,
-        VideoObjectAnnotation,
-        VideoClassificationAnnotation,
-        ScalarMetric,
-        ConfusionMatrixMetric
-    ]] = []
+    annotations: List[Union[ClassificationAnnotation, ObjectAnnotation,
+                            VideoObjectAnnotation,
+                            VideoClassificationAnnotation, ScalarMetric,
+                            ConfusionMatrixMetric]] = []
     extra: Dict[str, Any] = {}
 
     def object_annotations(self) -> List[ObjectAnnotation]:
@@ -63,13 +55,13 @@ def _get_annotations_by_type(self, annotation_type):
         ]
 
     def frame_annotations(
-            self
+        self
     ) -> Dict[str, Union[VideoObjectAnnotation, VideoClassificationAnnotation]]:
         frame_dict = defaultdict(list)
         for annotation in self.annotations:
             if isinstance(
                     annotation,
-                    (VideoObjectAnnotation, VideoClassificationAnnotation)):
+                (VideoObjectAnnotation, VideoClassificationAnnotation)):
                 frame_dict[annotation.frame].append(annotation)
         return frame_dict