diff --git a/supervision/metrics/utils/object_size.py b/supervision/metrics/utils/object_size.py
index 162879224..6c1e94089 100644
--- a/supervision/metrics/utils/object_size.py
+++ b/supervision/metrics/utils/object_size.py
@@ -98,7 +98,7 @@ def get_mask_size_category(mask: npt.NDArray[np.bool_]) -> npt.NDArray[np.int_]:
 
 def get_obb_size_category(xyxyxyxy: npt.NDArray[np.float32]) -> npt.NDArray[np.int_]:
     """
-    Get the size category of a oriented bounding boxes array.
+    Get the size category of an oriented bounding boxes array.
 
     Args:
         xyxyxyxy (np.ndarray): The bounding boxes array shaped (N, 4, 2).
@@ -107,25 +107,34 @@ def get_obb_size_category(xyxyxyxy: npt.NDArray[np.float32]) -> npt.NDArray[np.i
         (np.ndarray) The size category of each bounding box, matching
         the enum values of ObjectSizeCategory. Shaped (N,).
     """
-    if len(xyxyxyxy.shape) != 3 or xyxyxyxy.shape[1] != 4 or xyxyxyxy.shape[2] != 2:
+    if xyxyxyxy.shape != (len(xyxyxyxy), 4, 2):
         raise ValueError("Oriented bounding boxes must be shaped (N, 4, 2)")
 
     # Shoelace formula
     x = xyxyxyxy[:, :, 0]
     y = xyxyxyxy[:, :, 1]
-    x1, x2, x3, x4 = x.T
-    y1, y2, y3, y4 = y.T
     areas = 0.5 * np.abs(
-        (x1 * y2 + x2 * y3 + x3 * y4 + x4 * y1)
-        - (x2 * y1 + x3 * y2 + x4 * y3 + x1 * y4)
+        x[:, 0] * y[:, 1]
+        + x[:, 1] * y[:, 2]
+        + x[:, 2] * y[:, 3]
+        + x[:, 3] * y[:, 0]
+        - (
+            x[:, 1] * y[:, 0]
+            + x[:, 2] * y[:, 1]
+            + x[:, 3] * y[:, 2]
+            + x[:, 0] * y[:, 3]
+        )
     )
 
-    result = np.full(areas.shape, ObjectSizeCategory.ANY.value)
     SM, LG = SIZE_THRESHOLDS
-    result[areas < SM] = ObjectSizeCategory.SMALL.value
-    result[(areas >= SM) & (areas < LG)] = ObjectSizeCategory.MEDIUM.value
-    result[areas >= LG] = ObjectSizeCategory.LARGE.value
-    return result
+    categories = np.where(
+        areas < SM,
+        ObjectSizeCategory.SMALL.value,
+        np.where(
+            areas < LG, ObjectSizeCategory.MEDIUM.value, ObjectSizeCategory.LARGE.value
+        ),
+    )
+    return categories
 
 
 def get_detection_size_category(