diff --git a/ultralytics/__init__.py b/ultralytics/__init__.py
index 4014ac4a..1914e08c 100644
--- a/ultralytics/__init__.py
+++ b/ultralytics/__init__.py
@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = "8.2.27"
+__version__ = "8.2.28"
 
 import os
 
diff --git a/ultralytics/nn/autobackend.py b/ultralytics/nn/autobackend.py
index d2727fe2..6ec42fce 100644
--- a/ultralytics/nn/autobackend.py
+++ b/ultralytics/nn/autobackend.py
@@ -184,7 +184,7 @@ class AutoBackend(nn.Module):
             LOGGER.info(f"Loading {w} for ONNX Runtime inference...")
             check_requirements(("onnx", "onnxruntime-gpu" if cuda else "onnxruntime"))
             if IS_RASPBERRYPI or IS_JETSON:
-                # Fix error: module 'numpy.linalg._umath_linalg' has no attribute '_ilp64' when exporting to Tensorflow SavedModel on RPi and Jetson
+                # Fix 'numpy.linalg._umath_linalg' has no attribute '_ilp64' for TF SavedModel on RPi and Jetson
                 check_requirements("numpy==1.23.5")
             import onnxruntime
 
diff --git a/ultralytics/utils/ops.py b/ultralytics/utils/ops.py
index 5acf75ea..6dc6024a 100644
--- a/ultralytics/utils/ops.py
+++ b/ultralytics/utils/ops.py
@@ -402,7 +402,7 @@ def xyxy2xywh(x):
 def xywh2xyxy(x):
     """
     Convert bounding box coordinates from (x, y, width, height) format to (x1, y1, x2, y2) format where (x1, y1) is the
-    top-left corner and (x2, y2) is the bottom-right corner.
+    top-left corner and (x2, y2) is the bottom-right corner. Note: ops per 2 channels faster than per channel.
 
     Args:
         x (np.ndarray | torch.Tensor): The input bounding box coordinates in (x, y, width, height) format.
@@ -412,12 +412,10 @@ def xywh2xyxy(x):
     """
     assert x.shape[-1] == 4, f"input shape last dimension expected 4 but input shape is {x.shape}"
     y = torch.empty_like(x) if isinstance(x, torch.Tensor) else np.empty_like(x)  # faster than clone/copy
-    dw = x[..., 2] / 2  # half-width
-    dh = x[..., 3] / 2  # half-height
-    y[..., 0] = x[..., 0] - dw  # top left x
-    y[..., 1] = x[..., 1] - dh  # top left y
-    y[..., 2] = x[..., 0] + dw  # bottom right x
-    y[..., 3] = x[..., 1] + dh  # bottom right y
+    xy = x[..., :2]  # centers
+    wh = x[..., 2:] / 2  # half width-height
+    y[..., :2] = xy - wh  # top left xy
+    y[..., 2:] = xy + wh  # bottom right xy
     return y