OBB Docs updates (#7512)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Muhammad Rizwan Munawar <chr043416@gmail.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>

ultralytics/engine/results.py

@@ -605,7 +605,9 @@ class OBB(BaseTensor):
         conf (torch.Tensor | numpy.ndarray): The confidence values of the boxes.
         cls (torch.Tensor | numpy.ndarray): The class values of the boxes.
         id (torch.Tensor | numpy.ndarray): The track IDs of the boxes (if available).
-        xyxyxyxy (torch.Tensor | numpy.ndarray): The boxes in xyxyxyxy format normalized by original image size.
+        xyxyxyxyn (torch.Tensor | numpy.ndarray): The rotated boxes in xyxyxyxy format normalized by original image size.
+        xyxyxyxy (torch.Tensor | numpy.ndarray): The rotated boxes in xyxyxyxy format.
+        xyxy (torch.Tensor | numpy.ndarray): The horizontal boxes in xyxyxyxy format.
         data (torch.Tensor): The raw OBB tensor (alias for `boxes`).
 
     Methods:

ultralytics/trackers/basetrack.py

@@ -1,5 +1,5 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
-# This module defines the base classes and structures for object tracking in YOLO.
+"""This module defines the base classes and structures for object tracking in YOLO."""
 
 from collections import OrderedDict
 

ultralytics/trackers/track.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, AGPL-3.0 license
+
 from functools import partial
 from pathlib import Path
 

ultralytics/utils/plotting.py

@@ -365,7 +365,6 @@ class Annotator:
         self.tf = count_txt_size
         tl = self.tf or round(0.002 * (self.im.shape[0] + self.im.shape[1]) / 2) + 1
         tf = max(tl - 1, 1)
-        gap = int(24 * tl)  # gap between in_count and out_count based on line_thickness
 
         # Get text size for in_count and out_count
         t_size_in = cv2.getTextSize(str(counts), 0, fontScale=tl / 2, thickness=tf)[0]