Add https://youtu.be/uZ7SymQfqKI and track docs updates (#10351)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Muhammad Rizwan Munawar <muhammadrizwanmunawar123@gmail.com>

docs/en/modes/track.md

@@ -56,6 +56,10 @@ The default tracker is BoT-SORT.
 
 ## Tracking
 
+!!! Warning "Tracker Threshold Information"
+    
+    If object confidence score will be low, i.e lower than [`track_high_thresh`](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/trackers/bytetrack.yaml#L5), then there will be no tracks successfully returned and updated.
+
 To run the tracker on video streams, use a trained Detect, Segment or Pose model such as YOLOv8n, YOLOv8n-seg and YOLOv8n-pose.
 
 !!! Example
@@ -93,6 +97,10 @@ As can be seen in the above usage, tracking is available for all Detect, Segment
 
 ## Configuration
 
+!!! Warning "Tracker Threshold Information"
+    
+    If object confidence score will be low, i.e lower than [`track_high_thresh`](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/trackers/bytetrack.yaml#L5), then there will be no tracks successfully returned and updated.
+
 ### Tracking Arguments
 
 Tracking configuration shares properties with Predict mode, such as `conf`, `iou`, and `show`. For further configurations, refer to the [Predict](../modes/predict.md#inference-arguments) model page.

docs/en/reference/data/dataset.md

@@ -15,10 +15,6 @@ keywords: Ultralytics, YOLO, YOLODataset, SemanticDataset, data handling, data m
 
 <br><br>
 
-## ::: ultralytics.data.dataset.ClassificationDataset
-
-<br><br>
-
 ## ::: ultralytics.data.dataset.YOLOMultiModalDataset
 
 <br><br>
@@ -34,3 +30,7 @@ keywords: Ultralytics, YOLO, YOLODataset, SemanticDataset, data handling, data m
 ## ::: ultralytics.data.dataset.SemanticDataset
 
 <br><br>
+
+## ::: ultralytics.data.dataset.ClassificationDataset
+
+<br><br>

docs/en/reference/utils/__init__.md

@@ -63,6 +63,10 @@ keywords: Ultralytics, Utils, utilitarian functions, colorstr, yaml_save, set_lo
 
 <br><br>
 
+## ::: ultralytics.utils.read_device_model
+
+<br><br>
+
 ## ::: ultralytics.utils.is_ubuntu
 
 <br><br>
@@ -83,6 +87,14 @@ keywords: Ultralytics, Utils, utilitarian functions, colorstr, yaml_save, set_lo
 
 <br><br>
 
+## ::: ultralytics.utils.is_raspberrypi
+
+<br><br>
+
+## ::: ultralytics.utils.is_jetson
+
+<br><br>
+
 ## ::: ultralytics.utils.is_online
 
 <br><br>
@@ -103,11 +115,11 @@ keywords: Ultralytics, Utils, utilitarian functions, colorstr, yaml_save, set_lo
 
 <br><br>
 
-## ::: ultralytics.utils.is_git_dir
+## ::: ultralytics.utils.get_git_dir
 
 <br><br>
 
-## ::: ultralytics.utils.get_git_dir
+## ::: ultralytics.utils.is_git_dir
 
 <br><br>
 

docs/en/reference/utils/benchmarks.md

@@ -11,6 +11,10 @@ keywords: Ultralytics, ProfileModels, benchmarks, model profiling, performance o
 
 <br><br>
 
+## ::: ultralytics.utils.benchmarks.RF100Benchmark
+
+<br><br>
+
 ## ::: ultralytics.utils.benchmarks.ProfileModels
 
 <br><br>

docs/en/tasks/obb.md

@@ -18,16 +18,28 @@ The output of an oriented object detector is a set of rotated bounding boxes tha
 
     YOLOv8 OBB models use the `-obb` suffix, i.e. `yolov8n-obb.pt` and are pretrained on [DOTAv1](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/DOTAv1.yaml).
 
-<p align="center">
-  <br>
-  <iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/Z7Z9pHF8wJc"
-    title="YouTube video player" frameborder="0"
-    allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
-    allowfullscreen>
-  </iframe>
-  <br>
-  <strong>Watch:</strong> Object Detection using Ultralytics YOLOv8 Oriented Bounding Boxes (YOLOv8-OBB)
-</p>
+<table>
+  <tr>
+    <td align="center">
+      <iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/Z7Z9pHF8wJc"
+        title="YouTube video player" frameborder="0"
+        allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
+        allowfullscreen>
+      </iframe>
+      <br>
+      <strong>Watch:</strong> Object Detection using Ultralytics YOLOv8 Oriented Bounding Boxes (YOLOv8-OBB)
+    </td>
+    <td align="center">
+      <iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/uZ7SymQfqKI"
+        title="YouTube video player" frameborder="0"
+        allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
+        allowfullscreen>
+      </iframe>
+      <br>
+      <strong>Watch:</strong> Object Detection with YOLOv8-OBB using Ultralytics HUB
+    </td>
+  </tr>
+</table>
 
 ## Visual Samples