yolov9 doc

README.md

@@ -15,25 +15,35 @@ $ colcon build
 
 ## Usage
 
-### YOLOv8
+### YOLOv8 / YOLOv9
 
 ```shell
 $ ros2 launch yolov8_bringup yolov8.launch.py
 ```
 
+```shell
+$ ros2 launch yolov8_bringup yolov9.launch.py
+```
+
 <p align="center">
   <img src="./docs/rqt_graph_yolov8.png" width="100%" />
 </p>
 
+#### Topics
+
+- **/yolo/detections**: Objects detected by YOLO using the RGB images. Each object contains a bounding boxes and a class name. It may also include a mak or a list of keypoints.
+- **/yolo/tracking**: Objects detected and tracked from YOLO results. Each object is assigned a tracking ID.
+- **/yolo/debug_image**: Debug images showing the detected and tracked objects. They can be visualized with rviz2.
+
 #### Parameters
 
 - **model**: YOLOv8 model (default: yolov8m.pt)
-- **tracker**: tracker file (default: bytetrack.yaml)
+- **tracker**: Tracker file (default: bytetrack.yaml)
 - **device**: GPU/CUDA (default: cuda:0)
-- **enable**: wether to start YOLOv8 enabled (default: True)
-- **threshold**: detection threshold (default: 0.5)
-- **input_image_topic**: camera topic of RGB images (default: /camera/rgb/image_raw)
-- **image_reliability**: reliability for the image topic: 0=system default, 1=Reliable, 2=Best Effort (default: 2)
+- **enable**: Wether to start YOLOv8 enabled (default: True)
+- **threshold**: Detection threshold (default: 0.5)
+- **input_image_topic**: Camera topic of RGB images (default: /camera/rgb/image_raw)
+- **image_reliability**: Reliability for the image topic: 0=system default, 1=Reliable, 2=Best Effort (default: 2)
 
 ### YOLOv8 3D
 
@@ -45,6 +55,13 @@ $ ros2 launch yolov8_bringup yolov8_3d.launch.py
   <img src="./docs/rqt_graph_yolov8_3d.png" width="100%" />
 </p>
 
+#### Topics
+
+- **/yolo/detections**: Objects detected by YOLO using the RGB images. Each object contains a bounding boxes and a class name. It may also include a mak or a list of keypoints.
+- **/yolo/tracking**: Objects detected and tracked from YOLO results. Each object is assigned a tracking ID.
+- **/yolo/detections_3d**: 3D objects detected. YOLO results are used to crop the depth images to create the 3D bounding boxes and 3D keypoints.
+- **/yolo/debug_image**: Debug images showing the detected and tracked objects. They can be visualized with rviz2.
+
 #### Parameters
 
 - **model**: YOLOv8 model (default: yolov8m.pt)