readme updated

README.md

@@ -1,6 +1,6 @@
 # yolov8_ros
 
-ROS 2 wrap for [Ultralytics YOLOv8](https://github.com/ultralytics/ultralytics) to perform object detection and tracking, instance segmentation and human pose estamation. There are also 3D versions of object detection and human pose estimation based on Point Cloud.
+ROS 2 wrap for [Ultralytics YOLOv8](https://github.com/ultralytics/ultralytics) to perform object detection and tracking, instance segmentation and human pose estimation. There are also 3D versions of object detection and human pose estimation based on depth images.
 
 ## Installation
 
@@ -15,10 +15,41 @@ $ colcon build
 
 ## Usage
 
+### YOLOv8
+
 ```shell
 $ ros2 launch yolov8_bringup yolov8.launch.py
 ```
 
+#### Parameters
+
+- model: YOLOv8 model (default: yolov8m.pt)
+- 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)
+
+### YOLOv8 3D
+
+```shell
+$ ros2 launch yolov8_bringup yolov8_3d.launch.py
+```
+
+#### Parameters
+
+- model: YOLOv8 model (default: yolov8m.pt)
+- 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)
+- input_depth_topic: camera topic of depth images (default: /camera/depth/image_raw)
+- input_depth_info_topic: camera topic for info data (default: /camera/depth/camera_info)
+- depth_image_units_divisor: divisor to convert the depth image into metres (default: 1000)
+- target_frame: frame to transform the 3D boxes (default: base_link)
+- maximum_detection_threshold: maximum detection threshold in the z axis (default: 0.3)
+
 ## Demos
 
 ## Object Detection
@@ -53,7 +84,7 @@ $ ros2 launch yolov8_bringup yolov8.launch.py model:=yolov8m-pose.pt
 
 ## 3D Object Detection
 
-The 3D bounding boxes are calculated filtering the Point Cloud data from an RGB-D camera using the 2D bounding box. Only objects with a 3D bounding box are visualized in the 2D image.
+The 3D bounding boxes are calculated filtering the depth image data from an RGB-D camera using the 2D bounding box. Only objects with a 3D bounding box are visualized in the 2D image.
 
 ```shell
 $ ros2 launch yolov8_bringup yolov8_3d.launch.py
@@ -63,7 +94,7 @@ $ ros2 launch yolov8_bringup yolov8_3d.launch.py
 
 ## 3D Object Detection (Using Instance Segmentation Masks)
 
-In this, the Point Cloud data is filtered using the max and min values obtained from the instance masks. Only objects with a 3D bounding box are visualized in the 2D image.
+In this, the depth image data is filtered using the max and min values obtained from the instance masks. Only objects with a 3D bounding box are visualized in the 2D image.
 
 ```shell
 $ ros2 launch yolov8_bringup yolov8_3d.launch.py model:=yolov8m-seg.pt
@@ -73,7 +104,7 @@ $ ros2 launch yolov8_bringup yolov8_3d.launch.py model:=yolov8m-seg.pt
 
 ## 3D Human Pose
 
-Each keypoint is projected in the Point Cloud and visualized using purple spheres. Only objects with a 3D bounding box are visualized in the 2D image.
+Each keypoint is projected in the depth image and visualized using purple spheres. Only objects with a 3D bounding box are visualized in the 2D image.
 
 ```shell
 $ ros2 launch yolov8_bringup yolov8_3d.launch.py model:=yolov8m-pose.pt

yolov8_bringup/launch/yolov8_3d.launch.py

@@ -64,13 +64,13 @@ def generate_launch_description():
     input_depth_topic = LaunchConfiguration("input_depth_topic")
     input_depth_topic_cmd = DeclareLaunchArgument(
         "input_depth_topic",
-        default_value="/camera/aligned_depth_to_color/image_raw",
+        default_value="/camera/depth/image_raw",
         description="Name of the input depth topic")
 
     input_depth_info_topic = LaunchConfiguration("input_depth_info_topic")
     input_depth_info_topic_cmd = DeclareLaunchArgument(
         "input_depth_info_topic",
-        default_value="/camera/aligned_depth_to_color/camera_info",
+        default_value="/camera/depth/camera_info",
         description="Name of the input depth info topic")
 
     depth_image_units_divisor = LaunchConfiguration(