Static Object Detection

The RZ/V Static Object Detection package provides the following features:

Demonstrates the usage of the AI library (DRP-AI) wrapped in a ROS 2 node.
Supports the YOLOX Pascal VOC model (20 classes) for static object detection.
Supports multi-threaded processing.
Supports visualization through Foxglove Studio.

Quick hardware setup instructions

Complete the Prerequisites for Running Sample Applications.

Quick software setup instructions

Note

All subsequent operations must be executed inside the cross-compilation Docker container, which was set up in the common setup step.

Clone the required source from GitHub by using the vcs tool inside the Docker container.

Get the ros2_demo_workspace repository first:
```
cd ~/ros2_ws
git clone https://github.com/renesas-rdk/ros2_demo_workspace.git
```
Import the repositories by using the vcs command:
```
vcs import < ./ros2_demo_workspace/vcs_manifests/static_object_detection.target.lock.repos
```
It will clone all required repositories to the ./src folder.
Cross-compile the ROS 2 workspace and deploy it to the RZ/V2H RDK board.

Update the APT repository list in the target sysroot.
```
rzv2h-chroot apt update
```
Install the dependencies to the target board first:
```
sysroot-rosdep-install
```
It will take time if you run this command for the first time.

Cross-build the application:
```
cross-colcon-build
```
Deploy the binaries to the target board:
```
scp -r install ubuntu@board_ip:~/ros2_ws/
```
Note

Replace board_ip with the actual IP address of your board. Ensure that the ros2_ws directory exists at /home/ubuntu on the target board before running the scp command.

Start the application

Install the required dependencies on the RZ/V2H RDK board.
```
cd /home/ubuntu/ros2_ws
source /opt/ros/jazzy/setup.bash
rosdep install --from-paths ./install/*/share -y -r --ignore-src
```
The /home/ubuntu/ros2_ws directory is the location where you copied the cross-compiled workspace on the board.

Launch the Object Detection application.

Load the workspace environment:

source /opt/ros/jazzy/setup.bash
source ./install/setup.bash

For static object detection, use:

# Pascal VOC object detection on static image
ros2 launch rzv_object_detection static_object_detection_yolox.launch.py

# Hand detection on static image using YOLOX
ros2 launch rzv_object_detection static_hand_detection_yolox.launch.py

# Hand detection on static image using Gold YOLOX
ros2 launch rzv_object_detection static_hand_detection_gold_yolox.launch.py

For visualization using Foxglove Studio, refer to the Foxglove Visualization section for setup instructions.

The input layout file for Foxglove Studio is located at rzv_object_detection/config/foxglove/objects_detection.json inside the ROS 2 workspace.

For more details about the Static Object Detection application, refer to the README.md in the rzv_object_detection package.

v1.0.0 (2026-03-31): Initial release of the Static Object Detection sample application.