(1)Set up your development environment by following the instructions here
=> Already Done
(2)Clone isaac_ros_common and this repository under ${ISAAC_ROS_WS}/src.
cd ${ISAAC_ROS_WS}/src
git clone https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_common.git
git clone https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_object_detection.git
(3)Pull down a ROS Bag of sample data
cd ${ISAAC_ROS_WS}/src/isaac_ros_object_detection/isaac_ros_detectnet && \
git lfs pull -X "" -I "resources/rosbags"
(4)Launch the Docker container using the run_dev.sh script:
cd ${ISAAC_ROS_WS}/src/isaac_ros_common && \
./scripts/run_dev.sh
(5)Install this package’s dependencies
sudo apt-get install -y ros-humble-isaac-ros-detectnet ros-humble-isaac-ros-triton ros-humble-isaac-ros-dnn-image-encoder
(6)Run the quickstart setup script which will download the PeopleNet Model from NVIDIA GPU Cloud(NGC)
cd /workspaces/isaac_ros-dev/src/isaac_ros_object_detection/isaac_ros_detectnet && \
./scripts/setup_model.sh --height 632 --width 1200 --config-file resources/quickstart_config.pbtxt
(7)
cd /workspaces/isaac_ros-dev && \
ros2 launch isaac_ros_detectnet isaac_ros_detectnet_quickstart.launch.py
Reference:
https://nvidia-isaac-ros.github.io/repositories_and_packages/isaac_ros_object_detection/index.html#quickstarts