A ROS package to wrap openvino inference engine and get it working with Myriad and Intel CPU/GPUs
The main topic is to accelerate robotics developing using ROS with OpenVINO.
This package is designed on async api of Intel OpenVINO and allows an easy setup for object detection.
Entire package is born to support Myriad X, so it works perfectly with:
object detection node allows you to use a standard image topic and obtain a new topic with live result image. If you enable depth analysis you can add depth image topic to obtain 3d boxes, visible as markers in rviz.
You need some steps to get ros_openvino working.
If you are working on a Myriad based device (NCS, NCS2, AI Core, AI Core X) follow this guide because is faster.
If you have already this kind of stuffs, please take care to modify steps for your case.
catkin_ws
as your ROS workspace:cd ~/catkin_ws/src
git clone http://github.com/gbr1/ros_openvino.git
cd ~/catkin_ws
catkin_make
catkin_make install
all installation steps and a case of study configuration are described in Setup environment wiki page.
Remember that OpenVINO enviroment variables, ROS enviroment variables and ROS workspace need to be sourced in bashrc
.
There are some demo launch files.
Webcam and GPU
you need to install usb_cam node:
sudo apt-get install ros-kinetic-usb-cam
then type:
roslaunch ros_openvino gpu_demo_webcam.launch
Webcam and Myriad
you need to install usb_cam node:
sudo apt-get install ros-kinetic-usb-cam
then type:
roslaunch ros_openvino myriad_demo_webcam.launch
Realsense D435/D435i/D415 and Myriad
you need to install realsense package, follow here step-by-step according your environment setup.
After that, just type:
roslaunch ros_openvino myriad_demo_realsense.launch
Tests are done on UP2 with Intel Atom, 4GB of RAM and 64GB eMMC and AI Core X.
Results with a complete analysis with 4-5 object detected is about 30fps for rgb output and 16-18Hz for spatial calculation.
On GPU analysis drop down the frame rate.
If OpenVINO works on Ubuntu 18.04 this package should be compatible with ROS Melodic Morenia.
This package is distribuited under Affero GPLv3.
Copyright (c) 2019 Giovanni di Dio Bruno
Models:
are created using OpenVINO model downloader and converter.
Original mobilenet-ssd model are under Intel OpenVINO licenses.