A. Eye - Watch out for vehicles

This is a getting started guide for beginners to Intel Compute Stick and OpenVINO. I will be using pre-trained model from model zoo. I am going to build a vehicle alert system should. When a vehicle is approaching, Raspberry Pi will speak out the alert. This could be a very good use-case for visually impaired persons or for bikers who often don't see what's coming from behind.

Things you need

Hardwares

• Raspberry Pi 3 ( or 4 ) with 16GB SD card
• Intel Neural Compute Strick 2
• 3.5mm Speaker
• USB Power bank to power Raspberry Pi
• USB Keyboard and Mouse during setup
• HDMI Monitor during setup

Softwares

BalenaEtcher or Pi Imager to burn SD card with Raspbian OS.

OpenVINO Toolkit

Let's get started

Prepare SD Card

If you are familiar with Raspberry Pi, then you know first thing is to prepare your SD card with Raspbian OS. You can either use Balena Etcher (download from https://www.balena.io/etcher) or use Pi Imager. I would prefer Pi Imager as it's one less step to follow.

Choose the operating system ( Raspberry pi 3 32 bit ) and choose your SD card to flush. This may take few minutes. Once finished, unplug the SD card from your computer and insert into Raspberry Pi.

Configure Raspberry Pi 3

Connect USB keyboard, mouse and a HDMI monitor to raspberry pi. Connect the power which will turn boot up your Pi desktop. Follow the setup wizard and configure WiFi for your Pi. After reboot, open Raspberry Pi Configuration wizard and enable Camera and SSH. Optionally you can enable VNC viewer if you want to remote access your desktop.

Install OpenVINO Toolkit on Pi

You may follow the official documentation here or follow steps below.

Open Terminal window on your Pi and go to Downloads folder

cd ~/Downloads

and download OpenVINO sdk.

wget --no-check-certificate https://download.01.org/opencv/2020/openvinotoolkit/2020.4/l_openvino_toolkit_runtime_raspbian_p_2020.4.287.tgz

You should see the zip file as below

Then create a folder where OpenVINO will be installed

sudo mkdir -p /opt/intel/openvino

sudo tar -xf  l_openvino_toolkit_runtime_raspbian_p_<version>.tgz --strip 1 -C /opt/intel/openvino

sudo apt install cmake

echo "source /opt/intel/openvino/bin/setupvars.sh" >> ~/.bashrc

Close the terminal and open a new one. You should see below message which means your environment variables are setup

Now, it's time to add some USB rule for your NCS 2

sudo usermod -a -G users "$(whoami)"

sh /opt/intel/openvino/install_dependencies/install_NCS_udev_rules.sh

You are almost done ! Plug your NCS 2 stick to one of the USB port of your Pi and move to build process.

cd /home/pi

mkdir OpenVINO && OpenVINO

mkdir build && cd build

cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_CXX_FLAGS="-march=armv7-a" /opt/intel/openvino/deployment_tools/inference_engine/samples/c

make -j2 object_detection_sample_ssd

Now go one level up to OpenVINO folder

cd ..

And download my github repo which contains the python code and pre-trained vehicle detection models from model zoo

git clone https://github.com/just4give/openvio-vehicle-detection.git
cd openvio-vehicle-detection

Then install python dependencies via pip3

pip3 install -r requirements.txt

You all set to run your vehicle detection program. Before you do, there are few other things.

Install Camera Module

Connect your Pi Camera module to Pi and test it to make sure it's working by issuing below command from terminal

raspistill -v -o test.jpg

If all is well, you should see the image preview. If not, please read this document for full configuration.

Configure Audio

Follow this official document to configure audio output for you Pi. Once done run below command from terminal

aplay /home/pi/OpenVINO/openvio-vehicle-detection/alert.wav

All right, if you had success so far, you are ready to run your program for the first time :)

cd /home/pi/OpenVINO/openvio-vehicle-detection

and issue below command

python3 main.py -d MYRIAD -m vehicle-detection-adas-0002.xml -pt 0.9

My threshold is very high and the model was producing some falls vehicles. You may adjust the value based on your ambience light etc.

Congratulations !!! You have setup OpenVINO and ran your first program successfully. There are plenty of interesting and useful pre-trained models to explore -> https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/intel

What's next ? Your imagination has no limit. Learn to train your own models and explore the computer vision world.

This project is also published on PCBWay