A.R.M.D - a Robotics Mask Detector

Introduction: A.R.M.D - a Robotics Mask Detector

About: I am a robotics engineer and a part time programmer

A.R.M.D is a AI and Ml based project. It uses a camera to detect faces and further face masks. During this Corona Virus (Covid-19) worldwide pandemic wearing mask could only reduce the chance of getting affected. This robot could find mask and it also has a automated voice feedback system too. Now let's see how to make it !!


Raspberry pi 4B (4gb recomended )- amazon

Pi camera V2 - amazon

32 GB Class 10 A1 MicroSD card (With installed Raspberrypi Os) - amazon

Raspberry pi cooler fan and heat sink - amazon

Speaker - amazon

Step 1: Getting Things Ready

First for this project needs access to raspberry pi desktop. So you need a monitor mouse and a keyboard or you can use SSH or VNC.

Boot your Raspberry pi and clone this repository into your pi

git clone https://github.com/sanjus-robotic-studio/ARMD.git

Now install packages required for virtual env:

sudo pip3 install virtualenv
sudo pip3 install virtualenvwrapper

We need to edit the .profile file to set 1) the variable WORKON_HOME and VIRTUALENVWRAPPER_PYTHON to the path of the directory .virtualenvs which contains our virtual environments and 2) make known the location of the shell file, virualenvwrapper.sh. In a terminal window type:

sudo nano ~/.profile

Add these lines to the bottom of the file

export WORKON_HOME=$HOME/.virtualenvs 
source /usr/local/bin/virtualenvwrapper.sh

Now save and exit nano and type

source ~/.profile

Now navigate to your cloned local directory and create a virtual env "requir"

mkvirtualenv requir -p /usr/bin/YOUR_PYTHON_VERSION

And activate it

workon requir

Now install the files required for the project

pip3 install -r requirements.txt

This command will automatically install the required files

Now for the Text-To-Speech (TTS). We are going to use picoTTS, to install it follow this guide picoTTS

After installing picotts continue to the connections.

Step 2: Connection

Turn off you pi's power supply and connect the camera to the pi.

Connection to the leds:

Red Led

Positive - GPIO 17

Negative - Gnd

Green Led

Positive - GPIO 27

Negative - Gnd

Connect the aux cable to 3.5 mm audio jack and another end to the speaker .

Step 3: Testing

I have already trained the model and it is also included in the code. So if you want to add more images to the data set you can also add more images to the dataset folder and run the train-mask-detector.py file. Open a terminal and execute the following command

workon requir 
python3 train_mask_detector.py datase --dataset

Now lets test it. Open the ARMD.py file in any python idle and press F5.

The code will begin. Enjoy testing it!!

Step 4: Working

This is a full working video of A.R.M.D.

For more exciting projects follow my youtube channel and my blog

Youtube channel : https://bit.ly/33cGJSM

Blog :

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