MaraBytes / Face-Mask-Detection-Using-with-voice-output

This is a face mask detection system that checks when someone is wearing a mask and if not the system will produce a voice output that informs the person to wear His/Her mask

Face Mask detection with voice output

#Installation

🚀  Installation

1. Clone the repo

$ git clone https://github.com/Oyopiz/Face-Mask-Detection-Using-with-voice-output

2. Change your directory to the cloned repo

$ cd Face-Mask-Detection

3. Create a Python virtual environment named 'test' and activate it

$ virtualenv test

$ source test/bin/activate

4. Now, run the following command in your Terminal/Command Prompt to install the libraries required

$ pip3 install -r requirements.txt

💡 Working

1. Open terminal. Go into the cloned project directory and type the following command:

$ python3 train_mask_detector.py --dataset dataset

2. To detect face masks in an image type the following command:

$ python3 detect_mask_image.py --image images/pic1.jpeg

3. To detect face masks in real-time video streams type the following command:

$ python3 detect_mask_video.py 

🔑 Results

Our model gave 98% accuracy for Face Mask Detection after training via tensorflow-gpu==2.5.0

We got the following accuracy/loss training curve plot

Streamlit app

Face Mask Detector webapp using Tensorflow & Streamlit

command

$ streamlit run app.py 


## Internet of Things Device Setup

### Expected Hardware
* [Raspberry Pi 4 4GB with a case](https://www.canakit.com/raspberry-pi-4-4gb.html)
* [5MP OV5647 PiCamera from Arducam](https://www.arducam.com/docs/cameras-for-raspberry-pi/native-raspberry-pi-cameras/5mp-ov5647-cameras/)

### Getting Started
* Setup the Raspberry Pi case and Operating System by following the Getting Started section on page 3 at `documentation/CanaKit-Raspberry-Pi-Quick-Start-Guide-4.0.pdf` or https://www.canakit.com/Media/CanaKit-Raspberry-Pi-Quick-Start-Guide-4.0.pdf
  * With NOOBS, use the recommended operating system
* Setup the PiCamera
  * Assemble the PiCamera case from Arducam using `documentation/Arducam-Case-Setup.pdf` or https://www.arducam.com/docs/cameras-for-raspberry-pi/native-raspberry-pi-cameras/5mp-ov5647-cameras/
  * [Attach your PiCamera module to the Raspberry Pi and enable the camera](https://projects.raspberrypi.org/en/projects/getting-started-with-picamera/2)

### Raspberry Pi App Installation & Execution

> Run these commands after cloning the project

| Commands                                                                                                                     | Time to completion |
|------------------------------------------------------------------------------------------------------------------------------|--------------------|
| sudo apt install -y libatlas-base-dev liblapacke-dev gfortran                                                                | 1min               |
| sudo apt install -y libhdf5-dev libhdf5-103                                                                                  | 1min               |
| pip3 install -r requirements.txt                                                                                             | 1-3 mins           |
| wget "https://raw.githubusercontent.com/PINTO0309/Tensorflow-bin/master/tensorflow-2.4.0-cp37-none-linux_armv7l_download.sh" | less than 10 secs  |
| ./tensorflow-2.4.0-cp37-none-linux_armv7l_download.sh                                                                        | less than 10 secs  |
| pip3 install tensorflow-2.4.0-cp37-none-linux_armv7l.whl                                                                     | 1-3 mins           |

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