“A Deep Learning Based Model For Detecting Mask Over Face In Public Places To Curtail Community Spread Of Covid-19 Is Presented”
My name is YASH SHRIVASTAVA. At present I am pursuing my degree in Bachelor of Technology in Electronics and Communication Engineering from Lakshmi Narain College of Technology Excellence, Bhopal. My current CGPA is 9.3. I have done my schooling Panini Jnanpeeth School (M.P.). I have excellent problem-solving skills and ability to perform well in a team. Passionate of coding and contribute for the best with my skills for my service. Work to Achieve the Highest Goal. See Profile
My name is PUPUL BHATNAGAR. At present I am pursuing my degree in Bachelor of Technology in Electronics and Communication from Lakshmi Narain College of Technology Excellence, Bhopal. My current CGPA is 8.42. I have done my schooling from Carmel Convent Senior Secondary School B.H.E.L. Bhopal (M.P.). I am able to handle multiple tasks on a daily basis and eager to learn new skills. Passionate to learn new skills and create by contribution towards the service. See Profile
My name is SIMI KUSHWAHA. At present I am pursuing my degree in Bachelor of Technology in Electronics and Communication Engineering from Lakshmi Narain College of Technology Excellence, Bhopal. My current CGPA is 8.55. I have done my schooling from St. George Sr. Sec School Bhopal (M.P.). I’ve an optimistic mindset and do not shy away from hard work and dense deadlines and have lunacy towards the goals. See Profile
Our face mask detector didn't use any morphed masked images dataset. The model is accurate, and since we used the MobileNetV2 architecture, it’s also computationally efficient and thus making it easier to deploy the model to embedded systems (Raspberry Pi, Google Coral, etc.).
This system can therefore be used in real-time applications which require face-mask detection for safety purposes due to the outbreak of Covid-19. This project can be integrated with embedded systems for application in airports, railway stations, offices, schools, and public places to ensure that public safety guidelines are followed.
The dataset used can be downloaded here - Click to Download
This dataset consists of 3339 images belonging to two classes:
- with_mask: 1755 images
- without_mask: 1584 images
All the dependencies and required libraries are included in the file requirements.txt See here
- Clone the repo
https://github.com/yashshrivastavaa/Mask-Detection-Security.git- Change your directory to the cloned repo
$ cd Face-Mask-Detection- Create a Python virtual environment named 'test' and activate it
$ virtualenv test$ source test/bin/activate- Now, run the following command in your Terminal/Command Prompt to install the libraries required
$ pip3 install -r requirements.txt- Open terminal. Go into the cloned project directory and type the following command:
$ python3 train_mask_detector.py --dataset dataset- To detect face masks in an image type the following command:
$ python3 detect_mask_image.py --image images/pic1.jpeg- To detect face masks in real-time video streams type the following command:
$ python3 detect_mask_video.py Click Here for feedback & Suggestion