sarala-2210 / face-mask-detection

Wearing a protective face mask has become a new normal. Therefore, face mask detection has become a crucial task to help global society. This project presents a simplified approach to achieve this purpose using some basic Machine Learning packages like TensorFlow, Keras, OpenCV and MobileNet.

Face-Mask-Detection

COVID-19 pandemic has rapidly affected our day-to-day life disrupting world trade and movements. Wearing a protective face mask has become a new normal. Therefore, face mask detection has become a crucial task to help global society. This project presents a simplified approach to achieve this purpose using some basic Machine Learning packages like TensorFlow, Keras, OpenCV and MobileNet. The proposed method detects the face and then identifies if it has a mask on it or not. With further improvements these types of models could be integrated with CCTV cameras to detect and identify people without masks. 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.

Flow of Project:

SOFTWARE REQUIREMENTS:

Operating System : Windows 7 / 8 / 10

Packages :

• Tensorflow >=1.15.2
• Keras == 2.3.1
• Imutils == 0.5.3
• Numpy == 1.18.2
• Opencv-python == 4.2.0.*
• Matplotlib == 3.2.1
• Scikit-learn >= 0.20
• Scipy == 1.4.1
• Winsound

Programming Language: Python

Input: Dataset.zip

HARDWARE REQUIREMENTS:

• CPU: Intel i3 or greater / Microprocessors
• Ram: 4-8 GB
• Camera: In-built / USB Webcam
• Hard disk / micro SD card: >=16GB
• Monitor