Face Detection with mask

Project Title

Project Area of Specialization

Artificial Intelligence

Project Summary

A face detection with mask dataset consists of with mask and without mask images, we are going to use OpenCV to do real-time face detection from a live stream via our webcam and detect person that he use mask or not and also detect person with the help of eyes that it belong to record or not. We will use the dataset to build a COVID-19 “face detection with mask” with computer vision using.
1.Python
2.OpenCV
3.Tensor Flow
4.Keras
The main purpose of this project is to reduce the transformation of covid-19 .

Project Objectives

COVID19 (known as corona virus) is the latest epidemic virus that hit the human health in
2020. In 2020, the rapid spreading of COVID-19 has forced the World Health Organization to
declare COVID- 19 as a global pandemic. More than five million cases were infected by
COVID-19 in less than 6 months across 188 countries. The virus spreads through close contact
and in crowded and overcrowded areas.
Our goal is to identify whether the person on image/video stream is wearing a face mask or not
also identify using eye detection whether that person belongs to saved record or not with the
help of computer vision and deep learning.
A face mask detection dataset consists of with mask and without mask images, we are going to
use OpenCV to do real-time face detection from a live stream via our webcam. We will use the
dataset to build a COVID-19 “face detection with mask” with computer vision using Python,
OpenCV, and Tensor Flow and Keras.
The proposed model can be integrated with surveillance cameras to impede the COVID-19
transmission by allowing the detection of people who are wearing masks not wearing face
masks. The model is integration between deep learning and classical machine learning
techniques with opencv, tensor flow and keras.

Project Implementation Method

The corona virus COVID-19 pandemic is causing a global health crisis so the effective protection
methods is wearing a face mask in public areas according to the World Health Organization (WHO).
The COVID-19 pandemic forced governments across the world to impose lock downs to prevent virus
transmissions. Reports indicate that wearing facemasks at gathering places clearly reduces the risk of
virus transmission. An efficient and economic approach of using AI to create a safe environment. A
system using deep learning for “face detection with mask” will be presented.
COVID19 (known as corona virus) is the latest epidemic virus that hit the human health in 2020. In
2020, the rapid spreading of COVID-19 has forced the World Health Organization to declare COVID-
19 as a global pandemic. More than five million cases were infected by COVID-19 in less than 6
months across 188 countries. The virus spreads through close contact and in crowded and
overcrowded areas.
Our goal is to identify whether the person on image/video stream is wearing a face mask or not also
identify using eye detection whether that person belongs to saved record or not with the help of
computer vision and deep learning.
A face mask detection dataset consists of with mask and without mask images, we are going to use
OpenCV to do real-time face detection from a live stream via our webcam. We will use the dataset to
build a COVID-19 “face detection with mask” with computer vision using Python, OpenCV, and
Tensor Flow and Keras.
The proposed model can be integrated with surveillance cameras to impede the COVID-19
transmission by allowing the detection of people who are wearing masks not wearing face masks. The
model is integration between deep learning and classical machine learning techniques with opencv,
tensor flow and keras.

Benefits of the Project

The world is fighting with Covid19 pandemic. There are so many essential equipment's needed to fight against Corona virus.
One of such most essential is Face Mask.
Firstly face mask was not mandatory for everyone but as the day progresses scientist and Doctors have recommended everyone to wear face mask. Now To detect whether a person is wearing Face Mask or not, we will use Face Mask Detection Technique.
Face Detection with Mask Platform utilizes Artificial Network to perceive if a person does/doesn’t wear a mask and also with the help of eyes detect the person belong to record or not.
The application can be associated with any current or new IP cameras to identify individuals with/without a mask .

Technical Details of Final Deliverable

Our goal is to identify whether the person on image/video stream is wearing a face mask or not.
Identify using eye detection whether that person belongs to saved record or not with the help of computer vision and deep learning.
A face mask detection dataset consists of with mask and without mask images, we are going to use OpenCV to do real-time face detection from a live stream via our webcam. We will use the dataset to build a COVID-19 “face detection with mask” with computer vision using Python.

The proposed model can be integrated with surveillance cameras to impede the COVID-19 transmission by allowing the detection of people who are wearing masks not wearing face masks. The model is integration between deep learning and classical machine learning techniques