Real-time Face Mask Detection System using Transfer Learning.
As the Covid-19 virus outbreak continues, we as innovators take upon ourselves to come up with pioneering digital solutions. One of such solutions is a face mask detection system to identify whether or not a person is wearing a face mask. Covering our faces with a mask has become a new normal amidst the pandemic, as face masks are the only effective measure to prevent the virus outbreak, until the vaccine is developed. Many developed and underdeveloped nations worldwide have made it compulsory for people to wear masks if leaving home or visiting public places. Other precautionary measures are also advocated by the government to maintain safety and hygiene, apart from shielding faces.
Analysing the current scenario, wherein countries are lifting the lockdown and are trying to bring economic and commercial activities back on track, it is the at most priority of the government and the private organizations to make sure that everyone working or visiting a public or private place is wearing masks throughout the day, hence digital facemask detection system might be rather useful . The face mask detection platform can quickly identify the person with a mask, using cameras and analytics. Depending upon the requirements, the system can identify people without masks by generating an alarm or a notification to notify security or officials.
This covid-19 face mask detector works in two ways:
- Detecting face masks on images.
- Detecting face masks on live video stream.
I have made a combined dataset of images collected from various sources. The link for final dataset : https://drive.google.com/drive/folders/1VcxKvClxRhmE_Prntm5gFJ3ddRr-ullH?usp=sharing
This dataset consists of 3921 images out of which 2004 images are in the “with masks” folder, while 1917 images are in the “without masks” folder.