Face Mask Detection Deep Learning model using YOLOv7

[saleena-18]

Problem: YOLOv7 is 509% faster and Amidst the COVID-19 outbreak in India, with a surge in confirmed cases, the government continues to appeal for universal mask usage which aligns with the World Health Organization (WHO) directives to mitigate the virus’s spread.

Solution: A Deep Learning model for Face Mask Detection that would serve to identify whether the individuals
in an image or video frame are wearing a mask or not, or wearing it incorrectly.

Approach: We would be configuring and training a YOLOv7-based Deep Learning model using Python,
evaluating its performance metrics with accuracy curve, precision recall curve, f1-score, etc that would show the accuracy of the model. Then provide video and image input that would detect 3 instances - people wearing masks, not wearing, & people wearing incorrectly.

Importance: By integrating these models into security and surveillance systems or monitoring
applications, the model will be able to swiftly detect and flag instances of non-compliance
with mask-wearing guidelines. This enables proactive measures to be taken promptly,
reinforcing safety protocols and ensuring adherence to established regulations to safeguard
public health effectively.

[saleena-18]

I am a GSSOC '24 Contributor
I agree to follow the project's Code of Conduct
Can you please label this issue for 'gssoc' and the 'level.'
I'd love to work on this issue.
This would be practically helpful for the Government too during traffic surveillance in case of non-adherence to mask-wearing guidelines.
Github : https://github.com/saleena-18

[aryanchauh]

I'm GSSoC24 contributors can I please assign me this problem? @akshitagupta15june