Inspiration
Apple face ID gave us the idea that using face ID in colleges/universities to access doors and electronic environments will be a great alternative for physical and digital ID for students, so they don't need to carry their ID or mobile device ( I mean imagine your Phone died and you are stuck outside the door!)
What it does
So it captures student data by taking multiple pictures, and compare it with their ID photograph to recognize and authorize them inside the college premises.
How we built it
We used Programming languages - frontend - html, css, java script. backend - node.js. dbms- mongoDB. functions & libraries used - tensorflow, openCV, sklearn, mtcnn, ltsm
Challenges we ran into
The industry challenge that we took as our core idea is to let low quality cameras to still recongize the faces without much struggle, the model is trained to do that, the toughest part is to get accuracy here.
Accomplishments that we're proud of
Our accompolishment is achieving close to accuracy in low quality image processing.
What we learned
we learned that physical ID is painful
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