Modern attendance System leveraging modern cutting-edge technology of Deep Learning and Convolution Neural Network
This is a early version of backend of my project.
Deploy a colud based fully automated attendance system for any purpose e.g. School, College, MNC Office, Industrial Factory etc.
To replace traditional attendance system which has many flaws with a better automatted system. The existing flaws of traditional system:
- Takes alot of time in recording attendance of every student (specifically school/college)
- Proxy call among the student
- Punching Card passing - Sometime employee passes their punching card among colleague so that they could leave office early and later system record the exit time while their colleague leaves the office
- Biometric fingerprint machines have storage limit of 100/200/500/1000 records only so client end up buying multiple machines.
The folder sould be like following:
There are many features that can be extracted from the faces, in this solution I am calculating 128 features and save their encoded values and then compare these ecoding with the encodings of faces which exists in our database which in this case it is KNOWN_FACE folder. Find the best match with respect to some threshold (in this case I have used it as tollerance) we classify the face in the image belogs to that perticular person.
After classifying the image we log the name and time in a excel sheet and at the end of the day names that has not been recognised whole day been marked as absent.
