Facial recognition is a type of biometric technology that uses statistical measurements of people's features to digitally determine identity.
The system is developed for deploying an easy and a secure way of taking down attendance.
Why Facial recognition you may ask?
- Face recognition is time efficient.
- Face recognition can be used in many work environment.
- Fast and Accurate.
- Cheap and Easy Installation.
- Does not store personal data.
Face recognition devices create a 3D model of your face by mapping out distinct points. The system then stores a numerical code to represent this model. The numerical code cannot be used for anything other to check if it is you in front of the camera.
We use three libraries face_recognition,mtcnn and cv2 for Facial Recognition. Teacher can take attendance with just a single click, A closed portal is used for this. The teacher must first login to the online portal before he/she can take attendance. When the button is clicked the camera captures the photo which is then compared to the face encodings already stored in the database.
import face_recognition
image = face_recognition.load_image_file("your_file.jpg")
face_locations = face_recognition.face_locations(image)
Get the locations and outlines of each person's eyes, nose, mouth and chin. The face_detection command lets you find the location (pixel coordinatates) of any faces in an image.
from mtcnn.mtcnn import MTCNN
import cv2
img = cv2.imread("ivan.jpg")
detector = MTCNN()
It gives [x, y, width, height] under the key 'box'
face_encoding now contains a universal 'encoding' of the person's facial features that can be compared to any other picture of a face! Then we can compare the two face encodings are of the same person with compare_faces!