GitHub - zyncoder/ATTENDSCAN: Facial recognition is a vast domain, so before going in depth, let’s understand this technology in a nutshell. Firstly, the picture of a person is captured from a photo or video, when appeared alone or in a crowd. The facial recognition software reads the geometry of the face and extract key features like distance between the eyes, distance from forehead to chin, color of hair etc. The software identifies key features, sets facial landmarks and generates facial signatures from the image captured. This facial signature being a mathematical formula is used for comparison with the database of known faces. The difference between the obtained facial signature and database images are calculated through different mathematical techniques and the nearest is chosen as an optimum result. Finally, the determination is made, and the output indicates whether the image exists in the database or not.

Name	Name	Last commit message	Last commit date
Latest commit History 3 Commits
Attendance	Attendance
ImagesUnknown	ImagesUnknown
StudentDetails	StudentDetails
TrainingImageLabel	TrainingImageLabel
.DS_Store	.DS_Store
README.md	README.md
attendance.py	attendance.py
haarcascade_frontalface_default.xml	haarcascade_frontalface_default.xml

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haarcascade_frontalface_default.xml

install opencv and tkinter in anaconda and run attendance.py and enjoy. just make a folder named TrainingImageLabel.

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Facial recognition is a vast domain, so before going in depth, let’s understand this technology in a nutshell. Firstly, the picture of a person is captured from a photo or video, when appeared alone or in a crowd. The facial recognition software reads the geometry of the face and extract key features like distance between the eyes, distance from…

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