In this project, we are perform Facial recognition with high accuracy. and using machine learning creates a Attendance project that will use webcam to detect faces and record the attendance live in an excel sheet.
We seek to provide a valuable attendance service for both teachers and students. Reduce manual process errors by provide automated and a reliable attendance system uses face recognition technology.
Find face in images.
Analyze facial features.
Compare against known faces.
Make prediction.
Build With -
Python 3.9.1 Module Used - ○ Numpy - could be a library for Python, adding support for multi-dimensional arrays and matrices, in conjunction with an enormous assortment of high-level mathematical functions to operate on these arrays.
○ Datetime - It’s a combination of date and time along with the attributes year, month, day, hour, minute, second, microsecond, and info.
○ Face_Recognition - Recognize and manipulate faces from Python or the command line with the world’s simplest face recognition library.
○ OpenCV(came with both cv and cv2) - a library of programming functions primarily geared toward real-time computer vision. Note : in this project i'm using cv2
○ OS - The OS module in Python provides functions for interacting with the operating system. OS comes under Python's standard utility modules. All The Module are Latest Version.
Later, OpenCV came with both cv and cv2 . Now, there in the latest releases, there is only the cv2 module, and cv is a subclass inside cv2 . You need to call import cv2.cv as cv to access it.)
First download or clone the project.
Import the project to your favourit IDE.
Create an python enviroment.
Install all the packages.
Run the project using the command line or your IDE Run Button.
python -m venv env
.\env\Scripts\activate
Install below libraries:
pip install cmake
pip install dlib
pip install opencv/cv2
pip install numpy
pip install face_recognition
py AttendenceProject.py