This project involves development of web application which takes attendance as well as maintains attendance records.For this project I have used Python as coding language,Django as a framework and OpenCV as a computer vision library (face detection and recognition), Dlib, Open-Source Face Recognition Library, SQLITE as Database.It exhibits the attendance in form of graphical and tabular format in accordance to the requirement of admin/employee.The graphs help in visualization of data such as number of hours a particular employee has worked ,number of employees present at that day .This project can be implemented for places where attendance tracking is necessary.
- Registration
- Login / Logout
- Manage User Profile
- Update user profile
- View Attendance Report
- View Attendance by Date
- View Attendance by Employee
- Manage Attendance
- Mark IN your attendance 10.Mark OUT your attendance 11.Add photos 12.Add new employee 13.Train the system 14.View Attendance record by date 15.View no. of employee present today 16.View Total number of employees
ADMIN DASHBOARD 🧑💻
1.Registration of a new employee/student by admin
2.Clicking of photos by webcam for the dataset
3.Training of dataset
4.Viewing attendance report by admin
ATTENDANCE DASHBOARD-This dashboard gives the admin information regarding
a)Shows statistics-Number of employees present on that day ,graph for previous week and ongoing week (no of employee vs date)
b)Attendance report for a particular employee-attendence of a employee in a particular duration(duration is inserted by admin according to his convinence.Also this webpage shows graph between number of hours that employee worked on all the different days he was present
c)Attendance of all the employees for a particular date- Number of employees present on a particular date with graph representing number of hours each employee was present at that particular date(date is inserted by the admin according to his convinience)
5.Employee dashboard - Graph showing number of hours worked on all the dates when he was present and showing statistics such as intime and the out time of that employee
1.HOG face detector-Histogram Oriented Gradients (HOG) used in computer vision for object detection.
2.Shape Predictor-dilib Frontal Facial landmark predictor is used
Shape _predictor_68_face landmark -It estimates the location of 68 co-ordinates (x, y) that map the facial points of a particular person’s face.
1.Capturing image by webcam at that instant using vs=VedioStream (src=0)
2.Read from the image for each frame vs.read()
3.Resizing the image
4.Converting Coloured image to black and white image (for classifiers to work we need gray style image)
5.Storing the faces- Detecting all the images in the current frame and returning the co-ordinates of faces.
6.Drawing the rectangle around each face which webcam has captured.
7.Writing the captured face in the file in the folder. Before capturing the face, we need to tell the script whose face it is. We save the image in the dataset, but only the face part we crop the remaining part.
8.After capturing image stop the video stream .
For docummentation CLICK HERE.
For looking at the procedure CLICK HERE
ADMIN LOGIN CREDENTIALS
Username-admin
Password-admin(you can try abcd@1234)
For looking at the vedio presentation CLICK HERE
Utilisation of this technology seems to be wider range of effective results in the smooth functioning of industrial setup, government office's rural development projects, national identification, for beef up security at the borders,visa/passport allotment system, airport's security purposes and other similar arenas of enhancement.This will regulate systematic approach both in the developed and undeveloped nation's of the world.