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Attendance using Face Recognition

This project is made to take attendance in organisation(s). This uses face recognition to check a person's identity and mark him/her present or absent accordingly.

Project Description

This is an AI based project working on the principle of Computer Vision.
Using digital images and live feed it detects and recognizes human face and mark their attendance.
The sole purpose of this model is to detect a person and add their details separately in Attendance list.

Community

Code of Conduct
Contributing to Inaxia

Novelty

  • Instead of working on a single face, our model can recognize multiple face in one frame.
  • Our model not only recognizes a face but also mark attendance of that recognized person.
  • Our model update Attendance list in real-time (as soon as it recognizes a person).

Real-time Usage

  • Firstly, we open the webcam to take images of people present in front of the camera.
  • Then we check each of them if they exist in our data or not. If not, they'll be called as 'Unknown'.
  • After checking each of them with our data, we check that if they already marked as present or not. If not, we take that person's Registration no., Name & Entry time and mark them present.

Hardware & Software Requirements

  1. Hardware: Desktop or laptop with a webcam installed
  2. Minimum Specs: 4gb RAM and 80gb HDD dual core processor
  3. OS: macOS or Linux (Windows not officially support 'face_ recognition' library, but it might work)
  4. Programming Language: Python 2.7 or Python 3.3+
  5. Application: 'Spreadsheet' in macOS or 'LibreOffice Calc' in Linux

Output

Registration_No. Name Entry_Time
19BCE10191 Hardik 09:10:39
19BCE10118 Nishant 09:12:15
19BCE10119 Ankit 09:12:57
19BCE10314 Nandita 09:16:23

Result & Discussion

  • This method can detect multiple face in one frame and can be easily used in a classroom or in an office.
  • This system helps us to achieve desired results with better accuracy and less time consumption.
  • The precision or the accuracy of face recognition of our model is almost more than 90%.

Conclusion

Thus, the aim of this model is to capture the video of the students/colleagues, convert it into frames, relate it with the dataset to ensure their presence or absence, mark attendance to the particular student/colleagues to maintain the record. The Automated Classroom Attendance System helps in increasing the accuracy and speed ultimately achieve the high-precision real-time attendance to meet the need for automatic classroom evaluation.

Steps to Run

  1. Fork this repo
  2. Clone the forked repo to your local system
  3. Install the following libraries: (in Linux or macOS)
    1. cv2
    2. face_recogniton
    3. os
    4. math
    5. numpy
    6. datetime
  4. Add your image inside imageData folder in format -> name.registration.jpg, if adding more than one image of same person then format -> name.registration.(0,1,2).jpg, only after that it will recognize you.
  5. Run the code -> code.py
  6. If it will recognise you, your attendance will be there in Attendance.csv file

(Provide more than one image with different angle to get more accuracy)

Reference link

(Use this link when you unable to import face_recognition library) https://ourcodeworld.com/articles/read/841/how-to-install-and-use-the-python-face-recognition-and-detection-library-in-ubuntu-16-04

Support

If you like this project, don't forget to give it a ⭐