Face Recognition-Based Attendance System – with source code – Flask App – With GUI – 2023

Machine Learning Projects

So guys here comes the most awaited project of machine learning Face Recognition-based Attendance System. As the name says this project takes attendance using biometrics (in this case face) and is one of the most famous projects among college students out there.

I have tried to make the project the easiest way possible. So without any further due, Let’s do it…

See the working of the project here – https://youtu.be/A_fqShFAS64

Snapshots of our App…

Face Recognition-based Attendance System Home Page…

Face Recognition-based Attendance System

List Users Page…

Face Recognition-based Attendance System

Attendance Sheet

Face Recognition-based Attendance System

Code files for our Face Recognition-based Attendance System


import cv2
import os
from flask import Flask,request,render_template
from datetime import date
from datetime import datetime
import numpy as np
from sklearn.neighbors import KNeighborsClassifier
import pandas as pd
import joblib

#### Defining Flask App
app = Flask(__name__)

#### Saving Date today in 2 different formats
datetoday = date.today().strftime("%m_%d_%y")
datetoday2 = date.today().strftime("%d-%B-%Y")

#### Initializing VideoCapture object to access WebCam
face_detector = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

#### If these directories don't exist, create them
if not os.path.isdir('Attendance'):
if not os.path.isdir('static'):
if not os.path.isdir('static/faces'):
if f'Attendance-{datetoday}.csv' not in os.listdir('Attendance'):
    with open(f'Attendance/Attendance-{datetoday}.csv','w') as f:

#### get a number of total registered users
def totalreg():
    return len(os.listdir('static/faces'))

#### extract the face from an image
def extract_faces(img):
        if img.shape!=(0,0,0):
            gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
            face_points = face_detector.detectMultiScale(gray, 1.3, 5)
            return face_points
            return []
        return []
#### Identify face using ML model
def identify_face(facearray):
    model = joblib.load('static/face_recognition_model.pkl')
    return model.predict(facearray)

#### A function which trains the model on all the faces available in faces folder
def train_model():
    faces = []
    labels = []
    userlist = os.listdir('static/faces')
    for user in userlist:
        for imgname in os.listdir(f'static/faces/{user}'):
            img = cv2.imread(f'static/faces/{user}/{imgname}')
            resized_face = cv2.resize(img, (50, 50))
    faces = np.array(faces)
    knn = KNeighborsClassifier(n_neighbors=5)

#### Extract info from today's attendance file in attendance folder
def extract_attendance():
    df = pd.read_csv(f'Attendance/Attendance-{datetoday}.csv')
    names = df['Name']
    rolls = df['Roll']
    times = df['Time']
    l = len(df)
    return names,rolls,times,l

#### Add Attendance of a specific user
def add_attendance(name):
    username = name.split('_')[0]
    userid = name.split('_')[1]
    current_time = datetime.now().strftime("%H:%M:%S")
    df = pd.read_csv(f'Attendance/Attendance-{datetoday}.csv')
    if int(userid) not in list(df['Roll']):
        with open(f'Attendance/Attendance-{datetoday}.csv','a') as f:

def getallusers():
    userlist = os.listdir('static/faces')
    names = []
    rolls = []
    l = len(userlist)

    for i in userlist:
        name,roll = i.split('_')
    return userlist,names,rolls,l

def deletefolder(duser):
    pics = os.listdir(duser)
    for i in pics:


################## ROUTING FUNCTIONS #########################

#### Our main page
def home():
    names,rolls,times,l = extract_attendance()    
    return render_template('home.html',names=names,rolls=rolls,times=times,l=l,totalreg=totalreg(),datetoday2=datetoday2)  

#### This function will run when we click on Take Attendance Button
def start():
    if 'face_recognition_model.pkl' not in os.listdir('static'):
        return render_template('home.html',totalreg=totalreg(),datetoday2=datetoday2,mess='There is no trained model in the static folder. Please add a new face to continue.') 

    ret = True
    cap = cv2.VideoCapture(0)
    while ret:
        ret,frame = cap.read()
        if len(extract_faces(frame))>0:
            (x,y,w,h) = extract_faces(frame)[0]
            cv2.rectangle(frame,(x, y), (x+w, y+h), (255, 0, 20), 2)
            face = cv2.resize(frame[y:y+h,x:x+w], (50, 50))
            identified_person = identify_face(face.reshape(1,-1))[0]
            cv2.putText(frame,f'{identified_person}',(30,30),cv2.FONT_HERSHEY_SIMPLEX,1,(255, 0, 20),2,cv2.LINE_AA)
        if cv2.waitKey(1)==27:
    names,rolls,times,l = extract_attendance()    
    return render_template('home.html',names=names,rolls=rolls,times=times,l=l,totalreg=totalreg(),datetoday2=datetoday2) 

#### This function will run when we add a new user
def add():
    newusername = request.form['newusername']
    newuserid = request.form['newuserid']
    userimagefolder = 'static/faces/'+newusername+'_'+str(newuserid)
    if not os.path.isdir(userimagefolder):
    i,j = 0,0
    cap = cv2.VideoCapture(0)
    while 1:
        _,frame = cap.read()
        faces = extract_faces(frame)
        for (x,y,w,h) in faces:
            cv2.rectangle(frame,(x, y), (x+w, y+h), (255, 0, 20), 2)
            cv2.putText(frame,f'Images Captured: {i}/50',(30,30),cv2.FONT_HERSHEY_SIMPLEX,1,(255, 0, 20),2,cv2.LINE_AA)
            if j%10==0:
                name = newusername+'_'+str(i)+'.jpg'
        if j==500:
        cv2.imshow('Adding new User',frame)
        if cv2.waitKey(1)==27:
    print('Training Model')
    names,rolls,times,l = extract_attendance()    
    return render_template('home.html',names=names,rolls=rolls,times=times,l=l,totalreg=totalreg(),datetoday2=datetoday2) 

#### Our main function which runs the Flask App
if __name__ == '__main__':
  • Line 1-9: We are importing the required libraries.
  • Line 11-12: Defining the Flask App.
  • Line 15-19: Functions that return today’s date strings to use in the program ahead.
  • Line 22-24: Initializing VideoCapture object to access WebCam.
  • Line 27-34: Checking if the required folders are in place or not, If not create them.
  • Line 37-39: A function that calculates the number of total registered users.
  • Line 42-46: A function that extracts the face from an image.
  • Line 49-52: A function that Identifies face using ML model.
  • Line 55-69: A function that trains the model on all the faces available in the faces folder.
  • Line 72-79: A function that extracts info from today’s attendance file in the attendance folder.
  • Line 82-91: A function that adds the Attendance of a specific user in our today’s Attendance file.

Routing Functions:

  • Line 96-100: Our main page routing function.
  • Line 103-126: This function will run when we click on Take Attendance Button.
  • Line 129-160: This function will run when we add a new user.
  • Line 163-165: Our main function which runs the Flask App.


<!doctype html>
<html lang="en">

<style type='text/css'>
    * {
        padding: 0;
        margin: 0;
        font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;

    body {
        background-image: url('https://cutewallpaper.org/21/1920-x-1080-gif/1920x1080-Wallpapercartoon-Wallpapers-Driverlayer-Search-.gif');
        background-size: cover;
        font-family: sans-serif;
        margin-top: 40px;
        height: 100vh;
        padding: 0;
        margin: 0;

    table {
        border: 1px;
        font-family: arial, sans-serif;
        border-collapse: collapse;
        width: 86%;
        margin: auto;

    th {
        border: 1px solid black !important;
        padding: 5px;

    tr:nth-child(even) {
        background-color: #dddddd;

    <!-- Required meta tags -->
    <meta charset="utf-8">
    <meta name="viewport" content="width=device-width, initial-scale=1">
    <link rel="stylesheet" href="https://fonts.googleapis.com/icon?family=Material+Icons">

    <!-- Bootstrap CSS -->
    <link href="https://cdn.jsdelivr.net/npm/bootstrap@5.0.0-beta3/dist/css/bootstrap.min.css" rel="stylesheet"
        integrity="sha384-eOJMYsd53ii+scO/bJGFsiCZc+5NDVN2yr8+0RDqr0Ql0h+rP48ckxlpbzKgwra6" crossorigin="anonymous">

    <title>Face Recognition Based Attendance System</title>


    <div class='mt-3 text-center'>
        <h1 style="width: auto;margin: auto;color: white;padding: 11px;font-size: 44px;">Face Recognition Based
            Attendance System</h1>

    {% if mess%}
    <p class="text-center" style="color: red;font-size: 20px;">{{ mess }}</p>
    {% endif %}

    <div class="row text-center" style="padding: 20px;margin: 20px;">

        <div class="col"
            style="border-radius: 20px;padding: 0px;background-color:rgb(211,211,211,0.5);margin:0px 10px 10px 10px;min-height: 400px;">
            <h2 style="border-radius: 20px 20px 0px 0px;background-color: #0b4c61;color: white;padding: 10px;">Today's
                Attendance <i class="material-icons">assignment</i></h2>
            <a style="text-decoration: none;max-width: 300px;" href="/start">
                    style="font-size: 24px;font-weight: bold;border-radius: 10px;width:490px;padding: 10px;margin-top: 30px;margin-bottom: 30px;"
                    type='submit' class='btn btn-primary'>Take Attendance <i
            <table style="background-color: white;">
                    <td><b>S No</b></td>
                {% if l %}

                {% for i in range(l) %}
                    <td>{{ i+1 }}</td>
                    <td>{{ names[i] }}</td>
                    <td>{{ rolls[i] }}</td>
                    <td>{{ times[i] }}</td>
                {% endfor %}
                {% endif %}


        <div class="col"
            style="border-radius: 20px;padding: 0px;background-color:rgb(211,211,211,0.5);margin:0px 10px 10px 10px;height: 400px;">
            <form action='/add' method="POST" enctype="multipart/form-data">
                <h2 style="border-radius: 20px 20px 0px 0px;background-color: #0b4c61;color: white;padding: 10px;">Add
                    New User <i class="material-icons">control_point_duplicate</i></h2>
                <label style="font-size: 20px;"><b>Enter New User Name*</b></label>
                <input type="text" id="newusername" name='newusername'
                    style="font-size: 20px;margin-top:10px;margin-bottom:10px;" required>
                <label style="font-size: 20px;"><b>Enter New User Id*</b></label>
                <input type="number" id="newusereid" name='newuserid'
                    style="font-size: 20px;margin-top:10px;margin-bottom:10px;" required>
                <button style="width: 232px;margin-top: 20px;font-size: 20px;" type='submit' class='btn btn-dark'>Add
                    New User
                <h5 style="padding: 25px;"><i>Total Users in Database: {{totalreg}}</i></h5>




Source Code

Free Version:

Download the Source code for the Free version of Face Recognition-based Attendance System

Paid Version:

  • The paid version is a much more refined version.
  • It has live date and time functionality.
  • It has some extra features like ‘List Users’ functionality from where we can even delete the registered users.

You can Pay using the button below…

Working Video of our Project…

Do let me know if there’s any query regarding the Face Recognition-based Attendance System by contacting me via email or LinkedIn.

So this is all for this blog folks, thanks for reading it and I hope you are taking something with you after reading this and till the next time…


Check out my other machine learning projectsdeep learning projectscomputer vision projectsNLP projectsFlask projects at machinelearningprojects.net.

29 thoughts on “Face Recognition-Based Attendance System – with source code – Flask App – With GUI – 2023”

  1. Yakubu Nuhu Danjuma

    Great and wonderful project, keep it up. Sir I try executing program, but got this error: ValueError: bad marshal data (unknown type code), how to fix the problem. Thank you

  2. Hlw , I am getting some error when I will execute the following code. So I need you help to fix it
    How did I connect with you in mail or in linked in ?
    Please attach your I’d name

  3. Great Project, A request to you. Could you please make a video on how to run this project after downloading, it would be more helpful.

  4. I am getting an exception “cv2.error: OpenCV(4.6.0) D:\a\opencv-python\opencv-python\opencv\modules\objdetect\src\cascadedetect.cpp:1689: error: (-215:Assertion failed) !empty() in function ‘cv::CascadeClassifier::detectMultiScale'”
    How do I go about it. The App runs pretty well after entering userid and username when I try to add user it throws the error.

  5. First I would like to thank you for releasing it for free. May I ask: Is it possible to take attendance of multiple faces at the same time?

      1. Cảm ơn bạn nhiều. có thể xuất ra app apk cho android được không? hay chỉ chạy trên windows? Have a nice day!

  6. Hello. I want to thank you for making this project free, it really helped me learn Flask and OpenCV. Everything works exactly as intended. But such a question, in the PyCharm IDE, while the program is running, it always gives an error
    “DeprecationWarning: elementwise comparison failed; this will raise an error in the future. if extract_faces(frame) != ():”
    This error does not affect the operation of the program in any way, but is displayed anew every second. What could it be? Thank you very much for your work!

  7. Your project really helped me. I wanted to ask how can I add a new input for class/stream? Also add it in my csv file. Please help!

  8. Hello,
    I’m interested in purchasing the premium version of your project, but I’m having trouble with the payment process. Could you help me resolve this issue?

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