Real-Time Student Attendance Management System Project In Python
The Student Attendance Management System Project In Python was developed using Python OpenCV in Real-Time, This Attendance Management System Project In Python 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.
A Attendance Management System Using Face Recognition Python is a simple python script that recognizes faces and mark attendance for the recognized faces 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.
Student Attendance Management System : Features
- Check Camera
- Capture Faces
- Train Faces
- Recognize Faces & Attendance
- Automatic Email
Student Attendance Management System : Build With-
- Python 3.9
Module Used –
All The Module are Latest Version.
- OpenCV Contrib 4.0.1
- Pillow
- Numpy
- Pandas
- Shutil
- CSV
- yagmail
Face Recognition Algorithms –
- Haar Cascade
- LBPH (Local Binary Pattern Histogram)
This Attendance Management System Using Face Recognition In Python also includes a downloadable Attendance Management System Project In Python With Source Code for free, just find the downloadable source code below and click to start downloading.
By the way if you are new to python programming and you don’t know what would be the the Python IDE to use, I have here a list of Best Python IDE for Windows, Linux, Mac OS that will suit for you. I also have here How to Download and Install Latest Version of Python on Windows.
To start creating a Student Attendance Management System Project In Python, make sure that you have installed Python 3.9 and PyCharm in your computer.
Student Attendance Management System Project In Python : Prerequisites
Before starting with this Python project with source code, you should be familiar with the computer vision library of Python that is OpenCV, Pillow, Pandas, Shutil, CSV and Numpy.
OpenCV, Pillow, Pandas, Shutil, CSV and Numpy are the Python packages that are necessary for this project in Python. To install them, simply run this pip command in your terminal:
- pip install opencv-python
- pip install pillow
- pip install pandas
- pip install numpy
Student Attendance Management System Project In Python : Steps on how to run the project
Time needed: 5 minutes.
These are the steps on how to run Student Attendance Management System Project In Python
- Step 1: Download the given source code below.
First, download the given source code below and unzip the source code.
- Step 2: Import the project to your PyCharm IDE.
Next, import the source code you’ve download to your PyCharm IDE.
- Step 3: Install all the packages.
Next, Install all the requirements required for the system.
- Step 4: Run the project.
last, run the project with the command “py main.py”
Student Attendance Management System : Code For check_camera.py
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def camer(): import cv2 # Load the cascade face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') # To capture video from webcam. cap = cv2.VideoCapture(0) while True: # Read the frame _, img = cap.read() # Convert to grayscale gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # Detect the faces faces = face_cascade.detectMultiScale(gray, 1.3, 5, minSize=(30, 30),flags = cv2.CASCADE_SCALE_IMAGE) # Draw the rectangle around each face for (x, y, w, h) in faces: cv2.rectangle(img, (x, y), (x + w, y + h), (10,159,255), 2) # Display cv2.imshow('Webcam Check', img) # Stop if escape key is pressed if cv2.waitKey(1) & 0xFF == ord('q'): break # Release the VideoCapture object cap.release() cv2.destroyAllWindows() |
Student Attendance Management System : Code For Capture_Image.py
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import csv import cv2 import os # counting the numbers def is_number(s): try: float(s) return True except ValueError: pass try: import unicodedata unicodedata.numeric(s) return True except (TypeError, ValueError): pass return False # Take image function def takeImages(): Id = input("Enter Your Id: ") name = input("Enter Your Name: ") if(is_number(Id) and name.isalpha()): cam = cv2.VideoCapture(0) harcascadePath = "haarcascade_frontalface_default.xml" detector = cv2.CascadeClassifier(harcascadePath) sampleNum = 0 while(True): ret, img = cam.read() gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) faces = detector.detectMultiScale(gray, 1.3, 5, minSize=(30,30),flags = cv2.CASCADE_SCALE_IMAGE) for(x,y,w,h) in faces: cv2.rectangle(img, (x, y), (x+w, y+h), (10, 159, 255), 2) #incrementing sample number sampleNum = sampleNum+1 #saving the captured face in the dataset folder TrainingImage cv2.imwrite("TrainingImage" + os.sep +name + "."+Id + '.' + str(sampleNum) + ".jpg", gray[y:y+h, x:x+w]) #display the frame cv2.imshow('frame', img) #wait for 100 miliseconds if cv2.waitKey(100) & 0xFF == ord('q'): break # break if the sample number is more than 100 elif sampleNum > 100: break cam.release() cv2.destroyAllWindows() res = "Images Saved for ID : " + Id + " Name : " + name row = [Id, name] with open("StudentDetails"+os.sep+"StudentDetails.csv", 'a+') as csvFile: writer = csv.writer(csvFile) writer.writerow(row) csvFile.close() else: if(is_number(Id)): print("Enter Alphabetical Name") if(name.isalpha()): print("Enter Numeric ID") |
Student Attendance Management System : Code For Train_Image.py
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import os import time import cv2 import numpy as np from PIL import Image from threading import Thread # -------------- image labesl ------------------------ def getImagesAndLabels(path): # get the path of all the files in the folder imagePaths = [os.path.join(path, f) for f in os.listdir(path)] # print(imagePaths) # create empth face list faces = [] # create empty ID list Ids = [] # now looping through all the image paths and loading the Ids and the images for imagePath in imagePaths: # loading the image and converting it to gray scale pilImage = Image.open(imagePath).convert('L') # Now we are converting the PIL image into numpy array imageNp = np.array(pilImage, 'uint8') # getting the Id from the image Id = int(os.path.split(imagePath)[-1].split(".")[1]) # extract the face from the training image sample faces.append(imageNp) Ids.append(Id) return faces, Ids # ----------- train images function --------------- def TrainImages(): recognizer = cv2.face_LBPHFaceRecognizer.create() harcascadePath = "haarcascade_frontalface_default.xml" detector = cv2.CascadeClassifier(harcascadePath) faces, Id = getImagesAndLabels("TrainingImage") Thread(target = recognizer.train(faces, np.array(Id))).start() # Below line is optional for a visual counter effect Thread(target = counter_img("TrainingImage")).start() recognizer.save("TrainingImageLabel"+os.sep+"Trainner.yml") print("All Images") # Optional, adds a counter for images trained (You can remove it) def counter_img(path): imgcounter = 1 imagePaths = [os.path.join(path, f) for f in os.listdir(path)] for imagePath in imagePaths: print(str(imgcounter) + " Images Trained", end="\r") time.sleep(0.008) imgcounter += 1 |
Student Attendance Management System : Code For automail.py
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import os import yagmail body = "Attendence File" # email body filename = "Attendance"+os.sep+"Attendance_2019-08-29_13-09-07.csv" # attach the file # mail information # sent the mail yag.send( to=receiver, subject="Attendance Report", # email subject contents=body, # email body attachments=filename, # file attached ) |
Student Attendance Management System : Code For Recognize.py
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import datetime import os import time import cv2 import pandas as pd #------------------------- def recognize_attendence(): recognizer = cv2.face.LBPHFaceRecognizer_create() # cv2.createLBPHFaceRecognizer() recognizer.read("TrainingImageLabel"+os.sep+"Trainner.yml") harcascadePath = "haarcascade_frontalface_default.xml" faceCascade = cv2.CascadeClassifier(harcascadePath) df = pd.read_csv("StudentDetails"+os.sep+"StudentDetails.csv") font = cv2.FONT_HERSHEY_SIMPLEX col_names = ['Id', 'Name', 'Date', 'Time'] attendance = pd.DataFrame(columns=col_names) # Initialize and start realtime video capture cam = cv2.VideoCapture(0, cv2.CAP_DSHOW) cam.set(3, 640) # set video width cam.set(4, 480) # set video height # Define min window size to be recognized as a face minW = 0.1 * cam.get(3) minH = 0.1 * cam.get(4) while True: ret, im = cam.read() gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY) faces = faceCascade.detectMultiScale(gray, 1.2, 5,minSize = (int(minW), int(minH)),flags = cv2.CASCADE_SCALE_IMAGE) for(x, y, w, h) in faces: cv2.rectangle(im, (x, y), (x+w, y+h), (10, 159, 255), 2) Id, conf = recognizer.predict(gray[y:y+h, x:x+w]) if conf < 100: aa = df.loc[df['Id'] == Id]['Name'].values confstr = " {0}%".format(round(100 - conf)) tt = str(Id)+"-"+aa else: Id = ' Unknown ' tt = str(Id) confstr = " {0}%".format(round(100 - conf)) if (100-conf) > 67: ts = time.time() date = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d') timeStamp = datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S') aa = str(aa)[2:-2] attendance.loc[len(attendance)] = [Id, aa, date, timeStamp] tt = str(tt)[2:-2] if(100-conf) > 67: tt = tt + " [Pass]" cv2.putText(im, str(tt), (x+5,y-5), font, 1, (255, 255, 255), 2) else: cv2.putText(im, str(tt), (x + 5, y - 5), font, 1, (255, 255, 255), 2) if (100-conf) > 67: cv2.putText(im, str(confstr), (x + 5, y + h - 5), font,1, (0, 255, 0),1 ) elif (100-conf) > 50: cv2.putText(im, str(confstr), (x + 5, y + h - 5), font, 1, (0, 255, 255), 1) else: cv2.putText(im, str(confstr), (x + 5, y + h - 5), font, 1, (0, 0, 255), 1) attendance = attendance.drop_duplicates(subset=['Id'], keep='first') cv2.imshow('Attendance', im) if (cv2.waitKey(1) == ord('q')): break ts = time.time() date = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d') timeStamp = datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S') Hour, Minute, Second = timeStamp.split(":") fileName = "Attendance"+os.sep+"Attendance_"+date+"_"+Hour+"-"+Minute+"-"+Second+".csv" attendance.to_csv(fileName, index=False) print("Attendance Successful") cam.release() cv2.destroyAllWindows() |
Student Attendance Management System : Code For main.py
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import os # accessing the os functions import check_camera import Capture_Image import Train_Image import Recognize # creating the title bar function def title_bar(): os.system('cls') # for windows # title of the program print("\t**********************************************") print("\t***** Face Recognition Attendance System *****") print("\t**********************************************") # creating the user main menu function def mainMenu(): title_bar() print() print(10 * "*", "WELCOME MENU", 10 * "*") print("[1] Check Camera") print("[2] Capture Faces") print("[3] Train Images") print("[4] Recognize & Attendance") print("[5] Auto Mail") print("[6] Quit") while True: try: choice = int(input("Enter Choice: ")) if choice == 1: checkCamera() break elif choice == 2: CaptureFaces() break elif choice == 3: Trainimages() break elif choice == 4: RecognizeFaces() break elif choice == 5: os.system("py automail.py") break mainMenu() elif choice == 6: print("Thank You") break else: print("Invalid Choice. Enter 1-4") mainMenu() except ValueError: print("Invalid Choice. Enter 1-4\n Try Again") exit # --------------------------------------------------------- # calling the camera test function from check camera.py file def checkCamera(): check_camera.camer() key = input("Enter any key to return main menu") mainMenu() # -------------------------------------------------------------- # calling the take image function form capture image.py file def CaptureFaces(): Capture_Image.takeImages() key = input("Enter any key to return main menu") mainMenu() # ----------------------------------------------------------------- # calling the train images from train_images.py file def Trainimages(): Train_Image.TrainImages() key = input("Enter any key to return main menu") mainMenu() # -------------------------------------------------------------------- # calling the recognize_attendance from recognize.py file def RecognizeFaces(): Recognize.recognize_attendence() key = input("Enter any key to return main menu") mainMenu() # ---------------main driver ------------------ mainMenu() |
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Conclusion
Therefore, for this Project In Python Using OpenCV 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.
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