main.py

import cv2
import numpy as np
import face_recognition
import os
from datetime import datetime

# Define the path to the dataset
path = r'Enter your path'
images = []
classNames = []
myList = os.listdir(path)
print(myList)
for cl in myList:
    curImg = cv2.imread(os.path.join(path, cl))
    images.append(curImg)
    classNames.append(os.path.splitext(cl)[0])
print(classNames)

# Function to find encodings for all images in the dataset
def findEncodings(images):
    encodeList = []
    for img in images:
        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        encode = face_recognition.face_encodings(img)[0]
        encodeList.append(encode)
    return encodeList

# Function to mark attendance
def markAttendance(name):
    with open('Attendance.csv', 'r+') as f:
        myDataList = f.readlines()
        nameList = [line.split(',')[0] for line in myDataList]
        if name not in nameList:
            now = datetime.now()
            dtString = now.strftime('%H:%M:%S')
            f.writelines(f'\n{name},{dtString}')

# Find encodings for the known images
encodeListKnown = findEncodings(images)
print('Encoding Complete')

cap = cv2.VideoCapture(0)
present_students = set()

while True:
    success, img = cap.read()
    if not success:
        print("Failed to capture image")
        break
    
    # Resize the image for faster processing
    imgS = cv2.resize(img, (0, 0), None, 0.25, 0.25)
    imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)
    
    facesCurFrame = face_recognition.face_locations(imgS)
    encodesCurFrame = face_recognition.face_encodings(imgS, facesCurFrame)
    
    for encodeFace, faceLoc in zip(encodesCurFrame, facesCurFrame):
        matches = face_recognition.compare_faces(encodeListKnown, encodeFace)
        faceDis = face_recognition.face_distance(encodeListKnown, encodeFace)
        matchIndex = np.argmin(faceDis)
        
        name = "Unknown"
        if matches[matchIndex]:
            name = classNames[matchIndex].upper()
            markAttendance(name)
            present_students.add(name)
        
        y1, x2, y2, x1 = faceLoc
        y1, x2, y2, x1 = y1 * 4, x2 * 4, y2 * 4, x1 * 4
        cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 0), 2)
        cv2.rectangle(img, (x1, y2 - 35), (x2, y2), (0, 255, 0), cv2.FILLED)
        cv2.putText(img, name, (x1 + 6, y2 - 6), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255), 2)
    
    # Display present and absent students on the screen
    y_offset = 50
    cv2.putText(img, "Present Students:", (10, y_offset), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
    for i, student in enumerate(present_students):
        cv2.putText(img, student, (10, y_offset + (i + 1) * 30), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
    
    y_offset += (len(present_students) + 1) * 30
    cv2.putText(img, "Absent Students:", (10, y_offset), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
    absent_students = set(classNames) - present_students
    for i, student in enumerate(absent_students):
        cv2.putText(img, student, (10, y_offset + (i + 1) * 30), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)

    cv2.imshow('Webcam', img)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

# Print present and absent students to the console
print("Present students:", present_students)
print("Absent students:", absent_students)