main.py

import cv2
import pickle
import face_recognition
import numpy as np
import math
from ultralytics import YOLO

# Initialize video capture
cap = cv2.VideoCapture(0)
cap.set(3, 640)  # Set width
cap.set(4, 480)  # Set height

# Load the Encoding File
print("Loading encodings...")
encodings = open("GeneratedEncodings.p", "rb")
encodingListKnownWithIDs = pickle.load(encodings)
encodings.close()
encodeListKnown, studentIDs = encodingListKnownWithIDs
print("Encodings loaded.")

# Load the anti-spoofing model
model = YOLO("models/best.pt")
model.overrides['verbose'] = False
classNames = ["fake", "real"]
confidence = 0.9

while True:
    success, img = cap.read()
    
    # Anti-spoofing check
    results = model(img, stream=True)
    is_real = False
    for r in results:
        boxes = r.boxes
        for box in boxes:
            conf = math.ceil((box.conf[0] * 100))/100
            if conf > confidence:
                cls = int(box.cls[0])
                if classNames[cls] == "real":
                    is_real = True
                    break
        if is_real:
            break

    if is_real:
        # Face recognition
        imgS = cv2.resize(img, (0, 0), None, 0.25, 0.25)
        imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)    

        faceCurrentFrame = face_recognition.face_locations(imgS)
        encodeCurrentFrame = face_recognition.face_encodings(imgS, faceCurrentFrame)

        for encodeFace, faceLocation in zip(encodeCurrentFrame, faceCurrentFrame):
            matches = face_recognition.compare_faces(encodeListKnown, encodeFace)
            faceDistance = face_recognition.face_distance(encodeListKnown, encodeFace)
            matchIndex = np.argmin(faceDistance)
            if matches[matchIndex]:
                print("Known Face Detected")
                print(studentIDs[matchIndex])
    else:
        print("Spoofing Attempt Detected")

    cv2.imshow("Face Attendance", img)

    # Wait for a key press to break the loop
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()