Task 5

import cv2
import face_recognition

# Load Haar Cascade for face detection
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')

# Load known face and encode (Replace 'known_face.jpg' with your image)
known_image = face_recognition.load_image_file("known_face.jpg")
known_encoding = face_recognition.face_encodings(known_image)[0]

# Open webcam
cap = cv2.VideoCapture(0)

while True:
    ret, frame = cap.read()
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # Detect faces
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)

    for (x, y, w, h) in faces:
        face = frame[y:y+h, x:x+w]
        face_enc = face_recognition.face_encodings(face)

        if face_enc:
            match = face_recognition.compare_faces([known_encoding], face_enc[0])
            label = "Matched" if match[0] else "Unknown"
        else:
            label = "No Face"

        cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
        cv2.putText(frame, label, (x, y-10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)

    cv2.imshow("Face Recognition", frame)
    
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()