FaceEyDetection.py

import numpy as np
import cv2

cap = cv2.VideoCapture(0)

# Load Haar cascades for face and eye detection
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_eye.xml')

while True:
    ret, frame = cap.read()

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

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

    # Iterate through detected faces
    for (x, y, w, h) in faces:
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 3)

        # Define the region of interest (ROI) for eye detection within the face
        roi_gray = gray[y:y+w, x:x+w]
        roi_color = frame[y:y+h, x:x+w]

        # Detect eyes within the ROI
        eyes = eye_cascade.detectMultiScale(roi_gray, scaleFactor=1.1, minNeighbors=4, minSize=(30, 30))
        for (ex, ey, ew, eh) in eyes:
            cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)

    cv2.imshow('frame', frame)

    if cv2.waitKey(1) == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()