main.py

import cv2

# Load the cascade classifier
face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")

# Initialize the video capture
cap = cv2.VideoCapture(0)

while True:
    # Read a frame from the video capture
    _, frame = cap.read()

    # Convert the frame to grayscale
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # Detect faces in the frame
    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))

    # Draw a rectangle around the faces
    for (x, y, w, h) in faces:
        cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)

    # Show the frame
    cv2.imshow("Frame", frame)

    # Exit the loop if the 'q' key is pressed
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release the video capture and close the window
cap.release()
cv2.destroyAllWindows()