face_detection.py

import cv2
import numpy as np
import os

cascadePath = './haarcascade_frontalface_default.xml'
faceCascade = cv2.CascadeClassifier(cascadePath)

font = cv2.FONT_HERSHEY_SIMPLEX
# Initialize and start realtime video capture
cam = cv2.VideoCapture(0)
cam.set(3, 640)  # set video widht
cam.set(4, 480)  # set video height
# # Define min window size to be recognized as a face
minW = 0.1 * cam.get(3)
minH = 0.1 * cam.get(4)
while True:
    ret, img = cam.read()
    # img = cv2.flip(img, -1)  # Flip vertically
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    faces = faceCascade.detectMultiScale(
        gray,
        scaleFactor=1.2,
        minNeighbors=5,
        minSize=(int(minW), int(minH)),
    )
    for (x, y, w, h) in faces:
        cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
    cv2.imshow('camera', img)
    k = cv2.waitKey(10) & 0xff
    if k == 27:
        break
cam.release()
cv2.destroyAllWindows()