face_detect.py

import sys

import cv2
import imutils

# The locatio of the image and the cascade file path
imagePath = sys.argv[1]
cascPath = 'cascade.xml'

# Create the haar cascade
faceCascade = cv2.CascadeClassifier(cascPath)

# Read the image
image = cv2.imread(imagePath)

# Resize the image so it fits in the screen
image1 = imutils.resize(image, height=500)
gray = cv2.cvtColor(image1, cv2.COLOR_BGR2GRAY)

# Detect faces in the image
faces = faceCascade.detectMultiScale(
    gray,
    scaleFactor=1.1,
    minNeighbors=5,
    minSize=(30, 30),
    # flags = cv2.cv.CV_HAAR_SCALE_IMAGE
    flags=0
)

if format(len(faces)) == 1:
    print("Found {0} face!".format(len(faces)))
else:
    print("Found {0} faces!".format(len(faces)))

# Draw a rectangle around the faces
for (x, y, w, h) in faces:
    cv2.rectangle(image1, (x, y), (x + w, y + h), (0, 255, 0), 2)

cv2.imshow("Faces found", image1)
cv2.waitKey(0)