import cv2
# import glob
# import os

# creates a cascade classifier object
face_cascade=cv2.CascadeClassifier("haarcascade_frontalface_default.xml")

# os.chdir("C://")

img=cv2.imread("producers.jpg")

# temporarily converts image to gray scale so that the accuracy of the face detection algorythim is better
gray_img=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

faces=face_cascade.detectMultiScale(gray_img,
scaleFactor=1.03,
minNeighbors=7)

for x, y, w, h in faces:
    img=cv2.rectangle(img, (x,y),(x+w,y+h),(0,255,0),2)

print(type(faces))
print(faces)

# resized=cv2.resize(img,(int(img.shape[1]/2),int(img.shape[0]/2)))
cv2.imshow("Gray",img)
cv2.waitKey(0)
cv2.destroyAllWindows()
