face_detectr.py

import cv2
from random import randrange
# Load some pre-trained data on face frontals from opencv(haar cascade algorithm)
trained_face_data= cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

# Choose an image to detect faces in
#img = cv2.imread('Avengers.jpg')
# To capture video from webcame
webcam = cv2.VideoCapture(0)

# Iterates forever over frame
while True:

    # Read the current frame
    successful_frame_read, frame = webcam.read()

    # Must convert to grayscale
    grayscaled_img = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
   # cv2.imshow('Chetucity Face_Detector',grayscaled_img)

    # Detect Faces
    face_coordinates = trained_face_data.detectMultiScale(grayscaled_img)
   

    # Draw rectangles around the faces
    for (x, y, w, h) in face_coordinates:
        cv2.rectangle(frame, (x,y), (x+w, y+h), (randrange(256),randrange(256),randrange(256)),5)
    cv2.imshow('Chetucity Face_Detector',frame)
    key =   cv2.waitKey(1)

    #Stop if Q is pressed
    if key==81 or key==113:
        break

    # Release the VideoCapture object
webcam.release()
"""
# Detect Faces
face_coordinates = trained_face_data.detectMultiScale(grayscaled_img)

# Draw rectangles around the faces
for (x, y, w, h) in face_coordinates:
    cv2.rectangle(img, (x,y), (x+w, y+h), (randrange(256),randrange(256),randrange(256)),5)
    

# print(face_coordinates)

cv2.imshow('Chetucity Face_Detector',img)
cv2.waitKey()


print('code completed')

"""