face_recognition_part1.py

#program for collecting face samples

import cv2
import numpy as np


face_classifier = cv2.CascadeClassifier("C:/Python/Lib/site-packages/cv2/data/haarcascade_frontalface_default.xml")


def face_extractor(img):

    gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    faces = face_classifier.detectMultiScale(gray,1.3,5)

    if faces is():
        return None

    for(x,y,w,h) in faces:
        cropped_face = img[y:y+h, x:x+w]

    return  cropped_face




cap = cv2.VideoCapture(0)
count = 0

while True:
    ret, frame = cap.read()
    if face_extractor(frame) is not None:
        count+=1
        face = cv2.resize(face_extractor(frame),(200,200))
        face = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY)

        file_name_path = 'C:/ML_project/faces/user'+str(count)+'.jpg'
        cv2.imwrite(file_name_path,face)

        cv2.putText(face,str(count),(50,50),cv2.FONT_HERSHEY_COMPLEX,1,(0,255,0),2)
        cv2.imshow('Face Cropper', face)

    else:
        print('Face Not Found')
        pass

    if cv2.waitKey(1)==13 or count ==100:
        break

cap.release()
cv2.destroyAllWindows()
print('Collecting samples complted!!')