part-1_DataSet-Prepareing.py

import cv2


face_classifier = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')


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

    if len(faces) == 0:
        return None

    (x, y, w, h) = faces[0]
    return img[y:y+h, x:x+w]


count = 0
cap = cv2.VideoCapture(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 = 'E:\\AI-ML-Project\\Face-Lock-Unlock-System-RealTime\\Sample Images\\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("Sample Collected Successfully")