import cv2
import numpy as np
import os
import argparse

#ap = argparse.ArgumentParser()
#ap.add_argument("-p", "--pic", required=True, help="Pic")
#args = vars(ap.parse_args())
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read("trainer/trainer.yml")
cascadePath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascadePath)
font = cv2.FONT_HERSHEY_SIMPLEX
id = 0
names = ['None', 'Mthandazo']
cam = cv2.VideoCapture(0)
cam.set(3, 640)
cam.set(4, 480)
minW = 0.1*cam.get(3)
minH = 0.1*cam.get(4)
while True:
    ret, img = cam.read()
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    faces = faceCascade.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=5, minSize = (int(minW), int(minH)))
    for (x, y, w, h) in faces:
        cv2.rectangle(img, (x, y), (x+w, y+h), (0,255,0), 2)
        id, confidence = recognizer.predict(gray[y:y+h, x:x+w])
        if confidence < 100:
            id = names[id]
            confidence = " {0}%".format(round(100 - confidence))
        else:
            id = "unknown"
            confidence = " {0}%".format(round(100 - confidence))

        cv2.putText(img, str(id), (x+5, y-5), font, 1, (255,255,255), 2)
        cv2.putText(img, str(confidence), (x+5, y+h-5), font, 1, (255,255,0), 1)
    cv2.imshow('camera',img)
    if id == "Mthandazo":
        os.system("say welcome back Sir")
        break

    k = cv2.waitKey(10) & 0xff
    if k == 27:
        break

cam.release()
cam.destroyAllWindows()
