import cv2
import numpy as np
import os


def main():
    recognizer = cv2.face.LBPHFaceRecognizer_create()
    recognizer.read("F:/work/resource/face/trainer.yml")
    cascadePath = "F:/work/resource/face/haarcascades/haarcascade_frontalface_default.xml";
    faceCascade = cv2.CascadeClassifier(cascadePath)
    cv2.namedWindow("camera",cv2.WINDOW_AUTOSIZE)
    font = cv2.FONT_HERSHEY_SIMPLEX
    id = 0
    names = ['xukang',"xujihuan","xieqiping","daerzi"]
    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()
        img = cv2.flip(img,1)
        gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
        faces = faceCascade.detectMultiScale(gray,scaleFactor=1.2,minNeighbors=5)
        for (x,y,w,h) in faces:
            cv2.rectangle(img,(x,y),(x+w,y+h),(0,0,225),2)
            id,confidence = recognizer.predict(gray[y:y+h,x:x+w])
            if (confidence < 100):
                print(id)
                id = names[id]
                confidence = "  {0}%".format(round(100-confidence))
            else:
                id = "unknow"
                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)
        k = cv2.waitKey(10) & 0xff4
        if k == 27:
            break
    cam.release()
    cv2.destroyAllWindows()
main()