detector.py

import cv2
import numpy as np
recognizer =cv2.face.LBPHFaceRecognizer_create()
recognizer.read('trainner/trainner.yml')
cascadePath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascadePath)
cam = cv2.VideoCapture(0)
#font = cv2.cv.InitFont(cv2.cv.CV_FONT_HERSHEY_SIMPLEX, 1, 1, 0, 1, 1)
font = cv2.FONT_HERSHEY_SIMPLEX
while True:
    ret, im =cam.read()
    gray=cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
    faces=faceCascade.detectMultiScale(gray,1.2,5)
    for(x,y,w,h) in faces:
        cv2.rectangle(im,(x,y),(x+w,y+h),(225,0,0),2)
        Id, conf = recognizer.predict(gray[y:y+h,x:x+w])
        #cv2.cv.PutText(cv2.cv.fromarray(im),str(Id), (x,y+h),font, 255)
        #Id, conf = recognizer.predict(gray[y:y+h,x:x+w])
        print(conf,Id)
        if conf<200 :
            if Id==4:
               Id="Shubham"
            #elif Id==3:
            #    Id="case"
            else:
                Id="Dilshad khan"
        #cv2.cv.PutText(cv2.cv.fromarray(im),str(Id), (x,y+h),font, 255)
        cv2.putText(im, str(Id), (x,y+h), font, 1, (255,255,255), 2, cv2.LINE_AA)

    cv2.imshow('im',im)
    if cv2.waitKey(1) & 0xFF==ord('q'):
        break
cam.release()
cv2.destroyAllWindows()