Face Prediction is invalid in Opencv Python

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faces are showing Wrong Information in cv2.putText

Following is my code

 def start_webcam(self):
        try:
            face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml');
            capture = cv2.VideoCapture(1);
            while(True):
                ret, img = capture.read();
                gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
                faces = face_cascade.detectMultiScale(gray, 1.3, 5);
                for (x, y, w, h) in faces:
                    cv2.rectangle(img, (x, y), (x + w, y + h), (0, 0, 255), 2)
                    cv2.waitKey(10)
                cv2.imshow('img', img);
                #cv2.waitKey(100)
            #self.capture.set(cv2.CAP_PROP_FRAME_HEIGHT,480)
            #self.capture.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
            #self.timer=QTimer(self)
            #self.timer.timeout.connect(self.update_frame)
            #self.timer.start(5)
            capture.release()
            cv2.destroyAllWindows()
        except Exception:
            logging.exception("Connection issue")

 def stop_webcam(self):
        try:
            if self.studentid==0:
                self.displayMessageBox("Enter Student Information first")
                return;
            while(True):
                capture = cv2.VideoCapture(1);
                return_value, img=capture.read()
                gray=cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
                for i in range(5):
                 cv2.imwrite("dataSet/User." + str(self.studentid) + "." + str(i) + '.jpg',gray)
                 cv2.waitKey(100)
            del (capture)
            cv2.imshow("face",img)
            capture.release()

  def Traniner_Button(self):
        recognizer=cv2.face.LBPHFaceRecognizer_create()
        path='dataSet'

        def getImagesWithID(path):
            imagePaths=[os.path.join(path, f) for f in os.listdir(path)]
            faces=[]
            IDs=[]
            for imagePath in imagePaths:
                faceImg=Image.open(imagePath).convert('L')
                faceNp=np.array(faceImg, 'uint8')
                ID=int(os.path.split(imagePath)[-1].split('.')[1])
                faces.append(faceNp)
                IDs.append(ID)
                cv2.imshow("training", faceNp)
                cv2.waitKey(10)
            return np.array(IDs), faces

        def train():
            Ids, faces=getImagesWithID(path)
            recognizer.train(faces, Ids)
            recognizer.save('recognizer/trainingData.yml')
            cv2.destroyAllWindows()
        try:
            train()
        except Exception:
            logging.exception("Trainer Issue")

recognizer=cv2.face.LBPHFaceRecognizer_create()
        recognizer.read('recognizer/trainingData.yml')
        cascadePath=('haarcascade_frontalface_default.xml')
        faceCascade=cv2.CascadeClassifier(cascadePath);
        font=cv2.FONT_HERSHEY_SIMPLEX
        cam=cv2.VideoCapture(1)
        studentProf=None
        try:
            while True:
                ret, img=cam.read();
                gray=cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
                faces=faceCascade.detectMultiScale(gray, 1.2, 5)
                for (x, y, w, h) in faces:
                    cv2.rectangle(img, (x, y), (x + w, y + h), (225, 0, 0), 2)
                    imgId, confidence=recognizer.predict(gray[y:y + h, x:x + w])
                    studentProf = self.getStudentProfile(str(imgId))
                    if (studentProf != None):
                        cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
                        cv2.putText(img, str(studentProf), (x, y + h), font, 1, (255, 255, 255), 3)
                    cv2.waitKey(10)
                cv2.imshow('img', img)