I have worked on harcascade face detection and eye detection. it works well now i am stuck finding distance between two eyes. please provide me some logic or piece to code to achive this.

import cv2 
import math 
import numpy as np from scipy.spatial 
import distance as dist

            def midpoint(ptA, ptB):
                return ((ptA[0] + ptB[0]) * 0.5, (ptA[1] + ptB[1]) * 0.5)

            def calculateDistance(ex,ey,ew,eh):
                 dist = math.sqrt((ex - ew)**2 + (ey - eh)**2)
                 return dist
            # print calculateDistance(x1, y1, x2, y2)

            # using harcasde  for face
            face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
            # https://github.com/Itseez/opencv/blob/master/data/haarcascades/haarcascade_eye.xml
            eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')

            # read both the images of the face and the glasses
            image = cv2.imread('example_2.jpg')![image description](/upfiles/15116549809854402.png)

            gray    =   cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

            centers=[]
            faces = face_cascade.detectMultiScale(gray,1.3,5)

            #check for the face detected
            for (x,y,w,h) in faces:

                #create two Regions of Interest on face.
                roi_gray = gray[y:y+h, x:x+w]
                roi_color = image[y:y+h, x:x+w]
                eyes = eye_cascade.detectMultiScale(roi_gray)

                # Store the cordinates of eyes in the image to the 'center' array
                for (ex,ey,ew,eh) in eyes:
                    centers.append((x+int(ex+0.5*ew), y+int(ey+0.5*eh)))
                    # Point2f eye1, eye2;
                    # double res = cv::norm(eye1-eye2);

                    #creates rectangle with 'colour'
                    cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)


            overlay_img = np.ones(image.shape,np.uint8)*255

            #Create a mask and generate it's inverse.
            gray_glasses    =   cv2.cvtColor(overlay_img,   cv2.COLOR_BGR2GRAY)
            ret,    mask    =   cv2.threshold(gray_glasses, 110,    255,    cv2.THRESH_BINARY)
            mask_inv    =   cv2.bitwise_not(mask)
            temp    =   cv2.bitwise_and(image,  image,  mask=mask)
            temp2   =   cv2.bitwise_and(overlay_img,    overlay_img,    mask=mask_inv)
            final_img   =   cv2.add(temp,   temp2)

            # imS = cv2.resize(final_img, (1366, 768))
            # print calculateDistance(ex,ey,ew,eh)
            cv2.imshow('Final  Result', final_img)
            cv2.waitKey()
            cv2.destroyAllWindows()