How to show the offset difference value between base image and reference image in OpenCV?

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How can we show the offset difference value between base image and reference image when there is a position change?

Here are the Images attached. ( i resized your ~7 MB images and uploaded ~700 kb @sturkmen )

code :

import cv2
import numpy as np

def grab_contours(cnts):
    # if the length the contours tuple returned by cv2.findContours
    # is '2' then we are using either OpenCV v2.4, v4-beta, or
    # v4-official
    if len(cnts) == 2:
        cnts = cnts[0]

    # if the length of the contours tuple is '3' then we are using
    # either OpenCV v3, v4-pre, or v4-alpha
    elif len(cnts) == 3:
        cnts = cnts[1]

    # otherwise OpenCV has changed their cv2.findContours return
    # signature yet again and I have no idea WTH is going on
    else:
        raise Exception(("Contours tuple must have length 2 or 3, "
            "otherwise OpenCV changed their cv2.findContours return "
            "signature yet again. Refer to OpenCV's documentation "
            "in that case"))

    # return the actual contours array
    return cnts

image1 = cv2.imread("Img_Position1.png")
image2 = cv2.imread("Img_Position2.png")


ht = int(image1.shape[0] )  
wd = int(image1.shape[1])  
bgr = int(image1.shape[2])


print('Image1 Original Dimensions : ',image1.shape)
print('Image2 Original Dimensions : ',image2.shape)
print (ht)
print (wd)
print (bgr)

#difference = cv2.subtract(image1, image2)

if image1.shape == image2.shape:
    print("1")  
    difference = cv2.absdiff(image1,image2)
    b , g , r = cv2.split(difference)
    if cv2.countNonZero(b) == 0 and cv2.countNonZero(g) == 0 and cv2.countNonZero(r) == 0:
      print ("the images are same")
    else:
      print ("the images are different")      

 #image1 =cv2.resize(image1,(1000,600))
 #image2 =cv2.resize(image2,(1000,600))
else:
   print("2")
   image2 =cv2.resize(image2,(ht,wd))
   difference = cv2.subtract(image1,image2)
   b , g , r = cv2.split(difference)    

image1 =cv2.resize(image1,(1000,600))
image2 =cv2.resize(image2,(1000,600))

print('Image1 Original Dimensions : ',image1.shape)
print('Image2 Original Dimensions : ',image2.shape)

difference = cv2.resize(difference,(1000,600))


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

for i in range(0, 3):
    dilated = cv2.dilate(gray.copy(), None, iterations= i+ 1)

(T, thresh) = cv2.threshold(dilated, 3, 255, cv2.THRESH_BINARY)

cnts = cv2.findContours(thresh, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
cnts = grab_contours(cnts)

for c in cnts:
# fit a bounding box to the contour
    (x, y, w, h) = cv2.boundingRect(c)
    cv2.rectangle(image2, (x, y), (x + w, y + h), (0, 255, 0), 2)



cv2.imshow("image1",image1)
cv2.imshow("image2",image2)
cv2.imwrite("changes.png", image2)

cv2.waitKey(0)