# Jay Summet
#Calculating the difference/error between a 100 pixel "overlap"
#strip of two images.


import cv2
import numpy as np


#Used for final output display
def scaleTo8Bit(image, displayMin = None, displayMax=None ):

   if displayMin == None:
       displayMin = np.min(image)

   if displayMax == None:
      displayMax = np.max(image)

   np.clip(image, displayMin, displayMax, out=image)

   image = image - displayMin
   cf = 255. / (displayMax - displayMin)
   imageOut = ( cf * image).astype(np.uint8)

   return imageOut




#Linux window/threading setup code.
cv2.startWindowThread()
cv2.namedWindow("A")
cv2.namedWindow("B")
cv2.namedWindow("Error")

A = cv2.imread("A.jpg", cv2.IMREAD_GRAYSCALE)
B = cv2.imread("B.jpg", cv2.IMREAD_GRAYSCALE)

#Select the 100 rightmost pixels of A and leftmost of B:
A100 = A[:, -100: ]
B100 = B[:, 0:100 ]

#Display the output
cv2.imshow("A", A100)
cv2.imshow("B", B100)

#Convert to float:

A100 = A100.astype(float)
B100 = B100.astype(float)

diff = A100-B100
diff = np.square(diff)

error = scaleTo8Bit(diff)

cv2.imshow("Error", error)
cv2.imwrite("overlap_error.png", error)
cv2.waitKey(0)