# Example showing how to add/subtract/multiply image values together
# using numpy array math (not per pixel iteration...)
#
# We use a higher bit depth format to avoid underflow/overflow)
# and then convert back to an 8bit image.
#
# Python 2.7, OpenCV 2.4.X
#
# Jay Summet - Summer 2015
#
import cv2
import numpy as np


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
 


a = cv2.imread("a.jpg")
b = cv2.imread("b.jpg")

#Doing math with uint8 images will suffer from overflow and underflow!
#so we change the data type to int32 

a = np.int32(a)
b = np.int32(b)


c = scaleTo8Bit(a)
cv2.imshow("A", c)
cv2.waitKey(0)

c = scaleTo8Bit(b)
cv2.imshow("B", c)

#Pure subtraction:
c = a-b

#But we must convert back to uint8 if we want to display correctly!
c = scaleTo8Bit(c)
cv2.imshow("pure subtract", c)

c = a+b
c = scaleTo8Bit(c)
cv2.imshow("add", c)

c = a+b/2
c = scaleTo8Bit(c)
#cv2.imshow("avg", c)


c = np.minimum(a,b)
c = scaleTo8Bit(c)
cv2.imshow("min", c)

c = np.maximum(a,b)
c = scaleTo8Bit(c)
cv2.imshow("max", c)

ONE = np.ones( a.shape)
ONE = ONE * 255

c = ONE - (ONE-a ) * (ONE-b)
c = scaleTo8Bit(c)
cv2.imshow("screen",c)
cv2.waitKey(0)