# In Class
# Your Name: Kenneth Liang
# GTID: 902 798 997
# Your Name: Katie Sclafani
# GTID: 902 913 547

import cv2
import numpy as np
import scipy as sp

# findGrout stores locations where there is grout. It returns an array of 1s and 0s the size of the image, with 0s representing grout.
def findGrout(wallHSV):
   # The upper and lower values of grout color should be defined here, iteratively tweaked
   lower_grout_color = np.array([0,0,100], dtype=np.uint8)
   upper_grout_color = np.array([28,100,255], dtype=np.uint8)
   groutMask = cv2.inRange(wallHSV, lower_grout_color, upper_grout_color)
   cv2.imwrite("groutMask.jpg",groutMask)
   return groutMask

def mergeImgs(inWall, inPaint, inMask):
   # using the input mask and the inverse of that, the hue and saturation values of the paint image are mapped onto the bricks of the wall
   outImg = np.zeros(inWall.shape)
   invertMask = np.invert(inMask)/255
   inMask = inMask/255
   outImg[:,:,0] = inWall[:,:,0]*inMask[:,:] + inPaint[:,:,0]*invertMask[:,:]
   outImg[:,:,1] = inWall[:,:,1]*inMask[:,:] + inPaint[:,:,1]*invertMask[:,:]
   outImg[:,:,2] = inWall[:,:,2]*inMask[:,:] + inPaint[:,:,2]*invertMask[:,:]
   outImg = np.uint8(outImg)
   return outImg
   
def paintWall(inWall, inPaint):
   wallHSV = cv2.cvtColor(inWall, cv2.COLOR_BGR2HSV)
   paintHSV = cv2.cvtColor(inPaint, cv2.COLOR_BGR2HSV)
   groutMask = findGrout(wallHSV)
   mergedImg = mergeImgs(wallHSV, paintHSV, groutMask)
   outImg = cv2.cvtColor(mergedImg, cv2.COLOR_HSV2BGR)
   outImg = cv2.GaussianBlur(outImg,(5,5),1.7)
   return outImg

image1 = cv2.imread("brick5.JPG")
image2 = cv2.imread("streetArtCollage.jpg")
outImage = paintWall(image1, image2)
cv2.imwrite("mergeImage.jpg",outImage)