import numpy as np
import cv2
from matplotlib import pyplot as plt
img = cv2.imread('images/source/touch1.png')
#scale
#height, width = img.shape[:2]
#img = cv2.resize(img,(width/2, height/2), interpolation = cv2.INTER_CUBIC)

cv2.imshow('Main',img)
cv2.waitKey(0)
cv2.destroyAllWindows()

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

cv2.imshow('Gray',gray)
cv2.waitKey(0)
cv2.destroyAllWindows()


ret, thresh = cv2.threshold(gray,0,255,cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)

# noise removal
kernel = np.ones((3,3),np.uint8)
opening = cv2.morphologyEx(thresh,cv2.MORPH_OPEN,kernel, iterations = 2)

cv2.imshow('opening',opening)
cv2.waitKey(0)
cv2.destroyAllWindows()

"""""
opening = cv2.bitwise_not(opening)

cv2.imshow('Bitwise Not opening',opening)
cv2.waitKey(0)
cv2.destroyAllWindows()
"""""
# sure background area
sure_bg = cv2.dilate(opening,kernel,iterations=3)

cv2.imshow('sure_bg',sure_bg)
cv2.waitKey(0)
cv2.destroyAllWindows()

# Finding sure foreground area
dist_transform = cv2.distanceTransform(opening,cv2.DIST_L2,5)
ret, sure_fg = cv2.threshold(dist_transform,0.7*dist_transform.max(),255,0)

cv2.imshow('sure_fg',sure_fg)
cv2.waitKey(0)
cv2.destroyAllWindows()

# Finding unknown region
sure_fg = np.uint8(sure_fg)
unknown = cv2.subtract(sure_bg,sure_fg)

cv2.imshow('unknown',unknown)
cv2.waitKey(0)
cv2.destroyAllWindows()

# Marker labelling
ret, markers = cv2.connectedComponents(sure_fg)

# Add one to all labels so that sure background is not 0, but 1
markers = markers+1

# Now, mark the region of unknown with zero
markers[unknown==255] = 0
markers = cv2.watershed(img,markers)
img[markers == -1] = [0,0,255]  #the boundaries of objects will have a value of -1
cv2.imshow('Final Segmentation',img)
cv2.waitKey(0)
cv2.destroyAllWindows()
