import numpy as np
import cv2
from matplotlib import pyplot as plt
img = cv2.imread('water_coins.jpg')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

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

cimg = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
plt.imshow(cimg)
plt.show()
plt.imshow(thresh)
plt.show()

# noise removal
kernel = np.ones((3,3),np.uint8)
opening = cv2.morphologyEx(thresh,cv2.MORPH_OPEN,kernel, iterations = 2)
# sure background area
sure_bg = cv2.dilate(opening,kernel,iterations=3)
# 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)
# Finding unknown region
sure_fg = np.uint8(sure_fg)
unknown = cv2.subtract(sure_bg,sure_fg)

plt.imshow(dist_transform)
plt.show()
plt.imshow(unknown)
plt.show()

# Marker labelling
ret, markers = cv2.connectedComponents(sure_fg)
# Add one to all labels so that sure background is not 0, but 1
markers = markers + 10
# Now, mark the region of unknown with zero
markers[unknown==255] = 0

print('markers')
plt.imshow(markers)
plt.show()

water_markers = cv2.watershed(img,markers)
print('water_markers')
plt.imshow(water_markers)
plt.show()


cimg[water_markers == -1] = [255,0,0]

plt.imshow(cimg)
plt.show()