# -*- coding: utf-8 -*-

"""

Spyder Editor

"""

#importing things

import os

from skimage.feature import peak_local_max

from skimage.morphology import watershed

from scipy import ndimage

import numpy as np

import imutils

import cv2

#define image paths

infile = 'file path of original image'

outfile = 'file path of where you want to save the result'

#load image

image = cv2.imread(infile)

#convert to greyscale

grey = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

#thresholding

ret, thresh = cv2.threshold(grey, 49, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)

#watershed algorithm

D = ndimage.distance_transform_edt(thresh)

localMax = peak_local_max(D, indices=False, min_distance=20,

labels=thresh)

markers = ndimage.label(localMax, structure=np.ones((3, 3)))[0]

labels = watershed(-D, markers, mask=thresh)

for label in np.unique(labels):

if label == 0:

continue

mask = np.zeros(grey.shape, dtype="uint8")

mask[labels == label] = 255

contours = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,

cv2.CHAIN_APPROX_SIMPLE)

contours = imutils.grab_contours(contours)

# draw contours

drawn = cv2.drawContours(grey, contours, -1, (255,255,255), 1)

#drawing a rectangle in which text will live

x,y,w,h = 0,0,375,75

cv2.rectangle(drawn, (x,x), (x + w, y + h), (0,0,0), -1)

#displaying number of cells in picture

font = cv2.FONT_HERSHEY_DUPLEX

TopLeftCornerOfText = (10,10)

fontScale = 1

fontColor = (255,255,255)

lineType = 2

t = len(np.unique(labels))-1

s = 'number of cells: {0}'.format(t)

cv2.putText(drawn, s,

(x + int(w/10), y + int(h/2)),

font,

fontScale,

fontColor,

lineType)

# show the output image

cv2.imshow("result", drawn)

#save the output image

directory = outfile

os.chdir(directory)

filename = 'output.jpg'

cv2.imwrite(filename, drawn)

cv2.waitKey(0)