learnopencv/CenterofBlob/center_of_multiple_blob.py

import cv2
import numpy as np
import argparse

# create object to pass argument
arg_parse = argparse.ArgumentParser()
arg_parse.add_argument("-i", "--ipimage", required=True,
	help="input image path")
args = vars(arg_parse.parse_args())

# read image through command line 
img = cv2.imread(args["ipimage"])
# convert the image to grayscale
gray_image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# convert the grayscale image to binary image
ret,thresh = cv2.threshold(gray_image,127,255,0)

# find contour in the binary image
im2, contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
for c in contours:
	# calculate moments for each contour
	M = cv2.moments(c)
	cX = int(M["m10"] / M["m00"])
	cY = int(M["m01"] / M["m00"])
	
	
    # calculate x,y coordinate of center
	cv2.circle(img, (cX, cY), 5, (255, 255, 255), -1)
	cv2.putText(img, "centroid", (cX - 25, cY - 25),cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2)
	# display the image
	cv2.imshow("Image", img)
	cv2.waitKey(0)

# 3.4.1 im2, contours, hierarchy = cv.findContours(thresh, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
# 3.2.0 im2, contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)