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Here is counting object:

#!/usr/bin/python35
#OpenCV 3.3.1
#Date: 29th October, 2017

import cv2
import numpy as np
import sys

src = cv2.imread(fn, 1)
img = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
img = cv2.medianBlur(img, 5)
cimg = src.copy() # numpy function

circles = cv2.HoughCircles(img, cv2.HOUGH_GRADIENT, 1, 10, np.array([]), 100, 30, 1, 30)    

![image description](/upfiles/15092856528003828.jpg)if circles is not None: # Check if circles have been found and only then iterate over these and add them to the image
a, b, c = circles.shape
for i in range(b):
    cv2.circle(cimg, (circles[0][i][0], circles[0][i][1]), circles[0][i][2], (0, 0, 255), 3, cv2.LINE_AA)
    cv2.circle(cimg, (circles[0][i][0], circles[0][i][1]), 2, (0, 255, 0), 3, cv2.LINE_AA)  # draw center of circle of green
    print(i)

cv2.imshow("detected circles", cimg)
cv2.imshow("source", src)
cv2.waitKey(0)

Here is counting object:

#!/usr/bin/python35
#OpenCV 3.3.1
#Date: 29th October, 2017

import cv2
import numpy as np
import sys

src = cv2.imread(fn, 1)
img = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
img = cv2.medianBlur(img, 5)
cimg = src.copy() # numpy function

circles = cv2.HoughCircles(img, cv2.HOUGH_GRADIENT, 1, 10, np.array([]), 100, 30, 1, 30)    

![image description](/upfiles/15092856528003828.jpg)if circles is not None: # Check if circles have been found and only then iterate over these and add them to the image
a, b, c = circles.shape
for i in range(b):
    cv2.circle(cimg, (circles[0][i][0], circles[0][i][1]), circles[0][i][2], (0, 0, 255), 3, cv2.LINE_AA)
    cv2.circle(cimg, (circles[0][i][0], circles[0][i][1]), 2, (0, 255, 0), 3, cv2.LINE_AA)  # draw center of circle of green
    print(i)

cv2.imshow("detected circles", cimg)
cv2.imshow("source", src)
cv2.waitKey(0)

Here is counting object:

#!/usr/bin/python35
#OpenCV 3.3.1
#Date: 29th October, 2017

import cv2
import numpy as np
import sys

src = cv2.imread(fn, 1)
cv2.imread('board.jpg')
img = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
img = cv2.medianBlur(img, 5)
cimg = src.copy() # numpy function

circles = cv2.HoughCircles(img, cv2.HOUGH_GRADIENT, 1, 10, np.array([]), 100, 30, 1, 30)    

![image description](/upfiles/15092856528003828.jpg)if circles is not None: # Check if circles have been found and only then iterate over these and add them to the image
a, b, c = circles.shape
for i in range(b):
    cv2.circle(cimg, (circles[0][i][0], circles[0][i][1]), circles[0][i][2], (0, 0, 255), 3, cv2.LINE_AA)
    cv2.circle(cimg, (circles[0][i][0], circles[0][i][1]), 2, (0, 255, 0), 3, cv2.LINE_AA)  # draw center of circle of green
    print(i)

cv2.imshow("detected circles", cimg)
cv2.imshow("source", src)
cv2.waitKey(0)

C:\fakepath\board.jpg