In this tutorial, you will learn how you can count the number of objects on an image with Python using CV2.
This is our test image:
Let's jump to the code:
First we need to import our dependencies:
import cv2
import numpy as np
First we need to read our image:
img = cv2.imread('test.jpg')
then we will be converting it into grayscale
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
after that, we doing thresholding on image
_, thresh = cv2.threshold(img, 225, 255, cv2.THRESH_BINARY_INV)
kernal = np.ones((2, 2), np.uint8)
then we are doing dilation process, removing black distortion:
dilation = cv2.dilate(thresh, kernal, iterations=2)
next step is finding contour shapes:
contours, hierarchy = cv2.findContours(
dilation, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
Then we are getting number of contours (objects found):
objects = str(len(contours))
We can now print number of objects on an image
text = "Obj:"+str(objects)
cv2.putText(dilation, text, (10, 25), cv2.FONT_HERSHEY_SIMPLEX,
0.4, (240, 0, 159), 1)
For the lasr step we can show, original, threshold and dilation image:
cv2.imshow('Original', img)
cv2.imshow('Thresh', thresh)
cv2.imshow('Dilation', dilation)
cv2.waitKey(0)
cv2.destroyAllWindows()
This is our final result:
Thank you all.
Top comments (2)
Nice step-by-step explanations.
Good job
Thanks😀