How to count objects in image using python?

Question

I am trying to count the number of drops in this image and the coverage percentage of the area covered by those drops. I tried to convert this image into black and white, but the center color of those drops seems too similar to the background. So I only got something like the second picture. Is there any way to solve this problem or any better ideas? Thanks a lot.

Answer 1

You can fill the holes of your binary image using scipy.ndimage.binary_fill_holes. I also recommend using an automatic thresholding method such as Otsu's (avaible in scikit-image).

from skimage import io, filters
from scipy import ndimage
import matplotlib.pyplot as plt

im = io.imread('ba3g0.jpg', as_grey=True)
val = filters.threshold_otsu(im)
drops = ndimage.binary_fill_holes(im < val)
plt.imshow(drops, cmap='gray')
plt.show()

For the number of drops you can use another function of scikit-image

from skimage import measure
labels = measure.label(drops)
print(labels.max())

And for the coverage

print('coverage is %f' %(drops.mean()))

Answer 2

I used the following code to detect the number of contours in the image using OpenCV and python.

import cv2
import numpy as np
img = cv2.imread('ba3g0.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret,thresh = cv2.threshold(gray,127,255,1)
contours,h = cv2.findContours(thresh,1,2)
for cnt in contours:
    cv2.drawContours(img,[cnt],0,(0,0,255),1)

For further removing the contours inside another contour, you need to iterate over the entire list and compare and remove the internal contours. After that, the size of "contours" will give you the count