How to find the average diameter of the drops in an image. The drops on the image are raindrops, and the strip on which drops are superimposed has a size of 260 mm x 6.2 mm. This strip length and breadth could be considered a reference (perspective) size and can be used to measure the drop diameter or length of the x and y axes in mm. Also, how to label each drop with its diameter?

image = cv2.imread("1.png")
gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
# create a binary thresholded image
_, binary = cv2.threshold(gray, 225, 255, cv2.THRESH_BINARY_INV)
# show it

# find the contours from the thresholded image
contours, hierarchy = cv2.findContours(binary, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# draw all contours

for contour in contours:
    if (cv2.contourArea(contour) < 3000) & (cv2.contourArea(contour) > 4):
        image = cv2.drawContours(image, contours, -1, (1, 1, 1), 1)

        circles = image.copy()
        num_circles = len(contours)
        ave = 0
        rds = []
        center, radius = cv2.minEnclosingCircle(contour)
        cx = int(round(center[0]))
        cy = int(round(center[1]))
        rr = int(round(radius))
        # draw enclosing circle over beads
    #     cv2.circle(circles, (cx,cy), rr, (1,1,1), 1)
        # cumulate radii for average
        ave = ave   radius
        rds.append(rr)

# print average radius
ave_radius = ave / num_circles
print("average radius:", ave_radius)
print ("number of circles:", num_circles)

cv2.imwrite('beads_circles.jpg', circles)
plt.imshow(circles)
plt.show()

Here is the output

CodePudding user response：

import numpy as np
import matplotlib.pyplot as plt
import cv2
import glob
import os

img = cv2.imread("pip_ims/52.png")

image = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
# create a binary thresholded image
_, binary = cv2.threshold(gray, 225, 255, cv2.THRESH_BINARY_INV)

# find the contours from the thresholded image
contours, hierarchy = cv2.findContours(binary, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
dia_mm = []
for contour in contours:
    #image = cv2.drawContours(image, contours, -1, (1, 1, 1), 3)
    area = cv2.contourArea(contour)
    dia = 2*(area/np.pi)**(0.5) # calculating diameter from area
    print(dia)
    diamm = dia*(6.2/64) # converting diameter from pixels to mm
    dia_mm.append(diamm)
    print(diamm)
diameter = list(filter(lambda num: num != 0, dia_mm)) # removing zeros
diameter = np.array(diameter)
print(diameter.mean(), diameter.max(), diameter.min())