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Python

import cv2
import numpy as np
# Load the image
image_path = '555020.jpg' # replace with your image path
image = cv2.imread(image_path)
# Convert to grayscale
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Apply thresholding to get binary image
_, binary = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY)
# Find contours of the white regions
contours, _ = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# Draw contours on the original image (optional, for visualization)
for contour in contours:
cv2.drawContours(image, [contour], -1, (0, 255, 0), 2)
# Print positions of the white regions
for i, contour in enumerate(contours):
x, y, w, h = cv2.boundingRect(contour)
if w > 100:
print(f"White region {i+1}: x={x}, y={y}, width={w}, height={h}")
# Show the image with contours (optional, for visualization)
cv2.imshow('White regions', image)
cv2.waitKey(0)
cv2.destroyAllWindows()