Computing Distance Between Two Pixels in an Image Using Different Distance Metrics in Python

import cv2
import numpy as np
import math

def euclidean_distance(p, q):
    return math.sqrt((q[0] - p[0]) ** 2 + (q[1] - p[1]) ** 2)

def city_block_distance(p, q):
    return abs(q[0] - p[0]) + abs(q[1] - p[1])

def chessboard_distance(p, q):
    return max(abs(q[0] - p[0]), abs(q[1] - p[1]))

# Load the image
image = cv2.imread('image.jpg')

# Check if the image is loaded successfully
if image is None:
    print("Error: Could not load the image.")
    exit()

# Specify the pixel coordinates
p = (50, 50)
q = (100, 100)

# Calculate distances
euclidean = euclidean_distance(p, q)
city_block = city_block_distance(p, q)
chessboard = chessboard_distance(p, q)

# Display the results
print(f"Euclidean Distance between {p} and {q}: {euclidean}")
print(f"City Block (Manhattan) Distance between {p} and {q}: {city_block}")
print(f"Chessboard (Chebyshev) Distance between {p} and {q}: {chessboard}")

# Display the image with the selected pixels
cv2.circle(image, p, 5, (0, 0, 255), -1)  # Red circle at pixel p
cv2.circle(image, q, 5, (255, 0, 0), -1)  # Blue circle at pixel q
cv2.imshow('Image with Selected Pixels', image)
cv2.waitKey(0)
cv2.destroyAllWindows()