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With Python, comparing image using Structural Similarity Index (SSIM) or using a perceptual hashing algorithm like pHash.

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pip install scikit-image opencv-python

pip install python-phash

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Comparing Images using SSIM (Structural Similarity Index):

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import cv2

import numpy as np

from skimage import measure

1. Load images

img1 = cv2.imread('image1.jpg', 0) # grayscale

img2 = cv2.imread('image2.jpg', 0) # grayscale

1. Ensure both images have the same dimensions

assert img1.shape == img2.shape, "Images must have the same dimensions"

1. Compute SSIM

ssim = measure.compare_ssim(img1, img2)

print("SSIM:", ssim)

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Comparing Images using pHash (Perceptual Hashing):

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import phash

1. Load images

img1 = cv2.imread('image1.jpg')

img2 = cv2.imread('image2.jpg')

1. Compute pHash

hash1 = phash.dct_image_hash(img1)

hash2 = phash.dct_image_hash(img2)

1. Compare hashes

distance = hamming_distance(hash1, hash2)

print("Hamming Distance:", distance)

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