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

  pip install scikit-image opencv-python
  pip install python-phash

Comparing Images using SSIM (Structural Similarity Index):

import cv2
import numpy as np
from skimage import measure

# Load images

img1 = cv2.imread('image1.jpg', 0)  # grayscale
img2 = cv2.imread('image2.jpg', 0)  # grayscale

# Ensure both images have the same dimensions

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

# Compute SSIM

ssim = measure.compare_ssim(img1, img2)

print("SSIM:", ssim)

Comparing Images using pHash (Perceptual Hashing):

import phash

# Load images

img1 = cv2.imread('image1.jpg')
img2 = cv2.imread('image2.jpg')

# Compute pHash

hash1 = phash.dct_image_hash(img1)
hash2 = phash.dct_image_hash(img2)

# Compare hashes

distance = hamming_distance(hash1, hash2)

print("Hamming Distance:", distance)