correlation

import numpy as np
from scipy import signal
from scipy.stats import pearsonr
from imageio import imread
import os
import random

# function to find the correlation between two images
def find_correlation(image1, image2):
  # read the images and convert them to grayscale
  img1 = imread(image1, as_gray=True)
  img2 = imread(image2, as_gray=True)

  # compute the correlation using scipy's built-in function
  correlation, pvalue = pearsonr(img1.flatten(), img2.flatten())

  return correlation

# select 100 random images from the folder
folder = "Path to Folder"
images = os.listdir(folder)
random.shuffle(images)
images = images[:100]

# compute the correlation with the target image
target_image = "path to target image"
correlations = []
for image in images:
  correlations.append(find_correlation(os.path.join(folder, image), target_image))

# print the correlations
print("The Correlations Mean : \n")
print(np.mean(correlations))