This function is designed to generate comparison scores between two image using ssim from skimage.

comparison_scores_skimage.py

######################################################################################
# The concurrent.futures module is part of the standard Python library which provides 
# a high level API for launching asynchronous tasks.
######################################################################################
import concurrent.futures

#############################################################################################
# The OS module in provides functions for interacting with the operating system.
#
# os.path() provides various functions to handle pathnames.
# os.walk() generate the file names in a directory tree by walking the tree.
#############################################################################################
from os import path, walk

#############################################################################################
# The scikit-image module has a collection of algorithms for image processing.
#
# skimage.io.imread - load an image from a file.
#
# skimage.transform.resize - resizes an image to match a certain size.
# 
# skimage.metrics.structural_similarity - compute the mean structural similarity index 
# between two images.
#############################################################################################
from skimage.io import imread
from skimage.transform import resize
from skimage.metrics import structural_similarity as ssim


def determine_image_similarities(base_image, comparison_image):
    """
    Determine the computational score associated with two different images
    :param base_image: 
    :param comparison_image: 
    :return: comparison score
    """
    computational_score = ssim(base_image, comparison_image)
    return computational_score

image_folder = 'image_directory'

# https://scikit-image.org/docs/dev/api/skimage.transform.html?highlight=skimage%20transform%20resize#skimage.transform.resize
ref_image = resize(imread('base_image_name.jpeg', as_gray=True), (128, 128), preserve_range=True, mode='constant')

with concurrent.futures.ThreadPoolExecutor(max_workers=10) as thread_pool_executor:
    for (directory_path, directory_names, file_names) in walk(image_folder):
       for file_name in file_names:
          accepted_extensions = ('.bmp', '.gif', '.jpg', '.jpeg', '.png', '.svg', '.tiff')
          if file_name.endswith(accepted_extensions):
            compare_image = resize(imread(path.join(directory_path, file_name), as_gray=True), (128, 128), preserve_range=True, mode='constant')
            args = (ref_image, compare_image)
            future = [thread_pool_executor.submit(lambda p: determine_image_similarities(*p), args)]
            for hash_to_compare in concurrent.futures.as_completed(future):
               print(hash_to_compare)