from difflib import SequenceMatcher

def similarity_per(f1,f2):

with open(f1,errors="ignore") as file1,open(f2,errors="ignore") as file2:

file1_data=file1.read()

file2_data=file2.read()

similarity=SequenceMatcher(None,file1_data,file2_data).ratio()

print(f"these 2 files are {similarity*100} % similar")

if __name__ == '__main__':

f1=input("file 1 path :")

f2=input("file 2 path :")

similarity_per(f1,f2)

in the `main.py` file edit the following items:

"<input folder>",

"<output folder>",

"<watermark image>"

using the input folder path to loop over all images and output them to outputfolder.

Best practise is to use a image with transparent background.

import os

import sys

from os.path import join

from PIL import Image, ImageEnhance

def FolderSelectAndRun():

batch(

"<input folder>",

"<output folder>",

"<watermark image>"

)

basewidth = 2048

def batch(infolder, outfolder, watermark):

mark = Image.open(watermark)

count = 0

for root, dirs, files in os.walk(infolder):

for name in files:

try:

count += 1

im = Image.open(join(root, name))

# New image in the making

layer = Image.new('RGBA', im.size, (0, 0, 0, 0))

position = (im.size[0] - (mark.size[0] + 50),

im.size[1] - (mark.size[1] + 50))

layer.paste(mark, position)

new_image = Image.composite(layer, im, layer)

# Resize in perspective

wpercent = (basewidth / float(im.size[0]))

hsize = int((float(new_image.size[1]) * float(wpercent)))

smaller_new_image = new_image.resize(

(basewidth, hsize), Image.ANTIALIAS)

# Save new smaller image

smaller_new_image.save(

join(outfolder, ('with-watermark_' + name)), 'jpeg')

except Exception as error:

# Debug line while making changes

print('Caught this error: ' + repr(error))

if __name__ == '__main__':

FolderSelectAndRun()