8kun ImageMangler 0.0.2

# The purpose of this script is to take an existing image file
# split it up into a grid and make a stochastic change to each piece
# then stitch the image back together and save it to a new file
# future versions will have extra layers of extra types of stochastic changes
# to defeat censorship, changes must be unpredictable more than they are numerous

# INSTALL - Only module to install is Pillow, an easy "pip install Pillow" should get you going.
# USAGE - Install python, save this script as qimg-5.py and image file in same folder.
# From terminal in the same folder run "python qimg-5.py"
# you should see the output as well as have a new saved file in the same folder
# TESTED using python 3.7.1

import sys
import random
from PIL import Image

# INIT - nothing to change here
sectors = {}
xslice = 0
yslice = 0
imgslice = {}

# CONFIG section
density = 6
# How small do we want to make the slices, bigger is more. Must be even number

cornerkiller = 0
# Set the above to 1 if you want blacked out corners, set it to 0 if you want more mangled corners

imagefile = "bantest.png"
# The name of the file you want to convert, must be in same folder as script

outputfile = "noban"
# Prefix for the saved file

# Work starts here, you change it, you break it

im = Image.open(imagefile)
res = im.size

wsize = (int((res[0]) / density))
hsize = (int((res[1]) / density))
for h in range(density):
    for i in range(density):
        wslice = (wsize + xslice)
        hslice = (hsize + yslice)
        sector = (xslice, yslice, wslice, hslice)
        sectors[i] = sector
        yslice += hsize
        if (h == 0 and i == 0) or (h == 0 and i + 1 == density) or (h + 1 == density and i == 0) or (h + 1 == density and i + 1 == density):
            imgslice[i] = im.crop(sectors[i]).effect_spread(random.randint(3,5))
            if cornerkiller == 1:
                im.paste('#000000', sectors[i])
            else:
                im.paste(imgslice[i], sectors[i])
        else:
            imgslice[i] = im.crop(sectors[i]).effect_spread(random.randint(1,5))
            im.paste(imgslice[i], sectors[i])
    i = 0
    xslice += wsize
    yslice = 0
    wslice = 0
    hslice = 0
im.save(outputfile + imagefile)
im.close()