The other night I had a wacky idea of extracting each pixel from an image in order to save it as a plain text ASCII file.
Of course this is not ideal and can take a bit of time, but like most things I do with python its just for the fun of it.
I began to write a simple piece of code to extract each pixel from an image.
First off we need to import a few external libraries to assist:
#!/usr/bin/env python import Image import argparse import pickle
In order to give us some useful –help output I used argparse to take input:
parser = argparse.ArgumentParser() parser.add_argument('filename', help='Image to extract') parser.add_argument('output', help='Output file') args = parser.parse_args()
Once we have our file name we can load the image using PIL and grab the size of image:
im = Image.open(args.filename) width, height = im.size
Here we have to have some way to keep track of our Y and X Axis of pixels, we can do this with a couple strings:
y_cursor = 0 x_cursor = 0
We will need something to hold the data we collect, why not a list:
image = 
This block is a bit more complex, but all we are doing is stepping through each pixel kind of like a typewriter would do when writing a document. We are using the getpixel method from PIL to extract the pixels RGB information:
print 'Processing %s...' % args.filename while y_cursor < height: row =  while x_cursor < width: row.append(im.getpixel((x_cursor, y_cursor))) x_cursor += 1 x_cursor = 0 y_cursor += 1 image.append(row)
And lastly we will save all the captured data to a pickle file:
f = open(args.output, 'wb') pickle.dump(image, f)
Once this small script was created I attempted to serialize a JPEG image:
The details of the image are:
$ ls -lh mox.jpg -rw-r--r--@ 1 user staff 870K Nov 10 08:56 mox.jpg
And after running the above Python script I got a ASCII file of:
$ ls -lh output -rw-r--r-- 1 user staff 28M Nov 10 08:56 output
Yes, this made me chuckle. Going from 870K binary JPEG to 28M ASCII text, but as mentioned this is just a proof of concept.
The serialized data ended up being quite a few lines, 4916161 to be exact:
$ wc -l output 4916161 output
Lets go ahead and take a peak at the un-serialized data:
>>> import pickle >>> f = open('output', 'rb') >>> image = pickle.load(f) >>> >>> len(image) 960 >>> >>> len(image) 1280 >>> >>> image (40, 43, 34) >>> >>> image [(40, 43, 34), (39, 42, 33), (42, 45, 36), (41, 44, 35), (40, 43, 34), (38, 41, 32), .....
Now all that was left was to write another small script to take this ASCII content and turn it back in to a image.
Like before we will import our libraries and use argparse to take input:
#!/usr/bin/env python import Image import argparse import pickle parser = argparse.ArgumentParser() parser.add_argument('filename', help='Extracted Pickle File') parser.add_argument('output', help='Output Filename') args = parser.parse_args()
Since we have the filename from argparse we need to read it and parse it through pickle :
f = open(args.filename, 'rb') image = pickle.load(f)
Using the concept of one list per row I can determine the width and height of the original image via len:
height = len(image) width = len(image) size = (width, height)
Now we are ready to create the image container and reset our cursors to start position:
im = Image.new('RGB', size) # define our cursors to # parse over the images pixel by pixel y_cursor = 0 x_cursor = 0
Just like before use a typewriter motion to add to each pixel, here we use the PIL method putpixel :
print 'Building %s...' % args.output while y_cursor < height: while x_cursor < width: pixel = image[y_cursor][x_cursor] im.putpixel((x_cursor, y_cursor), pixel) x_cursor += 1 x_cursor = 0 y_cursor += 1
And lastly save the Image to our output file name:
$ ls -lh new_mox.png -rw-r--r-- 1 user staff 1.7M Nov 10 09:05 new_mox.png