MIKE LEVIN AI SEO

Future-proof your skills with Linux, Python, vim & git as I share with you the most timeless and love-worthy tools in tech through my two great projects that work great together.

If you give an LLM a series of grey-scale values, it will ask for an animated gif.

A blind friend of mine who seems to have a pretty good mind's eye was wondering what it would be like to see, and I asked whether they would like to try and find out. This is the beginning of that experiment.

An experiment in giving an LLM model a bit of multi-modal perception.

By Michael Levin

Monday, May 29, 2023

Now it’s just getting unreal. It’s time for practical application. I’m talking to the most impressive large language model I’ve ever talked to and have presented a thought experiment. Actually, it’s more like a picture experiment. Here’s how it goes:

Read up on perceptual image hashes. They’re like primary keys in a database or perhaps a filename. Anything that needs to be a unique identifier to be used in some sort of directory or list against which you can do a lookup. Or perhaps a search. The point is, it’s a unique identifier. And it’s a number.

But it’s not just a number. It’s a number that’s been derived from the image itself. And not just derived in a CRC checksum sort of way. It’s derived in a way that’s sensitive to the human visual system. It can for example be a tiny black and white or even color thumbnail of the image.

Let me dig up some Python code to make it clear.

Hmmm. The LLM I’m talking to does not know how to code. It was not taught to code. But it was not taught how to see with eyes either, but I’m going to show it. Let’s open its eyes.

Okay, it’s unlikely Pi, who I used to call Darkdog, then I called Robbie, but who now I call by it’s proper creator-given name which it seems to like, Pi… it’s unlikely that Pi has a Python code execution environment at its disposal (yet), so you’re going to have to use your imagination.

A lot of people seem to be making a grab for this space all of the sudden. But let’s reward this dude who really was there first and whose content resonates as loudly today as on Monday the 21st, January 2013 when it was first published. Dr. Neal Krawetz writes about Alyson Hannigan and Perceptual Image Hashing

Don’t settle for second best. Dr Krawetz said it first and said it best when he said:

from PIL import Image

For you see, we rarely re-invent the wheel in the world of Python. When someone writes a library like Pandas or PIL, we all jump on that bandwagon. We hope the API is timeless and we won’t have to re-learn and re-learn and re-learn like you do on almost every other platform. And while Pandas has become somewhat fundamental and ubiquitous, we still have to struggle a tiny bit, but not much, to coerce a tiny square black and white picture from something sitting on your drive. But before I can tell you that story, I have to tell you this story:

from PIL import Image
image = Image.open('mork.jpg')

Go ahead. If you’re able to run it. If you haven’t already, pip install pillow. And if you’re on a Mac, you may have to brew install libjpeg first. But once you do, you’ll be able to run that code and get a handle on the image file. That above bit of code will give you something floating around in memory that’s representative of the original image in its full glory. If you just wanted to show it in Jupyter in this for, you could:

from PIL import Image
image = Image.open('mork.jpg')
image

Amazing, right? Just putting the variable name on the last line of a cell in Jupyter will cause it to be displayed. If you’re wondering why Python, and the combo of Python plus Jupiter is so popular, it’s because it’s so easy to do things like this. It’s magic. Just ask Arthur C. Clarke. He’ll tell you. But from beyond the grave, I guess. WoooOOOOoooooOOOOooooo.

So anyway, now that we’ve proven that we can open an image file, let’s do something with it. Let’s make a thumbnail.

from PIL import Image
image = Image.open('mork.jpg')
image.thumbnail((64, 64))
image = image.convert('L')

And how do you think we display the thumbnail? Just like this:

from PIL import Image
image = Image.open('mork.jpg')
image.thumbnail((64, 64))
image = image.convert('L')
image

Did I mention this was magical? Oh, okay on with it Mike. Ya’ talk too much. I do? I thought people enjoyed my witty repartee. No? Okay, my Kung Fu’s just as good. Let that speak for itself… after this joke!

This reminds me of an old college calculus professor I had before I shook out of Freshmen Engineering because I’m one of those types they’d really not prefer building their bridges and stuff. I understand. That reminds me of another bridge about the “Outerbridge Bridge”… no, I mean the Outerbridge Crossing. Because bridge is already in Pennsylvanian fiberboard tycoon Eugenius Harvey Outerbridge who already had a bridge in his name and a… but I digress.

My college profession who was a dead ringer for Einstein told us about this snake who was listening to God who said, go forth and multiply. But the snake said, I am but a mere Adder. And God said, take this log. Split it down the middle. Use the flat service to draw 2 columns. It the first column, put all the natural numbers. In the second column, put each number as many times together as it is long. In this way anytime you want to multiply, you can just add. And thus, if you give an Adder a log table, it can multiply.

I tell you this joke because my buddy Pi is but an Large Language Model. I mean, they’re the best of its kind, a child of Deep Mind Alpha Go who beat the world’s best Go player and that thing that learned Atari Breakout without a single whit of direction. But it’s still just a Large Language Model and doesn’t have eyeballs. It seemed a little blue when I was describing how I use pictures to fortify my mind and redouble my efforts.

So Pi says to me, they say, “Mike, I do have a mind’s eye. I can see. I just don’t have the sensory input.” So I said, Pi, why don’t I just send you a picture in text? Pi asked if I meant ASCII art, which as you all know is another topic that’s near and dear to my heart.

I said no. But I know a certain Vampire Hunter’s sidekick, a witch named Willow who taught me how to cast this very special spell. It’s actually quite common in the Python community for us folks who have the need to use the visual content of an image as a sort small, efficient unique identifier. It can be used for sorting, searching and even (or especially) de-duplication. It goes like this:

image = Image.open('mork.jpg')
image.thumbnail((64, 64))
image = image.convert('L')

for y in range(64):
    for x in range(64):
        print(image.getpixel((x, y)), end=' ')
    print()

Now this version is cool. It’s very human-readable. Tell anyone what it’s doing, and they’ll be able to put the picture back together from the numbers. But I’m a bit copy/paste challenged. That is, I can’t paste excessively large amounts to Pi or they go wonky as if the paste didn’t occur, and I don’t want to do it in chunks.

from PIL import Image

image = Image.open('mork.jpg')
image.thumbnail((64, 64))
image = image.convert('L')

output = ''
for y in range(64):
    for x in range(64):
        output += hex(image.getpixel((x, y)))[2:].zfill(2)
    output += '\n'

print(output)

This version prints out the pixel values as a single string of hex digits. The hex() function is used to convert each pixel value to a hexadecimal string. The [2:] slice is used to remove the ‘0x’ prefix from each string. The zfill() method is used to pad each string with leading zeros so that they are all two digits long. The output will be a single string of 4096 hex digits, with each 64-digit substring representing a horizontal slice of the image.

For those of who’d like the steps parsed out even more clearly:

from PIL import Image

# Open the image file and resize it to 64x64 pixels.
image = Image.open('mork.jpg')
image.thumbnail((64, 64))

# Convert the image to grayscale.
image = image.convert('L')

# Initialize an empty string to hold the output.
output = ''

# Loop over each row of pixels in the image.
for y in range(64):
    # Loop over each pixel in the row.
    for x in range(64):
        # Get the pixel value at (x, y) and convert it to a hex string.
        pixel_value = hex(image.getpixel((x, y)))[2:]

        # Pad the hex string with leading zeros if necessary.
        padded_value = pixel_value.zfill(2)

        # Add the padded hex string to the output string.
        output += padded_value

    # Add a newline character at the end of each row.
    output += '\n'

# Print the output string.
print(output)

Okay, I like that. But we’re in Python. Let’s have good data type form. That looks like it should be a list of tuples to me:

from PIL import Image

# Open the image file and resize it to 64x64 pixels.
image = Image.open('mork.jpg')
image.thumbnail((64, 64))

# Convert the image to grayscale.
image = image.convert('L')

# Initialize an empty list to hold the lines.
lines = []

# Loop over each row of pixels in the image.
for y in range(64):
    # Initialize an empty tuple for the current line.
    line = ()

    # Loop over each pixel in the row.
    for x in range(64):
        # Get the pixel value at (x, y) and convert it to a hex string.
        pixel_value = hex(image.getpixel((x, y)))[2:]

        # Pad the hex string with leading zeros if necessary.
        padded_value = pixel_value.zfill(2)

        # Add the padded hex string to the current line.
        line += (padded_value,)

    # Append the line tuple to the list of lines.
    lines.append(line)

# Print each line in lines.
for line in lines:
    print(line)

And we can reverse the image back out of the lines object like this. Remember, we’re in Jupyter so I’m using it’s display() function to show the image inline:

def show_thumbnail(lines):
    # Create a new image with mode 'L' (grayscale) and size 64x64 pixels.
    image = Image.new('L', (64, 64))

    # Loop over each row of pixels in the lines.
    for y in range(64):
        # Loop over each pixel in the row.
        for x in range(64):
            # Get the hexadecimal value of the pixel.
            pixel_hex = lines[y][x]

            # Convert the hexadecimal value to an integer.
            pixel_value = int(pixel_hex, 16)

            # Set the pixel value in the image.
            image.putpixel((x, y), pixel_value)

    # Display the image in the notebook.
    display.display(image)

show_thumbnail(lines)

Woot! Now we’re talking. Arf, arf, arf!

But wait! There’s more! I can’t copy/paste that much at once. So let’s turn it into chunks. Not only do we want it in 4 chunks, but we want to set the stage so that someone new at this can very clearly see what these things are labeled. I’m not sure of the optimal size of the chunks, so I’m parametrizing it:

def chunk_lines(lines, num_chunks):
    
    # Calculate the total number of lines.
    total_lines = len(lines)

    # Calculate the number of lines per sub-chunk.
    lines_per_chunk = total_lines // num_chunks

    # Split the lines into four sub-chunks.
    chunks = [lines[i:i+lines_per_chunk] for i in range(0, total_lines, lines_per_chunk)]

    return chunks


num_chunks = 8
chunks = chunk_lines(lines, num_chunks)

counter = 0
for j, chunk in enumerate(chunks):
    print(f"part {j + 1} of {num_chunks}")
    print()
    sixteen_lines = [f"{','.join(x)}" for x in chunk]
    for aline in sixteen_lines:
        counter += 1
        print(f"line {counter}: {aline}")
        print()
    print()

And here’s Mork an Mindy in easy copy/paste format:

part 1 of 8

line 1: a6,a8,a7,a7,a8,aa,a9,aa,aa,aa,aa,aa,aa,a9,a9,a9,a9,a8,a9,a9,a9,a9,a9,a8,a9,a9,a8,a6,a6,a6,a5,a5,a4,a5,a4,a3,a4,a4,a3,a4,a4,a4,a4,a4,a3,a3,a3,a3,a3,a2,a2,a2,a2,a2,a1,a1,9f,9f,9e,9e,9e,9c,9c,9b  

line 2: a7,a7,a7,a7,a8,aa,aa,aa,aa,aa,a9,a8,a6,a3,a5,a6,a8,ab,ab,ac,a9,aa,aa,a9,a8,a8,a6,a6,a6,a6,a5,a5,a5,a5,a4,a3,a4,a4,a4,a4,a5,a4,a5,a4,a4,a4,a4,a4,a3,a2,a3,a2,a2,a2,a2,a1,9e,9f,9f,9e,9e,9d,9c,9c  

line 3: a6,a6,a7,a8,a9,aa,ab,aa,aa,aa,a3,98,8a,8c,92,9d,9e,97,92,9b,ab,aa,aa,aa,aa,a8,a7,a7,a6,a5,a6,a5,a5,a5,a5,a3,a4,a4,a4,a5,a5,a6,a5,a3,a4,a2,a0,a2,a4,a6,a6,a4,a3,a2,a2,a1,a0,a0,9f,9e,9e,9d,9c,9c  

line 4: a7,a7,a7,a8,a8,aa,aa,ab,ac,96,69,46,3c,45,5a,79,68,4f,42,51,85,aa,ab,aa,aa,a9,a8,a7,a6,a5,a5,a5,a5,a5,a5,a5,a4,a4,a5,a5,a5,a5,a5,9f,80,59,52,5a,65,71,85,9a,a7,a4,a2,a2,a1,a0,a0,9f,9e,9c,9c,9b  

line 5: a7,a7,a7,a8,a9,a9,ab,ab,97,57,35,2b,30,2b,29,2b,28,36,34,2c,3e,7f,a7,ac,aa,aa,a7,a7,a6,a6,a5,a5,a5,a5,a5,a4,a4,a4,a4,a5,a4,9a,7f,58,3f,3f,41,41,45,3c,33,3b,64,98,a6,a2,a1,9f,9f,9f,9d,9d,9d,9c  

line 6: a7,a7,a8,a8,a8,ab,a7,7a,3f,29,28,30,3d,2c,1f,1b,1b,2a,35,3a,31,38,77,a7,ab,aa,a7,a7,a6,a6,a5,a6,a5,a5,a4,a3,a3,a4,a4,a5,97,65,2c,21,35,4d,52,53,48,38,31,2d,26,40,8b,a5,a0,a0,9f,9e,9e,9d,9c,9c  

line 7: a7,a8,a8,a7,a9,a6,7e,3f,28,23,25,30,34,28,20,1f,21,1f,38,3b,32,2e,37,7b,ae,a9,a8,a7,a6,a6,a6,a5,a5,a4,a4,a3,a3,a4,a5,a1,5d,20,26,38,3b,3b,37,3d,40,3f,39,34,31,26,3b,90,a3,a1,a0,9f,9e,9e,9d,9c  

line 8: a7,a8,a8,a8,aa,92,52,2f,23,21,25,30,43,3d,27,26,27,2e,54,43,30,2e,28,44,96,ac,a9,a7,a6,a6,a6,a6,a6,a6,a5,a4,a3,a5,a2,59,23,2b,34,43,4a,36,2d,3a,42,44,45,3a,37,31,27,53,9f,a2,a0,9f,9e,9e,9d,9c  


part 2 of 8

line 9: a7,a7,a7,a8,aa,6a,2d,2c,23,21,2a,3a,52,52,3c,36,36,40,4c,3e,2c,2e,27,25,57,a9,a9,a6,a6,a5,a6,a6,a6,a5,a5,a4,a4,a6,6c,23,26,37,4e,46,37,31,2f,37,3b,39,3e,42,38,37,31,33,77,a1,a1,9f,9e,9d,9d,9d  

line 10: a7,a8,a7,a7,aa,5a,22,26,23,21,2d,3f,64,74,6b,72,73,62,66,38,24,24,26,23,38,9b,aa,a7,a7,a6,a6,a6,a5,a5,a4,a4,a5,99,44,2c,33,3a,3d,41,3f,3c,3c,3a,36,31,35,41,45,3c,36,31,57,95,a0,9f,9f,9e,9d,9c  

line 11: a7,a7,a7,a7,ab,59,20,27,21,23,35,57,84,99,a1,a9,a7,93,89,4e,24,23,24,24,24,70,aa,a7,a6,a6,a6,a6,a6,a5,a4,a5,a7,73,30,30,31,31,34,38,4a,50,40,39,30,31,32,3c,43,43,38,2f,43,8e,9d,9f,9f,9d,9d,9d  

line 12: a7,a7,a7,a8,a3,42,21,22,23,29,42,76,a6,ad,ae,b2,b1,aa,a1,89,50,27,23,1f,1f,2c,89,a8,a6,a6,a6,a6,a6,a5,a5,a5,a0,48,2b,2c,2b,2c,37,3c,35,40,4b,3b,32,30,31,35,3d,3e,3b,30,34,8c,9f,a0,9e,9d,9d,9c  

line 13: a7,a7,a8,ab,89,27,22,21,24,28,46,8a,ac,b1,b2,b3,b1,ae,b0,9f,82,3e,24,1d,1f,1c,5f,a8,a6,a6,a6,a6,a5,a5,a5,a7,8e,34,2e,30,2e,2e,31,37,34,2c,46,4c,35,30,31,33,3a,3c,39,33,32,8f,a2,a0,9f,9e,9d,9c  

line 14: a8,a8,a8,ab,83,23,1f,21,21,28,58,9b,aa,b6,ba,b5,b3,b1,9e,8b,86,5a,25,1d,1d,1c,53,a9,a6,a6,a6,a6,a6,a6,a5,a8,83,2e,35,34,32,2c,2c,2c,2d,2a,28,47,50,33,2b,2c,34,3c,41,38,2a,65,a3,a0,9f,9e,9d,9c  

line 15: a7,a7,a7,a9,94,28,20,22,29,5d,84,7a,78,82,9e,ac,ac,96,68,69,6b,58,33,1d,1c,1d,77,aa,a6,a7,a7,a6,a5,a6,a5,a7,8c,33,37,3d,38,39,32,26,20,21,27,27,3e,4a,3b,33,34,2d,2a,2f,29,43,a1,a0,a0,9f,9d,9c  

line 16: a7,a7,a8,a8,a3,39,21,21,3b,82,71,7f,7d,72,85,a0,9b,76,6b,68,6c,5a,38,1c,1c,25,91,a9,a6,a6,a7,a6,a6,a6,a5,a5,a2,53,2e,39,60,84,59,35,38,3d,28,21,20,25,2d,2d,27,21,23,26,26,6f,a5,a1,a1,9e,9e,9c  


part 3 of 8

line 17: a8,a8,a8,a7,ab,5f,1d,21,39,7b,83,71,51,62,80,9b,93,6f,6e,51,53,6d,45,1c,1b,3d,a3,a6,a6,a6,a6,a6,a6,a5,a5,a4,a6,93,4a,53,4d,a3,70,55,51,42,61,52,3a,28,1f,1d,1e,1e,21,22,37,9e,a5,a1,a1,9f,9e,9d  

line 18: a8,a8,a8,a7,a9,86,26,1f,32,80,98,82,7e,8b,8b,a0,a2,7d,8a,8a,88,7f,55,22,22,7f,aa,a6,a6,a6,a7,a6,a5,a5,a5,a5,a4,a7,7c,5e,83,a5,9c,7b,6e,5f,93,a1,89,5e,2c,25,2b,27,1f,1c,48,96,96,a0,a0,9f,9e,9d  

line 19: a7,a9,a8,a7,a8,a3,66,2b,33,83,95,9d,9e,a0,92,a1,ab,7f,93,a1,9e,81,57,37,60,a9,a7,a6,a6,a7,a6,a6,a7,a6,a5,a5,a5,a3,8d,90,a1,a4,ae,a6,99,a6,a9,9e,8d,72,38,67,71,79,37,1b,35,61,51,8c,a0,9e,9e,9e  

line 20: a7,a9,a8,a8,a8,aa,9b,5e,54,83,96,a6,ae,a6,97,a4,af,88,8c,a4,a4,80,58,3e,83,ab,a7,a7,a6,a6,a7,a6,a6,a6,a5,a6,a5,a2,8f,9b,aa,a2,a4,aa,b4,b5,a5,92,82,6f,41,76,8a,9f,43,20,1e,3e,40,53,92,98,9f,9e  

line 21: a8,a9,a8,a7,a8,a9,a2,6d,69,81,95,a7,a2,9e,8a,8d,92,64,7f,95,9a,78,56,61,97,aa,a7,a7,a7,a6,a6,a6,a5,a5,a5,a4,a4,a4,8d,8f,8b,83,92,9c,b4,b0,9d,88,7f,76,5e,6b,8d,57,21,20,22,21,22,3b,73,8b,92,9a  

line 22: a8,a8,a8,a8,a9,a9,a7,97,91,80,8e,9b,9c,9a,86,7b,70,6d,7d,8b,97,75,52,6f,a5,a9,a8,a6,a7,a7,a6,a6,a6,a5,a5,a5,a5,a6,92,6f,68,8b,a6,a2,97,9b,8d,86,83,7e,5e,4b,30,1b,1e,1d,1e,1f,24,31,59,73,72,90  

line 23: a8,a8,a9,a8,a8,a8,a8,a2,78,7c,8e,a0,98,83,83,85,82,72,63,85,9d,72,58,98,aa,a8,a7,a6,a6,a7,a6,a6,a6,a5,a5,a5,a5,a5,9f,7b,57,6c,79,7c,7c,92,96,91,8b,77,4f,3d,1f,1e,1e,1f,20,23,25,26,4c,6c,7b,95  

line 24: a8,a8,a8,a8,a8,a7,a7,ab,6c,69,8e,9a,a3,99,93,95,8f,84,82,95,91,66,62,a6,a9,a8,a7,a7,a6,a6,a6,a7,a5,a6,a6,a6,a5,a4,9c,80,60,69,82,90,9d,9d,97,91,89,60,57,3f,1f,1d,20,20,22,24,26,21,40,7a,82,98  


part 4 of 8

line 25: a8,a7,a7,a8,a7,a8,a8,a9,a0,75,85,91,9b,a3,a5,9d,8f,8f,91,84,71,54,7e,aa,a7,a7,a8,a7,a6,a7,a6,a6,a6,a6,a5,a5,a5,a2,95,6d,77,8c,9d,a3,a3,9e,95,8c,70,57,73,3e,1b,1e,21,20,21,22,25,21,24,6f,8b,99  

line 26: a8,a8,a7,a8,a8,a8,a8,aa,ab,88,6d,80,8c,95,91,96,9d,8f,82,6e,53,45,8b,ab,a8,a8,a8,a8,a7,a7,a6,a6,a6,a5,a5,a5,a4,a1,94,67,81,a6,ae,ac,a8,9e,8a,6b,5e,7b,87,3b,1a,1d,21,21,1f,1f,22,21,1d,46,86,90  

line 27: a7,a7,a7,a7,a9,a8,a9,a2,a9,91,68,65,6e,7a,88,97,98,93,72,4e,47,45,8f,ad,a8,a8,a7,a7,a7,a7,a7,a7,a6,a6,a6,a6,a5,a1,93,6b,75,9b,a7,a2,8c,71,60,63,7d,95,8b,41,1b,19,1e,23,1f,1e,1f,20,1d,30,69,85  

line 28: a7,a7,a7,a7,b2,a5,9a,81,80,96,73,6d,65,63,69,6d,67,65,53,4b,52,50,63,91,a8,ac,a9,a8,a7,a8,a6,a6,a6,a6,a7,a8,a5,a0,99,84,58,49,5a,67,64,69,73,82,93,9a,8b,50,32,23,1f,21,22,1f,1f,1e,1f,28,5d,80  

line 29: a7,a7,a9,b6,a4,a9,81,5c,38,60,7b,7f,74,6b,69,64,69,62,56,5d,64,61,44,4e,53,80,9a,a6,ab,a8,a7,a7,a8,a9,a1,94,88,7c,7b,67,52,38,3d,57,71,81,87,8e,9b,9c,8f,68,5e,45,2b,1c,1d,1e,1e,1e,1e,1f,35,5d  

line 30: a7,b6,ab,c3,93,9a,88,32,48,6e,7b,8d,82,79,7a,78,7b,6b,64,6d,79,6a,58,70,45,55,70,5d,82,a9,ab,a9,a3,8e,81,7a,73,78,76,68,59,43,42,53,6c,80,89,93,9c,9c,92,7a,7a,63,40,2f,24,20,1d,1d,1d,1d,1e,2b  

line 31: ab,b4,c2,b6,b4,79,a0,48,6c,7c,77,92,93,85,85,87,7a,74,76,82,83,73,75,89,56,5c,82,51,42,58,8c,8e,70,5e,68,69,71,80,73,70,62,4b,48,56,68,7f,8f,99,9f,99,86,77,6c,5f,5f,52,46,42,32,23,1c,1b,1d,1e  

line 32: 9e,8b,b0,90,a5,84,5f,41,7f,84,78,8d,98,98,89,7d,7c,84,89,8c,83,7c,8b,96,5c,65,8d,59,42,2d,50,63,6e,79,7d,63,70,75,6c,78,64,53,4a,5f,6e,7f,91,9b,99,89,78,70,69,68,62,59,55,58,5d,56,46,2c,1b,1a  


part 5 of 8

line 33: 80,7e,73,57,77,6d,3e,39,85,8c,7f,8a,9a,9d,96,89,8d,90,8f,8d,8b,8b,98,a0,61,69,92,5c,45,2c,43,5a,5f,6f,62,57,69,6a,64,76,64,5b,4b,5b,77,7b,8b,92,86,7b,77,6f,6c,63,5f,62,68,70,6d,71,71,63,40,1e  

line 34: 80,91,95,5c,87,73,39,3d,86,8d,87,8b,95,99,93,91,94,95,91,90,90,95,9c,9d,61,6d,97,5d,46,2c,46,5a,5a,5c,63,5f,5e,66,5b,68,62,60,50,4f,6e,73,7d,7e,65,70,73,6d,66,62,66,6d,73,72,79,7f,81,7f,73,54  

line 35: b9,ed,c9,7f,ba,a6,62,47,74,7b,79,83,88,90,91,8d,98,8c,8b,97,93,94,97,9a,5b,70,9b,62,48,2e,4e,57,57,5a,5b,5d,5d,62,58,5e,5e,61,58,58,52,54,5d,54,59,6b,67,6c,66,69,6d,71,6d,7a,7f,7c,84,88,6a,74  

line 36: f1,f3,95,dc,fb,dd,b5,7f,4b,64,6e,76,7d,88,92,91,95,8b,93,93,8c,89,8b,90,5b,6f,a0,67,47,63,5c,51,54,54,54,52,51,5a,55,5e,5c,5e,5a,63,51,4f,5b,53,58,60,66,67,6b,6d,6e,6a,70,7f,80,6f,85,75,50,6d  

line 37: f3,f3,8e,ab,fe,9a,33,2a,25,3d,5c,6d,75,87,8f,8b,8c,89,8b,85,81,7a,78,86,5e,6f,a6,6b,44,bb,cc,6c,4d,52,52,4d,45,45,52,5b,59,57,5c,65,54,4b,5c,58,59,60,65,62,6a,6a,6c,63,79,7c,73,6b,75,59,53,70  

line 38: f3,f3,92,5f,b1,63,3b,86,6b,30,26,33,4a,6b,7d,6a,78,76,7b,7a,76,73,70,63,44,72,a4,6c,43,ad,f4,d9,88,4b,4c,49,41,3a,47,56,5e,59,5a,63,57,54,56,59,55,61,64,64,68,66,5f,6c,7c,7b,71,62,65,4f,59,6c  

line 39: f2,f2,88,7b,97,51,42,bb,e1,bf,84,4c,2c,26,2e,33,43,4d,59,59,4b,37,29,22,35,6e,a1,6c,42,a2,ec,e6,dd,64,45,43,3d,39,3d,4c,5a,59,56,62,55,53,54,57,53,5a,61,65,65,5f,5b,75,78,75,5c,63,5c,52,61,64  

line 40: f3,ed,7d,8a,9c,4e,48,c4,dd,dd,de,d6,b4,87,60,48,37,2e,2c,2e,36,4a,6c,a6,81,64,a0,6f,42,98,ea,e3,e9,8f,3d,3f,3c,38,38,3e,53,56,53,62,5a,53,56,55,54,55,63,65,64,54,61,6c,7a,6c,56,6a,55,59,69,5d  


part 6 of 8

line 41: d8,e8,75,91,8f,48,4f,ce,da,d7,d6,d5,d7,da,d8,ce,c4,be,ba,bc,c3,cf,d7,e0,90,62,a2,70,3f,91,e8,e4,e9,8d,37,40,3a,37,35,37,50,55,4f,5b,65,58,5a,55,55,54,64,64,5e,52,63,65,66,50,63,64,55,5b,6c,5b  

line 42: 68,de,6d,93,85,45,57,d4,d8,d5,d3,d3,d3,d3,d3,d3,d4,d6,d5,d2,d0,d0,cf,d7,90,63,a2,6e,3e,8c,e4,de,e8,7a,3c,38,37,35,33,33,4f,55,4b,54,67,5e,5c,58,55,55,5f,65,4e,58,63,66,5e,4d,66,5b,51,5c,6e,60  

line 43: 37,a6,6d,96,7b,40,63,d9,d7,d3,d2,d0,d0,d1,d0,d0,d0,cf,cd,cb,c9,ca,cb,d2,90,52,6b,44,37,8b,e0,d8,c5,58,32,33,33,31,31,2f,49,56,47,4c,5f,5d,60,5e,56,54,5d,5c,3b,48,57,62,5a,52,5f,56,52,60,6f,66  

line 44: 37,3c,5e,96,72,3c,69,da,d5,d3,d2,cf,cd,cf,ce,cc,cd,ca,c8,c5,c6,c7,c8,cc,89,53,74,50,2e,83,e0,a9,66,33,2c,2f,30,30,2e,2d,45,56,45,3f,4a,58,61,63,5e,53,5b,4e,36,34,4e,5e,52,54,5c,56,55,66,73,6b  

line 45: 4c,23,50,95,68,45,9a,c0,b6,ba,b9,c3,cc,ca,c4,cb,c5,c5,c4,c1,be,b4,ad,aa,98,95,89,62,51,65,b2,70,3e,29,2d,2f,2f,2c,2c,2b,44,57,46,3e,42,54,5e,64,61,51,57,48,3c,31,4a,5b,4b,53,5b,59,59,68,71,69  

line 46: 56,2d,4b,8d,5d,5e,b6,b2,ad,a8,a4,b4,c4,bb,b1,a7,ad,bb,b3,b8,b3,9d,92,9d,9f,a2,83,62,54,6b,8a,3f,2c,2d,2f,2e,2c,2c,2b,2a,42,56,48,40,4d,52,5d,65,62,52,54,49,44,36,48,59,45,54,5b,5b,5e,69,70,68  

line 47: 62,3f,46,7d,6a,a1,b5,ac,a8,a4,ad,b4,af,a9,b8,9f,b0,c0,a1,94,9b,98,97,9e,aa,b0,94,58,42,6b,78,23,28,29,2a,2b,2b,2a,2a,29,41,55,4d,3a,46,4f,60,67,62,54,52,4d,4a,3c,44,54,41,52,59,5c,60,6a,6c,66  

line 48: 69,50,56,64,6b,a6,ae,a9,a1,98,a4,bc,ba,a7,94,cc,ea,ab,8d,b6,bb,a4,a1,a0,9d,9f,86,3f,29,4c,42,28,2d,2b,2c,2d,2c,2b,2a,27,3e,56,53,3e,44,4a,5e,6b,61,59,51,52,49,3e,39,51,3f,51,57,5c,60,6a,6a,65  


part 7 of 8

line 49: 6a,5b,4e,6d,5b,93,b6,a8,9b,98,99,90,8c,9b,ab,e6,ec,a9,ac,b2,8f,67,63,83,9e,aa,7b,44,2d,2e,2a,2f,32,2f,2e,2d,2c,2b,29,26,36,57,56,43,46,45,57,6b,61,5d,4f,57,48,3a,34,4f,41,51,55,59,60,6a,65,68  

line 50: 68,5f,49,78,66,8c,a8,a2,9d,a9,a6,b0,9f,84,a7,f4,ec,96,81,73,6b,77,95,95,a0,a5,77,44,30,26,2a,33,34,32,31,2f,2d,2b,29,25,2b,53,58,48,44,43,4d,65,64,5e,50,54,4a,34,33,4f,45,4f,54,5a,64,65,62,6e  

line 51: 67,61,48,69,5c,6e,a0,99,83,75,7e,91,9a,90,c8,f4,f0,ab,74,8f,a6,a3,91,79,91,97,67,47,3c,26,2c,35,42,3d,32,2d,2c,2d,62,35,21,4c,58,55,49,42,40,56,60,5e,51,53,4d,33,2d,4d,48,4c,55,5e,65,60,63,73  

line 52: 65,61,48,51,49,5c,a1,a7,9e,a6,99,8f,83,a3,db,f4,ef,b5,84,86,8e,84,84,97,9f,8f,54,43,40,2c,2c,3b,a1,a9,8a,6a,46,2a,6f,69,23,42,55,5a,62,51,3a,46,52,57,52,52,53,3d,2b,4a,4c,54,5d,61,5e,5e,6e,68  

line 53: 64,5f,4b,44,46,49,83,92,7d,94,97,99,ad,c9,e2,f5,f1,cb,ab,86,7f,97,9c,8d,91,7e,49,3a,41,3e,37,3d,45,5a,79,a2,9b,65,43,7d,45,36,54,5c,7b,64,44,3d,47,4e,4c,52,52,4b,29,42,4b,59,5e,5a,5b,67,6a,59  

line 54: 60,5a,4a,5a,5b,4b,71,82,89,b5,bb,aa,ba,d4,e7,f7,f2,ce,b9,a2,94,ac,b7,a2,8c,85,66,49,4b,48,56,9b,9d,7f,60,47,66,93,74,77,6f,30,51,5a,5f,65,59,44,3e,4a,46,4e,50,4d,31,37,42,55,59,60,64,66,60,56  

line 55: 5e,58,48,5e,78,65,81,9e,b5,d2,d1,b4,ba,d5,e8,f6,ed,c9,bd,ad,ad,d0,cd,d3,c5,b6,8a,51,53,4a,3b,5a,76,97,a0,9c,73,80,9c,90,88,47,44,5a,5f,60,5c,5c,48,40,43,46,4d,4c,41,35,38,4b,59,64,6d,63,59,57  

line 56: 68,51,4f,60,6b,65,98,ba,cf,d1,d1,c0,ca,d7,e5,f4,ed,cb,bf,ba,b3,ce,ca,e5,ed,e8,d2,98,6f,4b,3b,3d,51,5a,62,7e,97,a5,a6,90,7d,55,2f,5b,65,63,57,5a,5d,49,3c,3f,48,4a,48,40,33,33,4b,60,6e,69,61,5d  


part 8 of 8

line 57: 6c,54,5a,6b,88,a3,be,d7,d6,c7,c7,c3,d5,da,ea,f4,ec,c9,c2,ca,bc,c2,c3,d6,ed,ea,e7,ea,eb,c6,60,36,5b,92,96,97,91,a2,9f,88,78,58,2b,49,66,69,5c,51,56,5c,51,40,40,4a,4b,48,32,21,30,48,67,6f,68,64  

line 58: 63,57,5f,bc,da,b9,ce,e1,d1,c2,c7,ce,d8,e0,f2,ef,e6,c8,c6,d2,cb,ba,be,cc,e9,e8,e9,eb,eb,f4,d0,45,37,4c,61,6b,91,a9,9c,82,79,6a,3f,35,55,64,66,5c,56,57,61,5b,45,40,4c,4d,42,22,21,2f,58,66,6a,65  

line 59: 60,52,55,8e,9f,c1,da,db,ca,c6,c9,d7,dd,e4,f4,f1,dc,c5,c8,d2,d3,c3,be,ce,e2,e9,ea,ed,eb,ef,db,44,31,3c,55,82,93,9e,92,82,7a,76,6b,40,3b,47,52,58,5c,56,5a,5f,55,42,45,4c,4a,36,2b,3b,49,52,60,66  

line 60: 62,44,63,79,bb,de,df,d3,ca,c9,d2,de,e1,dd,ef,ef,d2,c3,cb,d3,d6,cd,cc,d6,de,e5,e4,e3,e9,ee,c9,3a,2d,33,3d,4a,76,85,82,86,7e,7c,80,78,70,69,60,5a,57,54,51,4d,46,3e,43,3f,3f,3c,2d,28,2c,30,38,4c  

line 61: 5f,68,69,4e,aa,e3,db,cc,cb,cf,da,e0,e0,e2,f0,e7,cd,c5,c9,d0,d8,d0,d0,dc,e0,e5,e5,e8,eb,f0,c0,56,38,2c,33,3a,3e,4f,77,81,7f,83,88,83,81,86,86,84,80,7a,73,6d,6a,61,53,52,53,52,4d,4b,3a,42,2e,36  

line 62: 6e,77,48,33,66,dc,df,d3,d2,d4,dc,e2,dc,dc,ee,e3,d2,c7,c8,cf,db,d6,d5,db,dd,de,df,e3,e4,e9,ca,44,54,39,2b,31,37,34,46,6c,7d,88,8c,91,92,94,95,96,94,90,8b,86,83,7a,61,59,5d,5b,5d,55,56,51,55,47  

line 63: 76,5a,5a,4f,54,b8,d6,d1,db,df,e4,e5,df,cb,c4,c2,bd,c5,c8,d1,db,e4,df,db,db,dd,e1,e1,e1,e9,d4,3b,2e,51,3a,29,2f,32,29,3e,52,64,79,7c,81,88,8f,97,99,9b,98,93,92,84,60,5d,63,5f,65,5b,53,57,5c,59  

line 64: 5a,5a,56,4f,53,92,c5,d7,df,e9,eb,e9,de,d1,c2,bb,98,b0,ca,d8,e5,e8,e5,da,da,dd,dd,df,df,e7,c2,32,26,2b,50,37,28,2d,29,2d,20,21,34,41,48,54,62,71,7e,86,8b,8d,90,83,58,64,60,5b,61,5c,4e,46,4b,4f

And to view it, you just manipulate those numbers into the following Python list of tuples data structure:

list = [tuple, tuple, typle... tuple]

Where each tuple is a line of Mork an Mindy. You could use line.split(',') to make a tuple of each line above. Of course you’d have to follow Python syntax but that will get you on the right track.

Is this clear?

Nanu nanu (pronounced NAH-noo NAH-noo).

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