Kinda almost https://twitter.com/RaminNasibov/status/981834971403911168

pasta_machine.py

import numpy as np
import matplotlib.image as mpimg
import matplotlib.pyplot as plt


PASTA_SIZE = 16
NUM_IMAGE_SPLITS = 2
IMAGE_LOCATION = 'something.png'

image = mpimg.imread(IMAGE_LOCATION)


def pasta_machine(image, pasta_size, number_of_output_images):
    '''Split the `image` into strips of size `pasta_size`, divide into 
    `number_of_output_images` groups, and glue the strips together, and
    return the `number_of_images` images. Crops the input image.
    
    image: numpy array (height, width, channels)
    pasta_size: (int): pixels per strip
    number_of_output_images: number of images to return
    
    returns: (number_of_output_images, ~height // number_of_output_images, width, channels): note 
      the height is cropped if needed.
    '''
    h, w, c = image.shape
    # trim the image so that when it is divided into groups of pasta, 
    # the two new images are the same size.
    h = (h // (pasta_size * number_of_output_images)) * pasta_size * number_of_output_images
    image = image[:h, :, :]
    
    # split image into strips of width pasta_size, and divide into
    # two groups.
    image = image.reshape(
        h // pasta_size // number_of_output_images, 
        number_of_output_images, 
        pasta_size, 
        w, c)
    # now split into the two groups (transpose) and glue the strips together (vstack)
    image = np.vstack(image.transpose(0, 2, 1, 3, 4))
    # make the first dimension the number_of_output_images images
    image = image.transpose(1, 0, 2, 3)
    return image

# pasta the image
first_pasta_pass = pasta_machine(image, PASTA_SIZE, NUM_IMAGE_SPLITS)

# admire the image
plt.imshow(np.vstack(first_pasta_pass))
plt.axis('off')
plt.show()

# glue the two images together
double_image = np.hstack(first_pasta_pass)

# rotate the image
rotated_double_image = double_image.transpose(1, 0, 2)

# pasta the double image
rotated_pasta_quad_image = pasta_machine(rotated_double_image, PASTA_SIZE, NUM_IMAGE_SPLITS)

# rotate them back
pasta_quad_image = rotated_pasta_quad_image.transpose(0, 2, 1, 3)

# and glue the two images together
quad_image = np.hstack(pasta_quad_image)

# admire the image
fig = plt.figure(figsize=(12, 12))
plt.imshow(quad_image)
plt.axis('off')
plt.show()