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# pip install pymupdf

import fitz

src = fitz.open("QM_SS24_Skript.pdf")
doc = fitz.open()

LEFT_MARGIN = 100
RIGHT_MARGIN = 100

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# Written by Splines, https://github.com/splines
# Change WITH_PUTBACKS to True or False to change if we allow putbacks or not

# In order to run this, you need to install Graphviz first,
#  see the installation guide here:
# https://graphviz.readthedocs.io/en/stable/#installation


from typing import List
import numpy as np

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def change_brightness(color, amount=1):
    """
    Changes the brightness of the given color by multiplying luminosity
    by the given amount.
    
    Input can be a matplotlib color string, hex string, or RGB tuple.
    
    The color gets brighter when amount > 1 and darker when amount < 1.
    The resulting luminosity is restricted to [0,1].

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# Installation
# Run `pip install pyaudio` first
# If that throws an error, you need to install a "wheel" first (pre-packaged binary)
# Follow the instructions here: https://stackoverflow.com/a/71073645/9655481
# e.g. I use Python 3.9.6 and installed the file "PyAudio‑0.2.11‑cp39‑cp39‑win_amd64.whl"
# from here: https://www.lfd.uci.edu/~gohlke/pythonlibs/#pyaudio

import time

import matplotlib.pyplot as plt

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# 🌐 MNIST Dataset
# https://deepai.org/dataset/mnist

import numpy as np
from matplotlib import pyplot as plt

with open('./mnist/train-images.idx3-ubyte', 'rb') as images_file,\
        open('./mnist/train-labels.idx1-ubyte', 'rb') as labels_file:

    # --- Images Header

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# --- Images Header
# 4x 32-bit big-endian integer
images_header = np.fromfile(images_file, dtype='>i4', count=4)

images_magic_number = images_header[0]
images_count = images_header[1]
row_count = images_header[2]
col_count = images_header[3]
pixel_count = row_count*col_count

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import numpy as np
from matplotlib import pyplot as plt

with open('./mnist/train-images.idx3-ubyte', 'rb') as images_file,\
        open('./mnist/train-labels.idx1-ubyte', 'rb') as labels_file: