ErraticGenerator erraticgenerator

## gfonts-2-filter-func.py
import re

def filter_fonts(df, regex_filters):
    df_new = pd.concat([df.filter(regex=re.compile(regex, re.IGNORECASE), axis=1).sum(axis=1).astype(bool) for regex in regex_filters], axis=1)
    mask = df_new.all(axis=1)
    return list(df.loc[mask].family)

filtered_fontnames = filter_fonts(df, ['Black', 'cyrillic', '_serif'])
filtered_fontnames

## gfonts-2-all-fonts-path.py
import glob

# change the root directory according to your setup
ROOT = '../../input/fonts/ofl'

# some fonts are within /ofl/fontname/static directory (2 levels deep)
all_fonts_path = glob.glob(ROOT + '/**/**/*.ttf', recursive=True)
print('number of font files in total: ', len(all_fonts_path))

## gfonts-2-filter-fonts-get-paths.py
def filter_fonts_get_paths(df, root='./', variants=['_'], subsets=['_'], category=''):
    # exceptions
    if not variants or variants == [''] or variants == '': variants = ['_']
    if not subsets or subsets == [''] or subsets == '': subsets = ['_']
    # apply filters
    regex_filters = variants + subsets + ['_'+category]
    df_new = pd.concat([df.filter(regex=re.compile(regex, re.IGNORECASE), axis=1).sum(axis=1).astype(bool) for regex in regex_filters], axis=1)
    mask = df_new.all(axis=1)
    filtered_fontnames = list(df.loc[mask].family)


## gfonts-2-preview.py
import random

IMG_HEIGHT = 512
IMG_WIDTH = 512

paths = filter_fonts_get_paths(df, root=ROOT, subsets=[''], variants=['bold'], category='')
r = random.randrange(0, len(paths))

# sample text and font
text = "G"

## gfonts-2-everything.py
from IPython.display import clear_output

# display images
monitor = False

# font filtering
df = pd.read_csv('./google-fonts-annotaion.csv')
paths = filter_fonts_get_paths(df, root=ROOT, subsets=['latin'], variants=['bold'], category='serif')

# text setup

## p5js-mp4-export-2.html
<!DOCTYPE html>
<html lang="en">

<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Document</title>
    <script src="https://unpkg.com/h264-mp4-encoder/embuild/dist/h264-mp4-encoder.web.js"></script>
    <script src="https://cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js"></script>
</head>

## p5-textToPoints-1.html
<!DOCTYPE html>
<html lang="en">

<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Document</title>
    <script src="https://cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js"></script>
</head>

## p5-textToPoints-2.html
<!DOCTYPE html>
<html lang="en">

<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Document</title>
    <script src="https://cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js"></script>
</head>

## p5-textToPoints-opentypejs.html
<!DOCTYPE html>
<html lang="en">

<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Document</title>
    <script src="https://cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js"></script>
    <script src="https://cdn.jsdelivr.net/npm/opentype.js@latest/dist/opentype.min.js"></script>
</head>

## p5-word-anim-1.js
function setup() {
    createCanvas(800, 400)
    background(0)

    const str = 'Hello, world! Hi, there! Nice to meet you!'
    const wordsStr = str.split(' ')

    textSize(48)

    // track word position
	import re

	def filter_fonts(df, regex_filters):
	df_new = pd.concat([df.filter(regex=re.compile(regex, re.IGNORECASE), axis=1).sum(axis=1).astype(bool) for regex in regex_filters], axis=1)
	mask = df_new.all(axis=1)
	return list(df.loc[mask].family)

	filtered_fontnames = filter_fonts(df, ['Black', 'cyrillic', '_serif'])
	filtered_fontnames
	import glob

	# change the root directory according to your setup
	ROOT = '../../input/fonts/ofl'

	# some fonts are within /ofl/fontname/static directory (2 levels deep)
	all_fonts_path = glob.glob(ROOT + '///*.ttf', recursive=True)
	print('number of font files in total: ', len(all_fonts_path))
	def filter_fonts_get_paths(df, root='./', variants=['_'], subsets=['_'], category=''):
	# exceptions
	if not variants or variants == [''] or variants == '': variants = ['_']
	if not subsets or subsets == [''] or subsets == '': subsets = ['_']
	# apply filters
	regex_filters = variants + subsets + ['_'+category]
	df_new = pd.concat([df.filter(regex=re.compile(regex, re.IGNORECASE), axis=1).sum(axis=1).astype(bool) for regex in regex_filters], axis=1)
	mask = df_new.all(axis=1)
	filtered_fontnames = list(df.loc[mask].family)
	import random

	IMG_HEIGHT = 512
	IMG_WIDTH = 512

	paths = filter_fonts_get_paths(df, root=ROOT, subsets=[''], variants=['bold'], category='')
	r = random.randrange(0, len(paths))

	# sample text and font
	text = "G"
	from IPython.display import clear_output

	# display images
	monitor = False

	# font filtering
	df = pd.read_csv('./google-fonts-annotaion.csv')
	paths = filter_fonts_get_paths(df, root=ROOT, subsets=['latin'], variants=['bold'], category='serif')

	# text setup
	<!DOCTYPE html>
	<html lang="en">

	<head>
	<meta charset="UTF-8">
	<meta name="viewport" content="width=device-width, initial-scale=1.0">
	<title>Document</title>
	<script src="https://unpkg.com/h264-mp4-encoder/embuild/dist/h264-mp4-encoder.web.js"></script>
	<script src="https://cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js"></script>
	</head>
	function setup() {
	createCanvas(800, 400)
	background(0)

	const str = 'Hello, world! Hi, there! Nice to meet you!'
	const wordsStr = str.split(' ')

	textSize(48)

	// track word position