erraticgenerator

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"

erraticgenerator

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)
    

erraticgenerator

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))

erraticgenerator

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

erraticgenerator

regex_filters = ['_regular', '_japanese', '_serif']

df_new = pd.concat([df.filter(regex=regex, axis=1).sum(axis=1).astype(bool) for regex in regex_filters], axis=1)
mask = df_new.all(axis=1)

df.loc[mask]

erraticgenerator

mask = (df.filter(regex='chinese', axis=1).sum(axis=1).astype(bool) & 
       df.filter(regex='sans-serif', axis=1).sum(axis=1).astype(bool))
df_selected = df[mask]
df_selected

erraticgenerator

mask = (df.filter(regex='thin', axis=1).sum(axis=1).astype(bool) &
        df.filter(regex='regular', axis=1).sum(axis=1).astype(bool) & 
        df.filter(regex='thai', axis=1).sum(axis=1).astype(bool))
df_selected = df[mask]
df_selected

erraticgenerator

print('Number of fonts in each variant:')
print(df[df.filter(regex=r'^variants_', axis=1).columns].eq(1).sum().sort_values(ascending=False))

print('\nNumber of fonts in each subset:')
print(df[df.filter(regex=r'^subsets_', axis=1).columns].eq(1).sum().sort_values(ascending=False))

print('\nNumber of fonts in each category:')
print(df[df.filter(regex=r'^category_', axis=1).columns].eq(1).sum().sort_values(ascending=False))

erraticgenerator

# modules we need this time
import matplotlib.pyplot as plt
from PIL import Image,ImageDraw,ImageFont
import pandas as pd
import numpy as np

# load the CSV we created in the last post
df = pd.read_csv('./google-fonts-annotaion.csv')

erraticgenerator

import matplotlib.pyplot as plt
from sklearn.preprocessing import MultiLabelBinarizer
import pandas as pd
import numpy as np