nikopartanen

import wave
from deepspeech import Model, version
import numpy as np
import sys
import subprocess
from pipes import quote
import shlex
import pympi

# This code is essentially taken from DeepSpeech native_client repository

nikopartanen

# This is an example from Niko Partanen how to use Copius transliterator from Python.
# The idea is to replicate the form that the website uses, and send that information
# there directly. For the website it essentially looks like someone would be just using
# it normally. 

import requests
from lxml import html

def run_copius_transliterator(language, text, direction):
    

nikopartanen

library(tidyverse)
library(lingtypology)

kpv <- read_csv("https://raw.githubusercontent.com/langdoc/kpv-geography/master/kpv.csv")

map.feature(languages = kpv$language,
            features = kpv$dialect,
            label = kpv$settlement,
            latitude = kpv$latitude,
            longitude = kpv$longitude)

nikopartanen

import xml.etree.cElementTree as ET

from PIL import Image
import numpy as np
from google.protobuf.json_format import MessageToJson

import matplotlib.pyplot as plt
import matplotlib.patches as patches
from pathlib import Path
import sklearn as sk

nikopartanen

from pathlib import Path
import xml.etree.cElementTree as ET
import re

# Tieto noista ylä- ja alaindekseistä on merkitty tällaisiin elementteihin:
# textStyle {offset:13; length:1;superscript:true;}
# Niistä pitää poimia milloin niitä on, j amiten pitkiä ne ovat

def get_offset_info(offsets):
    

nikopartanen

lang=$1

export GTLANG_$lang=/mnt/data/trunk/langs/$lang

cd /mnt/data/trunk/langs/$lang
make clean
./autogen.sh
./configure --with-hfst --without-xfst --enable-tokenisers --enable-reversed-intersect --enable-alignment --enable-apertium --enable-dicts --enable-morpher
make
make install

nikopartanen

nikopartanen

### This is Niko Partanen's example R script that splits the National
### Library of Finland's dataset OCR Ground Truth Pages (Swedish Fraktur)
### into line-image–text-file pairs that can be used with training
### models with Tesseract. Same approach works easily also with Ocropy
### Data source:
### https://digi.kansalliskirjasto.fi/opendata

library(tidyverse)
library(xml2)
library(measurements)

nikopartanen

library(overpass)
library(sf)

settlements <- 'area[name~"Адыгея|Кабардино-Балкария|Карачаево-Черкесия|Ставропольский край|Краснодарский край"];
(node["place"~"city|village|town|hamlet|isolated_dwelling"](area););
out;'

query_result <- overpass_query(settlements)

nikopartanen

#!/usr/bin/python
# -*- coding: utf-8 -*-

# http://stackoverflow.com/questions/5574702/how-to-print-to-stderr-in-python
from __future__ import print_function
import sys
def eprint(*args, **kwargs):
    print(*args, file=sys.stderr, **kwargs)

import errno