def main():
starttime = datetime.now()
conf = util.get_config('DEFAULT')
sym_wordcorrect(conf)
endtime = datetime.now()
elapsed = endtime - starttime
print(f"Start: {starttime.strftime('%H:%M:%S')}")
print(f"End: {endtime.strftime('%H:%M:%S')}")
print(f"Elapsed: {elapsed}")
def main():
"""Run the OCR pipeline."""
starttime = datetime.now()
conf = util.get_config()
cnf = util.Confs(conf)
do_ocr(cnf.tessconf['imgdir'],
cnf.tessconf['outdir'],
traineddata_labels=['Fraktur', 'dan', 'frk'])
endtime = datetime.now()
elapsed = endtime - starttime
print(f"Start: {starttime.strftime('%H:%M:%S')}")
print(f"End: {endtime.strftime('%H:%M:%S')}")
print(f"Elapsed: {elapsed}")
# Core libraries
import configparser
import os
from datetime import datetime
# Image processing
try:
from PIL import Image
except ImportError:
import Image
import myutils as util
# try to speed up!
import multiprocessing as mp
import pytesseract
from itertools import product
conf = util.get_config()
pth = util.Confs(conf)
pytesseract.pytesseract.tesseract_cmd = pth.tessconf['tess_bin']
tessdata_dir_config = fr'''--tessdata-dir "{pth.tessconf['tessdata_dir']}"'''
def process(arg_tuple):
"""OCR process."""
path, outdir, traineddata_label = arg_tuple
# for image in [sorted(os.listdir(path))[0]]: # Use this to only OCR first page in novel/sample.
for image in os.listdir(path):
# Create image path with join
imagepath = os.path.join(path, image)
print(f'Working on {imagepath}')
# Convert image to text
def main():
"""Run the OCR pipeline."""
starttime = datetime.now()
config = util.get_config()
# Generate various paths and create them if necessary.
conf = util.Confs(config).corrconf
*_, param_str = util.get_params(conf)
pth = util.CorrPaths(conf)
# Which OCR traineddata should be used?
# Note! frk.traineddata must be downloaded from tessdata_fast in order to work:
# https://github.com/tesseract-ocr/tessdata_fast/blob/master/frk.traineddata
# Same for dan.traineddata: https://github.com/tesseract-ocr/tessdata_fast/blob/master/dan.traineddata
# fraktur.traineddata can be downloaded from tessdata_best:
# https://github.com/tesseract-ocr/tessdata_best/blob/master/script/Fraktur.traineddata
traineddata_labels = ['Fraktur', 'dan', 'frk']
tess_outdirs = [
os.path.join(pth.fulloutputdir, f'tess_out_{label}')
for label in traineddata_labels
]
uncorrected_dir = os.path.join(pth.fulloutputdir, conf['base_ocr'])
corrected_dir = os.path.join(pth.fulloutputdir, param_str)
# Steps of the pipeline. Set options in the config file for which processing steps to perform.
if conf.getboolean('run_make_dictionary'):
make_dic(conf['metadir'])
if conf.getboolean('run_pdf2img'):
pdfs2imgs(pth.frakturpaths, pth.img_dir, int(conf['split_size']))
if conf.getboolean('run_ocr'):
do_ocr(pth.img_dir, pth.fulloutputdir, traineddata_labels)
if conf.getboolean('correct_easy'):
correct_easy_fraktur_errors(uncorrected_dir, corrected_dir)
uncorrected_dir = corrected_dir
if conf.getboolean('correct_hard'):
correct_hard_fraktur_errors(uncorrected_dir, pth.fulloutputdir,
corrected_dir)
uncorrected_dir = corrected_dir
if conf.getboolean('sym_wordcorrect'):
sym_wordcorrect(conf, uncorrected_dir, corrected_dir)
# TODO Will it make any sense to employ SymSpell at the bigram level? Probably not?
# if conf.getboolean('make_basic_gold_vrt'):
# gold_vrt_gen = generate_novels_vrt(corrpaths.gold_novels_dir, corrpaths.corp_label)
# write_novels_vrt(gold_vrt_gen, corrpaths.basic_gold_vrt_path)
# if conf.getboolean('annotate_gold_vrt'):
# text_annotation_generator = generate_gold_annotations(corrpaths.basic_gold_vrt_path, corrpaths.ocr_kb_dir,
# conf['texton_out_dir'], corrpaths.corp_label, tess_outdirs,
# [corrected_dir], conf) # TODO single dir instead of list of dirs?
# write_annotated_gold_vrt(text_annotation_generator, corrpaths.local_annotated_gold_vrt_path)
# shutil.copy(corrpaths.local_annotated_gold_vrt_path, corrpaths.annotated_gold_vrt_path)
# if conf.getboolean('analyze_errors'):
# # TODO Not very transparent error when n_datasets is wrong.
# analyze_gold_vrt(corrpaths.annotated_gold_vrt_path, conf, corrpaths.analyses_dir, param_str, n_datasets=5)
# if conf.getboolean('write_korp_configs'):
# util.write_frakturgold_mode(conf['frakturgold_mode_template'],
# conf['gold_vrt_p_attrs'],
# conf['frakturgold_mode_outpath'])
# shutil.copy(conf['frakturgold_mode_outpath'], os.path.join(corrpaths.vrt_dir, 'memo_frakturgold_mode.js'))
# util.write_frakturgold_encodescript(conf['frakturgold_encode_template'],
# corrpaths.annotated_outdir,
# conf['gold_vrt_p_attrs'],
# conf['frakturgold_encode_outpath'])
# shutil.copy(conf['frakturgold_encode_outpath'], os.path.join(corrpaths.vrt_dir, 'encode_MEMO_fraktur_gold.sh'))
# if conf.getboolean('write_word'):
# pass
endtime = datetime.now()
elapsed = endtime - starttime
print(f"Start: {starttime.strftime('%H:%M:%S')}")
print(f"End: {endtime.strftime('%H:%M:%S')}")
print(f"Elapsed: {elapsed}")