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# -*- coding: utf-8 -*-
"""
pdf2text.py - convert pdf files to text files using OCR
"""
import logging
import os
import re
import shutil
import time
from datetime import date
from os.path import basename, dirname, join
from pathlib import Path
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s %(levelname)s %(message)s",
datefmt="%m/%d/%Y %I:%M:%S",
)
os.environ["USE_TORCH"] = "1"
from cleantext import clean
from doctr.io import DocumentFile
from doctr.models import ocr_predictor
from spellchecker import SpellChecker
def simple_rename(filepath, target_ext=".txt"):
"""simple_rename - get a new str to rename a file"""
_fp = Path(filepath)
basename = _fp.stem
return f"OCR_{basename}_{target_ext}"
def rm_local_text_files(name_contains="RESULT_"):
"""
rm_local_text_files - remove local text files
"""
files = [
f
for f in Path.cwd().iterdir()
if f.is_file() and f.suffix == ".txt" and name_contains in f.name
]
logging.info(f"removing {len(files)} text files")
for f in files:
os.remove(f)
logging.info("done")
def corr(
s: str,
add_space_when_numerics=False,
exceptions=["e.g.", "i.e.", "etc.", "cf.", "vs.", "p."],
) -> str:
"""corrects spacing in a string
Args:
s (str): the string to correct
add_space_when_numerics (bool, optional): [add a space when a period is between two numbers, example 5.73]. Defaults to False.
exceptions (list, optional): [do not change these substrings]. Defaults to ['e.g.', 'i.e.', 'etc.', 'cf.', 'vs.', 'p.'].
Returns:
str: the corrected string
"""
if add_space_when_numerics:
s = re.sub(r"(\d)\.(\d)", r"\1. \2", s)
s = re.sub(r"\s+", " ", s)
s = re.sub(r'\s([?.!"](?:\s|$))', r"\1", s)
# fix space before apostrophe
s = re.sub(r"\s\'", r"'", s)
# fix space after apostrophe
s = re.sub(r"'\s", r"'", s)
# fix space before comma
s = re.sub(r"\s,", r",", s)
for e in exceptions:
expected_sub = re.sub(r"\s", "", e)
s = s.replace(expected_sub, e)
return s
def fix_punct_spaces(string: str) -> str:
"""
fix_punct_spaces - fix spaces around punctuation
:param str string: input string
:return str: string with spaces fixed
"""
fix_spaces = re.compile(r"\s*([?!.,]+(?:\s+[?!.,]+)*)\s*")
string = fix_spaces.sub(lambda x: "{} ".format(x.group(1).replace(" ", "")), string)
string = string.replace(" ' ", "'")
string = string.replace(' " ', '"')
return string.strip()
def clean_OCR(ugly_text: str) -> str:
"""
clean_OCR - clean up the OCR text
:param str ugly_text: input text to be cleaned
:return str: cleaned text
"""
# Remove all the newlines.
cleaned_text = ugly_text.replace("\n", " ")
# Remove all the tabs.
cleaned_text = cleaned_text.replace("\t", " ")
# Remove all the double spaces.
cleaned_text = cleaned_text.replace(" ", " ")
# Remove all the spaces at the beginning of the text.
cleaned_text = cleaned_text.lstrip()
# remove all instances of "- " and " - "
cleaned_text = cleaned_text.replace("- ", "")
cleaned_text = cleaned_text.replace(" -", "")
return fix_punct_spaces(cleaned_text)
def move2completed(
from_dir, filename, new_folder: str = "completed", verbose: bool = False
):
"""
move2completed - move a file to a new folder
"""
old_filepath = join(from_dir, filename)
new_filedirectory = join(from_dir, new_folder)
if not os.path.isdir(new_filedirectory):
os.mkdir(new_filedirectory)
if verbose:
print("created new directory for files at: \n", new_filedirectory)
new_filepath = join(new_filedirectory, filename)
try:
shutil.move(old_filepath, new_filepath)
logging.info("successfully moved the file {} to */completed.".format(filename))
except:
logging.info(
"ERROR! unable to move file to \n{}. Please investigate".format(
new_filepath
)
)
custom_replace_list = {
"t0": "to",
"'$": "'s",
",,": ", ",
"_ ": " ",
" '": "'",
}
replace_corr_exceptions = {
"i. e.": "i.e.",
"e. g.": "e.g.",
"e. g": "e.g.",
" ,": ",",
}
spell = SpellChecker()
def check_word_spelling(word: str) -> bool:
"""
check_word_spelling - check the spelling of a word
Args:
word (str): word to check
Returns:
bool: True if word is spelled correctly, False if not
"""
misspelled = spell.unknown([word])
return len(misspelled) == 0
def eval_and_replace(text: str, match_token: str = "- ") -> str:
"""
eval_and_replace - conditionally replace all instances of a substring in a string based on whether the eliminated substring results in a valid word
Args:
text (str): text to evaluate
match_token (str, optional): token to replace. Defaults to "- ".
Returns:
str: text with replaced tokens
"""
if match_token not in text:
return text
else:
while True:
full_before_text = text.split(match_token, maxsplit=1)[0]
before_text = [
char for char in full_before_text.split()[-1] if char.isalpha()
]
before_text = "".join(before_text)
full_after_text = text.split(match_token, maxsplit=1)[-1]
after_text = [char for char in full_after_text.split()[0] if char.isalpha()]
after_text = "".join(after_text)
full_text = before_text + after_text
if check_word_spelling(full_text):
text = full_before_text + full_after_text
else:
text = full_before_text + " " + full_after_text
if match_token not in text:
break
return text
def cleantxt_ocr(ugly_text, lower=False, lang: str = "en") -> str:
"""
cleantxt_ocr - clean text from OCR
https://pypi.org/project/clean-text/
Args:
ugly_text (str): text to clean
lower (bool, optional): lowercase text. Defaults to False.
lang (str, optional): language of text. Defaults to "en".
Returns:
str: cleaned text
"""
cleaned_text = clean(
ugly_text,
fix_unicode=True, # fix various unicode errors
to_ascii=True, # transliterate to closest ASCII representation
lower=lower, # lowercase text
no_line_breaks=True, # fully strip line breaks as opposed to only normalizing them
no_urls=True, # replace all URLs with a special token
no_emails=True, # replace all email addresses with a special token
no_phone_numbers=True, # replace all phone numbers with a special token
no_numbers=False, # replace all numbers with a special token
no_digits=False, # replace all digits with a special token
no_currency_symbols=False, # replace all currency symbols with a special token
no_punct=False, # remove punctuations
replace_with_punct="", # instead of removing punctuations you may replace them
replace_with_url="this url",
replace_with_email="this email",
replace_with_phone_number="this phone number",
lang=lang, # set to 'de' for German special handling
)
return cleaned_text
def format_ocr_out(OCR_data):
"""format OCR output to text"""
if isinstance(OCR_data, list):
text = " ".join(OCR_data)
else:
text = str(OCR_data)
_clean = cleantxt_ocr(text)
return corr(_clean)
def postprocess(text: str) -> str:
"""to be used after recombining the lines"""
proc = corr(cleantxt_ocr(text))
for k, v in custom_replace_list.items():
proc = proc.replace(str(k), str(v))
proc = corr(proc)
for k, v in replace_corr_exceptions.items():
proc = proc.replace(str(k), str(v))
return eval_and_replace(proc)
def result2text(result, as_text=False) -> str or list:
"""Convert OCR result to text"""
full_doc = []
for i, page in enumerate(result.pages, start=1):
text = ""
for block in page.blocks:
text += "\n\t"
for line in block.lines:
for word in line.words:
# print(dir(word))
text += word.value + " "
full_doc.append(text)
return "\n".join(full_doc) if as_text else full_doc
def convert_PDF_to_Text(
PDF_file,
ocr_model=None,
max_pages: int = 20,
) -> str:
"""
convert_PDF_to_Text - convert a PDF file to text
:param str PDF_file: path to PDF file
:param ocr_model: model to use for OCR, defaults to None (uses the default model)
:param int max_pages: maximum number of pages to process, defaults to 20
:return str: text from PDF
"""
st = time.perf_counter()
PDF_file = Path(PDF_file)
ocr_model = ocr_predictor(pretrained=True) if ocr_model is None else ocr_model
logging.info(f"starting OCR on {PDF_file.name}")
doc = DocumentFile.from_pdf(PDF_file)
truncated = False
if len(doc) > max_pages:
logging.warning(
f"PDF has {len(doc)} pages, which is more than {max_pages}.. truncating"
)
doc = doc[:max_pages]
truncated = True
# Analyze
logging.info(f"running OCR on {len(doc)} pages")
result = ocr_model(doc)
raw_text = result2text(result)
proc_text = [format_ocr_out(r) for r in raw_text]
fin_text = [postprocess(t) for t in proc_text]
ocr_results = "\n\n".join(fin_text)
fn_rt = time.perf_counter() - st
logging.info("OCR complete")
results_dict = {
"num_pages": len(doc),
"runtime": round(fn_rt, 2),
"date": str(date.today()),
"converted_text": ocr_results,
"truncated": truncated,
"length": len(ocr_results),
}
return results_dict
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