034875a88a
- Since tesseract (i.e. an ocr backend) is an optional requiremnt of mayan, we shouldn't fail, if it is not found. - S.a https://github.com/mayan-edms/mayan-edms/issues/50
137 lines
4.3 KiB
Python
137 lines
4.3 KiB
Python
from __future__ import absolute_import
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import logging
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import os
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import tempfile
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import sh
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from django.utils.translation import ugettext as _
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from common.settings import TEMPORARY_DIRECTORY
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from common.utils import fs_cleanup
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from converter.api import convert
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from documents.models import DocumentPage
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from .exceptions import UnpaperError
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from .literals import (DEFAULT_OCR_FILE_FORMAT, UNPAPER_FILE_FORMAT,
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DEFAULT_OCR_FILE_EXTENSION)
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from .parsers import parse_document_page
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from .parsers.exceptions import ParserError, ParserUnknownFile
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from .runtime import language_backend, ocr_backend
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from .settings import UNPAPER_PATH, LANGUAGE
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logger = logging.getLogger(__name__)
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try:
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UNPAPER = sh.Command(UNPAPER_PATH).bake(overwrite=True, no_multi_pages=True)
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except sh.CommandNotFound:
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logger.debug('unpaper not found')
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UNPAPER = None
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def do_document_ocr(queue_document):
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"""
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Try first to extract text from document pages using the registered
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parser, if the parser fails or if there is no parser registered for
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the document mimetype do a visual OCR by calling the corresponding
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OCR backend
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"""
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for document_page in queue_document.document.pages.all():
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try:
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# Try to extract text by means of a parser
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parse_document_page(document_page)
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except (ParserError, ParserUnknownFile):
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# Fall back to doing visual OCR
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document_filepath = document_page.document.get_image_cache_name(page=document_page.page_number, version=document_page.document_version.pk)
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logger.debug('document_filepath: %s' % document_filepath)
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unpaper_input = convert(document_filepath, file_format=UNPAPER_FILE_FORMAT)
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logger.debug('unpaper_input: %s' % unpaper_input)
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unpaper_output = execute_unpaper(input_filepath=unpaper_input)
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logger.debug('unpaper_output: %s' % unpaper_output)
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# Convert to TIFF
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pre_ocr_filepath = convert(input_filepath=unpaper_output, file_format=DEFAULT_OCR_FILE_FORMAT)
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logger.debug('pre_ocr_filepath: %s' % pre_ocr_filepath)
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# Tesseract needs an explicit file extension
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pre_ocr_filepath_w_ext = os.extsep.join([pre_ocr_filepath, DEFAULT_OCR_FILE_EXTENSION])
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logger.debug('pre_ocr_filepath_w_ext: %s' % pre_ocr_filepath_w_ext)
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os.rename(pre_ocr_filepath, pre_ocr_filepath_w_ext)
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try:
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ocr_text = ocr_backend.execute(pre_ocr_filepath_w_ext, LANGUAGE)
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document_page.content = ocr_cleanup(ocr_text)
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document_page.page_label = _(u'Text from OCR')
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document_page.save()
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except Exception as e:
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logger.debug('missing ocr backend: %s' % ocr_backend)
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logger.debug('I/O error({0}): {1}'.format(e.errno, e.strerror))
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finally:
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fs_cleanup(pre_ocr_filepath_w_ext)
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fs_cleanup(unpaper_input)
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fs_cleanup(document_filepath)
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fs_cleanup(unpaper_output)
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def ocr_cleanup(text):
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"""
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Cleanup the OCR's output passing it thru the selected language's
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cleanup filter
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"""
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output = []
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for line in text.splitlines():
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line = line.strip()
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for word in line.split():
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if language_backend:
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result = language_backend.check_word(word)
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else:
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result = word
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if result:
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output.append(result)
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output.append(u'\n')
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return u' '.join(output)
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def clean_pages():
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"""
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Tool that executes the OCR cleanup code on all of the existing
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documents
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"""
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for page in DocumentPage.objects.all():
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if page.content:
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page.content = ocr_cleanup(page.content)
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page.save()
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def execute_unpaper(input_filepath, output_filepath=None):
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"""
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Executes the program unpaper using subprocess's Popen
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"""
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if UNPAPER:
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if not output_filepath:
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fd, output_filepath = tempfile.mkstemp(dir=TEMPORARY_DIRECTORY)
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try:
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UNPAPER(input_filepath, output_filepath)
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except sh.ErrorReturnCode as exception:
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logger.error(exception)
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raise UnpaperError(exception.stderr)
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else:
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return output_filepath
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finally:
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os.close(fd)
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else:
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return input_filepath
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