199 lines
7.4 KiB
Python
199 lines
7.4 KiB
Python
import os
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import subprocess
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from django.utils.importlib import import_module
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from django.template.defaultfilters import slugify
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from django.core.exceptions import ObjectDoesNotExist
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from converter.conf.settings import UNPAPER_PATH
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from converter.conf.settings import OCR_OPTIONS
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from converter.conf.settings import DEFAULT_OPTIONS
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from converter.conf.settings import LOW_QUALITY_OPTIONS
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from converter.conf.settings import HIGH_QUALITY_OPTIONS
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from converter.conf.settings import GRAPHICS_BACKEND
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from exceptions import UnpaperError
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#from converter.conf.settings import UNOCONV_PATH
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from common import TEMPORARY_DIRECTORY
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from converter import TRANFORMATION_CHOICES
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from documents.utils import document_save_to_temp_dir
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QUALITY_DEFAULT = u'quality_default'
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QUALITY_LOW = u'quality_low'
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QUALITY_HIGH = u'quality_high'
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QUALITY_SETTINGS = {QUALITY_DEFAULT: DEFAULT_OPTIONS,
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QUALITY_LOW: LOW_QUALITY_OPTIONS, QUALITY_HIGH: HIGH_QUALITY_OPTIONS}
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def _lazy_load(fn):
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_cached = []
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def _decorated():
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if not _cached:
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_cached.append(fn())
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return _cached[0]
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return _decorated
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@_lazy_load
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def _get_backend():
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return import_module(GRAPHICS_BACKEND)
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try:
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backend = _get_backend()
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except ImportError:
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raise ImportError(u'Missing or incorrect converter backend: %s' % GRAPHICS_BACKEND)
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def cleanup(filename):
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''' tries to remove the given filename. Ignores non-existent files '''
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try:
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os.remove(filename)
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except OSError:
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pass
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def execute_unpaper(input_filepath, output_filepath):
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command = []
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command.append(UNPAPER_PATH)
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command.append(u'--overwrite')
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command.append(input_filepath)
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command.append(output_filepath)
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proc = subprocess.Popen(command, close_fds=True, stderr=subprocess.PIPE)
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return_code = proc.wait()
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if return_code != 0:
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raise UnpaperError(proc.stderr.readline())
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"""
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def execute_unoconv(input_filepath, output_filepath, arguments=''):
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command = [UNOCONV_PATH]
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command.extend(['--stdout'])
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command.extend(shlex.split(str(arguments)))
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command.append(input_filepath)
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proc = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
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with open(output_filepath, 'w') as output:
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shutil.copyfileobj(proc.stdout, output)
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return (proc.wait(), proc.stderr.read())
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"""
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def cache_cleanup(input_filepath, size, quality=QUALITY_DEFAULT, page=0, format=u'jpg', extra_options=u''):
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filepath = create_image_cache_filename(input_filepath, size=size, page=page, format=format, quality=quality, extra_options=extra_options)
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try:
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os.remove(filepath)
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except OSError:
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pass
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def create_image_cache_filename(input_filepath, *args, **kwargs):
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if input_filepath:
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temp_filename, separator = os.path.splitext(os.path.basename(input_filepath))
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temp_path = os.path.join(TEMPORARY_DIRECTORY, temp_filename)
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final_filepath = []
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[final_filepath.append(str(arg)) for arg in args]
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final_filepath.extend([u'%s_%s' % (key, value) for key, value in kwargs.items()])
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temp_path += slugify(u'_'.join(final_filepath))
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return temp_path
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else:
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return None
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def in_image_cache(input_filepath, size, page=0, format=u'jpg', quality=QUALITY_DEFAULT, extra_options=u'', zoom=100, rotation=0):
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output_filepath = create_image_cache_filename(input_filepath, size=size, page=page, format=format, quality=quality, extra_options=extra_options, zoom=zoom, rotation=rotation)
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if os.path.exists(output_filepath):
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return output_filepath
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else:
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return None
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def convert(input_filepath, size, quality=QUALITY_DEFAULT, cache=True, page=0, format=u'jpg', extra_options=u'', mimetype=None, extension=None, cleanup_files=True, zoom=100, rotation=0):
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unoconv_output = None
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output_filepath = create_image_cache_filename(input_filepath, size=size, page=page, format=format, quality=quality, extra_options=extra_options, zoom=zoom, rotation=rotation)
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if os.path.exists(output_filepath):
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return output_filepath
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'''
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if extension:
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if extension.lower() == 'ods':
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unoconv_output = '%s_pdf' % output_filepath
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status, error_string = execute_unoconv(input_filepath, unoconv_output, arguments='-f pdf')
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if status:
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errors = get_errors(error_string)
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raise ConvertError(status, errors)
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cleanup(input_filepath)
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input_filepath = unoconv_output
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'''
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try:
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input_arg = u'%s[%s]' % (input_filepath, page)
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extra_options += u' -resize %s' % size
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if zoom != 100:
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extra_options += u' -resize %d%% ' % zoom
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if rotation != 0 and rotation != 360:
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extra_options += u' -rotate %d ' % rotation
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if format == u'jpg':
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extra_options += u' -quality 85'
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backend.execute_convert(input_filepath=input_arg, arguments=extra_options, output_filepath=u'%s:%s' % (format, output_filepath), quality=quality)
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finally:
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if cleanup_files:
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cleanup(input_filepath)
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if unoconv_output:
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cleanup(unoconv_output)
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return output_filepath
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def get_page_count(input_filepath):
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try:
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return len(backend.execute_identify(unicode(input_filepath)).splitlines())
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except Exception, e:
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#TODO: send to other page number identifying program
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return 1
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def convert_document_for_ocr(document, page=0, format='tif'):
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#Extract document file
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input_filepath = document_save_to_temp_dir(document, document.uuid)
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#Convert for OCR
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temp_filename, separator = os.path.splitext(os.path.basename(input_filepath))
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temp_path = os.path.join(TEMPORARY_DIRECTORY, temp_filename)
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transformation_output_file = u'%s_trans%s%s%s' % (temp_path, page, os.extsep, format)
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unpaper_input_file = u'%s_unpaper_in%s%spnm' % (temp_path, page, os.extsep)
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unpaper_output_file = u'%s_unpaper_out%s%spnm' % (temp_path, page, os.extsep)
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convert_output_file = u'%s_ocr%s%s%s' % (temp_path, page, os.extsep, format)
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input_arg = u'%s[%s]' % (input_filepath, page)
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transformation_list = []
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try:
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#Catch invalid or non existing pages
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document_page = document.documentpage_set.get(document=document, page_number=page + 1)
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for page_transformation in document_page.documentpagetransformation_set.all():
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if page_transformation.transformation in TRANFORMATION_CHOICES:
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output = TRANFORMATION_CHOICES[page_transformation.transformation] % eval(page_transformation.arguments)
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transformation_list.append(output)
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except ObjectDoesNotExist:
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pass
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tranformation_string = ' '.join(transformation_list)
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try:
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#Apply default transformations
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backend.execute_convert(input_filepath=input_arg, quality=QUALITY_HIGH, arguments=tranformation_string, output_filepath=transformation_output_file)
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#Do OCR operations
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backend.execute_convert(input_filepath=transformation_output_file, arguments=OCR_OPTIONS, output_filepath=unpaper_input_file)
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# Process by unpaper
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execute_unpaper(input_filepath=unpaper_input_file, output_filepath=unpaper_output_file)
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# Convert to tif
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backend.execute_convert(input_filepath=unpaper_output_file, output_filepath=convert_output_file)
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finally:
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cleanup(transformation_output_file)
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cleanup(unpaper_input_file)
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cleanup(unpaper_output_file)
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return convert_output_file
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