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