mirror of
https://gitlab.ub.uni-bielefeld.de/sfb1288inf/ocr.git
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475 lines
20 KiB
Python
Executable File
475 lines
20 KiB
Python
Executable File
#!/usr/bin/env python2.7
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# coding=utf-8
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"""
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ocr
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Usage: For usage instructions run with option --help
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Authors: Patrick Jentsch <p.jentsch@uni-bielefeld.de
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Stephan Porada <sporada@uni-bielefeld.de>
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"""
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from argparse import ArgumentParser
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from natsort import natsorted
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from pyflow import WorkflowRunner
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import multiprocessing
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import os
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import sys
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import tempfile
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TESSERACT_MODELS = ['deu', 'eng', 'enm', 'fra', 'frk', 'frm', 'ita', 'por',
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'spa']
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def parse_args():
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parser = ArgumentParser(description='OCR Pipeline utilizing tesseract.')
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parser.add_argument('-i', '--input-directory',
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help='Input directory (only PDF files get processed)',
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required=True)
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parser.add_argument('-o', '--output-directory',
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help='Output directory',
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required=True)
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parser.add_argument('-l', '--language',
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choices=TESSERACT_MODELS,
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required=True)
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parser.add_argument('--binarize',
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action='store_true',
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help='Use ocropy binarisation as preprocessing step.')
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parser.add_argument('--log-dir')
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parser.add_argument('--n-cores',
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default=min(4, multiprocessing.cpu_count()),
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help='Total number of cores available.',
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type=int)
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parser.add_argument('--intermediate-directory')
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parser.add_argument('--zip',
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help='Zips all results in different archives depending'
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' on result types. Also zips everything into one '
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'archive.')
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return parser.parse_args()
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class OCRPipelineJob:
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"""An OCR pipeline job class
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Each input file of the pipeline is represented as an OCR pipeline job,
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which holds all necessary information for the pipeline to process it.
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Arguments:
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file -- Path to the file
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output_dir -- Path to a directory, where job results a stored
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intermediate_dir -- Path to a directory, where intermediate files are
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stored.
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"""
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def __init__(self, file, output_dir, intermediate_dir):
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self.file = file
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self.intermediate_dir = intermediate_dir
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self.name = os.path.basename(file).rsplit('.', 1)[0]
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self.output_dir = output_dir
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class OCRPipeline(WorkflowRunner):
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def __init__(self, input_dir, lang, output_dir, binarize, intermediate_dir,
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n_cores, zip):
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self.input_dir = input_dir
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self.lang = lang
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self.output_dir = output_dir
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self.binarize = binarize
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if intermediate_dir is None:
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self.intermediate_dir = os.path.join(output_dir, 'tmp')
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else:
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self.intermediate_dir = tempfile.mkdtemp(dir=intermediate_dir)
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self.n_cores = n_cores
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if zip is None:
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self.zip = zip
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else:
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if zip.lower().endswith('.zip'):
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# Remove .zip file extension if provided
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self.zip = zip[:-4]
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self.zip = self.zip if self.zip else 'output'
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else:
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self.zip = zip
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self.jobs = collect_jobs(self.input_dir,
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self.output_dir,
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self.intermediate_dir)
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def workflow(self):
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if not self.jobs:
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return
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'''
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' ##################################################
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' # setup output directory #
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' ##################################################
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'''
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setup_output_directory_tasks = []
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for i, job in enumerate(self.jobs):
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cmd = 'mkdir'
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cmd += ' -p'
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cmd += ' "{}"'.format(job.intermediate_dir)
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cmd += ' "{}"'.format(os.path.join(job.output_dir, 'poco'))
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lbl = 'setup_output_directory_-_{}'.format(i)
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task = self.addTask(command=cmd, label=lbl)
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setup_output_directory_tasks.append(task)
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'''
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' ##################################################
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' # split input #
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' ##################################################
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'''
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split_input_tasks = []
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n_cores = min(self.n_cores, max(1, int(self.n_cores / len(self.jobs))))
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for i, job in enumerate(self.jobs):
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input_file = job.file
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output_file = '{}/page-%d.tif'.format(job.intermediate_dir)
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cmd = 'gs'
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cmd += ' -dBATCH'
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cmd += ' -dNOPAUSE'
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cmd += ' -dNumRenderingThreads={}'.format(n_cores)
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cmd += ' -dQUIET'
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cmd += ' -r300'
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cmd += ' -sDEVICE=tiff24nc'
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cmd += ' -sCompression=lzw'
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cmd += ' "-sOutputFile={}"'.format(output_file)
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cmd += ' "{}"'.format(input_file)
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deps = 'setup_output_directory_-_{}'.format(i)
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lbl = 'split_input_-_{}'.format(i)
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task = self.addTask(command=cmd, dependencies=deps, label=lbl, nCores=n_cores) # noqa
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split_input_tasks.append(task)
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if self.binarize:
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'''
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' The binarization_tasks list is created based on the output files
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' of the split_tasks. So wait until they are finished.
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'''
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self.waitForTasks()
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'''
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' ##################################################
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' # binarization #
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' ##################################################
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'''
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binarization_tasks = []
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'''
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' We run ocropus-nlbin with either four or, if there are less then
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' four cores available for this workflow, the available core
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' number.
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'''
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n_cores = min(4, self.n_cores)
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for i, job in enumerate(self.jobs):
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input_dir = job.intermediate_dir
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output_dir = job.intermediate_dir
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files = filter(lambda x: x.endswith('.tif'), os.listdir(input_dir)) # noqa
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files = natsorted(files)
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files = map(lambda x: os.path.join(input_dir, x), files)
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cmd = 'ocropus-nlbin "{}"'.format('" "'.join(files))
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cmd += ' --nocheck'
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cmd += ' --output "{}"'.format(output_dir)
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cmd += ' --parallel "{}"'.format(n_cores)
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print(cmd)
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deps = 'split_input_-_{}'.format(i)
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lbl = 'binarization_-_{}'.format(i)
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task = self.addTask(command=cmd, dependencies=deps, label=lbl, nCores=n_cores) # noqa
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binarization_tasks.append(task)
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self.waitForTasks()
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'''
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' ##################################################
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' # Renaming of binarization output files #
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' ##################################################
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'''
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for i, job in enumerate(self.jobs):
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input_dir = job.intermediate_dir
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output_dir = job.intermediate_dir
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files = filter(lambda x: x.endswith('.bin.png'), os.listdir(input_dir)) # noqa
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for file in files:
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# int conversion is done in order to trim leading zeros
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page_number = int(file.split('.', 1)[0])
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output_file = 'page-{}.bin.png'.format(page_number)
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os.rename(os.path.join(output_dir, file),
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os.path.join(output_dir, output_file))
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'''
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' The ocr_tasks are created based of the output files of either the
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' split_tasks or binarization_tasks. So wait until they are
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' finished.
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'''
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self.waitForTasks()
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'''
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' ##################################################
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' # ocr #
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' ##################################################
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'''
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ocr_tasks = []
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'''
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' Tesseract runs fastest with four cores. So we run it with either four
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' or, if there are less then four cores available for this workflow,
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' the available core number.
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'''
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n_cores = min(4, self.n_cores)
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for i, job in enumerate(self.jobs):
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input_dir = job.intermediate_dir
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output_dir = job.intermediate_dir
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files = os.listdir(input_dir)
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if self.binarize:
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deps = 'binarization_-_{}'.format(i)
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files = filter(lambda x: x.endswith('.bin.png'), files)
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else:
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deps = 'split_input_-_{}'.format(i)
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files = filter(lambda x: x.endswith('.tif'), files)
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files = natsorted(files)
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files = map(lambda x: os.path.join(input_dir, x), files)
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for j, file in enumerate(files):
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if self.binarize:
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output_file_base = os.path.join(output_dir, file.rsplit('.', 2)[0]) # noqa
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else:
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output_file_base = os.path.join(output_dir, file.rsplit('.', 1)[0]) # noqa
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cmd = 'tesseract "{}" "{}"'.format(file, output_file_base)
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cmd += ' -l "{}"'.format(self.lang)
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cmd += ' hocr pdf txt'
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cmd += ' && '
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cmd += 'sed -i \'s+{}/++g\' "{}".hocr'.format(input_dir, output_file_base) # noqa
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lbl = 'ocr_-_{}-{}'.format(i, j)
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task = self.addTask(command=cmd, dependencies=deps, label=lbl, nCores=n_cores) # noqa
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ocr_tasks.append(task)
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'''
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' The following jobs are created based of the output files of the
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' ocr_tasks. So wait until they are finished.
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'''
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self.waitForTasks()
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'''
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' ##################################################
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' # combined pdf creation #
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' ##################################################
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'''
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combined_pdf_creation_tasks = []
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n_cores = min(self.n_cores, max(1, int(self.n_cores / len(self.jobs))))
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for i, job in enumerate(self.jobs):
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input_dir = job.intermediate_dir
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output_file = os.path.join(job.output_dir, '{}.pdf'.format(job.name)) # noqa
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files = filter(lambda x: x.endswith('.pdf'), os.listdir(input_dir))
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files = natsorted(files)
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files = map(lambda x: os.path.join(input_dir, x), files)
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cmd = 'gs'
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cmd += ' -dBATCH'
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cmd += ' -dNOPAUSE'
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cmd += ' -dNumRenderingThreads={}'.format(n_cores)
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cmd += ' -dPDFSETTINGS=/ebook'
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cmd += ' -dQUIET'
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cmd += ' -sDEVICE=pdfwrite'
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cmd += ' "-sOutputFile={}"'.format(output_file)
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cmd += ' "{}"'.format('" "'.join(files))
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deps = filter(lambda x: x.startswith('ocr_-_{}'.format(i)), ocr_tasks) # noqa
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lbl = 'combined_pdf_creation_-_{}'.format(i)
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task = self.addTask(command=cmd, dependencies=deps, label=lbl, nCores=n_cores) # noqa
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combined_pdf_creation_tasks.append(task)
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'''
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' ##################################################
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' # combined txt creation #
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' ##################################################
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'''
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combined_txt_creation_tasks = []
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for i, job in enumerate(self.jobs):
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input_dir = job.intermediate_dir
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output_file = os.path.join(job.output_dir, '{}.txt'.format(job.name)) # noqa
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files = filter(lambda x: x.endswith('.txt'), os.listdir(input_dir))
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files = natsorted(files)
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files = map(lambda x: os.path.join(input_dir, x), files)
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cmd = 'cat "{}" > "{}"'.format('" "'.join(files), output_file)
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deps = filter(lambda x: x.startswith('ocr_-_{}'.format(i)), ocr_tasks) # noqa
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lbl = 'combined_txt_creation_-_{}'.format(i)
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task = self.addTask(command=cmd, dependencies=deps, label=lbl)
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combined_txt_creation_tasks.append(task)
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'''
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' ##################################################
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' # tei p5 creation #
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' ##################################################
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'''
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tei_p5_creation_tasks = []
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for i, job in enumerate(self.jobs):
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input_dir = job.intermediate_dir
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output_file = os.path.join(job.output_dir, '{}.xml'.format(job.name)) # noqa
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files = filter(lambda x: x.endswith('.hocr'),
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os.listdir(input_dir))
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files = natsorted(files)
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files = map(lambda x: os.path.join(input_dir, x), files)
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cmd = 'hocrtotei "{}" "{}"'.format('" "'.join(files),
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output_file)
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deps = filter(lambda x: x.startswith('ocr_-_{}'.format(i)), ocr_tasks) # noqa
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lbl = 'tei_p5_creation_-_{}'.format(i)
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task = self.addTask(command=cmd, dependencies=deps, label=lbl)
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tei_p5_creation_tasks.append(task)
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'''
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' ##################################################
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' # poco bundle creation #
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' ##################################################
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'''
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poco_bundle_creation_tasks = []
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for i, job in enumerate(self.jobs):
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input_dir = job.intermediate_dir
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output_dir = os.path.join(job.output_dir, 'poco')
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files = os.listdir(input_dir)
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if self.binarize:
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files = filter(lambda x: x.endswith(('.bin.png', '.hocr')), files) # noqa
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else:
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files = filter(lambda x: x.endswith(('.tif', '.hocr')), files)
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files = natsorted(files)
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files = map(lambda x: os.path.join(input_dir, x), files)
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cmd = 'mv "{}" "{}"'.format('" "'.join(files), output_dir)
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deps = filter(lambda x: x.startswith('ocr_-_{}'.format(i)), ocr_tasks) # noqa
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deps.append('tei_p5_creation_-_{}'.format(i))
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lbl = 'poco_bundle_creation_-_{}'.format(i)
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task = self.addTask(command=cmd, dependencies=deps, label=lbl)
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poco_bundle_creation_tasks.append(task)
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'''
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' The following jobs are created based of the output files of the
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' combined_pdf_creation_tasks. So wait until they are finished.
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'''
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self.waitForTasks()
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'''
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' ##################################################
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' # cleanup #
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' ##################################################
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'''
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cleanup_tasks = []
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for i, job in enumerate(self.jobs):
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input_dir = job.intermediate_dir
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cmd = 'rm -r "{}"'.format(input_dir)
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deps = ['combined_pdf_creation_-_{}'.format(i),
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'combined_txt_creation_-_{}'.format(i),
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'poco_bundle_creation_-_{}'.format(i),
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'tei_p5_creation_-_{}'.format(i)]
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lbl = 'job_cleanup_-_{}'.format(i)
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task = self.addTask(command=cmd, dependencies=deps, label=lbl)
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cleanup_tasks.append(task)
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input_dir = self.intermediate_dir
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cmd = 'rm -r "{}"'.format(input_dir)
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deps = cleanup_tasks
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lbl = 'pipeline_cleanup'
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task = self.addTask(command=cmd, dependencies=deps, label=lbl)
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cleanup_tasks.append(task)
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self.waitForTasks()
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'''
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' ##################################################
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' # zip creation #
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' ##################################################
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'''
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zip_creation_tasks = []
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if self.zip is not None:
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# zip all files
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cmd = 'cd "{}"'.format(self.output_dir)
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cmd += ' && '
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cmd += 'zip'
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cmd += ' -r'
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cmd += ' "{}.all.zip" .'.format(self.zip)
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cmd += ' -x "pyflow.data*" "*tmp*"'
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cmd += ' -i "*.pdf" "*.txt" "*.xml" "*.hocr" "*.{}"'.format('bin.png' if self.binarize else 'tif') # noqa
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cmd += ' && '
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cmd += 'cd -'
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deps = combined_pdf_creation_tasks + combined_txt_creation_tasks + poco_bundle_creation_tasks # noqa
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lbl = 'zip_creation_-_all'
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task = self.addTask(command=cmd, dependencies=deps, label=lbl)
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zip_creation_tasks.append(task)
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# zip PDF files
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cmd = 'cd "{}"'.format(self.output_dir)
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cmd += ' && '
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cmd += 'zip'
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cmd += ' -r'
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cmd += ' "{}.pdf.zip" .'.format(self.zip)
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cmd += ' -x "pyflow.data*" "*tmp*"'
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cmd += ' -i "*.pdf"'
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cmd += ' && '
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cmd += 'cd -'
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deps = combined_pdf_creation_tasks
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lbl = 'zip_creation_-_pdf'
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task = self.addTask(command=cmd, dependencies=deps, label=lbl)
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zip_creation_tasks.append(task)
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# zip TXT files
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cmd = 'cd "{}"'.format(self.output_dir)
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cmd += ' && '
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cmd += 'zip'
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cmd += ' -r'
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cmd += ' "{}.txt.zip" .'.format(self.zip)
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cmd += ' -x "pyflow.data*" "*tmp*"'
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cmd += ' -i "*.txt"'
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cmd += ' && '
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cmd += 'cd -'
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deps = combined_txt_creation_tasks
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lbl = 'zip_creation_-_txt'
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task = self.addTask(command=cmd, dependencies=deps, label=lbl)
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zip_creation_tasks.append(task)
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# zip XML files
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cmd = 'cd "{}"'.format(self.output_dir)
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cmd += ' && '
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cmd += 'zip'
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cmd += ' -r'
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cmd += ' "{}.xml.zip" .'.format(self.zip)
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cmd += ' -x "pyflow.data*" "*tmp*"'
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cmd += ' -i "*.xml"'
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cmd += ' && '
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cmd += 'cd -'
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deps = tei_p5_creation_tasks
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lbl = 'zip_creation_-_xml'
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task = self.addTask(command=cmd, dependencies=deps, label=lbl)
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zip_creation_tasks.append(task)
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# zip PoCo bundles
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cmd = 'cd "{}"'.format(self.output_dir)
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cmd += ' && '
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cmd += 'zip'
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cmd += ' -r'
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cmd += ' "{}.poco.zip" .'.format(self.zip)
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cmd += ' -x "pyflow.data*" "*tmp*"'
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cmd += ' -i "*.hocr" "*.{}"'.format('bin.png' if self.binarize else 'tif') # noqa
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cmd += ' && '
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cmd += 'cd -'
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deps = poco_bundle_creation_tasks
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lbl = 'zip_creation_-_poco'
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task = self.addTask(command=cmd, dependencies=deps, label=lbl)
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zip_creation_tasks.append(task)
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def collect_jobs(input_dir, output_dir, intermediate_dir):
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jobs = []
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for file in os.listdir(input_dir):
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if os.path.isdir(os.path.join(input_dir, file)):
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jobs += collect_jobs(os.path.join(input_dir, file),
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os.path.join(output_dir, file))
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elif file.lower().endswith('.pdf'):
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job = OCRPipelineJob(os.path.join(input_dir, file),
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os.path.join(output_dir, file),
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os.path.join(intermediate_dir, file))
|
|
jobs.append(job)
|
|
return jobs
|
|
|
|
|
|
def main():
|
|
args = parse_args()
|
|
ocr_pipeline = OCRPipeline(args.input_directory, args.language,
|
|
args.output_directory, args.binarize,
|
|
args.intermediate_directory, args.n_cores,
|
|
args.zip)
|
|
retval = ocr_pipeline.run(
|
|
dataDirRoot=(args.log_dir or args.output_directory),
|
|
nCores=args.n_cores
|
|
)
|
|
sys.exit(retval)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
main()
|