ocr/ocr_pyflow
2019-01-11 15:54:15 +01:00

316 lines
13 KiB
Python
Executable File

#!/usr/bin/env python2.7
# coding=utf-8
"""
ocr_pyflow.py
Date: 18/10/2018
Usage: For usage instructions run with option --help
Author: Madis Rumming <mrumming@uni-bielefeld.de>
"""
__author__ = "Madis Rumming <mrumming@uni-bielefeld.de>"
__copyright__ = "Copyright 2018, Data Infrastructure and Digital Humanities,\
SFB 1288, Bielefeld University"
__version__ = "0.7"
__maintainer__ = "Patrick Jentsch"
__email__ = "p.jentsch@uni-bielefeld.de"
__status__ = "Development"
import argparse
import multiprocessing
import os
import shlex
import sys
import unicodedata
from pyflow import WorkflowRunner
''' TODO:
' Implement --end-page: Last page to ocr
' Implement --memMb: Total amount of memory (RAM) available for this workflow. Default: 2048 * nCores
' Implement --rotate: Rotate pages from input (90, 180, 270)
' Implement --split-pages: Split pages in half after possible rotation
' Implement --start-page: First page to ocr
'''
def parse_arguments():
parser = argparse.ArgumentParser("Performs OCR of (historical) documents utilizing OCRopus for preprocessing and Tesseract OCR \
for OCR. Available outputs are HOCR, PDF, shrinked PDF, and simple DTAbf \
(TEI P5 compliant). Software requirements: imagemagick, ocropus, pdftk, pdftoppm, poppler-utils, pyflow, python2.7, tesseract")
parser.add_argument("-i",
dest="inputDir",
help="Input directory.",
required=True)
parser.add_argument("-l",
choices=["deu", "deu_frak", "eng", "enm", "fra", "spa", "frm"],
dest='lang',
help="Language for OCR",
required=True)
parser.add_argument("-o",
dest="outputDir",
help="Output directory.",
required=True)
parser.add_argument("--skip-image",
action='store_true',
default=False,
dest="skip_images",
help="Skip detection of images as input.",
required=False)
parser.add_argument("--skip-pdf",
action='store_true',
default=False,
dest="skip_pdf",
help="Skip detection of PDFs as input.",
required=False)
parser.add_argument("--pdf",
action='store_true',
default=False,
dest='pdf',
help="Create PDF files.",
required=False)
parser.add_argument("--keep-intermediates",
action='store_true',
default=False,
dest="keepIntermediates",
help="Keep intermediate files.",
required=False)
parser.add_argument("--nCores",
default=multiprocessing.cpu_count(),
dest="nCores",
help="Total number of cores available.",
required=False,
type=int)
return parser.parse_args()
class OCRWorkflow(WorkflowRunner):
def __init__(self, jobs, lang, pdf, keepIntermediates, nCores):
self.jobs = jobs
self.lang = lang
self.pdf = pdf
self.keepIntermediates = keepIntermediates
self.nCores = nCores
def workflow(self):
###
# Task "mkdir_job": create output directories
# Dependencies: None
###
mkdir_jobs = []
mkdir_job_number = 0
for job in self.jobs["images"] + self.jobs["pdf"]:
mkdir_job_number += 1
cmd = "mkdir -p %s %s %s %s" % (
os.path.join(job["output_dir"], "hocr_files"),
os.path.join(job["output_dir"], "tmp", "ocropus-nlbin"),
os.path.join(job["output_dir"], "tmp", "tesseract"),
os.path.join(job["output_dir"], "tmp", "tiff_files"))
cmd = shlex.escape(cmd);
mkdir_jobs.append(self.addTask(label="mkdir_job_-_%i" % (mkdir_job_number), command=cmd))
###
# Task "split_job": split input file into one tiff file per page
# Dependencies: mkdir_jobs
###
split_jobs = []
split_job_number = 0
for job in self.jobs["images"]:
split_job_number += 1
# TODO: Make the following command work
'''
cmd = "convert %s %s" % (
job["path"],
os.path.join(job["output_dir"], "tmp", "tiff_files", os.path.basename(job["path"]).rsplit(".", 1)[0] + "-%sd.tif" % ("%")))
'''
# WORKAROUND
cmd = "tiff2pdf -o %s %s && pdftoppm %s %s -tiff -r 300 -tiffcompression lzw -cropbox && rm %s" % (
os.path.join(job["output_dir"], "tmp", "tiff_files", os.path.basename(job["path"]).rsplit(".", 1)[0] + ".pdf"),
job["path"],
os.path.join(job["output_dir"], "tmp", "tiff_files", os.path.basename(job["path"]).rsplit(".", 1)[0] + ".pdf"),
os.path.join(job["output_dir"], "tmp", "tiff_files", os.path.basename(job["path"]).rsplit(".", 1)[0]),
os.path.join(job["output_dir"], "tmp", "tiff_files", os.path.basename(job["path"]).rsplit(".", 1)[0] + ".pdf"))
cmd = shlex.escape(cmd);
split_jobs.append(self.addTask(label="split_job_-_%i" % (split_job_number), command=cmd, dependencies=mkdir_jobs))
for job in self.jobs["pdf"]:
split_job_number += 1
cmd = "pdftoppm %s %s -tiff -r 300 -tiffcompression lzw -cropbox" % (
job["path"],
os.path.join(job["output_dir"], "tmp", "tiff_files", os.path.basename(job["path"]).rsplit(".", 1)[0]))
cmd = shlex.escape(cmd);
split_jobs.append(self.addTask(label="split_job_-_%i" % (split_job_number), command=cmd, dependencies=mkdir_jobs))
###
# Task "ocropus_nlbin_job": binarize tiff files from previous split
# Dependencies: split_jobs
###
ocropusnlbin_jobs = []
ocropusnlbin_job_number = 0
for job in self.jobs["images"] + self.jobs["pdf"]:
ocropusnlbin_job_number += 1
cmd = "ocropus-nlbin -o %s %s" % (
os.path.join(job["output_dir"], "tmp", "ocropus-nlbin"),
os.path.join(job["output_dir"], "tmp", "tiff_files", os.path.basename(job["path"]).rsplit(".", 1)[0] + "-*.tif"))
cmd = shlex.escape(cmd);
ocropusnlbin_jobs.append(self.addTask(label="ocropusnlbin_job_-_%i" % (ocropusnlbin_job_number), command=cmd, dependencies=split_jobs))
###
# Task "tesseract_job": perform OCR on binarized images
# Dependencies: ocropusnlbin_jobs
###
self.waitForTasks()
tesseract_jobs = []
tesseract_job_number = 0
for job in self.jobs["images"] + self.jobs["pdf"]:
# This list is empty if you don't wait for ocropus_nlbin_jobs to complete
for file in filter(lambda x: x.endswith(".bin.png"), os.listdir(os.path.join(job["output_dir"], "tmp", "ocropus-nlbin"))):
tesseract_job_number += 1
cmd = "tesseract %s %s -l %s hocr %s" % (
os.path.join(job["output_dir"], "tmp", "ocropus-nlbin", file),
os.path.join(job["output_dir"], "tmp", "tesseract", file.rsplit(".", 2)[0]),
self.lang,
"pdf" if self.pdf else "")
cmd = shlex.escape(cmd);
tesseract_jobs.append(self.addTask(label="tesseract_job_-_%i" % (tesseract_job_number), command=cmd, dependencies=ocropusnlbin_jobs, nCores=min(4, self.nCores)))
###
# Task "pdf_merge_job": Merge PDF files
# Dependencies: tesseract_jobs
###
pdf_merge_jobs = []
pdf_merge_job_number = 0
if self.pdf:
for job in self.jobs["images"] + self.jobs["pdf"]:
pdf_merge_job_number += 1
cmd = "pdftk %s cat output %s" % (
os.path.join(job["output_dir"], "tmp", "tesseract", "*.pdf"),
os.path.join(job["output_dir"], os.path.basename(job["path"].rsplit(".", 1)[0] + ".pdf")))
cmd = shlex.escape(cmd);
pdf_merge_jobs.append(self.addTask(label="pdf_merge_job_-_%i" % (pdf_merge_job_number), command=cmd, dependencies=tesseract_jobs))
###
# Task "pdf_to_txt_jobs":
# Dependencies: pdf_merge_jobs
###
pdf_to_txt_jobs = []
pdf_to_txt_job_number = 0
if self.pdf:
for job in self.jobs["images"] + self.jobs["pdf"]:
pdf_to_txt_job_number += 1
cmd = "pdftotext -raw %s" % (
os.path.join(job["output_dir"], os.path.basename(job["path"].rsplit(".", 1)[0] + ".pdf")))
cmd = shlex.escape(cmd);
pdf_merge_jobs.append(self.addTask(label="pdf_to_txt_job_-_%i" % (pdf_to_txt_job_number), command=cmd, dependencies=pdf_merge_jobs))
###
# Task "move_hocr_job": move hocr files from <output_dir>/tmp/tesseract to <output_dir>/hocr_files
# Dependencies: tesseract_jobs
###
move_hocr_jobs = []
move_hocr_job_number = 0
for job in self.jobs["images"] + self.jobs["pdf"]:
move_hocr_job_number += 1
cmd = "mv %s %s" % (
os.path.join(job["output_dir"], "tmp", "tesseract", "*.hocr"),
os.path.join(job["output_dir"], "hocr_files"))
cmd = shlex.escape(cmd);
move_hocr_jobs.append(self.addTask(label="move_hocr_job_-_%i" % (move_hocr_job_number), command=cmd, dependencies=tesseract_jobs))
###Total amount of memory (RAM) available for this workflow. Default: 2048 * nCores"
# Task "hocr_to_teip5_job": create TEI P5 file from hocr files
# Dependencies: move_hocr_jobs
###
hocr_to_teip5_jobs = []
hocr_to_teip5_job_number = 0
for job in self.jobs["images"] + self.jobs["pdf"]:
hocr_to_teip5_job_number += 1
cmd = "parse_hocr %s %s" % (
os.path.join(job["output_dir"], "hocr_files"),
os.path.join(os.path.join(job["output_dir"], os.path.basename(job["path"]).rsplit(".", 1)[0] + ".xml")))
cmd = shlex.escape(cmd);
hocr_to_teip5_jobs.append(self.addTask(label="hocr_to_teip5_job_-_%i" % (hocr_to_teip5_job_number), command=cmd, dependencies=move_hocr_jobs))
###
# Task "cleanup_job": remove temporary files
# Dependencies: All
###
self.waitForTasks()
cleanup_jobs = []
cleanup_job_counter = 0
if not self.keepIntermediates:
for job in self.jobs["images"] + self.jobs["pdf"]:
cleanup_job_counter += 1
cmd = "rm -r %s" % (os.path.join(job["output_dir"], "tmp"))
cmd = shlex.escape(cmd);
cleanup_jobs.append(self.addTask(label="cleanup_job_-_%i" % (cleanup_job_counter), command=cmd))
def analyze_jobs(inputDir, outputDir, skip_pdf=False, skip_images=False):
files = os.listdir(inputDir)
images = []
pdf = []
if not skip_images:
for file in filter(lambda x: x.endswith(".tif") or x.endswith(".tiff"), files):
images.append({"path": os.path.join(inputDir, file), "output_dir": os.path.join(outputDir, file.rsplit(".", 1)[0])})
if not skip_pdf:
for file in filter(lambda x: x.endswith(".pdf"), files):
pdf.append({"path": os.path.join(inputDir, file), "output_dir": os.path.join(outputDir, file.rsplit(".", 1)[0])})
for subDir in filter(lambda x: os.path.isdir(os.path.join(inputDir, x)), files):
subDirFiles = os.listdir(os.path.join(inputDir, subDir))
if not skip_images:
for file in filter(lambda x: x.endswith(".tif") or x.endswith(".tiff"), subDirFiles):
images.append({"path": os.path.join(inputDir, subDir, file), "output_dir": os.path.join(outputDir, subDir, file.rsplit(".", 1)[0])})
if not skip_pdf:
for file in filter(lambda x: x.endswith(".pdf"), subDirFiles):
pdf.append({"path": os.path.join(inputDir, subDir, file), "output_dir": os.path.join(outputDir, subDir, file.rsplit(".", 1)[0])})
return {"pdf": pdf, "images": images}
def normalize_input_filenames(path):
###
# Normalize input filenames and directories to avoid bugs and also for better usage and readability.
###
for file in os.listdir(path):
file_with_path = os.path.join(path, file)
if os.path.isdir(file_with_path):
normalize_input_filenames(file_with_path)
new_file_with_path = os.path.join(path, unicodedata.normalize("NFKD", file.decode("utf-8")).encode("ascii", "ignore").replace(" ", "_"))
os.rename(file_with_path, new_file_with_path)
def main():
args = parse_arguments()
normalize_input_filenames(args.inputDir)
jobs = analyze_jobs(args.inputDir, args.outputDir, skip_pdf=args.skip_pdf, skip_images=args.skip_images)
wflow = OCRWorkflow(jobs, args.lang, args.pdf, args.keepIntermediates, args.nCores)
retval = wflow.run(nCores=args.nCores)
sys.exit(retval)
if __name__ == "__main__":
main()