This commit is contained in:
Patrick Jentsch 2019-05-16 00:09:19 +02:00
parent 03b1054560
commit 4c0ba270db

147
ocr
View File

@ -36,6 +36,12 @@ def parse_arguments():
requirements: imagemagick, ocropus, pdftoppm, pdfunite, \
poppler-utils, pyflow, python2.7, python3.5, tesseract'
)
parser.add_argument(
'-i',
dest='inputDirectory',
help='The input directory.',
required=True
)
parser.add_argument(
'-l',
dest='lang',
@ -43,18 +49,10 @@ def parse_arguments():
required=True
)
parser.add_argument(
'--i',
default=os.path.normpath('/files_for_ocr'),
dest='inputDirectory',
help='The input directory.',
required=False
)
parser.add_argument(
'--o',
default=os.path.normpath('/files_from_ocr'),
'-o',
dest='outputDirectory',
help='The output directory.',
required=False
required=True
)
parser.add_argument(
'--skip-binarisation',
@ -93,7 +91,9 @@ class OCRWorkflow(WorkflowRunner):
def workflow(self):
'''
' Creating output directories...
' ##################################################
' # Create output directories #
' ##################################################
'''
create_output_directories_jobs = []
for index, job in enumerate(self.jobs):
@ -119,7 +119,9 @@ class OCRWorkflow(WorkflowRunner):
)
'''
' Splitting...
' ##################################################
' # Split #
' ##################################################
'''
split_jobs = []
split_job_nCores = min(
@ -128,7 +130,7 @@ class OCRWorkflow(WorkflowRunner):
)
for index, job in enumerate(self.jobs):
if job['filename'].endswith(('.tif', '.tiff')):
cmd = 'convert "%s" -compress LZW -density 300 -scene 1 "%s"/page-%%d.tif' % (
cmd = 'convert "%s" -compress LZW -density 300 -scene 1 "%s/page-%%d.tif"' % (
job['path'],
os.path.join(job['output_dir'], 'tmp')
)
@ -148,7 +150,15 @@ class OCRWorkflow(WorkflowRunner):
if not self.skipBinarisation:
'''
' Binarising...
' The binarisation_jobs are created based of the output files of
' the split_jobs. So wait until they are finished.
'''
self.waitForTasks()
'''
' ##################################################
' # Binarise #
' ##################################################
'''
binarisation_jobs = []
'''
@ -158,10 +168,17 @@ class OCRWorkflow(WorkflowRunner):
'''
binarisation_job_nCores = min(4, self.nCores)
for index, job in enumerate(self.jobs):
cmd = 'ls --quoting-style=shell-escape -v "%s"/*.tif | xargs ocropus-nlbin --output "%s" --parallel "%i"' % (
files = os.listdir(os.path.join(job['output_dir'], 'tmp'))
files = filter(lambda x: x.endswith('.tif'), files)
files.sort(key=lambda x: int(re.search(r'\d+', x).group(0)))
files = map(
lambda x: '"' + os.path.join(job['output_dir'], 'tmp', x) + '"',
files
)
cmd = 'ocropus-nlbin --output "%s" --parallel "%i" %s' % (
os.path.join(job['output_dir'], 'tmp'),
os.path.join(job['output_dir'], 'tmp'),
binarisation_job_nCores
binarisation_job_nCores,
' '.join(files)
)
binarisation_jobs.append(
self.addTask(
@ -173,25 +190,30 @@ class OCRWorkflow(WorkflowRunner):
)
'''
' Normalising file names from binarisation...
' The post_binarisation_jobs are created based of the output files
' of the binarisation_jobs. So wait until they are finished.
'''
self.waitForTasks()
'''
' ##################################################
' # Normalise file names from binarisation #
' ##################################################
'''
post_binarisation_jobs = []
for index, job in enumerate(self.jobs):
number = 0
files = os.listdir(os.path.join(job['output_dir'], 'tmp'))
files = filter(lambda x: x.endswith('.bin.png'), files)
files = sorted(
files,
key=lambda x: int(re.search(r'\d+', x).group(0))
)
files.sort()
for file in files:
cmd = 'mv "%s" "%s"' % (
os.path.join(job['output_dir'], 'tmp', file),
os.path.join(job['output_dir'], 'tmp', 'page-%i.%s' % (
int(file.split('.', 1)[0]),
file.split('.', 1)[1])
),
os.path.join(
job['output_dir'],
'tmp',
'page-%i.bin.png' % (int(file.split('.', 1)[0]))
)
)
post_binarisation_jobs.append(
self.addTask(
@ -206,9 +228,17 @@ class OCRWorkflow(WorkflowRunner):
number += 1
'''
' Performing OCR...
' The ocr_jobs are created based of the output files of either the
' split_jobs or post_binarisation_jobs. So wait until they are
' finished.
'''
self.waitForTasks()
'''
' ##################################################
' # Optical Character Recognition #
' ##################################################
'''
ocr_jobs = []
'''
' Tesseract runs fastest with four cores. So we run it with either four
@ -223,19 +253,20 @@ class OCRWorkflow(WorkflowRunner):
if self.lang == "deu_frak":
ocr_job_nCores = 1
for index, job in enumerate(self.jobs):
number = 0
files = os.listdir(os.path.join(job['output_dir'], 'tmp'))
if self.skipBinarisation:
files = filter(lambda x: x.endswith('.tif'), files)
else:
files = filter(lambda x: x.endswith('.bin.png'), files)
files = sorted(
files,
key=lambda x: int(re.search(r'\d+', x).group(0))
files.sort(key=lambda x: int(re.search(r'\d+', x).group(0)))
files = map(
lambda x: os.path.join(job['output_dir'], 'tmp', x),
files
)
number = 0
for file in files:
cmd = 'tesseract "%s" "%s" -l "%s" hocr pdf txt' % (
os.path.join(job['output_dir'], 'tmp', file),
file,
os.path.join(
job['output_dir'],
'tmp',
@ -253,7 +284,6 @@ class OCRWorkflow(WorkflowRunner):
),
post_binarisation_jobs
)
print(ocr_job_dependencies)
ocr_jobs.append(
self.addTask(
command=cmd,
@ -265,7 +295,15 @@ class OCRWorkflow(WorkflowRunner):
number += 1
'''
' Creating TEI P5 files...
' The following jobs are created based of the output files of the
' ocr_jobs. So wait until they are finished.
'''
self.waitForTasks()
'''
' ##################################################
' # Create TEI P5 files #
' ##################################################
'''
hocr_to_tei_jobs = []
for index, job in enumerate(self.jobs):
@ -273,7 +311,7 @@ class OCRWorkflow(WorkflowRunner):
os.path.join(job['output_dir'], 'tmp'),
os.path.join(
job['output_dir'],
job['filename'].rsplit('.', 1)[0] + '.xml'
os.path.join(job['output_dir'], job['name'] + '.xml')
)
)
hocr_to_tei_jobs.append(
@ -288,15 +326,24 @@ class OCRWorkflow(WorkflowRunner):
)
'''
' Merging PDF files...
' ##################################################
' # Merge PDF files #
' ##################################################
'''
pdf_merge_jobs = []
for index, job in enumerate(self.jobs):
cmd = '(ls --quoting-style=shell-escape -v "%s"/*.pdf && echo "\'%s\'") | xargs pdfunite' % (
os.path.join(job['output_dir'], 'tmp'),
files = os.listdir(os.path.join(job['output_dir'], 'tmp'))
files = filter(lambda x: x.endswith('.pdf'), files)
files.sort(key=lambda x: int(re.search(r'\d+', x).group(0)))
files = map(
lambda x: '"' + os.path.join(job['output_dir'], 'tmp', x) + '"',
files
)
cmd = 'pdfunite %s "%s"' % (
' '.join(files),
os.path.join(
job['output_dir'],
job['filename'].rsplit('.', 1)[0] + '.pdf'
os.path.join(job['output_dir'], job['name'] + '.pdf')
)
)
pdf_merge_jobs.append(
@ -311,15 +358,24 @@ class OCRWorkflow(WorkflowRunner):
)
'''
' Merging text files...
' ##################################################
' # Merge text files #
' ##################################################
'''
txt_merge_jobs = []
for index, job in enumerate(self.jobs):
cmd = 'ls --quoting-style=shell-escape -v "%s"/*.txt | xargs cat > "%s"' % (
os.path.join(job['output_dir'], 'tmp'),
files = os.listdir(os.path.join(job['output_dir'], 'tmp'))
files = filter(lambda x: x.endswith('.txt'), files)
files.sort(key=lambda x: int(re.search(r'\d+', x).group(0)))
files = map(
lambda x: '"' + os.path.join(job['output_dir'], 'tmp', x) + '"',
files
)
cmd = 'cat %s > "%s"' % (
' '.join(files),
os.path.join(
job['output_dir'],
job['filename'].rsplit('.', 1)[0] + '.txt'
os.path.join(job['output_dir'], job['name'] + '.txt')
)
)
txt_merge_jobs.append(
@ -334,7 +390,9 @@ class OCRWorkflow(WorkflowRunner):
)
'''
' Cleanup...
' ##################################################
' # Cleanup #
' ##################################################
'''
cleanup_jobs = []
if self.keepIntermediates:
@ -407,6 +465,7 @@ def analyze_jobs(inputDirectory, outputDirectory):
jobs.append(
{
'filename': file,
'name': file.rsplit('.', 1)[0],
'output_dir': os.path.join(outputDirectory, file),
'path': os.path.join(inputDirectory, file)
}