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Patrick Jentsch
2019-05-20 11:10:40 +02:00
parent 93de923b4e
commit e1462152fe
2 changed files with 16 additions and 14 deletions
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18
ocr
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@ -21,7 +21,7 @@ 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
' Default: 2048 * n_cores
' 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
@ -123,7 +123,7 @@ class OCRWorkflow(WorkflowRunner):
' ##################################################
'''
split_jobs = []
split_job_nCores = min(
split_job_n_cores = min(
self.n_cores,
max(1, int(self.n_cores / len(self.jobs)))
)
@ -148,7 +148,7 @@ class OCRWorkflow(WorkflowRunner):
command=cmd,
dependencies='create_output_directories_job_-_%i' % (index),
label='split_job_-_%i' % (index),
nCores=split_job_nCores
nCores=split_job_n_cores
)
)
@ -170,7 +170,7 @@ class OCRWorkflow(WorkflowRunner):
' four cores available for this workflow, the available core
' number.
'''
binarisation_job_nCores = min(4, self.n_cores)
binarisation_job_n_cores = min(4, self.n_cores)
for index, job in enumerate(self.jobs):
files = os.listdir(os.path.join(job['output_dir'], 'tmp'))
files = filter(lambda x: x.endswith('.tif'), files)
@ -181,7 +181,7 @@ class OCRWorkflow(WorkflowRunner):
)
cmd = 'ocropus-nlbin --output "%s" --parallel "%i" %s' % (
os.path.join(job['output_dir'], 'tmp'),
binarisation_job_nCores,
binarisation_job_n_cores,
' '.join(files)
)
binarisation_jobs.append(
@ -189,7 +189,7 @@ class OCRWorkflow(WorkflowRunner):
command=cmd,
dependencies='split_job_-_%i' % (index),
label='binarisation_job_-_%i' % (index),
nCores=binarisation_job_nCores
nCores=binarisation_job_n_cores
)
)
@ -249,13 +249,13 @@ class OCRWorkflow(WorkflowRunner):
' or, if there are less then four cores available for this workflow,
' the available core number.
'''
ocr_job_nCores = min(4, self.n_cores)
ocr_job_n_cores = min(4, self.n_cores)
'''
' WORKAROUND: Tesseract only uses one core for the deu_frak language
' model, so the workflow will also only reserve one in this case.
'''
if self.lang == "deu_frak":
ocr_job_nCores = 1
ocr_job_n_cores = 1
for index, job in enumerate(self.jobs):
files = os.listdir(os.path.join(job['output_dir'], 'tmp'))
if self.skip_binarisation:
@ -293,7 +293,7 @@ class OCRWorkflow(WorkflowRunner):
command=cmd,
dependencies=ocr_job_dependencies,
label='ocr_job_-_%i-%i' % (index, number),
nCores=ocr_job_nCores
nCores=ocr_job_n_cores
)
)
number += 1