qurator-spk/sbb_binarization
1
0
Fork 0
mirror of https://github.com/qurator-spk/sbb_binarization.git synced 2025-06-30 22:49:54 +02:00
Code Issues Releases Wiki Activity

Merge pull request #31 from bertsky/factor-setup

Browse source 
Factor setup
This commit is contained in:
vahidrezanezhad 2022-04-20 15:39:32 +02:00 • committed by GitHub
commit e1575268d7
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
3 changed files with 53 additions and 19 deletions
Download patch file Download diff file Expand all files Collapse all files

2
sbb_binarize/ocrd-tool.json
View file

@ -19,6 +19,8 @@
"model": {
"description": "Directory containing HDF5 models. Can be an absolute path or a path relative to the current working directory or $SBB_BINARIZE_DATA environment variable (if set)",
"type": "string",
"format": "uri",
"content-type": "text/directory",
"required": true
}
}

62
sbb_binarize/ocrd_cli.py
View file

@ -39,32 +39,60 @@ class SbbBinarizeProcessor(Processor):
def __init__(self, *args, **kwargs):
kwargs['ocrd_tool'] = OCRD_TOOL['tools'][TOOL]
kwargs['version'] = OCRD_TOOL['version']
if not(kwargs.get('show_help', None) or kwargs.get('dump_json', None) or kwargs.get('show_version')):
LOG = getLogger('processor.SbbBinarize.__init__')
if not 'model' in kwargs['parameter']:
raise ValueError("'model' parameter is required")
model_path = Path(kwargs['parameter']['model'])
if not model_path.is_absolute():
if 'SBB_BINARIZE_DATA' in environ and environ['SBB_BINARIZE_DATA']:
LOG.info("Environment variable SBB_BINARIZE_DATA is set to '%s' - prepending to model value '%s'. If you don't want this mechanism, unset the SBB_BINARIZE_DATA environment variable.", environ['SBB_BINARIZE_DATA'], model_path)
model_path = Path(environ['SBB_BINARIZE_DATA']).joinpath(model_path)
model_path = model_path.resolve()
if not model_path.is_dir():
raise FileNotFoundError("Does not exist or is not a directory: %s" % model_path)
kwargs['parameter']['model'] = str(model_path)
super().__init__(*args, **kwargs)
if hasattr(self, 'output_file_grp'):
# processing context
self.setup()
def setup(self):
"""
Set up the model prior to processing.
"""
LOG = getLogger('processor.SbbBinarize.__init__')
if not 'model' in self.parameter:
raise ValueError("'model' parameter is required")
# resolve relative path via environment variable
model_path = Path(self.parameter['model'])
if not model_path.is_absolute():
if 'SBB_BINARIZE_DATA' in environ and environ['SBB_BINARIZE_DATA']:
LOG.info("Environment variable SBB_BINARIZE_DATA is set to '%s'" \
" - prepending to model value '%s'. If you don't want this mechanism," \
" unset the SBB_BINARIZE_DATA environment variable.",
environ['SBB_BINARIZE_DATA'], model_path)
model_path = Path(environ['SBB_BINARIZE_DATA']).joinpath(model_path)
model_path = model_path.resolve()
if not model_path.is_dir():
raise FileNotFoundError("Does not exist or is not a directory: %s" % model_path)
# resolve relative path via OCR-D ResourceManager
model_path = self.resolve_resource(str(model_path))
self.binarizer = SbbBinarizer(model_dir=model_path, logger=LOG)
def process(self):
"""
Binarize with sbb_binarization
Binarize images with sbb_binarization (based on selectional auto-encoders).
For each page of the input file group, open and deserialize input PAGE-XML
and its respective images. Then iterate over the element hierarchy down to
the requested ``operation_level``.
For each segment element, retrieve a raw (non-binarized) segment image
according to the layout annotation (from an existing ``AlternativeImage``,
or by cropping into the higher-level images, and deskewing when applicable).
Pass the image to the binarizer (which runs in fixed-size windows/patches
across the image and stitches the results together).
Serialize the resulting bilevel image as PNG file and add it to the output
file group (with file ID suffix ``.IMG-BIN``) along with the output PAGE-XML
(referencing it as new ``AlternativeImage`` for the segment element).
Produce a new PAGE output file by serialising the resulting hierarchy.
"""
LOG = getLogger('processor.SbbBinarize')
assert_file_grp_cardinality(self.input_file_grp, 1)
assert_file_grp_cardinality(self.output_file_grp, 1)
oplevel = self.parameter['operation_level']
model_path = self.resolve_resource(self.parameter['model'])
binarizer = SbbBinarizer(model_dir=model_path, logger=LOG)
for n, input_file in enumerate(self.input_files):
file_id = make_file_id(input_file, self.output_file_grp)
@ -78,7 +106,7 @@ class SbbBinarizeProcessor(Processor):
if oplevel == 'page':
LOG.info("Binarizing on 'page' level in page '%s'", page_id)
bin_image = cv2pil(binarizer.run(image=pil2cv(page_image), use_patches=True))
bin_image = cv2pil(self.binarizer.run(image=pil2cv(page_image), use_patches=True))
# update METS (add the image file):
bin_image_path = self.workspace.save_image_file(bin_image,
file_id + '.IMG-BIN',

8
sbb_binarize/sbb_binarize.py
View file

@ -15,6 +15,7 @@ environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
stderr = sys.stderr
sys.stderr = open(devnull, 'w')
from keras.models import load_model
from keras.backend import tensorflow_backend
sys.stderr = stderr
import tensorflow as tf
@ -38,12 +39,14 @@ class SbbBinarizer:
self.models.append(self.load_model(model_file))
def start_new_session(self):
config = tf.ConfigProto()
config = tf.compat.v1.ConfigProto()
config.gpu_options.allow_growth = True
self.session = tf.Session(config=config) # tf.InteractiveSession()
self.session = tf.compat.v1.Session(config=config) # tf.InteractiveSession()
tensorflow_backend.set_session(self.session)
def end_session(self):
tensorflow_backend.clear_session()
self.session.close()
del self.session
@ -55,6 +58,7 @@ class SbbBinarizer:
return model, model_height, model_width, n_classes
def predict(self, model_in, img, use_patches):
tensorflow_backend.set_session(self.session)
model, model_height, model_width, n_classes = model_in
img_org_h = img.shape[0]