sbb_binarization is integrated into eynollah works in framework of ocrd - sbb_binarization in ocrd works for individual images by the way as standalone flowing from directory can be used now. For eynollah in ocrd framework I have added -light version as default parameter.

pull/142/merge
vahidrezanezhad 1 month ago
parent 0914b5ff8a
commit 8409de0e58

@ -28,6 +28,7 @@ classifiers = [
[project.scripts] [project.scripts]
eynollah = "eynollah.cli:main" eynollah = "eynollah.cli:main"
ocrd-eynollah-segment = "eynollah.ocrd_cli:main" ocrd-eynollah-segment = "eynollah.ocrd_cli:main"
ocrd-sbb-binarize = "eynollah.ocrd_cli_binarization:cli"
[project.urls] [project.urls]
Homepage = "https://github.com/qurator-spk/eynollah" Homepage = "https://github.com/qurator-spk/eynollah"

@ -4964,7 +4964,6 @@ class Eynollah:
polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_separators_d, boxes, boxes_d, polygons_of_marginals, contours_tables = self.run_boxes_no_full_layout(image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier, table_prediction, erosion_hurts) polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_separators_d, boxes, boxes_d, polygons_of_marginals, contours_tables = self.run_boxes_no_full_layout(image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier, table_prediction, erosion_hurts)
###polygons_of_marginals = self.dilate_textregions_contours(polygons_of_marginals) ###polygons_of_marginals = self.dilate_textregions_contours(polygons_of_marginals)
if self.full_layout: if self.full_layout:
cv2.imwrite('dewar_page.png', image_page)
if not self.light_version: if not self.light_version:
img_bin_light = None img_bin_light = None
polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_separators_d, regions_fully, regions_without_separators, polygons_of_marginals, contours_tables = self.run_boxes_full_layout(image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier, img_only_regions, table_prediction, erosion_hurts, img_bin_light) polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_separators_d, regions_fully, regions_without_separators, polygons_of_marginals, contours_tables = self.run_boxes_full_layout(image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier, img_only_regions, table_prediction, erosion_hurts, img_bin_light)

@ -0,0 +1,47 @@
{
"version": "0.1.0",
"git_url": "https://github.com/qurator-spk/sbb_binarization",
"tools": {
"ocrd-sbb-binarize": {
"executable": "ocrd-sbb-binarize",
"description": "Pixelwise binarization with selectional auto-encoders in Keras",
"categories": ["Image preprocessing"],
"steps": ["preprocessing/optimization/binarization"],
"input_file_grp": [],
"output_file_grp": [],
"parameters": {
"operation_level": {
"type": "string",
"enum": ["page", "region"],
"default": "page",
"description": "PAGE XML hierarchy level to operate on"
},
"model": {
"description": "Directory containing HDF5 or SavedModel/ProtoBuf models. Can be an absolute path or a path relative to the OCR-D resource location, the current working directory or the $SBB_BINARIZE_DATA environment variable (if set)",
"type": "string",
"format": "uri",
"content-type": "text/directory",
"required": true
}
},
"resources": [
{
"url": "https://github.com/qurator-spk/sbb_binarization/releases/download/v0.0.11/saved_model_2020_01_16.zip",
"name": "default",
"type": "archive",
"path_in_archive": "saved_model_2020_01_16",
"size": 563147331,
"description": "default models provided by github.com/qurator-spk (SavedModel format)"
},
{
"url": "https://github.com/qurator-spk/sbb_binarization/releases/download/v0.0.11/saved_model_2021_03_09.zip",
"name": "default-2021-03-09",
"type": "archive",
"path_in_archive": ".",
"size": 133230419,
"description": "updated default models provided by github.com/qurator-spk (SavedModel format)"
}
]
}
}
}

@ -28,6 +28,16 @@
"type": "boolean", "type": "boolean",
"default": true, "default": true,
"description": "Try to detect all element subtypes, including drop-caps and headings" "description": "Try to detect all element subtypes, including drop-caps and headings"
},
"light_version": {
"type": "boolean",
"default": true,
"description": "Try to detect all element subtypes in light version"
},
"textline_light": {
"type": "boolean",
"default": true,
"description": "Light version need textline light"
}, },
"tables": { "tables": {
"type": "boolean", "type": "boolean",

@ -0,0 +1,158 @@
from os import environ
from os.path import join
from pathlib import Path
from pkg_resources import resource_string
from json import loads
from PIL import Image
import numpy as np
import cv2
from click import command
from ocrd_utils import (
getLogger,
assert_file_grp_cardinality,
make_file_id,
MIMETYPE_PAGE
)
from ocrd import Processor
from ocrd_modelfactory import page_from_file
from ocrd_models.ocrd_page import AlternativeImageType, to_xml
from ocrd.decorators import ocrd_cli_options, ocrd_cli_wrap_processor
from .sbb_binarize import SbbBinarizer
OCRD_TOOL = loads(resource_string(__name__, 'ocrd-tool-binarization.json').decode('utf8'))
TOOL = 'ocrd-sbb-binarize'
def cv2pil(img):
return Image.fromarray(img.astype('uint8'))
def pil2cv(img):
# from ocrd/workspace.py
color_conversion = cv2.COLOR_GRAY2BGR if img.mode in ('1', 'L') else cv2.COLOR_RGB2BGR
pil_as_np_array = np.array(img).astype('uint8') if img.mode == '1' else np.array(img)
return cv2.cvtColor(pil_as_np_array, color_conversion)
class SbbBinarizeProcessor(Processor):
def __init__(self, *args, **kwargs):
kwargs['ocrd_tool'] = OCRD_TOOL['tools'][TOOL]
kwargs['version'] = OCRD_TOOL['version']
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 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']
for n, input_file in enumerate(self.input_files):
file_id = make_file_id(input_file, self.output_file_grp)
page_id = input_file.pageId or input_file.ID
LOG.info("INPUT FILE %i / %s", n, page_id)
pcgts = page_from_file(self.workspace.download_file(input_file))
self.add_metadata(pcgts)
pcgts.set_pcGtsId(file_id)
page = pcgts.get_Page()
page_image, page_xywh, _ = self.workspace.image_from_page(page, page_id, feature_filter='binarized')
if oplevel == 'page':
LOG.info("Binarizing on 'page' level in page '%s'", page_id)
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',
page_id=input_file.pageId,
file_grp=self.output_file_grp)
page.add_AlternativeImage(AlternativeImageType(filename=bin_image_path, comments='%s,binarized' % page_xywh['features']))
elif oplevel == 'region':
regions = page.get_AllRegions(['Text', 'Table'], depth=1)
if not regions:
LOG.warning("Page '%s' contains no text/table regions", page_id)
for region in regions:
region_image, region_xywh = self.workspace.image_from_segment(region, page_image, page_xywh, feature_filter='binarized')
region_image_bin = cv2pil(binarizer.run(image=pil2cv(region_image), use_patches=True))
region_image_bin_path = self.workspace.save_image_file(
region_image_bin,
"%s_%s.IMG-BIN" % (file_id, region.id),
page_id=input_file.pageId,
file_grp=self.output_file_grp)
region.add_AlternativeImage(
AlternativeImageType(filename=region_image_bin_path, comments='%s,binarized' % region_xywh['features']))
elif oplevel == 'line':
region_line_tuples = [(r.id, r.get_TextLine()) for r in page.get_AllRegions(['Text'], depth=0)]
if not region_line_tuples:
LOG.warning("Page '%s' contains no text lines", page_id)
for region_id, line in region_line_tuples:
line_image, line_xywh = self.workspace.image_from_segment(line, page_image, page_xywh, feature_filter='binarized')
line_image_bin = cv2pil(binarizer.run(image=pil2cv(line_image), use_patches=True))
line_image_bin_path = self.workspace.save_image_file(
line_image_bin,
"%s_%s_%s.IMG-BIN" % (file_id, region_id, line.id),
page_id=input_file.pageId,
file_grp=self.output_file_grp)
line.add_AlternativeImage(
AlternativeImageType(filename=line_image_bin_path, comments='%s,binarized' % line_xywh['features']))
self.workspace.add_file(
ID=file_id,
file_grp=self.output_file_grp,
pageId=input_file.pageId,
mimetype=MIMETYPE_PAGE,
local_filename=join(self.output_file_grp, file_id + '.xml'),
content=to_xml(pcgts))
@command()
@ocrd_cli_options
def cli(*args, **kwargs):
return ocrd_cli_wrap_processor(SbbBinarizeProcessor, *args, **kwargs)

@ -49,6 +49,8 @@ class EynollahProcessor(Processor):
'curved_line': self.parameter['curved_line'], 'curved_line': self.parameter['curved_line'],
'full_layout': self.parameter['full_layout'], 'full_layout': self.parameter['full_layout'],
'allow_scaling': self.parameter['allow_scaling'], 'allow_scaling': self.parameter['allow_scaling'],
'light_version': self.parameter['light_version'],
'textline_light': self.parameter['textline_light'],
'headers_off': self.parameter['headers_off'], 'headers_off': self.parameter['headers_off'],
'tables': self.parameter['tables'], 'tables': self.parameter['tables'],
'override_dpi': self.parameter['dpi'], 'override_dpi': self.parameter['dpi'],

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