def test_hashable():
"""
https://github.com/OCR-D/ocrd_segment/issues/45
"""
pcgts = page_from_image(create_ocrd_file_with_defaults(url=assets.path_to('kant_aufklaerung_1784/data/OCR-D-IMG/INPUT_0017.tif')))
page = pcgts.get_Page()
testset = set()
testset.add(pcgts)
testset.add(page)
def test_serialize_no_empty_readingorder():
"""
https://github.com/OCR-D/core/issues/602
"""
pcgts = page_from_image(create_ocrd_file_with_defaults(url=assets.path_to('kant_aufklaerung_1784/data/OCR-D-IMG/INPUT_0017.tif')))
pcgts.get_Page().set_ReadingOrder(ReadingOrderType())
assert pcgts.get_Page().get_ReadingOrder()
pcgts = parseString(to_xml(pcgts, skip_declaration=True))
assert not pcgts.get_Page().get_ReadingOrder()
def convert(cocofile, directory):
"""Convert MS-COCO JSON to METS/PAGE XML files.
Load JSON ``cocofile`` (in MS-COCO format)
and chdir to ``directory`` (which it refers to).
Start a METS file mets.xml with references to
the image files (under fileGrp ``OCR-D-IMG``)
and their corresponding PAGE-XML annotations
(under fileGrp ``OCR-D-GT-SEG-BLOCK``), as
parsed from ``cocofile`` and written using
the same basename.
"""
resolver = Resolver()
with pushd_popd(directory):
workspace = resolver.workspace_from_nothing('.')
# https://github.com/ibm-aur-nlp/PubLayNet
workspace.mets.unique_identifier = 'ocrd_PubLayNet_' + directory
coco = json.load(cocofile)
LOG.info('Loaded JSON for %d images with %d regions in %d categories',
len(coco['images']), len(coco['annotations']),
len(coco['categories']))
categories = dict()
for cat in coco['categories']:
categories[cat['id']] = cat['name']
images = dict()
for image in coco['images']:
images[image['id']] = image
for annotation in coco['annotations']:
image = images[annotation['image_id']]
regions = image.setdefault('regions', list())
regions.append(annotation)
del coco
LOG.info('Parsing annotations into PAGE-XML')
for image in images.values():
page_id = 'p' + str(image['id'])
file_base, file_ext = os.path.splitext(image['file_name'])
filename = file_base + '.xml'
image_file = workspace.add_file('OCR-D-IMG',
ID='OCR-D-IMG_' + page_id,
pageId=page_id,
mimetype=EXT_TO_MIME[file_ext],
local_filename=image['file_name'])
LOG.info('Added page %s file %s of type %s', image_file.pageId,
image_file.local_filename, image_file.mimetype)
pcgts = page_from_image(image_file)
pcgts.set_pcGtsId(page_id)
page = pcgts.get_Page()
assert page.imageWidth == image['width']
assert page.imageHeight == image['height']
for region in image['regions']:
polygon = np.array(region['segmentation'])
polygon = np.reshape(polygon, (polygon.shape[1] // 2, 2))
coords = CoordsType(points=points_from_polygon(polygon))
category = categories[region['category_id']]
region_id = 'r' + str(region['id'])
if category == 'text':
region_obj = TextRegionType(
id=region_id,
Coords=coords,
type_=TextTypeSimpleType.PARAGRAPH)
page.add_TextRegion(region_obj)
elif category == 'title':
region_obj = TextRegionType(
id=region_id,
Coords=coords,
type_=TextTypeSimpleType.HEADING) # CAPTION?
page.add_TextRegion(region_obj)
elif category == 'list':
region_obj = TextRegionType(
id=region_id,
Coords=coords,
type_=TextTypeSimpleType.LISTLABEL) # OTHER?
page.add_TextRegion(region_obj)
elif category == 'table':
region_obj = TableRegionType(id=region_id, Coords=coords)
page.add_TableRegion(region_obj)
elif category == 'figure':
region_obj = ImageRegionType(id=region_id, Coords=coords)
page.add_ImageRegion(region_obj)
else:
raise Exception('unknown image category: %s' % category)
page_file = workspace.add_file('OCR-D-GT-SEG-BLOCK',
ID='OCR-D-GT-SEG-BLOCK_' + page_id,
pageId=page_id,
mimetype=MIMETYPE_PAGE,
local_filename=filename,
content=to_xml(pcgts))
LOG.info('Added page %s file %s with %d regions', page_file.pageId,
page_file.local_filename, len(image['regions']))
LOG.info('All done')
workspace.save_mets()