def process(self):
"""
Segment with ocropy
"""
for (n, input_file) in enumerate(self.input_files):
log.info("INPUT FILE %i / %s", n, input_file)
downloaded_file = self.workspace.download_file(input_file)
log.info("downloaded_file %s", downloaded_file)
pcgts = page_from_file(downloaded_file)
page_width = pcgts.get_Page().get_imageWidth()
page_height = pcgts.get_Page().get_imageHeight()
# TODO binarized variant from get_AlternativeImage()
image_url = pcgts.get_Page().imageFilename
log.info("pcgts %s", pcgts)
binary = ocrolib.read_image_binary(
self.workspace.download_url(image_url))
binary = 1 - binary
scale = self.parameter['scale'] if self.parameter[
'scale'] != 0 else psegutils.estimate_scale(binary)
log.debug(binary)
pseg = self.compute_segmentation(binary, scale)
log.debug("pseg=%s", pseg)
# TODO reading order / enumber
# log.debug("finding reading order")
# lines = psegutils.compute_lines(pseg, scale)
# order = psegutils.reading_order([l.bounds for l in lines])
# lsort = psegutils.topsort(order)
regions = ocrolib.RegionExtractor()
regions.setPageLines(pseg)
dummyRegion = TextRegionType(
id="dummy",
Coords=CoordsType(
points="0,0 %s,0 %s,%s 0,%s" %
(page_width, page_width, page_height, page_height)))
pcgts.get_Page().add_TextRegion(dummyRegion)
for lineno in range(1, regions.length()):
log.debug("id=%s bbox=%s", regions.id(lineno),
regions.bbox(lineno))
textline = TextLineType(
id=concat_padded("line", lineno),
Coords=CoordsType(
points=points_from_y0x0y1x1(regions.bbox(lineno))))
dummyRegion.add_TextLine(textline)
ID = concat_padded(self.output_file_grp, n)
self.workspace.add_file(ID=ID,
file_grp=self.output_file_grp,
mimetype=MIMETYPE_PAGE,
local_filename="%s/%s.xml" %
(self.output_file_grp, ID),
content=to_xml(pcgts))
def _process_region(self, it, region, rogroup, region_image,
region_coords):
LOG = getLogger('processor.TesserocrSegmentTable')
# equivalent to GetComponentImages with raw_image=True,
# (which would also give raw coordinates),
# except we are also interested in the iterator's BlockType() here,
index = 0
if rogroup:
for elem in (rogroup.get_RegionRefIndexed() +
rogroup.get_OrderedGroupIndexed() +
rogroup.get_UnorderedGroupIndexed()):
if elem.index >= index:
index = elem.index + 1
while it and not it.Empty(RIL.BLOCK):
bbox = it.BoundingBox(RIL.BLOCK)
polygon = polygon_from_x0y0x1y1(bbox)
polygon = coordinates_for_segment(polygon, region_image,
region_coords)
points = points_from_polygon(polygon)
coords = CoordsType(points=points)
# if xywh['w'] < 30 or xywh['h'] < 30:
# LOG.info('Ignoring too small region: %s', points)
# it.Next(RIL.BLOCK)
# continue
#
# add the region reference in the reading order element
# (but ignore non-text regions entirely)
ID = region.id + "_%04d" % index
subregion = TextRegionType(id=ID,
Coords=coords,
type=TextTypeSimpleType.PARAGRAPH)
block_type = it.BlockType()
if block_type == PT.FLOWING_TEXT:
pass
elif block_type == PT.HEADING_TEXT:
subregion.set_type(TextTypeSimpleType.HEADING)
elif block_type == PT.PULLOUT_TEXT:
subregion.set_type(TextTypeSimpleType.FLOATING)
elif block_type == PT.CAPTION_TEXT:
subregion.set_type(TextTypeSimpleType.CAPTION)
elif block_type == PT.VERTICAL_TEXT:
subregion.set_orientation(90.0)
else:
it.Next(RIL.BLOCK)
continue
LOG.info("Detected cell '%s': %s (%s)", ID, points,
membername(PT, block_type))
region.add_TextRegion(subregion)
if rogroup:
rogroup.add_RegionRefIndexed(
RegionRefIndexedType(regionRef=ID, index=index))
#
# iterator increment
#
index += 1
it.Next(RIL.BLOCK)
def _process_segment(self, page_image, page, page_xywh, page_id,
input_file, n, mrcnn_model, class_names):
img_array = ocrolib.pil2array(page_image)
results = mrcnn_model.detect([img_array], verbose=1)
r = results[0]
page_xywh['features'] += ',blksegmented'
for i in range(len(r['rois'])):
width, height, _ = img_array.shape
min_x = r['rois'][i][0]
min_y = r['rois'][i][1]
max_x = r['rois'][i][2]
max_y = r['rois'][i][3]
#small post-processing incase of paragrapgh to not cut last alphabets
if (min_x - 5) > width and r['class_ids'][i] == 2:
min_x -= 5
if (max_x + 10) < width and r['class_ids'][i] == 2:
min_x += 10
# this can be tested, provided whether we need previous comments or not?
region_img = img_array[min_x:max_x, min_y:
max_y] #extract from points and img_array
region_img = ocrolib.array2pil(region_img)
file_id = input_file.ID.replace(self.input_file_grp,
self.image_grp)
if file_id == input_file.ID:
file_id = concat_padded(self.image_grp, n)
file_path = self.workspace.save_image_file(region_img,
file_id + "_" + str(i),
page_id=page_id,
file_grp=self.image_grp)
ai = AlternativeImageType(filename=file_path,
comments=page_xywh['features'])
coords = CoordsType(
"%i,%i %i,%i %i,%i %i,%i" %
(min_x, min_y, max_x, min_y, max_x, max_y, min_x, max_y))
textregion = TextRegionType(Coords=coords,
type_=class_names[r['class_ids'][i]])
textregion.add_AlternativeImage(ai)
page.add_TextRegion(textregion)
def render_text_region(self, text_region: TextRegionType) -> None:
line: TextLineType
word: WordType
glyph: GlyphType
for line in text_region.get_TextLine():
self.render_type(line)
for word in line.get_Word():
self.render_type(word)
for glyph in word.get_Glyph():
self.render_type(glyph)
def process(self):
"""
Segment with kraken
"""
log = getLogger('processor.KrakenSegment')
for (n, input_file) in enumerate(self.input_files):
log.info("INPUT FILE %i / %s", n, input_file)
downloaded_file = self.workspace.download_file(input_file)
log.info("downloaded_file %s", downloaded_file)
pcgts = page_from_file(downloaded_file)
# TODO binarized variant from get_AlternativeImage()
image_url = pcgts.get_Page().imageFilename
log.info("pcgts %s", pcgts)
im = self.workspace.resolve_image_as_pil(image_url)
log.info('Segmenting')
log.info('Params %s', self.parameter)
res = segment(im, self.parameter['text_direction'],
self.parameter['scale'],
self.parameter['maxcolseps'],
self.parameter['black_colseps'])
if self.parameter['script_detect']:
res = detect_scripts(im, res)
dummyRegion = TextRegionType()
pcgts.get_Page().add_TextRegion(dummyRegion)
# print(res)
for lineno, box in enumerate(res['boxes']):
textline = TextLineType(
id=concat_padded("line", lineno),
Coords=CoordsType(points=points_from_x0y0x1y1(box)))
dummyRegion.add_TextLine(textline)
ID = concat_padded(self.output_file_grp, n)
self.workspace.add_file(self.output_file_grp,
pageId=input_file.pageId,
ID=ID,
mimetype=MIMETYPE_PAGE,
local_filename="%s/%s.xml" %
(self.output_file_grp, ID),
content=to_xml(pcgts).encode('utf-8'))
def test_alternative_image_additions():
pcgts = PcGtsType(pcGtsId="foo")
assert pcgts.pcGtsId == 'foo'
# act
# Page/AlternativeImage
page = PageType()
pcgts.set_Page(page)
page.add_AlternativeImage(AlternativeImageType())
# TextRegion/AlternativeImage
region = TextRegionType()
page.add_TextRegion(region)
region.add_AlternativeImage(AlternativeImageType())
# TextLine/AlternativeImage
line = TextLineType()
region.add_TextLine(line)
line.add_AlternativeImage(AlternativeImageType())
# Word/AlternativeImage
word = WordType()
line.add_Word(word)
word.add_AlternativeImage(AlternativeImageType())
# Glyph/AlternativeImage
glyph = GlyphType()
word.add_Glyph(glyph)
glyph.add_AlternativeImage(AlternativeImageType())
def process(self):
"""
Performs the region segmentation.
"""
with tesserocr.PyTessBaseAPI(path=TESSDATA_PREFIX) as tessapi:
# print(self.input_file_grp)
for (n, input_file) in enumerate(self.input_files):
# print(input_file)
pcgts = page_from_file(self.workspace.download_file(input_file))
image = self.workspace.resolve_image_as_pil(pcgts.get_Page().imageFilename)
log.debug("Detecting regions with tesseract")
tessapi.SetImage(image)
for component in tessapi.GetComponentImages(tesserocr.RIL.BLOCK, True):
points, index = points_from_xywh(component[1]), component[2]
#
# the region reference in the reading order element
#
ID = "region%04d" % index
log.debug("Detected region '%s': %s", ID, points)
# <pg:ReadingOrder>
ro = pcgts.get_Page().get_ReadingOrder()
if ro is None:
ro = ReadingOrderType()
pcgts.get_Page().set_ReadingOrder(ro)
# <pg:OrderedGroup>
og = ro.get_OrderedGroup()
if og is None:
og = OrderedGroupType(id="reading-order")
ro.set_OrderedGroup(og)
# <pg:RegionRefIndexed>
og.add_RegionRefIndexed(RegionRefIndexedType(regionRef=ID, index=index))
#
# text region
#
pcgts.get_Page().add_TextRegion(TextRegionType(id=ID, Coords=CoordsType(points=points)))
ID = concat_padded(self.output_file_grp, n)
self.workspace.add_file(
ID=ID,
file_grp=self.output_file_grp,
mimetype=MIMETYPE_PAGE,
local_filename='%s/%s' % (self.output_file_grp, ID),
content=to_xml(pcgts).encode('utf-8'),
)
def add_region(region: RectSegment, index: int, region_type: str):
from ocrd_utils import coordinates_for_segment, points_from_polygon
polygon = polygon_from_segment(region)
polygon = coordinates_for_segment(polygon, page_image, page_coords)
points = points_from_polygon(polygon)
indexed_id = "region%04d" % index
coords = CoordsType(points=points)
if region_type == "text":
page.add_TextRegion(
TextRegionType(id=indexed_id, Coords=coords))
elif region_type == "image":
page.add_ImageRegion(
ImageRegionType(id=indexed_id, Coords=coords))
else:
page.add_NoiseRegion(
NoiseRegionType(id=indexed_id, Coords=coords))
def add_region(region: Segment, index: int, type: str):
indexed_id = "region%04d" % index
points = str([
(region.x_start, region.y_start),
(region.x_start, region.y_end),
(region.x_end, region.y_start),
(region.x_end, region.y_end),
])
coords = CoordsType(points=points)
if type == "text":
page.add_TextRegion(
TextRegionType(id=indexed_id, Coords=coords))
elif type == "image":
page.add_ImageRegion(
ImageRegionType(id=indexed_id, Coords=coords))
else:
page.add_NoiseRegion(
NoiseRegionType(id=indexed_id, Coords=coords))
def _process_page(page, page_image, page_xywh, pageId, file_id):
settings = SegmentationSettings(debug=False,
enable_preprocessing=False)
# TODO: does this still need to be cropped or do we not need page_xywh?
# Same for points below
# page_image[page_xywh["x"]:page_xywh["w"], page_xywh["y"]:page_xywh["h"]]
regions, classification = Segmentator(settings).segmentate_image(
np.asarray(page_image))
count = 0
for region, prediction in zip(regions, classification):
ID = "region%04d" % count
points = str(list(region.exterior.coords))
coords = CoordsType(points=points)
# FIXME: these are not all types in the model, also check if they match
if prediction == 1:
page.add_TextRegion(TextRegionType(id=ID, Coords=coords))
elif prediction == 2:
page.add_ImageRegion(ImageRegionType(id=ID, Coords=coords))
else:
page.add_NoiseRegion(NoiseRegionType(id=ID, Coords=coords))
count += 1
def test_alternativeImage(self):
pcgts = PcGtsType(pcGtsId="foo")
self.assertEqual(pcgts.pcGtsId, 'foo')
# Page/AlternativeImage
page = PageType()
pcgts.set_Page(page)
page.add_AlternativeImage(AlternativeImageType())
# TextRegion/AlternativeImage
region = TextRegionType()
page.add_TextRegion(region)
region.add_AlternativeImage(AlternativeImageType())
# TextLine/AlternativeImage
line = TextLineType()
region.add_TextLine(line)
line.add_AlternativeImage(AlternativeImageType())
# Word/AlternativeImage
word = WordType()
line.add_Word(word)
word.add_AlternativeImage(AlternativeImageType())
# Glyph/AlternativeImage
glyph = GlyphType()
word.add_Glyph(glyph)
glyph.add_AlternativeImage(AlternativeImageType())
def build_pagexml_full_layout(
self, found_polygons_text_region, found_polygons_text_region_h,
page_coord, order_of_texts, id_of_texts,
all_found_texline_polygons, all_found_texline_polygons_h,
all_box_coord, all_box_coord_h, found_polygons_text_region_img,
found_polygons_tables, found_polygons_drop_capitals,
found_polygons_marginals, all_found_texline_polygons_marginals,
all_box_coord_marginals, slopes, slopes_h, slopes_marginals,
cont_page, polygons_lines_to_be_written_in_xml):
self.logger.debug('enter build_pagexml_full_layout')
# create the file structure
pcgts = self.pcgts if self.pcgts else create_page_xml(
self.image_filename, self.height_org, self.width_org)
page = pcgts.get_Page()
page.set_Border(
BorderType(Coords=CoordsType(
points=self.calculate_page_coords(cont_page))))
counter = EynollahIdCounter()
_counter_marginals = EynollahIdCounter(region_idx=len(order_of_texts))
id_of_marginalia = [
_counter_marginals.next_region_id for _ in found_polygons_marginals
]
xml_reading_order(page, order_of_texts, id_of_marginalia)
for mm in range(len(found_polygons_text_region)):
textregion = TextRegionType(
id=counter.next_region_id,
type_='paragraph',
Coords=CoordsType(points=self.calculate_polygon_coords(
found_polygons_text_region[mm], page_coord)))
page.add_TextRegion(textregion)
self.serialize_lines_in_region(textregion,
all_found_texline_polygons, mm,
page_coord, all_box_coord, slopes,
counter)
self.logger.debug('len(found_polygons_text_region_h) %s',
len(found_polygons_text_region_h))
for mm in range(len(found_polygons_text_region_h)):
textregion = TextRegionType(
id=counter.next_region_id,
type_='header',
Coords=CoordsType(points=self.calculate_polygon_coords(
found_polygons_text_region_h[mm], page_coord)))
page.add_TextRegion(textregion)
self.serialize_lines_in_region(textregion,
all_found_texline_polygons_h, mm,
page_coord, all_box_coord_h,
slopes_h, counter)
for mm in range(len(found_polygons_marginals)):
marginal = TextRegionType(
id=counter.next_region_id,
type_='marginalia',
Coords=CoordsType(points=self.calculate_polygon_coords(
found_polygons_marginals[mm], page_coord)))
page.add_TextRegion(marginal)
self.serialize_lines_in_marginal(
marginal, all_found_texline_polygons_marginals, mm, page_coord,
all_box_coord_marginals, slopes_marginals, counter)
for mm in range(len(found_polygons_drop_capitals)):
page.add_TextRegion(
TextRegionType(
id=counter.next_region_id,
type_='drop-capital',
Coords=CoordsType(points=self.calculate_polygon_coords(
found_polygons_drop_capitals[mm], page_coord))))
for mm in range(len(found_polygons_text_region_img)):
page.add_ImageRegion(
ImageRegionType(
id=counter.next_region_id,
Coords=CoordsType(points=self.calculate_polygon_coords(
found_polygons_text_region_img[mm], page_coord))))
for mm in range(len(polygons_lines_to_be_written_in_xml)):
page.add_SeparatorRegion(
ImageRegionType(
id=counter.next_region_id,
Coords=CoordsType(points=self.calculate_polygon_coords(
polygons_lines_to_be_written_in_xml[mm],
[0, 0, 0, 0]))))
for mm in range(len(found_polygons_tables)):
page.add_TableRegion(
TableRegionType(
id=counter.next_region_id,
Coords=CoordsType(points=self.calculate_polygon_coords(
found_polygons_tables[mm], page_coord))))
return pcgts
def _process_segment(self, page_image, page, page_xywh, page_id,
input_file, mask, dpi):
LOG = getLogger('processor.AnybaseocrBlockSegmenter')
# check for existing text regions and whether to overwrite them
if page.get_TextRegion() or page.get_TableRegion():
if self.parameter['overwrite']:
LOG.info('removing existing text/table regions in page "%s"',
page_id)
page.set_TextRegion([])
else:
LOG.warning('keeping existing text/table regions in page "%s"',
page_id)
# check if border exists
border_polygon = None
if page.get_Border():
border_coords = page.get_Border().get_Coords()
border_points = polygon_from_points(border_coords.get_points())
border_polygon = Polygon(border_points)
LOG.info('detecting regions on page "%s"', page_id)
img_array = ocrolib.pil2array(page_image)
if len(img_array.shape) <= 2:
img_array = np.stack((img_array, ) * 3, axis=-1)
# convert to incidence matrix
class_ids = np.array([[
1 if category in self.parameter['active_classes'] else 0
for category in CLASS_NAMES
]],
dtype=np.int32)
results = self.mrcnn_model.detect([img_array],
verbose=0,
active_class_ids=class_ids)
r = results[0]
LOG.info('found %d candidates on page "%s"', len(r['rois']), page_id)
th = self.parameter['th']
# check for existing semgentation mask
# this code executes only when the workflow had tiseg run before with use_deeplr=true
if mask:
mask = ocrolib.pil2array(mask)
mask = mask // 255
mask = 1 - mask
# multiply all the bounding box part with 2
for i in range(len(r['rois'])):
min_y, min_x, max_y, max_x = r['rois'][i]
mask[min_y:max_y, min_x:max_x] *= i + 2
# check for left over pixels and add them to the bounding boxes
pixel_added = True
while pixel_added:
pixel_added = False
left_over = np.where(mask == 1)
for y, x in zip(left_over[0], left_over[1]):
local_mask = mask[y - th:y + th, x - th:x + th]
candidates = np.where(local_mask > 1)
candidates = [k for k in zip(candidates[0], candidates[1])]
if len(candidates) > 0:
pixel_added = True
# find closest pixel with x>1
candidates.sort(key=lambda j: np.sqrt((j[0] - th)**2 +
(j[1] - th)**2))
index = local_mask[candidates[0]] - 2
# add pixel to mask/bbox
# y,x to bbox with index
if y < r['rois'][index][0]:
r['rois'][index][0] = y
elif y > r['rois'][index][2]:
r['rois'][index][2] = y
if x < r['rois'][index][1]:
r['rois'][index][1] = x
elif x > r['rois'][index][3]:
r['rois'][index][3] = x
# update the mask
mask[y, x] = index + 2
for i in range(len(r['rois'])):
class_id = r['class_ids'][i]
if class_id >= len(CLASS_NAMES):
raise Exception(
'Unexpected class id %d - model does not match' % class_id)
# find hull contours on masks
if self.parameter['use_masks']:
r.setdefault('polygons', list())
# estimate glyph scale (roughly)
scale = int(dpi / 6)
scale = scale + (scale + 1) % 2 # odd
for i in range(len(r['rois'])):
mask = r['masks'][:, :, i]
mask = cv2.dilate(mask.astype(np.uint8),
np.ones((scale, scale), np.uint8)) > 0
# close mask until we have a single outer contour
contours = None
for _ in range(10):
mask = cv2.morphologyEx(
mask.astype(np.uint8), cv2.MORPH_CLOSE,
np.ones((scale, scale), np.uint8)) > 0
contours, _ = cv2.findContours(mask.astype(np.uint8),
cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
if len(contours) == 1:
break
r['polygons'].append(Polygon(
contours[0][:, 0, :])) # already in x,y order
# to reduce overlaps, apply IoU-based non-maximum suppression
# (and other post-processing against overlaps) across classes,
# but not on the raw pixels, but the smoothed hull polygons
LOG.info('post-processing detections on page "%s"', page_id)
worse = []
if self.parameter['post_process']:
active = True
def _merge_rois(i, j):
"""merges i into j"""
nonlocal r, active
r['rois'][j][0] = min(r['rois'][i][0], r['rois'][j][0])
r['rois'][j][1] = min(r['rois'][i][1], r['rois'][j][1])
r['rois'][j][2] = max(r['rois'][i][2], r['rois'][j][2])
r['rois'][j][3] = max(r['rois'][i][3], r['rois'][j][3])
r['polygons'][j] = r['polygons'][i].union(r['polygons'][j])
#r['scores'][j] = max(r['scores'][i], r['scores'][i])
active = True
# find overlapping pairs
while active:
active = False
for i in range(len(r["class_ids"])):
if i in worse:
continue
for j in range(i + 1, len(r['class_ids'])):
if j in worse:
continue
iclass = r['class_ids'][i]
jclass = r['class_ids'][j]
iname = CLASS_NAMES[iclass]
jname = CLASS_NAMES[jclass]
if (iname == 'drop-capital') != (jname
== 'drop-capital'):
# ignore drop-capital overlapping with others
continue
# rs todo: lower priority for footnote?
if (r['rois'][i][1] > r['rois'][j][3]
or r['rois'][i][3] < r['rois'][j][1]
or r['rois'][i][0] > r['rois'][j][2]
or r['rois'][i][2] < r['rois'][j][0]):
# no overlap (cut)
continue
iscore = r['scores'][i]
jscore = r['scores'][j]
if not self.parameter['use_masks']:
LOG.debug(
"roi %d[%s] overlaps roi %d[%s] and %s (replacing)",
i, iname, j, jname,
"looses" if iscore < jscore else "wins")
if iscore < jscore:
worse.append(i)
break
else:
worse.append(j)
continue
# compare masks
ipoly = r['polygons'][i]
jpoly = r['polygons'][j]
isize = ipoly.area
jsize = jpoly.area
inter = ipoly.intersection(jpoly).area
union = ipoly.union(jpoly).area
# LOG.debug("%d/%d %dpx/%dpx shared %dpx overall %dpx",
# i, j, isize, jsize, inter, union)
if inter / isize > self.parameter['min_share_drop']:
LOG.debug(
"roi %d[%s] contains roi %d[%s] (replacing)",
j, jname, i, iname)
worse.append(i)
break
elif inter / jsize > self.parameter['min_share_drop']:
LOG.debug(
"roi %d[%s] contains roi %d[%s] (replacing)",
i, iname, j, jname)
worse.append(j)
elif inter / union > self.parameter['min_iou_drop']:
LOG.debug(
"roi %d[%s] heavily overlaps roi %d[%s] and %s (replacing)",
i, iname, j, jname,
"looses" if iscore < jscore else "wins")
if iscore < jscore:
worse.append(i)
break
else:
worse.append(j)
elif inter / isize > self.parameter['min_share_merge']:
LOG.debug("roi %d[%s] covers roi %d[%s] (merging)",
j, jname, i, iname)
worse.append(i)
_merge_rois(i, j)
break
elif inter / jsize > self.parameter['min_share_merge']:
LOG.debug("roi %d[%s] covers roi %d[%s] (merging)",
i, iname, j, jname)
worse.append(j)
_merge_rois(j, i)
elif inter / union > self.parameter['min_iou_merge']:
LOG.debug(
"roi %d[%s] slightly overlaps roi %d[%s] and %s (merging)",
i, iname, j, jname,
"looses" if iscore < jscore else "wins")
if iscore < jscore:
worse.append(i)
_merge_rois(i, j)
break
else:
worse.append(j)
_merge_rois(j, i)
# define reading order on basis of coordinates
partial_order = np.zeros((len(r['rois']), len(r['rois'])), np.uint8)
for i, (min_y_i, min_x_i, max_y_i, max_x_i) in enumerate(r['rois']):
for j, (min_y_j, min_x_j, max_y_j,
max_x_j) in enumerate(r['rois']):
if min_x_i < max_x_j and max_x_i > min_x_j:
# xoverlaps
if min_y_i < min_y_j:
partial_order[i, j] = 1
else:
min_y = min(min_y_i, min_y_j)
max_y = max(max_y_i, max_y_j)
min_x = min(min_x_i, min_x_j)
max_x = max(max_x_i, max_x_j)
if next(
(False
for (min_y_k, min_x_k, max_y_k, max_x_k) in r['rois']
if (min_y_k < max_y and max_y_k > min_y
and min_x_k < max_x and max_x_k > min_x)), True):
# no k in between
if ((min_y_j + max_y_j) / 2 < min_y_i
and (min_y_i + max_y_i) / 2 > max_y_j):
# vertically unrelated
partial_order[j, i] = 1
elif max_x_i < min_x_j:
partial_order[i, j] = 1
def _topsort(po):
visited = np.zeros(po.shape[0], np.bool)
result = list()
def _visit(k):
if visited[k]:
return
visited[k] = True
for l in np.nonzero(po[:, k])[0]:
_visit(l)
result.append(k)
for k in range(po.shape[0]):
_visit(k)
return result
reading_order = _topsort(partial_order)
# Creating Reading Order object in PageXML
order_group = OrderedGroupType(caption="Regions reading order",
id=page_id)
reading_order_object = ReadingOrderType()
reading_order_object.set_OrderedGroup(order_group)
page.set_ReadingOrder(reading_order_object)
for i in range(len(r['rois'])):
width, height, _ = img_array.shape
min_y, min_x, max_y, max_x = r['rois'][i]
score = r['scores'][i]
class_id = r['class_ids'][i]
class_name = CLASS_NAMES[class_id]
if i in worse:
LOG.debug(
"Ignoring instance %d[%s] overlapping better/larger neighbour",
i, class_name)
continue
if self.parameter['use_masks']:
region_polygon = r['polygons'][i].exterior.coords[:-1]
else:
region_polygon = polygon_from_bbox(
max(min_x - 5, 0) if class_name == 'paragraph' else min_x,
min_y,
min(max_x +
10, width) if class_name == 'paragraph' else max_x,
max_y)
# convert to absolute coordinates
region_polygon = coordinates_for_segment(region_polygon,
page_image, page_xywh)
# intersect with parent and plausibilize
cut_region_polygon = Polygon(region_polygon)
if border_polygon:
cut_region_polygon = border_polygon.intersection(
cut_region_polygon)
if cut_region_polygon.is_empty:
LOG.warning('region %d does not intersect page frame', i)
continue
if not cut_region_polygon.is_valid:
LOG.warning('region %d has invalid polygon', i)
continue
region_polygon = cut_region_polygon.exterior.coords[:-1]
region_coords = CoordsType(points_from_polygon(region_polygon),
conf=score)
read_order = reading_order.index(i)
region_args = {
'custom': 'readingOrder {index:' + str(read_order) + ';}',
'id': 'region%04d' % i,
'Coords': region_coords
}
if class_name == 'image':
image_region = ImageRegionType(**region_args)
page.add_ImageRegion(image_region)
elif class_name == 'table':
table_region = TableRegionType(**region_args)
page.add_TableRegion(table_region)
elif class_name == 'graphics':
graphic_region = GraphicRegionType(**region_args)
page.add_GraphicRegion(graphic_region)
else:
region_args['type_'] = class_name
textregion = TextRegionType(**region_args)
page.add_TextRegion(textregion)
order_index = reading_order.index(i)
regionRefIndex = RegionRefIndexedType(index=order_index,
regionRef=region_args['id'])
order_group.add_RegionRefIndexed(regionRefIndex)
LOG.info('added %s region on page "%s"', class_name, page_id)
def process(self):
"""Performs region segmentation by reading from COCO annotations.
Open and deserialize the COCO JSON file from the second input file group.
(It lists region categories/subtypes, file names and segmentations for all pages.)
Open and deserialize each PAGE input file (or generate from image input file)
from the first input file group. Now find this page in COCO:
- try to match the PAGE ``imageFilename`` or METS file path matches to some
COCO ``file_name``, otherwise
- try to match the numeric part of the METS physical page ID to some
COCO ``id``, otherwise
- skip with an error.
Then create and add a region for each ``segmentation``, converting its polygon
to coordinate points and its COCO category to a region type (and subtype),
either for a PubLayNet classification or PAGE classification (as produced by
ocrd-segment-extract-pages), as indicated by ``source``.
Produce a new output file by serialising the resulting hierarchy.
Afterwards, if there are still COCO images left unaccounted for (i.e. without
corresponding input files), then show a warning.
"""
LOG = getLogger('processor.ImportCOCOSegmentation')
# Load JSON
assert_file_grp_cardinality(self.input_file_grp, 2, 'base and COCO')
# pylint: disable=attribute-defined-outside-init
self.input_file_grp, coco_grp = self.input_file_grp.split(',')
# pylint: disable=attribute-defined-outside-init
if not self.input_files:
LOG.warning('No input files to process')
return
if coco_grp in self.workspace.mets.file_groups:
try:
cocofile = next(
f for f in self.workspace.mets.find_files(fileGrp=coco_grp)
# if f.mimetype == 'application/json' and not f.pageId
if not f.pageId)
except StopIteration:
raise Exception(
"no non-page-specific file in second file group (COCO file)",
coco_grp)
cocofile = self.workspace.download_file(cocofile).local_filename
elif os.path.isfile(coco_grp):
cocofile = coco_grp
else:
raise Exception("file not found in second file group (COCO file)",
coco_grp)
LOG.info('Loading COCO annotations from "%s" into memory...', cocofile)
with open(cocofile, 'r') as inp:
coco = json.load(inp)
LOG.info('Loaded JSON for %d images with %d regions in %d categories',
len(coco['images']), len(coco['annotations']),
len(coco['categories']))
coco_source = 'PubLayNet'
# Convert to usable dicts
# classes:
categories = dict()
subcategories = dict()
for cat in coco['categories']:
if cat['source'] == 'PAGE':
coco_source = 'PAGE'
if 'supercategory' in cat and cat['supercategory']:
categories[cat['id']] = cat['supercategory']
subcategories[cat['id']] = cat['name']
else:
categories[cat['id']] = cat['name']
# images and annotations:
images_by_id = dict()
images_by_filename = dict()
for image in coco['images']:
images_by_id[image['id']] = image
images_by_filename[image['file_name']] = image
for annotation in coco['annotations']:
image = images_by_id[annotation['image_id']]
regions = image.setdefault('regions', list())
regions.append(annotation)
del coco
LOG.info('Converting %s annotations into PAGE-XML', coco_source)
for n, input_file in enumerate(self.input_files):
page_id = input_file.pageId or input_file.ID
num_page_id = int(page_id.strip(page_id.strip("0123456789")))
LOG.info("INPUT FILE %i / %s", n, page_id)
pcgts = page_from_file(self.workspace.download_file(input_file))
self.add_metadata(pcgts)
page = pcgts.get_Page()
# find COCO image
if page.imageFilename in images_by_filename:
image = images_by_filename[page.imageFilename]
elif num_page_id in images_by_id:
image = images_by_id[num_page_id]
else:
LOG.error('Page "%s" / file "%s" not found in COCO', page_id,
page.imageFilename)
# todo: maybe we should at least write the (unchanged) output PAGE?
continue
if image['width'] != page.imageWidth:
LOG.error(
'Page "%s" width %d does not match annotated width %d',
page_id, page.imageWidth, image['width'])
if image['height'] != page.imageHeight:
LOG.error(
'Page "%s" height %d does not match annotated height %d',
page_id, page.imageHeight, image['height'])
# todo: remove existing segmentation first?
for region in image['regions']:
assert isinstance(
region['segmentation'],
list), "importing RLE/mask segmentation not implemented"
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']]
if region['category_id'] in subcategories:
subcategory = subcategories[region['category_id']]
else:
subcategory = None
region_id = 'r' + str(region['id'])
LOG.info('Adding region %s:%s [area %d]', category, subcategory
or '', region['area'])
if coco_source == 'PubLayNet':
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 region category: %s' %
category)
else: # 'PAGE'
args = {'id': region_id, 'Coords': coords}
if subcategory:
typedict = {
"TextRegion": TextTypeSimpleType,
"GraphicRegion": GraphicsTypeSimpleType,
"ChartType": ChartTypeSimpleType
}
if category in typedict:
subtype = membername(typedict[category],
subcategory)
if subtype == subcategory:
# not predefined in PAGE: use other + custom
args['custom'] = "subtype:%s" % subcategory
args['type_'] = "other"
else:
args['type_'] = subcategory
else:
args['custom'] = "subtype:%s" % subcategory
if category + 'Type' not in globals():
raise Exception('unknown region category: %s' %
category)
region_type = globals()[category + 'Type']
if region_type is BorderType:
page.set_Border(BorderType(Coords=coords))
else:
region_obj = region_type(**args)
getattr(page, 'add_%s' % category)(region_obj)
# remove image from dicts
images_by_id.pop(num_page_id, None)
images_by_filename.pop(page.imageFilename, None)
file_id = make_file_id(input_file, self.output_file_grp)
self.workspace.add_file(ID=file_id,
file_grp=self.output_file_grp,
pageId=input_file.pageId,
mimetype=MIMETYPE_PAGE,
local_filename=os.path.join(
self.output_file_grp,
file_id + '.xml'),
content=to_xml(pcgts))
# warn of remaining COCO images
if images_by_filename and not self.page_id:
LOG.warning('%d images remain unaccounted for after processing',
len(images_by_filename))
if LOG.isEnabledFor(logging.DEBUG):
for filename in images_by_filename:
LOG.debug('not found in workspace: "%s"', filename)
def build_pagexml_no_full_layout(
self, found_polygons_text_region, page_coord, order_of_texts,
id_of_texts, all_found_texline_polygons, all_box_coord,
found_polygons_text_region_img, found_polygons_marginals,
all_found_texline_polygons_marginals, all_box_coord_marginals,
slopes, slopes_marginals, cont_page,
polygons_lines_to_be_written_in_xml, found_polygons_tables):
self.logger.debug('enter build_pagexml_no_full_layout')
# create the file structure
pcgts = self.pcgts if self.pcgts else create_page_xml(
self.image_filename, self.height_org, self.width_org)
page = pcgts.get_Page()
page.set_Border(
BorderType(Coords=CoordsType(
points=self.calculate_page_coords(cont_page))))
counter = EynollahIdCounter()
if len(found_polygons_text_region) > 0:
_counter_marginals = EynollahIdCounter(
region_idx=len(order_of_texts))
id_of_marginalia = [
_counter_marginals.next_region_id
for _ in found_polygons_marginals
]
xml_reading_order(page, order_of_texts, id_of_marginalia)
for mm in range(len(found_polygons_text_region)):
textregion = TextRegionType(
id=counter.next_region_id,
type_='paragraph',
Coords=CoordsType(points=self.calculate_polygon_coords(
found_polygons_text_region[mm], page_coord)),
)
page.add_TextRegion(textregion)
self.serialize_lines_in_region(textregion,
all_found_texline_polygons, mm,
page_coord, all_box_coord, slopes,
counter)
for mm in range(len(found_polygons_marginals)):
marginal = TextRegionType(
id=counter.next_region_id,
type_='marginalia',
Coords=CoordsType(points=self.calculate_polygon_coords(
found_polygons_marginals[mm], page_coord)))
page.add_TextRegion(marginal)
self.serialize_lines_in_marginal(
marginal, all_found_texline_polygons_marginals, mm, page_coord,
all_box_coord_marginals, slopes_marginals, counter)
for mm in range(len(found_polygons_text_region_img)):
img_region = ImageRegionType(id=counter.next_region_id,
Coords=CoordsType())
page.add_ImageRegion(img_region)
points_co = ''
for lmm in range(len(found_polygons_text_region_img[mm])):
points_co += str(
int((found_polygons_text_region_img[mm][lmm, 0, 0] +
page_coord[2]) / self.scale_x))
points_co += ','
points_co += str(
int((found_polygons_text_region_img[mm][lmm, 0, 1] +
page_coord[0]) / self.scale_y))
points_co += ' '
img_region.get_Coords().set_points(points_co[:-1])
for mm in range(len(polygons_lines_to_be_written_in_xml)):
sep_hor = SeparatorRegionType(id=counter.next_region_id,
Coords=CoordsType())
page.add_SeparatorRegion(sep_hor)
points_co = ''
for lmm in range(len(polygons_lines_to_be_written_in_xml[mm])):
points_co += str(
int((polygons_lines_to_be_written_in_xml[mm][lmm, 0, 0]) /
self.scale_x))
points_co += ','
points_co += str(
int((polygons_lines_to_be_written_in_xml[mm][lmm, 0, 1]) /
self.scale_y))
points_co += ' '
sep_hor.get_Coords().set_points(points_co[:-1])
for mm in range(len(found_polygons_tables)):
tab_region = TableRegionType(id=counter.next_region_id,
Coords=CoordsType())
page.add_TableRegion(tab_region)
points_co = ''
for lmm in range(len(found_polygons_tables[mm])):
points_co += str(
int((found_polygons_tables[mm][lmm, 0, 0] + page_coord[2])
/ self.scale_x))
points_co += ','
points_co += str(
int((found_polygons_tables[mm][lmm, 0, 1] + page_coord[0])
/ self.scale_y))
points_co += ' '
tab_region.get_Coords().set_points(points_co[:-1])
return pcgts
def _process_element(self,
element,
ignore,
image,
coords,
element_id,
file_id,
page_id,
zoom=1.0,
rogroup=None):
"""Add PAGE layout elements by segmenting an image.
Given a PageType, TableRegionType or TextRegionType ``element``, and
a corresponding binarized PIL.Image object ``image`` with coordinate
metadata ``coords``, run line segmentation with Ocropy.
If operating on the full page (or table), then also detect horizontal
and vertical separators, and aggregate the lines into text regions
afterwards.
Add the resulting sub-segments to the parent ``element``.
If ``ignore`` is not empty, then first suppress all foreground components
in any of those segments' coordinates during segmentation, and if also
in full page/table mode, then combine all separators among them with the
newly detected separators to guide region segmentation.
"""
LOG = getLogger('processor.OcropySegment')
if not image.width or not image.height:
LOG.warning("Skipping '%s' with zero size", element_id)
return
element_array = pil2array(image)
element_bin = np.array(element_array <= midrange(element_array),
np.bool)
sep_bin = np.zeros_like(element_bin, np.bool)
ignore_labels = np.zeros_like(element_bin, np.int)
for i, segment in enumerate(ignore):
LOG.debug('masking foreground of %s "%s" for "%s"',
type(segment).__name__[:-4], segment.id, element_id)
# mark these segments (e.g. separator regions, tables, images)
# for workflows where they have been detected already;
# these will be:
# - ignored during text line segmentation (but not h/v-line detection)
# - kept and reading-ordered during region segmentation (but not seps)
segment_polygon = coordinates_of_segment(segment, image, coords)
# If segment_polygon lies outside of element (causing
# negative/above-max indices), either fully or partially,
# then this will silently ignore them. The caller does
# not need to concern herself with this.
if isinstance(segment, SeparatorRegionType):
sep_bin[draw.polygon(segment_polygon[:, 1], segment_polygon[:,
0],
sep_bin.shape)] = True
ignore_labels[draw.polygon(
segment_polygon[:, 1], segment_polygon[:, 0],
ignore_labels.shape)] = i + 1 # mapped back for RO
if isinstance(element, PageType):
element_name = 'page'
fullpage = True
report = check_page(element_bin, zoom)
elif isinstance(element, TableRegionType) or (
# sole/congruent text region of a table region?
element.id.endswith('_text')
and isinstance(element.parent_object_, TableRegionType)):
element_name = 'table'
fullpage = True
report = check_region(element_bin, zoom)
else:
element_name = 'region'
fullpage = False
report = check_region(element_bin, zoom)
LOG.info('computing line segmentation for %s "%s"', element_name,
element_id)
# TODO: we should downscale if DPI is large enough to save time
try:
if report:
raise Exception(report)
line_labels, hlines, vlines, images, colseps, scale = compute_segmentation(
# suppress separators and ignored regions for textline estimation
# but keep them for h/v-line detection (in fullpage mode):
element_bin,
seps=(sep_bin + ignore_labels) > 0,
zoom=zoom,
fullpage=fullpage,
spread_dist=round(self.parameter['spread'] / zoom * 300 /
72), # in pt
# these are ignored when not in fullpage mode:
maxcolseps=self.parameter['maxcolseps'],
maxseps=self.parameter['maxseps'],
maximages=self.parameter['maximages']
if element_name != 'table' else 0,
csminheight=self.parameter['csminheight'],
hlminwidth=self.parameter['hlminwidth'])
except Exception as err:
if isinstance(element, TextRegionType):
LOG.error('Cannot line-segment region "%s": %s', element_id,
err)
# as a fallback, add a single text line comprising the whole region:
element.add_TextLine(
TextLineType(id=element_id + "_line",
Coords=element.get_Coords()))
else:
LOG.error('Cannot line-segment %s "%s": %s', element_name,
element_id, err)
return
LOG.info('Found %d text lines for %s "%s"',
len(np.unique(line_labels)) - 1, element_name, element_id)
# post-process line labels
if isinstance(element, (PageType, TableRegionType)):
# aggregate text lines to text regions
try:
# pass ignored regions as "line labels with initial assignment",
# i.e. identical line and region labels
# to detect their reading order among the others
# (these cannot be split or grouped together with other regions)
line_labels = np.where(line_labels, line_labels + len(ignore),
ignore_labels)
# suppress separators/images in fg and try to use for partitioning slices
sepmask = np.maximum(np.maximum(hlines, vlines),
np.maximum(sep_bin, images))
region_labels = lines2regions(
element_bin,
line_labels,
rlabels=ignore_labels,
sepmask=np.maximum(sepmask, colseps), # add bg
# decide horizontal vs vertical cut when gaps of similar size
prefer_vertical=not isinstance(element, TableRegionType),
gap_height=self.parameter['gap_height'],
gap_width=self.parameter['gap_width'],
scale=scale,
zoom=zoom)
LOG.info('Found %d text regions for %s "%s"',
len(np.unique(region_labels)) - 1, element_name,
element_id)
except Exception as err:
LOG.error('Cannot region-segment %s "%s": %s', element_name,
element_id, err)
region_labels = np.where(line_labels > len(ignore),
1 + len(ignore), line_labels)
# prepare reading order group index
if rogroup:
if isinstance(rogroup,
(OrderedGroupType, OrderedGroupIndexedType)):
index = 0
# start counting from largest existing index
for elem in (rogroup.get_RegionRefIndexed() +
rogroup.get_OrderedGroupIndexed() +
rogroup.get_UnorderedGroupIndexed()):
if elem.index >= index:
index = elem.index + 1
else:
index = None
# find contours around region labels (can be non-contiguous):
region_no = 0
for region_label in np.unique(region_labels):
if not region_label:
continue # no bg
region_mask = region_labels == region_label
region_line_labels = line_labels * region_mask
region_line_labels0 = np.setdiff1d(region_line_labels, [0])
if not np.all(region_line_labels0 > len(ignore)):
# existing region from `ignore` merely to be ordered
# (no new region, no actual text lines)
region_line_labels0 = np.intersect1d(
region_line_labels0, ignore_labels)
assert len(region_line_labels0) == 1, \
"region label %d has both existing regions and new lines (%s)" % (
region_label, str(region_line_labels0))
region = ignore[region_line_labels0[0] - 1]
if rogroup and region.parent_object_ == element and not isinstance(
region, SeparatorRegionType):
index = page_add_to_reading_order(
rogroup, region.id, index)
LOG.debug('Region label %d is for ignored region "%s"',
region_label, region.id)
continue
# normal case: new lines inside new regions
# remove binary-empty labels, and re-order locally
order = morph.reading_order(region_line_labels)
order[np.setdiff1d(region_line_labels0,
element_bin * region_line_labels)] = 0
region_line_labels = order[region_line_labels]
# avoid horizontal gaps
region_line_labels = hmerge_line_seeds(element_bin,
region_line_labels,
scale,
seps=np.maximum(
sepmask, colseps))
region_mask |= region_line_labels > 0
# find contours for region (can be non-contiguous)
regions, _ = masks2polygons(
region_mask * region_label,
element_bin,
'%s "%s"' % (element_name, element_id),
min_area=6000 / zoom / zoom,
simplify=ignore_labels * ~(sep_bin))
# find contours for lines (can be non-contiguous)
lines, _ = masks2polygons(region_line_labels,
element_bin,
'region "%s"' % element_id,
min_area=640 / zoom / zoom)
# create new lines in new regions (allocating by intersection)
line_polys = [Polygon(polygon) for _, polygon in lines]
for _, region_polygon in regions:
region_poly = prep(Polygon(region_polygon))
# convert back to absolute (page) coordinates:
region_polygon = coordinates_for_segment(
region_polygon, image, coords)
region_polygon = polygon_for_parent(
region_polygon, element)
if region_polygon is None:
LOG.warning(
'Ignoring extant region contour for region label %d',
region_label)
continue
# annotate result:
region_no += 1
region_id = element_id + "_region%04d" % region_no
LOG.debug('Region label %d becomes ID "%s"', region_label,
region_id)
region = TextRegionType(
id=region_id,
Coords=CoordsType(
points=points_from_polygon(region_polygon)))
# find out which line (contours) belong to which region (contours)
line_no = 0
for i, line_poly in enumerate(line_polys):
if not region_poly.intersects(line_poly): # .contains
continue
line_label, line_polygon = lines[i]
# convert back to absolute (page) coordinates:
line_polygon = coordinates_for_segment(
line_polygon, image, coords)
line_polygon = polygon_for_parent(line_polygon, region)
if line_polygon is None:
LOG.warning(
'Ignoring extant line contour for region label %d line label %d',
region_label, line_label)
continue
# annotate result:
line_no += 1
line_id = region_id + "_line%04d" % line_no
LOG.debug('Line label %d becomes ID "%s"', line_label,
line_id)
line = TextLineType(
id=line_id,
Coords=CoordsType(
points=points_from_polygon(line_polygon)))
region.add_TextLine(line)
# if the region has received text lines, keep it
if region.get_TextLine():
element.add_TextRegion(region)
LOG.info('Added region "%s" with %d lines for %s "%s"',
region_id, line_no, element_name, element_id)
if rogroup:
index = page_add_to_reading_order(
rogroup, region.id, index)
# add additional image/non-text regions from compute_segmentation
# (e.g. drop-capitals or images) ...
image_labels, num_images = morph.label(images)
LOG.info('Found %d large non-text/image regions for %s "%s"',
num_images, element_name, element_id)
# find contours around region labels (can be non-contiguous):
image_polygons, _ = masks2polygons(
image_labels, element_bin,
'%s "%s"' % (element_name, element_id))
for image_label, polygon in image_polygons:
# convert back to absolute (page) coordinates:
region_polygon = coordinates_for_segment(
polygon, image, coords)
region_polygon = polygon_for_parent(region_polygon, element)
if region_polygon is None:
LOG.warning(
'Ignoring extant region contour for image label %d',
image_label)
continue
region_no += 1
# annotate result:
region_id = element_id + "_image%04d" % region_no
element.add_ImageRegion(
ImageRegionType(
id=region_id,
Coords=CoordsType(
points=points_from_polygon(region_polygon))))
# split rulers into separator regions:
hline_labels, num_hlines = morph.label(hlines)
vline_labels, num_vlines = morph.label(vlines)
LOG.info('Found %d/%d h/v-lines for %s "%s"', num_hlines,
num_vlines, element_name, element_id)
# find contours around region labels (can be non-contiguous):
hline_polygons, _ = masks2polygons(
hline_labels, element_bin,
'%s "%s"' % (element_name, element_id))
vline_polygons, _ = masks2polygons(
vline_labels, element_bin,
'%s "%s"' % (element_name, element_id))
for _, polygon in hline_polygons + vline_polygons:
# convert back to absolute (page) coordinates:
region_polygon = coordinates_for_segment(
polygon, image, coords)
region_polygon = polygon_for_parent(region_polygon, element)
if region_polygon is None:
LOG.warning('Ignoring extant region contour for separator')
continue
# annotate result:
region_no += 1
region_id = element_id + "_sep%04d" % region_no
element.add_SeparatorRegion(
SeparatorRegionType(
id=region_id,
Coords=CoordsType(
points=points_from_polygon(region_polygon))))
# annotate a text/image-separated image
element_array[sepmask] = np.amax(element_array) # clip to white/bg
image_clipped = array2pil(element_array)
file_path = self.workspace.save_image_file(
image_clipped,
file_id + '.IMG-CLIP',
page_id=page_id,
file_grp=self.output_file_grp)
element.add_AlternativeImage(
AlternativeImageType(filename=file_path,
comments=coords['features'] + ',clipped'))
else:
# get mask from region polygon:
region_polygon = coordinates_of_segment(element, image, coords)
region_mask = np.zeros_like(element_bin, np.bool)
region_mask[draw.polygon(region_polygon[:, 1], region_polygon[:,
0],
region_mask.shape)] = True
# ensure the new line labels do not extrude from the region:
line_labels = line_labels * region_mask
# find contours around labels (can be non-contiguous):
line_polygons, _ = masks2polygons(line_labels,
element_bin,
'region "%s"' % element_id,
min_area=640 / zoom / zoom)
line_no = 0
for line_label, polygon in line_polygons:
# convert back to absolute (page) coordinates:
line_polygon = coordinates_for_segment(polygon, image, coords)
line_polygon = polygon_for_parent(line_polygon, element)
if line_polygon is None:
LOG.warning(
'Ignoring extant line contour for line label %d',
line_label)
continue
# annotate result:
line_no += 1
line_id = element_id + "_line%04d" % line_no
element.add_TextLine(
TextLineType(
id=line_id,
Coords=CoordsType(
points=points_from_polygon(line_polygon))))
if not sep_bin.any():
return # no derived image
# annotate a text/image-separated image
element_array[sep_bin] = np.amax(element_array) # clip to white/bg
image_clipped = array2pil(element_array)
file_path = self.workspace.save_image_file(
image_clipped,
file_id + '.IMG-CLIP',
page_id=page_id,
file_grp=self.output_file_grp)
# update PAGE (reference the image file):
element.add_AlternativeImage(
AlternativeImageType(filename=file_path,
comments=coords['features'] + ',clipped'))
def _process_segment(self, page_image, page, region_xywh, page_id,
input_file, n):
binary = ocrolib.pil2array(page_image)
binary = np.array(1 - binary / np.amax(binary), 'B')
if page.get_TextRegion() is None or len(page.get_TextRegion()) < 1:
min_x, max_x = (0, binary.shape[0])
min_y, max_y = (0, binary.shape[1])
textregion = TextRegionType(
Coords=CoordsType("%i,%i %i,%i %i,%i %i,%i" %
(min_x, min_y, max_x, min_y, max_x, max_y,
min_x, max_y)))
page.add_TextRegion(textregion)
else:
textregion = page.get_TextRegion()[-1]
ocrolib.write_image_binary("test.bin.png", binary)
if self.parameter['scale'] == 0:
scale = psegutils.estimate_scale(binary)
else:
scale = self.parameter['scale']
if np.isnan(
scale) or scale > 1000.0 or scale < self.parameter['minscale']:
LOG.warning("%s: bad scale (%g); skipping\n" % (fname, scale))
return
segmentation = self.compute_segmentation(binary, scale)
if np.amax(segmentation) > self.parameter['maxlines']:
LOG.warning("%s: too many lines %i",
(fname, np.amax(segmentation)))
return
lines = psegutils.compute_lines(segmentation, scale)
order = psegutils.reading_order([l.bounds for l in lines])
lsort = psegutils.topsort(order)
# renumber the labels so that they conform to the specs
nlabels = np.amax(segmentation) + 1
renumber = np.zeros(nlabels, 'i')
for i, v in enumerate(lsort):
renumber[lines[v].label] = 0x010000 + (i + 1)
segmentation = renumber[segmentation]
lines = [lines[i] for i in lsort]
cleaned = ocrolib.remove_noise(binary, self.parameter['noise'])
region_xywh['features'] += ",textline"
for i, l in enumerate(lines):
ocrolib.write_image_binary("test.bin.png", binary[l.bounds[0],
l.bounds[1]])
min_x, max_x = (l.bounds[0].start, l.bounds[0].stop)
min_y, max_y = (l.bounds[1].start, l.bounds[1].stop)
img = binary[l.bounds[0], l.bounds[1]]
img = np.array(255 * (img > ocrolib.midrange(img)), 'B')
img = ocrolib.array2pil(img)
file_id = input_file.ID.replace(self.input_file_grp,
self.image_grp)
if file_id == input_file.ID:
file_id = concat_padded(self.image_grp, n)
file_path = self.workspace.save_image_file(img,
file_id + "_" + str(i),
page_id=page_id,
file_grp=self.image_grp)
ai = AlternativeImageType(filename=file_path,
comments=region_xywh['features'])
line = TextLineType(
Coords=CoordsType("%i,%i %i,%i %i,%i %i,%i" %
(min_x, min_y, max_x, min_y, max_x, max_y,
min_x, max_y)))
line.add_AlternativeImage(ai)
textregion.add_TextLine(line)
def test_deskewing(plain_workspace):
#from ocrd_utils import initLogging, setOverrideLogLevel
#setOverrideLogLevel('DEBUG')
size = (3000, 4000)
poly = [[1403, 2573], [1560, 2573], [1560, 2598], [2311,
2598], [2311, 2757],
[2220, 2757], [2220, 2798], [2311, 2798], [2311, 2908],
[1403, 2908]]
xywh = xywh_from_polygon(poly)
bbox = bbox_from_polygon(poly)
skew = 4.625
image = Image.new('L', size)
image = polygon_mask(image, poly)
#image.show(title='image')
pixels = np.count_nonzero(np.array(image) > 0)
name = 'foo0'
assert plain_workspace.save_image_file(image, name, 'IMG')
pcgts = page_from_file(next(plain_workspace.mets.find_files(ID=name)))
page = pcgts.get_Page()
region = TextRegionType(
id='nonrect',
Coords=CoordsType(points=points_from_polygon(poly)),
orientation=-skew)
page.add_TextRegion(region)
page_image, page_coords, _ = plain_workspace.image_from_page(page, '')
#page_image.show(title='page_image')
assert list(image.getdata()) == list(page_image.getdata())
assert np.all(page_coords['transform'] == np.eye(3))
reg_image, reg_coords = plain_workspace.image_from_segment(
region, page_image, page_coords, feature_filter='deskewed', fill=0)
assert list(image.crop(bbox).getdata()) == list(reg_image.getdata())
assert reg_image.width == xywh['w'] == 908
assert reg_image.height == xywh['h'] == 335
assert reg_coords['transform'][0, 2] == -xywh['x']
assert reg_coords['transform'][1, 2] == -xywh['y']
# same fg after cropping to minimal bbox
reg_pixels = np.count_nonzero(np.array(reg_image) > 0)
assert pixels == reg_pixels
# now with deskewing (test for size after recropping)
reg_image, reg_coords = plain_workspace.image_from_segment(region,
page_image,
page_coords,
fill=0)
#reg_image.show(title='reg_image')
assert reg_image.width == 932 > xywh['w']
assert reg_image.height == 382 > xywh['h']
assert reg_coords['transform'][0, 1] != 0
assert reg_coords['transform'][1, 0] != 0
assert 'deskewed' in reg_coords['features']
# same fg after cropping to minimal bbox (roughly - due to aliasing)
reg_pixels = np.count_nonzero(np.array(reg_image) > 0)
assert np.abs(pixels - reg_pixels) / pixels < 0.005
reg_array = np.array(reg_image) > 0
# now via AlternativeImage
path = plain_workspace.save_image_file(reg_image, region.id + '_img',
'IMG')
region.add_AlternativeImage(
AlternativeImageType(filename=path, comments=reg_coords['features']))
logger_capture = FIFOIO(256)
logger_handler = logging.StreamHandler(logger_capture)
#logger_handler.setFormatter(logging.Formatter(fmt=LOG_FORMAT, datefmt=LOG_TIMEFMT))
logger = logging.getLogger('ocrd_utils.crop_image')
logger.addHandler(logger_handler)
reg_image2, reg_coords2 = plain_workspace.image_from_segment(region,
page_image,
page_coords,
fill=0)
#reg_image2.show(title='reg_image2')
logger_output = logger_capture.getvalue()
logger_capture.close()
assert logger_output == ''
assert reg_image2.width == reg_image.width
assert reg_image2.height == reg_image.height
assert np.allclose(reg_coords2['transform'], reg_coords['transform'])
assert reg_coords2['features'] == reg_coords['features']
# same fg after cropping to minimal bbox (roughly - due to aliasing)
reg_pixels2 = np.count_nonzero(np.array(reg_image) > 0)
assert reg_pixels2 == reg_pixels
reg_array2 = np.array(reg_image2) > 0
assert 0.98 < np.sum(reg_array == reg_array2) / reg_array.size <= 1.0
def _process_page(self, it, page, page_image, page_coords, page_id):
LOG = getLogger('processor.TesserocrSegmentRegion')
# equivalent to GetComponentImages with raw_image=True,
# (which would also give raw coordinates),
# except we are also interested in the iterator's BlockType() here,
# and its BlockPolygon()
index = 0
ro = page.get_ReadingOrder()
if not ro:
ro = ReadingOrderType()
page.set_ReadingOrder(ro)
og = ro.get_OrderedGroup()
if og:
# start counting from largest existing index
for elem in (og.get_RegionRefIndexed() +
og.get_OrderedGroupIndexed() +
og.get_UnorderedGroupIndexed()):
if elem.index >= index:
index = elem.index + 1
else:
# new top-level group
og = OrderedGroupType(id="reading-order")
ro.set_OrderedGroup(og)
while it and not it.Empty(RIL.BLOCK):
# (padding will be passed to both BoundingBox and GetImage)
# (actually, Tesseract honours padding only on the left and bottom,
# whereas right and top are increased less!)
bbox = it.BoundingBox(RIL.BLOCK, padding=self.parameter['padding'])
# sometimes these polygons are not planar, which causes
# PIL.ImageDraw.Draw.polygon (and likely others as well)
# to misbehave; however, PAGE coordinate semantics prohibit
# multi-path polygons!
# (probably a bug in Tesseract itself, cf. tesseract#2826):
if self.parameter['crop_polygons']:
polygon = it.BlockPolygon()
else:
polygon = polygon_from_x0y0x1y1(bbox)
polygon = coordinates_for_segment(polygon, page_image, page_coords)
polygon2 = polygon_for_parent(polygon, page)
if polygon2 is not None:
polygon = polygon2
points = points_from_polygon(polygon)
coords = CoordsType(points=points)
if polygon2 is None:
LOG.info('Ignoring extant region: %s', points)
it.Next(RIL.BLOCK)
continue
# if xywh['w'] < 30 or xywh['h'] < 30:
# LOG.info('Ignoring too small region: %s', points)
# it.Next(RIL.BLOCK)
# continue
# region_image_bin = it.GetBinaryImage(RIL.BLOCK)
# if not region_image_bin.getbbox():
# LOG.info('Ignoring binary-empty region: %s', points)
# it.Next(RIL.BLOCK)
# continue
#
# add the region reference in the reading order element
# (will be removed again if Separator/Noise region below)
ID = "region%04d" % index
og.add_RegionRefIndexed(
RegionRefIndexedType(regionRef=ID, index=index))
#
# region type switch
#
block_type = it.BlockType()
if block_type in [
PT.FLOWING_TEXT,
PT.HEADING_TEXT,
PT.PULLOUT_TEXT,
PT.CAPTION_TEXT,
# TABLE is contained in PTIsTextType, but
# it is a bad idea to create a TextRegion
# for it (better set `find_tables` False):
# PT.TABLE,
# will also get a 90° @orientation
# (but that can be overridden by deskew/OSD):
PT.VERTICAL_TEXT
]:
region = TextRegionType(id=ID,
Coords=coords,
type=TextTypeSimpleType.PARAGRAPH)
if block_type == PT.VERTICAL_TEXT:
region.set_orientation(90.0)
elif block_type == PT.HEADING_TEXT:
region.set_type(TextTypeSimpleType.HEADING)
elif block_type == PT.PULLOUT_TEXT:
region.set_type(TextTypeSimpleType.FLOATING)
elif block_type == PT.CAPTION_TEXT:
region.set_type(TextTypeSimpleType.CAPTION)
page.add_TextRegion(region)
if self.parameter['sparse_text']:
region.set_type(TextTypeSimpleType.OTHER)
region.add_TextLine(
TextLineType(id=region.id + '_line', Coords=coords))
elif block_type in [
PT.FLOWING_IMAGE, PT.HEADING_IMAGE, PT.PULLOUT_IMAGE
]:
region = ImageRegionType(id=ID, Coords=coords)
page.add_ImageRegion(region)
elif block_type in [PT.HORZ_LINE, PT.VERT_LINE]:
region = SeparatorRegionType(id=ID, Coords=coords)
page.add_SeparatorRegion(region)
# undo appending in ReadingOrder
og.set_RegionRefIndexed(og.get_RegionRefIndexed()[:-1])
elif block_type in [PT.INLINE_EQUATION, PT.EQUATION]:
region = MathsRegionType(id=ID, Coords=coords)
page.add_MathsRegion(region)
elif block_type == PT.TABLE:
# without API access to StructuredTable we cannot
# do much for a TableRegionType (i.e. nrows, ncols,
# coordinates of cells for recursive regions etc),
# but this can be achieved afterwards by segment-table
region = TableRegionType(id=ID, Coords=coords)
page.add_TableRegion(region)
else:
region = NoiseRegionType(id=ID, Coords=coords)
page.add_NoiseRegion()
# undo appending in ReadingOrder
og.set_RegionRefIndexed(og.get_RegionRefIndexed()[:-1])
LOG.info("Detected region '%s': %s (%s)", ID, points,
membername(PT, block_type))
#
# iterator increment
#
index += 1
it.Next(RIL.BLOCK)
if (not og.get_RegionRefIndexed() and not og.get_OrderedGroupIndexed()
and not og.get_UnorderedGroupIndexed()):
# schema forbids empty OrderedGroup
ro.set_OrderedGroup(None)
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()
def process(self):
"""Segment pages into regions+lines, tables into cells+lines, or regions into lines.
Open and deserialise PAGE input files and their respective images,
then iterate over the element hierarchy down to the requested level.
Depending on ``level-of-operation``, consider existing segments:
- If ``overwrite_separators=True`` on ``page`` level, then
delete any SeparatorRegions.
- If ``overwrite_regions=True`` on ``page`` level, then
delete any top-level TextRegions (along with ReadingOrder).
- If ``overwrite_regions=True`` on ``table`` level, then
delete any TextRegions in TableRegions (along with their OrderGroup).
- If ``overwrite_lines=True`` on ``region`` level, then
delete any TextLines in TextRegions.
- If ``overwrite_order=True`` on ``page`` or ``table`` level, then
delete the reading order OrderedGroup entry corresponding
to the (page/table) segment.
Next, get each element image according to the layout annotation (from
the alternative image of the page/region, or by cropping via coordinates
into the higher-level image) in binarized form, and represent it as an array
with non-text regions and (remaining) text neighbours suppressed.
Then compute a text line segmentation for that array (as a label mask).
When ``level-of-operation`` is ``page`` or ``table``, this also entails
detecting
- up to ``maximages`` large foreground images,
- up to ``maxseps`` foreground h/v-line separators and
- up to ``maxcolseps`` background column separators
before text line segmentation itself, as well as aggregating text lines
to text regions afterwards.
Text regions are detected via a hybrid variant recursive X-Y cut algorithm
(RXYC): RXYC partitions the binarized image in top-down manner by detecting
horizontal or vertical gaps. This implementation uses the bottom-up text line
segmentation to guide the search, and also uses both pre-existing and newly
detected separators to alternatively partition the respective boxes into
non-rectangular parts.
During line segmentation, suppress the foreground of all previously annotated
regions (of any kind) and lines, except if just removed due to ``overwrite``.
During region aggregation however, combine the existing separators with the
new-found separators to guide the column search.
All detected segments (both text line and text region) are sorted according
to their reading order (assuming a top-to-bottom, left-to-right ordering).
When ``level-of-operation`` is ``page``, prefer vertical (column-first)
succession of regions. When it is ``table``, prefer horizontal (row-first)
succession of cells.
Then for each resulting segment label, convert its background mask into
polygon outlines by finding the outer contours consistent with the element's
polygon outline. Annotate the result by adding it as a new TextLine/TextRegion:
- If ``level-of-operation`` is ``region``, then append the new lines to the
parent region.
- If it is ``table``, then append the new lines to their respective regions,
and append the new regions to the parent table.
(Also, create an OrderedGroup for it as the parent's RegionRef.)
- If it is ``page``, then append the new lines to their respective regions,
and append the new regions to the page.
(Also, create an OrderedGroup for it in the ReadingOrder.)
Produce a new output file by serialising the resulting hierarchy.
"""
LOG = getLogger('processor.OcropySegment')
# FIXME: allow passing a-priori info on reading order / textline order
# (and then pass on as ``bt`` and ``rl``; however, there may be a mixture
# of different scripts; also, vertical writing needs internal rotation
# because our line segmentation only works for horizontal writing)
overwrite_lines = self.parameter['overwrite_lines']
overwrite_regions = self.parameter['overwrite_regions']
overwrite_separators = self.parameter['overwrite_separators']
overwrite_order = self.parameter['overwrite_order']
oplevel = self.parameter['level-of-operation']
assert_file_grp_cardinality(self.input_file_grp, 1)
assert_file_grp_cardinality(self.output_file_grp, 1)
for (n, input_file) in enumerate(self.input_files):
LOG.info("INPUT FILE %i / %s", n, input_file.pageId
or input_file.ID)
file_id = make_file_id(input_file, self.output_file_grp)
pcgts = page_from_file(self.workspace.download_file(input_file))
self.add_metadata(pcgts)
page_id = pcgts.pcGtsId or input_file.pageId or input_file.ID # (PageType has no id)
page = pcgts.get_Page()
# TODO: also allow grayscale_normalized (try/except?)
page_image, page_coords, page_image_info = self.workspace.image_from_page(
page, page_id, feature_selector='binarized')
if self.parameter['dpi'] > 0:
zoom = 300.0 / self.parameter['dpi']
elif page_image_info.resolution != 1:
dpi = page_image_info.resolution
if page_image_info.resolutionUnit == 'cm':
dpi *= 2.54
LOG.info('Page "%s" uses %f DPI', page_id, dpi)
zoom = 300.0 / dpi
else:
zoom = 1
# aggregate existing regions so their foreground can be ignored
ignore = (page.get_ImageRegion() + page.get_LineDrawingRegion() +
page.get_GraphicRegion() + page.get_ChartRegion() +
page.get_MapRegion() + page.get_MathsRegion() +
page.get_ChemRegion() + page.get_MusicRegion() +
page.get_AdvertRegion() + page.get_NoiseRegion() +
page.get_UnknownRegion() + page.get_CustomRegion())
if oplevel == 'page' and overwrite_separators:
page.set_SeparatorRegion([])
else:
ignore.extend(page.get_SeparatorRegion())
# prepare reading order
reading_order = dict()
ro = page.get_ReadingOrder()
if ro:
rogroup = ro.get_OrderedGroup() or ro.get_UnorderedGroup()
if rogroup:
page_get_reading_order(reading_order, rogroup)
# get segments to process / overwrite
if oplevel == 'page':
ignore.extend(page.get_TableRegion())
regions = list(page.get_TextRegion())
if regions:
# page is already region-segmented
if overwrite_regions:
LOG.info('removing existing TextRegions in page "%s"',
page_id)
# we could remove all other region types as well,
# but this is more flexible (for workflows with
# specialized separator/image/table detectors):
page.set_TextRegion([])
page.set_ReadingOrder(None)
ro = None
else:
LOG.warning(
'keeping existing TextRegions in page "%s"',
page_id)
ignore.extend(regions)
# create reading order if necessary
if not ro or overwrite_order:
ro = ReadingOrderType()
page.set_ReadingOrder(ro)
rogroup = ro.get_OrderedGroup() or ro.get_UnorderedGroup()
if not rogroup:
# new top-level group
rogroup = OrderedGroupType(id="reading-order")
ro.set_OrderedGroup(rogroup)
# go get TextRegions with TextLines (and SeparatorRegions):
self._process_element(page,
ignore,
page_image,
page_coords,
page_id,
file_id,
input_file.pageId,
zoom,
rogroup=rogroup)
if (not rogroup.get_RegionRefIndexed()
and not rogroup.get_OrderedGroupIndexed()
and not rogroup.get_UnorderedGroupIndexed()):
# schema forbids empty OrderedGroup
ro.set_OrderedGroup(None)
elif oplevel == 'table':
ignore.extend(page.get_TextRegion())
regions = list(page.get_TableRegion())
if not regions:
LOG.warning('Page "%s" contains no table regions', page_id)
for region in regions:
subregions = region.get_TextRegion()
if subregions:
# table is already cell-segmented
if overwrite_regions:
LOG.info(
'removing existing TextRegions in table "%s"',
region.id)
region.set_TextRegion([])
roelem = reading_order.get(region.id)
# replace by empty group with same index and ref
# (which can then take the cells as subregions)
reading_order[
region.id] = page_subgroup_in_reading_order(
roelem)
else:
LOG.warning(
'skipping table "%s" with existing TextRegions',
region.id)
continue
# TODO: also allow grayscale_normalized (try/except?)
region_image, region_coords = self.workspace.image_from_segment(
region,
page_image,
page_coords,
feature_selector='binarized')
# ignore everything but the current table region
subignore = regions + ignore
subignore.remove(region)
# create reading order group if necessary
roelem = reading_order.get(region.id)
if not roelem:
LOG.warning(
"Page '%s' table region '%s' is not referenced in reading order (%s)",
page_id, region.id, "no target to add cells to")
elif overwrite_order:
# replace by empty ordered group with same (index and) ref
# (which can then take the cells as subregions)
roelem = page_subgroup_in_reading_order(roelem)
reading_order[region.id] = roelem
elif isinstance(
roelem,
(OrderedGroupType, OrderedGroupIndexedType)):
LOG.warning(
"Page '%s' table region '%s' already has an ordered group (%s)",
page_id, region.id, "cells will be appended")
elif isinstance(
roelem,
(UnorderedGroupType, UnorderedGroupIndexedType)):
LOG.warning(
"Page '%s' table region '%s' already has an unordered group (%s)",
page_id, region.id, "cells will not be appended")
roelem = None
else:
# replace regionRef(Indexed) by group with same index and ref
# (which can then take the cells as subregions)
roelem = page_subgroup_in_reading_order(roelem)
reading_order[region.id] = roelem
# go get TextRegions with TextLines (and SeparatorRegions)
self._process_element(region,
subignore,
region_image,
region_coords,
region.id,
file_id + '_' + region.id,
input_file.pageId,
zoom,
rogroup=roelem)
else: # 'region'
regions = list(page.get_TextRegion())
# besides top-level text regions, line-segment any table cells,
# and for tables without any cells, add a pseudo-cell
for region in page.get_TableRegion():
subregions = region.get_TextRegion()
if subregions:
regions.extend(subregions)
else:
subregion = TextRegionType(
id=region.id + '_text',
Coords=region.get_Coords(),
# as if generated from parser:
parent_object_=region)
region.add_TextRegion(subregion)
regions.append(subregion)
if not regions:
LOG.warning('Page "%s" contains no text regions', page_id)
for region in regions:
if region.get_TextLine():
if overwrite_lines:
LOG.info(
'removing existing TextLines in page "%s" region "%s"',
page_id, region.id)
region.set_TextLine([])
else:
LOG.warning(
'keeping existing TextLines in page "%s" region "%s"',
page_id, region.id)
ignore.extend(region.get_TextLine())
# TODO: also allow grayscale_normalized (try/except?)
region_image, region_coords = self.workspace.image_from_segment(
region,
page_image,
page_coords,
feature_selector='binarized')
# if the region images have already been clipped against their neighbours specifically,
# then we don't need to suppress all neighbours' foreground generally here
if 'clipped' in region_coords['features'].split(','):
ignore = []
# go get TextLines
self._process_element(region, ignore, region_image,
region_coords, region.id,
file_id + '_' + region.id,
input_file.pageId, zoom)
# update METS (add the PAGE file):
file_path = os.path.join(self.output_file_grp, file_id + '.xml')
pcgts.set_pcGtsId(file_id)
out = self.workspace.add_file(ID=file_id,
file_grp=self.output_file_grp,
pageId=input_file.pageId,
local_filename=file_path,
mimetype=MIMETYPE_PAGE,
content=to_xml(pcgts))
LOG.info('created file ID: %s, file_grp: %s, path: %s', file_id,
self.output_file_grp, out.local_filename)
def _process_segment(self, page_image, page, page_xywh, page_id,
input_file, n, mrcnn_model, class_names, mask):
LOG = getLogger('OcrdAnybaseocrBlockSegmenter')
# check for existing text regions and whether to overwrite them
border = None
if page.get_TextRegion():
if self.parameter['overwrite']:
LOG.info('removing existing TextRegions in page "%s"', page_id)
page.set_TextRegion([])
else:
LOG.warning('keeping existing TextRegions in page "%s"',
page_id)
return
# check if border exists
if page.get_Border():
border_coords = page.get_Border().get_Coords()
border_points = polygon_from_points(border_coords.get_points())
border = Polygon(border_points)
# page_image, page_xy = self.workspace.image_from_segment(page.get_Border(), page_image, page_xywh)
img_array = ocrolib.pil2array(page_image)
page_image.save('./checkthis.png')
if len(img_array.shape) <= 2:
img_array = np.stack((img_array, ) * 3, axis=-1)
results = mrcnn_model.detect([img_array], verbose=1)
r = results[0]
th = self.parameter['th']
# check for existing semgentation mask
# this code executes only when use_deeplr is set to True in ocrd-tool.json file
if mask:
mask = ocrolib.pil2array(mask)
mask = mask // 255
mask = 1 - mask
# multiply all the bounding box part with 2
for i in range(len(r['rois'])):
min_x = r['rois'][i][0]
min_y = r['rois'][i][1]
max_x = r['rois'][i][2]
max_y = r['rois'][i][3]
mask[min_x:max_x, min_y:max_y] *= i + 2
cv2.imwrite('mask_check.png', mask * (255 / (len(r['rois']) + 2)))
# check for left over pixels and add them to the bounding boxes
pixel_added = True
while pixel_added:
pixel_added = False
left_over = np.where(mask == 1)
for x, y in zip(left_over[0], left_over[1]):
local_mask = mask[x - th:x + th, y - th:y + th]
candidates = np.where(local_mask > 1)
candidates = [k for k in zip(candidates[0], candidates[1])]
if len(candidates) > 0:
pixel_added = True
# find closest pixel with x>1
candidates.sort(key=lambda j: np.sqrt((j[0] - th)**2 +
(j[1] - th)**2))
index = local_mask[candidates[0]] - 2
# add pixel to mask/bbox
# x,y to bbox with index
if x < r['rois'][index][0]:
r['rois'][index][0] = x
elif x > r['rois'][index][2]:
r['rois'][index][2] = x
if y < r['rois'][index][1]:
r['rois'][index][1] = y
elif y > r['rois'][index][3]:
r['rois'][index][3] = y
# update the mask
mask[x, y] = index + 2
# resolving overlapping problem
bbox_dict = {} # to check any overlapping bbox
class_id_check = []
for i in range(len(r['rois'])):
min_x = r['rois'][i][0]
min_y = r['rois'][i][1]
max_x = r['rois'][i][2]
max_y = r['rois'][i][3]
region_bbox = [min_y, min_x, max_y, max_x]
for key in bbox_dict:
for bbox in bbox_dict[key]:
# checking for ymax case with vertical overlapping
# along with y, check both for xmax and xmin
if (region_bbox[3] <= bbox[3] and region_bbox[3] >= bbox[1]
and ((region_bbox[0] >= bbox[0]
and region_bbox[0] <= bbox[2]) or
(region_bbox[2] >= bbox[0]
and region_bbox[2] <= bbox[2]) or
(region_bbox[0] <= bbox[0]
and region_bbox[2] >= bbox[2]))
and r['class_ids'][i] != 5):
r['rois'][i][2] = bbox[1] - 1
# checking for ymin now
# along with y, check both for xmax and xmin
if (region_bbox[1] <= bbox[3] and region_bbox[1] >= bbox[1]
and ((region_bbox[0] >= bbox[0]
and region_bbox[0] <= bbox[2]) or
(region_bbox[2] >= bbox[0]
and region_bbox[2] <= bbox[2]) or
(region_bbox[0] <= bbox[0]
and region_bbox[2] >= bbox[2]))
and r['class_ids'][i] != 5):
r['rois'][i][0] = bbox[3] + 1
if r['class_ids'][i] not in class_id_check:
bbox_dict[r['class_ids'][i]] = []
class_id_check.append(r['class_ids'][i])
bbox_dict[r['class_ids'][i]].append(region_bbox)
# resolving overlapping problem code
# define reading order on basis of coordinates
reading_order = []
for i in range(len(r['rois'])):
width, height, _ = img_array.shape
min_x = r['rois'][i][0]
min_y = r['rois'][i][1]
max_x = r['rois'][i][2]
max_y = r['rois'][i][3]
if (min_y - 5) > width and r['class_ids'][i] == 2:
min_y -= 5
if (max_y + 10) < width and r['class_ids'][i] == 2:
min_y += 10
reading_order.append((min_y, min_x, max_y, max_x))
reading_order = sorted(reading_order,
key=lambda reading_order:
(reading_order[1], reading_order[0]))
for i in range(len(reading_order)):
min_y, min_x, max_y, max_x = reading_order[i]
min_y = 0
i_poly = Polygon([[min_x, min_y], [max_x, min_y], [max_x, max_y],
[min_x, max_y]])
for j in range(i + 1, len(reading_order)):
min_y, min_x, max_y, max_x = reading_order[j]
j_poly = Polygon([[min_x, min_y], [max_x, min_y],
[max_x, max_y], [min_x, max_y]])
inter = i_poly.intersection(j_poly)
if inter:
reading_order.insert(j + 1, reading_order[i])
del reading_order[i]
# Creating Reading Order object in PageXML
order_group = OrderedGroupType(caption="Regions reading order",
id=page_id)
for i in range(len(r['rois'])):
min_x = r['rois'][i][0]
min_y = r['rois'][i][1]
max_x = r['rois'][i][2]
max_y = r['rois'][i][3]
if (min_y - 5) > width and r['class_ids'][i] == 2:
min_y -= 5
if (max_y + 10) < width and r['class_ids'][i] == 2:
min_y += 10
region_polygon = [[min_x, min_y], [max_x, min_y], [max_x, max_y],
[min_x, max_y]]
if border:
cut_region_polygon = border.intersection(
Polygon(region_polygon))
if cut_region_polygon.is_empty:
continue
else:
cut_region_polygon = Polygon(region_polygon)
order_index = reading_order.index((min_y, min_x, max_y, max_x))
region_id = '%s_region%04d' % (page_id, i)
regionRefIndex = RegionRefIndexedType(index=order_index,
regionRef=region_id)
order_group.add_RegionRefIndexed(regionRefIndex)
reading_order_object = ReadingOrderType()
reading_order_object.set_OrderedGroup(order_group)
page.set_ReadingOrder(reading_order_object)
for i in range(len(r['rois'])):
width, height, _ = img_array.shape
min_x = r['rois'][i][0]
min_y = r['rois'][i][1]
max_x = r['rois'][i][2]
max_y = r['rois'][i][3]
if (min_y - 5) > width and r['class_ids'][i] == 2:
min_y -= 5
if (max_y + 10) < width and r['class_ids'][i] == 2:
min_y += 10
# one change here to resolve flipped coordinates
region_polygon = [[min_y, min_x], [max_y, min_x], [max_y, max_x],
[min_y, max_x]]
cut_region_polygon = border.intersection(Polygon(region_polygon))
if cut_region_polygon.is_empty:
continue
cut_region_polygon = [
j for j in zip(list(cut_region_polygon.exterior.coords.xy[0]),
list(cut_region_polygon.exterior.coords.xy[1]))
][:-1]
# checking whether coordinates are flipped
region_polygon = coordinates_for_segment(cut_region_polygon,
page_image, page_xywh)
region_points = points_from_polygon(region_polygon)
read_order = reading_order.index((min_y, min_x, max_y, max_x))
# this can be tested, provided whether we need previous comments or not?
# resolving overlapping problem
region_img = img_array[min_x:max_x, min_y:
max_y] # extract from points and img_array
region_img = ocrolib.array2pil(region_img)
file_id = make_file_id(input_file, self.output_file_grp)
file_path = self.workspace.save_image_file(
region_img,
file_id + "_" + str(i),
page_id=page_id,
file_grp=self.output_file_grp)
# ai = AlternativeImageType(filename=file_path, comments=page_xywh['features'])
region_id = '%s_region%04d' % (page_id, i)
coords = CoordsType(region_points)
# incase of imageRegion
if r['class_ids'][i] == 15:
image_region = ImageRegionType(
custom='readingOrder {index:' + str(read_order) + ';}',
id=region_id,
Coords=coords,
type_=class_names[r['class_ids'][i]])
# image_region.add_AlternativeImage(ai)
page.add_ImageRegion(image_region)
continue
if r['class_ids'][i] == 16:
table_region = TableRegionType(
custom='readingOrder {index:' + str(read_order) + ';}',
id=region_id,
Coords=coords,
type_=class_names[r['class_ids'][i]])
# table_region.add_AlternativeImage(ai)
page.add_TableRegion(table_region)
continue
if r['class_ids'][i] == 17:
graphic_region = GraphicRegionType(
custom='readingOrder {index:' + str(read_order) + ';}',
id=region_id,
Coords=coords,
type_=class_names[r['class_ids'][i]])
# graphic_region.add_AlternativeImage(ai)
page.add_GraphicRegion(graphic_region)
continue
textregion = TextRegionType(custom='readingOrder {index:' +
str(read_order) + ';}',
id=region_id,
Coords=coords,
type_=class_names[r['class_ids'][i]])
# textregion.add_AlternativeImage(ai)
#border = page.get_Border()
# if border:
# border.add_TextRegion(textregion)
# else:
page.add_TextRegion(textregion)
def process(self):
for (n, input_file) in enumerate(self.input_files):
pcgts = page_from_file(self.workspace.download_file(input_file))
fname = pcgts.get_Page().imageFilename
img = self.workspace.resolve_image_as_pil(fname)
param = self.parameter
base, _ = ocrolib.allsplitext(fname)
#basefile = ocrolib.allsplitext(os.path.basename(fpath))[0]
if param['parallel'] < 2:
print_info("=== %s " % (fname))
raw = ocrolib.read_image_gray(img.filename)
flat = raw
#flat = np.array(binImg)
# estimate skew angle and rotate
if param['maxskew'] > 0:
if param['parallel'] < 2:
print_info("estimating skew angle")
d0, d1 = flat.shape
o0, o1 = int(param['bignore'] * d0), int(param['bignore'] * d1)
flat = amax(flat) - flat
flat -= amin(flat)
est = flat[o0:d0 - o0, o1:d1 - o1]
ma = param['maxskew']
ms = int(2 * param['maxskew'] * param['skewsteps'])
angle = self.estimate_skew_angle(est,
linspace(-ma, ma, ms + 1))
flat = interpolation.rotate(flat,
angle,
mode='constant',
reshape=0)
flat = amax(flat) - flat
else:
angle = 0
# self.write_angles_to_pageXML(base,angle)
# estimate low and high thresholds
if param['parallel'] < 2:
print_info("estimating thresholds")
d0, d1 = flat.shape
o0, o1 = int(param['bignore'] * d0), int(param['bignore'] * d1)
est = flat[o0:d0 - o0, o1:d1 - o1]
if param['escale'] > 0:
# by default, we use only regions that contain
# significant variance; this makes the percentile
# based low and high estimates more reliable
e = param['escale']
v = est - filters.gaussian_filter(est, e * 20.0)
v = filters.gaussian_filter(v**2, e * 20.0)**0.5
v = (v > 0.3 * amax(v))
v = morphology.binary_dilation(v,
structure=ones(
(int(e * 50), 1)))
v = morphology.binary_dilation(v,
structure=ones(
(1, int(e * 50))))
if param['debug'] > 0:
imshow(v)
ginput(1, param['debug'])
est = est[v]
lo = stats.scoreatpercentile(est.ravel(), param['lo'])
hi = stats.scoreatpercentile(est.ravel(), param['hi'])
# rescale the image to get the gray scale image
if param['parallel'] < 2:
print_info("rescaling")
flat -= lo
flat /= (hi - lo)
flat = clip(flat, 0, 1)
if param['debug'] > 0:
imshow(flat, vmin=0, vmax=1)
ginput(1, param['debug'])
deskewed = 1 * (flat > param['threshold'])
# output the normalized grayscale and the thresholded images
print_info("%s lo-hi (%.2f %.2f) angle %4.1f" %
(pcgts.get_Page().imageFilename, lo, hi, angle))
if param['parallel'] < 2:
print_info("writing")
ocrolib.write_image_binary(base + ".ds.png", deskewed)
orientation = TextRegionType(orientation=angle)
pcgts.get_Page().add_TextRegion(orientation)
ID = concat_padded(self.output_file_grp, n)
self.workspace.add_file(ID=ID,
file_grp=self.output_file_grp,
pageId=input_file.pageId,
mimetype="image/png",
url=base + ".ds.png",
local_filename='%s/%s' %
(self.output_file_grp, ID),
content=to_xml(pcgts).encode('utf-8'))