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reorder: also cover heuristic RO besides model-based…

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- CLI: rename `machine-based-reading-order` → `reorder`
- CLI: default to heuristic, add `-mb` / `--model_based`
  for old behaviour
- CLI: add `-dim` / `--dir_imgs` for path resolution of
  image files (needed for col-classifier phase of heuristic
  RO)
- in heuristic mode:
  - `setup_models()`: load `page` and `col_classifier` models
    instead of `reading_order`
  - `read_xml()`: also extract skew angle and `img_filename`,
    as well as table region labels
  - `run_single()`: resolve image file name by trying PAGE
    `@imageFilename` with prefixes and trying PAGE XML
    basename with typical image suffixes
  - `run_single()`: read images and run column classifier
    (which may crop andresize the image and); adapt extracted
    label map and contours to new size if resized
  - derive non-separator mask (`regions_without_separators`)
    by setting separators and images to zero in region map
  - deskew if necessary (masks and contours)
  - then call `do_order_of_regions_heuristic()`
- also log output file
This commit is contained in:
Robert Sachunsky 2026-07-20 02:10:56 +02:00
parent 282095f921
commit 5d1fecac87
3 changed files with 141 additions and 19 deletions
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2
src/eynollah/cli/__init__.py
View file

@ -10,7 +10,7 @@ from .cli_readingorder import readingorder_cli
main.add_command(binarize_cli, 'binarization')
main.add_command(enhance_cli, 'enhancement')
main.add_command(layout_cli, 'layout')
main.add_command(readingorder_cli, 'machine-based-reading-order')
main.add_command(readingorder_cli, 'reorder')
main.add_command(models_cli, 'models')
main.add_command(ocr_cli, 'ocr')
main.add_command(extract_images_cli, 'extract-images')

21
src/eynollah/cli/cli_readingorder.py
View file

@ -3,6 +3,12 @@ import click
@click.command(context_settings=dict(
help_option_names=['-h', '--help'],
show_default=True))
@click.option(
"--model_based",
"-mb",
help="use machine-learning model instead of heuristic rules",
is_flag=True,
)
@click.option(
"--input",
"-i",
@ -15,6 +21,12 @@ import click
help="directory of PAGE-XML input files (instead of --input)",
type=click.Path(exists=True, file_okay=False),
)
@click.option(
"--dir_imgs",
"-dim",
help="directory of image input files (in addition to --dir_in or --input; filename stems must match the XML files, with image file format suffixes). Not needed for --model_based.",
type=click.Path(exists=True, file_okay=False),
)
@click.option(
"--out",
"-o",
@ -29,17 +41,20 @@ import click
is_flag=True,
)
@click.pass_context
def readingorder_cli(ctx, input, dir_in, out, overwrite):
def readingorder_cli(ctx, model_based, input, dir_in, dir_imgs, out, overwrite):
"""
Generate ReadingOrder from ML model
Generate ReadingOrder for existing segmentation from ML model or from heuristic rules
"""
from ..reorder import Reorder
assert bool(input) != bool(dir_in), "Either -i (single input) or -di (directory) must be provided, but not both."
assert bool(model_based) or bool(dir_imgs), "For heuristic reading order, -dim must be provided, too."
orderer = Reorder(model_zoo=ctx.obj.model_zoo,
device=ctx.obj.device)
device=ctx.obj.device,
model_based=model_based)
orderer.run(overwrite=overwrite,
xml_filename=input,
dir_in=dir_in,
dir_imgs=dir_imgs,
dir_out=out,
)

125
src/eynollah/reorder.py
View file

@ -43,14 +43,32 @@ class Reorder(Eynollah):
model_zoo: EynollahModelZoo,
logger : Optional[logging.Logger] = None,
device: str = '',
model_based: bool = True,
# also expose these on CLI?
ignore_page_extraction: bool = False,
right2left : bool = False,
input_binary: bool = False,
num_col_upper: int = 0,
num_col_lower: int = 0,
):
self.logger = logger or logging.getLogger('eynollah.mbreorder')
self.logger = logger or logging.getLogger('eynollah.reorder')
self.model_based = model_based
self.ignore_page_extraction = ignore_page_extraction
self.tables = True # for find_num_col
self.right2left = right2left
self.input_binary = input_binary
self.num_col_upper = num_col_upper
self.num_col_lower = num_col_lower
self.model_zoo = model_zoo
self.setup_models(device=device)
def setup_models(self, device=''):
if self.model_based:
loadable = ['reading_order']
else:
loadable = ['page', 'col_classifier']
if self.input_binary:
loadable.append('binarization')
self.model_zoo.load_models(*loadable, device=device)
for model in loadable:
self.logger.debug("model %s has input shape %s", model,
@ -64,9 +82,10 @@ class Reorder(Eynollah):
label_seps=6,
label_marg=8,
label_drop=4,
label_tabs=10,
):
tree1 = ET.parse(xml_file, parser = ET.XMLParser(encoding='utf-8'))
root1=tree1.getroot()
tree1 = ET.parse(xml_file, parser=ET.XMLParser(encoding='utf-8'))
root1 = tree1.getroot()
alltags=[elem.tag for elem in root1.iter()]
link=alltags[0].split('}')[0]+'}'
@ -76,6 +95,8 @@ class Reorder(Eynollah):
page = root1.find(link+'Page')
height = int(page.get('imageHeight', 0))
width = int(page.get('imageWidth', 0))
skew = -float(page.get('orientation', 0))
img_filename = page.get('imageFilename', '')
for jj in root1.iter(link+'RegionRefIndexed'):
index_tot_regions.append(jj.attrib['index'])
@ -97,6 +118,7 @@ class Reorder(Eynollah):
seps_cont = []
imgs_cont = []
tabs_cont = []
text_para_cont = []
text_para_ids = []
text_drop_cont = []
@ -136,6 +158,9 @@ class Reorder(Eynollah):
text_para_cont.append(cont)
text_para_ids.append(id_)
elif nn.tag.endswith('}TableRegion'):
tabs_cont.append(cont)
elif nn.tag.endswith('}GraphicRegion'):
imgs_cont.append(cont)
@ -150,6 +175,7 @@ class Reorder(Eynollah):
img = cv2.fillPoly(img, pts=text_head_cont, color=label_head)
img = cv2.fillPoly(img, pts=text_marg_cont, color=label_marg)
img = cv2.fillPoly(img, pts=text_drop_cont, color=label_drop)
img = cv2.fillPoly(img, pts=tabs_cont, color=label_tabs)
img = cv2.fillPoly(img, pts=imgs_cont, color=label_imgs)
img = cv2.fillPoly(img, pts=seps_cont, color=label_seps)
@ -158,7 +184,7 @@ class Reorder(Eynollah):
text_para_ids, text_head_ids, text_drop_ids,
text_para_cont, text_head_cont, text_drop_cont,
tot_region_ref,
width, height,
width, height, skew, img_filename,
index_tot_regions,
img)
@ -166,6 +192,7 @@ class Reorder(Eynollah):
overwrite: bool = False,
xml_filename: Optional[str] = None,
dir_in: Optional[str] = None,
dir_imgs: Optional[str] = None,
dir_out: Optional[str] = None,
):
"""
@ -184,15 +211,21 @@ class Reorder(Eynollah):
raise ValueError("run requires either a single image filename or a directory")
for xml_filename in ls_xmls:
self.run_single(xml_filename, dir_out=dir_out, overwrite=overwrite)
self.run_single(xml_filename,
dir_out=dir_out,
dir_imgs=dir_imgs,
overwrite=overwrite)
if dir_in:
self.logger.info("All jobs done in %.1fs", time.time() - t0_tot)
def run_single(self,
xml_filename: str,
dir_imgs: Optional[str] = None,
dir_out: Optional[str] = None,
overwrite: bool = False
overwrite: bool = False,
label_imgs=5,
label_seps=6,
) -> None:
self.logger.info(xml_filename)
t0 = time.time()
@ -203,7 +236,7 @@ class Reorder(Eynollah):
para_ids, head_ids, drop_ids,
para_cont, head_cont, drop_cont,
_, # FIXME: do not ignore existing RO (tot_region_ref)
width, height,
width, height, skew, img_filename,
_, # FIXME: do not ignore existing RO (index_tot_regions)
region_labels) = self.read_xml(xml_filename)
@ -211,11 +244,83 @@ class Reorder(Eynollah):
self.logger.debug("ordering %d paragraphs, %d headings and %d drop-capitals",
len(para_ids), len(head_ids), len(drop_ids))
if self.model_based:
order_text = self.do_order_of_regions_with_model(
para_cont,
head_cont,
drop_cont,
region_labels)
else:
if img_filename and (
os.path.exists(img_path := img_filename) or
os.path.exists(img_path := os.path.join('..', img_filename)) or
dir_imgs and
os.path.exists(img_path := os.path.join(dir_imgs, img_filename)) or
dir_imgs and
os.path.exists(img_path := os.path.join(dir_imgs, os.path.basename(img_filename)))):
img_filename = img_path
else:
xml_basename = Path(xml_filename).with_suffix('')
def try_suffixes(basename, suffixes):
for suf in suffixes:
if (filename := basename.with_suffix(suf)).exists():
yield filename
elif dir_imgs and (filename := (dir_imgs / basename).with_suffix(suf)).exists():
yield filename
img_filename = next(try_suffixes(xml_basename,
['.tif', '.TIF',
'.jpg', '.JPG',
'.png', '.PNG',
'.jpeg', '.gif']))
# load and analyse image
image = self.cache_images(image_filename=img_filename)
_, num_col, _ = self.resize_and_enhance_image_with_column_classifier(image)
if image['img_res'].shape[:2] != region_labels.shape:
# image was resized by col-classifier
# so bring label map to same size
# (order rules have similar expectations)
region_labels = resize_image(region_labels, *image['img_res'].shape[:2])
scale_factor = np.array([[image['scale_x'], image['scale_y']]])
para_cont = [(cont * scale_factor).astype(int) for cont in para_cont]
head_cont = [(cont * scale_factor).astype(int) for cont in head_cont]
drop_cont = [(cont * scale_factor).astype(int) for cont in drop_cont]
# in Eynollah: regions_without_separators
nonsep_labels = np.copy(region_labels)
nonsep_labels[label_seps] = 0
nonsep_labels[label_imgs] = 0
# deskew
if np.abs(skew) >= 0.13: # in Eynollah: SLOPE_THRESHOLD
_, region_labels, nonsep_labels = self.get_deskewed_masks(
skew, np.zeros((1, 1)), region_labels, nonsep_labels)
# also deskew contours
# (directly instead of match_deskewed_contours)
# rotate_image() does not enlarge canvas,
# so our calculation must compensate
h_o, w_o = image['img_res'].shape[:2]
M = cv2.getRotationMatrix2D((0.5 * w_o, 0.5 * h_o), -skew, 1.0)[:2, :2]
cos = np.abs(M[0, 0])
sin = np.abs(M[0, 1])
off = np.array([[0.5 * (w_o * cos + h_o * sin - w_o),
0.5 * (w_o * sin + h_o * cos - h_o)]],
dtype=int)
if skew > 0:
off[0, 1] = -off[0, 1]
else:
off[0, 0] = -off[0, 0]
para_cont = [np.dot(cont, M).astype(int) - off for cont in para_cont]
head_cont = [np.dot(cont, M).astype(int) - off for cont in head_cont]
drop_cont = [np.dot(cont, M).astype(int) - off for cont in drop_cont]
order_text = self.do_order_of_regions_heuristic(
para_cont,
head_cont,
drop_cont,
region_labels,
nonsep_labels,
num_col,
False) # in Eynollah: erosion_hurts
all_text_ids = all_text_ids[order_text]
@ -243,7 +348,9 @@ class Reorder(Eynollah):
page.findall(link+'PrintSpace'))
page.insert(pos, ro_new)
tree_xml.write(os.path.join(dir_out or "", file_name + '.xml'),
output_filename = os.path.join(dir_out or "", file_name + '.xml')
self.logger.info("output filename: '%s'", output_filename)
tree_xml.write(output_filename,
xml_declaration=True,
method='xml',
encoding="utf-8",