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Download evaluation_kit/box_grouping/models.py from RLALT/ACoPDoc: direct link, hf CLI and curl.
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https://huggingface.co/datasets/RLALT/ACoPDoc/resolve/main/evaluation_kit/box_grouping/models.py
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hf download hf://datasets/RLALT/ACoPDoc/evaluation_kit/box_grouping/models.py
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curl -L -o models.py https://huggingface.co/datasets/RLALT/ACoPDoc/resolve/main/evaluation_kit/box_grouping/models.py
8.44 kB
| from __future__ import annotations | |
| from dataclasses import dataclass | |
| from typing import Any | |
| from geometry import ( | |
| Box, | |
| polygon_area, | |
| polygon_intersection, | |
| point_in_convex_polygon, | |
| ) | |
| REDUNDANT_BOX_MIN_OVERLAP_RATIO = 0.95 | |
| IMAGE_RELATED_LABELS = frozenset( | |
| { | |
| "Photo", | |
| "Graphics", | |
| "SealFigure", | |
| "FrontPicture", | |
| } | |
| ) | |
| HEADER_TITLE_LIKE_LABELS = frozenset( | |
| { | |
| "Headline", | |
| "Kicker", | |
| "Banner", | |
| "Deck", | |
| "Subhead", | |
| "Nameplate", | |
| "Masthead", | |
| "FrontStory", | |
| } | |
| ) | |
| IMAGE_HEADER_FILTER_LABELS = IMAGE_RELATED_LABELS | HEADER_TITLE_LIKE_LABELS | |
| def _normalize_whitespace(text: str) -> str: | |
| """Local helper to avoid circular import with spatial.py.""" | |
| return " ".join(text.split()) | |
| class Word: | |
| box: Box | |
| text: str | |
| def center(self) -> tuple[float, float]: | |
| return ( | |
| (self.box.x_min + self.box.x_max) / 2.0, | |
| (self.box.y_min + self.box.y_max) / 2.0, | |
| ) | |
| class AnnotationBox: | |
| box_id: str | |
| rect: Box | |
| text: str | |
| has_transcription: bool | |
| rotation: float | |
| polygon: tuple[tuple[float, float], ...] | |
| bounds: Box | |
| labels: tuple[str, ...] = () | |
| letter_count: int = 0 | |
| latin_or_cyrillic_letter_count: int = 0 | |
| non_armenian_letter_ratio: float = 0.0 | |
| excluded_as_non_armenian_text: bool = False | |
| parent_box_id: str | None = None | |
| reading_order: int | None = None | |
| def contains_point(self, x: float, y: float) -> bool: | |
| if not self.bounds.contains_point(x, y): | |
| return False | |
| return point_in_convex_polygon((x, y), self.polygon) | |
| def overlap_area_with_box(self, box: Box) -> float: | |
| if self.bounds.intersection(box) is None: | |
| return 0.0 | |
| return polygon_area(polygon_intersection(box.to_polygon(), self.polygon)) | |
| class PredictedRow: | |
| row_id: str | |
| words: list[Word] | |
| def text(self) -> str: | |
| return " ".join(word.text for word in self.words if word.text.strip()) | |
| def annotation_box_contains_annotation_box(container: AnnotationBox, inner: AnnotationBox) -> bool: | |
| if container.box_id == inner.box_id: | |
| return False | |
| if polygon_area(container.polygon) <= polygon_area(inner.polygon): | |
| return False | |
| if ( | |
| inner.bounds.x_min < container.bounds.x_min - 1e-6 | |
| or inner.bounds.y_min < container.bounds.y_min - 1e-6 | |
| or inner.bounds.x_max > container.bounds.x_max + 1e-6 | |
| or inner.bounds.y_max > container.bounds.y_max + 1e-6 | |
| ): | |
| return False | |
| return all(container.contains_point(point[0], point[1]) for point in inner.polygon) | |
| def annotation_box_overlap_ratio(container: AnnotationBox, inner: AnnotationBox) -> float: | |
| inner_area = polygon_area(inner.polygon) | |
| if inner_area <= 0: | |
| return 0.0 | |
| overlap_area = polygon_area(polygon_intersection(inner.polygon, container.polygon)) | |
| return overlap_area / inner_area | |
| def annotation_boxes_have_compatible_text(container: AnnotationBox, inner: AnnotationBox) -> bool: | |
| container_text = _normalize_whitespace(container.text) | |
| inner_text = _normalize_whitespace(inner.text) | |
| if not container_text or not inner_text: | |
| return False | |
| return ( | |
| container_text == inner_text | |
| or inner_text in container_text | |
| or container_text in inner_text | |
| ) | |
| def decomposable_container_box_ids(boxes: list[AnnotationBox]) -> frozenset[str]: | |
| """Return box_ids of containers whose text is exactly reproduced by | |
| concatenating (in reading order) two or more boxes it contains. | |
| Some annotations squeeze multiple side-by-side columns (e.g. a folioline | |
| with page number / title / date, or a paragraph split across two print | |
| columns) into one wide box, encoding the correct reading order only in | |
| the transcription's word order. When that box also has separately | |
| annotated children covering the same content, evaluating against the | |
| children directly sidesteps having to guess the column layout from | |
| geometry alone. | |
| """ | |
| textful = [b for b in boxes if b.has_transcription and b.text.strip()] | |
| # `parent_id` is overloaded in this dataset: for text fragments of a | |
| # squeezed container it means "part of this box's text", but the same | |
| # field also links unrelated story components (headline, caption, ...) | |
| # to a page anchor box, so it can't be trusted as a children set on its | |
| # own — it must independently reconstruct the container's text, same as | |
| # the geometric candidates below. | |
| children_by_declared_parent: dict[str, list[AnnotationBox]] = {} | |
| for b in textful: | |
| if b.parent_box_id: | |
| children_by_declared_parent.setdefault(b.parent_box_id, []).append(b) | |
| def reconstructs(children: list[AnnotationBox], container_text: str) -> bool: | |
| if len(children) < 2: | |
| return False | |
| order_keys = [ | |
| lambda b: (b.rect.y_min, b.rect.x_min), | |
| lambda b: (b.rect.x_min, b.rect.y_min), | |
| ] | |
| if all(b.reading_order is not None for b in children): | |
| order_keys.insert(0, lambda b: b.reading_order) | |
| for order_key in order_keys: | |
| ordered = sorted(children, key=order_key) | |
| reconstructed = _normalize_whitespace(" ".join(b.text for b in ordered)) | |
| if reconstructed == container_text: | |
| return True | |
| return False | |
| decomposable: set[str] = set() | |
| for container in textful: | |
| container_text = _normalize_whitespace(container.text) | |
| if len(container_text) < 10: | |
| continue | |
| # Geometric containment catches most cases, but a fraction-of-a-degree | |
| # rotation mismatch between an annotated box and its (visually | |
| # identical) parent can make a rotated-polygon corner fall a hair | |
| # outside the parent, failing strict containment. `parent_id` is | |
| # immune to that, so it's tried as an independent candidate set | |
| # rather than merged with the geometric one (merging would pull in | |
| # unrelated same-parent siblings and break the exact-text check). | |
| declared_children = children_by_declared_parent.get(container.box_id, []) | |
| geometric_children = [ | |
| b | |
| for b in textful | |
| if b.box_id != container.box_id | |
| and annotation_box_contains_annotation_box(container, b) | |
| ] | |
| if reconstructs(declared_children, container_text) or reconstructs( | |
| geometric_children, container_text | |
| ): | |
| decomposable.add(container.box_id) | |
| return frozenset(decomposable) | |
| def filter_redundant_annotation_boxes(boxes: list[AnnotationBox]) -> list[AnnotationBox]: | |
| filtered_boxes: list[AnnotationBox] = [] | |
| for candidate in boxes: | |
| is_redundant = False | |
| for other in boxes: | |
| if other.box_id == candidate.box_id: | |
| continue | |
| if polygon_area(other.polygon) <= polygon_area(candidate.polygon): | |
| continue | |
| if not annotation_boxes_have_compatible_text(other, candidate): | |
| continue | |
| if annotation_box_contains_annotation_box(other, candidate): | |
| is_redundant = True | |
| break | |
| if annotation_box_overlap_ratio(other, candidate) >= REDUNDANT_BOX_MIN_OVERLAP_RATIO: | |
| is_redundant = True | |
| break | |
| if not is_redundant: | |
| filtered_boxes.append(candidate) | |
| return filtered_boxes | |
| def annotation_box_type(annotation_box: AnnotationBox) -> str | None: | |
| return annotation_box.labels[0] if annotation_box.labels else None | |
| def annotation_box_metadata(annotation_box: AnnotationBox) -> dict[str, Any]: | |
| return { | |
| "box_id": annotation_box.box_id, | |
| "box_type": annotation_box_type(annotation_box), | |
| "labels": list(annotation_box.labels), | |
| } | |
| def gt_box_report(annotation_box: AnnotationBox) -> dict[str, Any]: | |
| # Inline rounded_box to avoid circular import with spatial.py | |
| rounded = [round(v, 3) for v in [ | |
| annotation_box.bounds.x_min, | |
| annotation_box.bounds.y_min, | |
| annotation_box.bounds.x_max, | |
| annotation_box.bounds.y_max, | |
| ]] | |
| return { | |
| **annotation_box_metadata(annotation_box), | |
| "box": rounded, | |
| } | |