Datasets:
File size: 2,499 Bytes
326f5f7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 | import unicodedata
from typing import Dict, List, Tuple, Optional
def norm(text: str) -> str:
"""Text normalization: lowercase + remove whitespace/punctuation + keep alphanumerics only."""
if not text:
return ""
text = unicodedata.normalize('NFKC', text)
text = text.lower()
text = ''.join(c for c in text if c.isalnum())
return text
def poly_to_bbox(poly: List[List[float]]) -> Tuple[float, float, float, float]:
"""Convert polygon to bbox."""
xs = [p[0] for p in poly]
ys = [p[1] for p in poly]
return (min(xs), min(ys), max(xs), max(ys))
def bbox_iou(box1: Tuple, box2: Tuple) -> float:
"""Compute IoU."""
x1_1, y1_1, x2_1, y2_1 = box1
x1_2, y1_2, x2_2, y2_2 = box2
xi1, yi1 = max(x1_1, x1_2), max(y1_1, y1_2)
xi2, yi2 = min(x2_1, x2_2), min(y2_1, y2_2)
inter = max(0, xi2 - xi1) * max(0, yi2 - yi1)
union = (x2_1 - x1_1) * (y2_1 - y1_1) + (x2_2 - x1_2) * (y2_2 - y1_2) - inter
return inter / union if union > 0 else 0.0
def point_in_bbox(point: Tuple[float, float], bbox: Tuple) -> bool:
"""Check whether a point is inside a bbox."""
x, y = point
x1, y1, x2, y2 = bbox
return x1 <= x <= x2 and y1 <= y <= y2
def bbox_center(bbox: Tuple) -> Tuple[float, float]:
"""Return the bbox center point."""
x1, y1, x2, y2 = bbox
return ((x1 + x2) / 2, (y1 + y2) / 2)
def union_bboxes(bboxes: List[Tuple]) -> Tuple:
"""Merge multiple bboxes."""
if not bboxes:
return (0, 0, 0, 0)
x1 = min(b[0] for b in bboxes)
y1 = min(b[1] for b in bboxes)
x2 = max(b[2] for b in bboxes)
y2 = max(b[3] for b in bboxes)
return (x1, y1, x2, y2)
def group_into_lines(items: List[Dict], y_threshold: float = 10.0) -> List[List[Dict]]:
"""Cluster OCR items into lines by y-axis distance."""
if not items:
return []
sorted_items = sorted(items, key=lambda it: (it['bbox'][1] + it['bbox'][3]) / 2)
lines = []
current_line = [sorted_items[0]]
for item in sorted_items[1:]:
y_cur = (item['bbox'][1] + item['bbox'][3]) / 2
y_prev = (current_line[-1]['bbox'][1] + current_line[-1]['bbox'][3]) / 2
if abs(y_cur - y_prev) < y_threshold:
current_line.append(item)
else:
lines.append(current_line)
current_line = [item]
lines.append(current_line)
# Sort each line by x coordinate
for line in lines:
line.sort(key=lambda it: it['bbox'][0])
return lines |