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98 changes: 90 additions & 8 deletions unstructured/partition/pdf_image/pdfminer_processing.py
Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,7 @@
from typing import TYPE_CHECKING, Any, BinaryIO, Iterable, List, Optional, Union, cast

import numpy as np
from numba import njit
from pdfminer.layout import LTChar, LTContainer, LTTextBox
from pdfminer.pdftypes import PDFObjRef
from pdfminer.utils import open_filename
Expand Down Expand Up @@ -599,14 +600,8 @@ def bboxes1_is_almost_subregion_of_bboxes2(
bboxes2"""
coords1 = get_coords_from_bboxes(bboxes1, round_to=round_to)
coords2 = get_coords_from_bboxes(bboxes2, round_to=round_to)

inter_area, boxa_area, boxb_area = areas_of_boxes_and_intersection_area(
coords1, coords2, round_to=round_to
)

return (inter_area / np.maximum(boxa_area, EPSILON_AREA) > threshold) & (
boxa_area <= boxb_area.T
)
# for maximum speed use the numba JIT version
return _bboxes1_is_almost_subregion_of_bboxes2_numba(coords1, coords2, threshold)


def boxes_self_iou(bboxes, threshold: float = 0.5, round_to: int = DEFAULT_ROUND) -> np.ndarray:
Expand Down Expand Up @@ -1136,3 +1131,90 @@ def try_argmin(array: np.ndarray) -> int:
return int(np.argmin(array))
except IndexError:
return -1


@njit(cache=True, fastmath=True)
def _get_coords_from_bboxes_numba(bboxes, round_to: int):
"""
Numba-accelerated version of get_coords_from_bboxes supporting only np.ndarray input
or a sequence of objects which have .x1, .y1, .x2, .y2
Only float fields supported due to numba's type constraints.
"""
if isinstance(bboxes, np.ndarray):
arr = np.empty_like(bboxes)
# Use numpy-based rounding for the same behavior
arr[:] = np.round(bboxes, round_to)
return arr

n = len(bboxes)
coords = np.zeros((n, 4), dtype=np.float64)

for i in range(n):
bbox = bboxes[i]
coords[i, 0] = bbox.x1
coords[i, 1] = bbox.y1
coords[i, 2] = bbox.x2
coords[i, 3] = bbox.y2

for r in range(coords.shape[0]):
for c in range(coords.shape[1]):
# mimic np.round to requested decimals
power = 10.0**round_to
coords[r, c] = np.round(coords[r, c] * power) / power

return coords


@njit(cache=True, fastmath=True)
def _areas_of_boxes_and_intersection_area_numba(
coords1: np.ndarray, coords2: np.ndarray, round_to: int = DEFAULT_ROUND
):
n1 = coords1.shape[0]
n2 = coords2.shape[0]
inter_area = np.zeros((n1, n2), dtype=np.float64)
boxa_area = np.zeros((n1, 1), dtype=np.float64)
boxb_area = np.zeros((n2, 1), dtype=np.float64)

for a in range(n1):
x11 = coords1[a, 0]
y11 = coords1[a, 1]
x12 = coords1[a, 2]
y12 = coords1[a, 3]
boxa_area[a, 0] = np.round((x12 - x11 + 1) * (y12 - y11 + 1), round_to)

for b in range(n2):
x21 = coords2[b, 0]
y21 = coords2[b, 1]
x22 = coords2[b, 2]
y22 = coords2[b, 3]
boxb_area[b, 0] = np.round((x22 - x21 + 1) * (y22 - y21 + 1), round_to)

ixmin = max(x11, x21)
iymin = max(y11, y21)
ixmax = min(x12, x22)
iymax = min(y12, y22)
iw = max(ixmax - ixmin + 1, 0.0)
ih = max(iymax - iymin + 1, 0.0)
inter = iw * ih
inter_area[a, b] = np.round(inter, round_to)

return inter_area, boxa_area, boxb_area


@njit(cache=True, fastmath=True)
def _bboxes1_is_almost_subregion_of_bboxes2_numba(coords1, coords2, threshold: float) -> np.ndarray:
# Use DEFAULT_ROUND as the default for rounding
inter_area, boxa_area, boxb_area = _areas_of_boxes_and_intersection_area_numba(
coords1, coords2, DEFAULT_ROUND
)
n1, n2 = inter_area.shape
out = np.zeros((n1, n2), dtype=np.bool_)
for i in range(n1):
for j in range(n2):
# preserve computation method
if boxa_area[i, 0] > boxb_area[j, 0]:
continue
val = inter_area[i, j] / max(boxa_area[i, 0], EPSILON_AREA)
if val > threshold:
out[i, j] = True
return out