789 lines
29 KiB
Python
789 lines
29 KiB
Python
from __future__ import division
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import os
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import sys
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import copy
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import types
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import logging
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import copy_reg
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import warnings
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import subprocess
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import numpy as np
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from .core import Table, Geometry
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from .image_processing import (adaptive_threshold, find_lines, find_table_contours,
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find_table_joints)
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from .utils import (scale_to_pdf, scale_to_image, segments_bbox, text_in_bbox,
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merge_close_values, get_table_index, get_score, count_empty,
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encode_list, get_text_objects, get_page_layout)
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__all__ = ['Stream', 'Lattice']
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logger = logging.getLogger('app_logger')
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def _reduce_method(m):
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if m.im_self is None:
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return getattr, (m.im_class, m.im_func.func_name)
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else:
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return getattr, (m.im_self, m.im_func.func_name)
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copy_reg.pickle(types.MethodType, _reduce_method)
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class Stream:
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"""Stream looks for spaces between text elements to form a table.
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If you want to give columns, ytol or mtol for each table
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when specifying multiple table areas, make sure that their length
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is equal to the length of table_area. Mapping between them is based
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on index.
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If you don't want to specify columns for the some tables in a pdf
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page having multiple tables, pass them as empty strings.
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For example: ['', 'x1,x2,x3,x4', '']
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Parameters
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----------
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table_area : list
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List of strings of the form x1,y1,x2,y2 where
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(x1, y1) -> left-top and (x2, y2) -> right-bottom in PDFMiner's
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coordinate space, denoting table areas to analyze.
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(optional, default: None)
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columns : list
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List of strings where each string is comma-separated values of
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x-coordinates in PDFMiner's coordinate space.
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(optional, default: None)
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ytol : list
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List of ints specifying the y-tolerance parameters.
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(optional, default: [2])
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mtol : list
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List of ints specifying the m-tolerance parameters.
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(optional, default: [0])
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margins : tuple
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PDFMiner margins. (char_margin, line_margin, word_margin)
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(optional, default: (1.0, 0.5, 0.1))
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split_text : bool
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Whether or not to split a text line if it spans across
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different cells.
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(optional, default: False)
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flag_size : bool
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Whether or not to highlight a substring using <s></s>
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if its size is different from rest of the string, useful for
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super and subscripts.
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(optional, default: True)
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debug : bool
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Set to True to generate a matplotlib plot of
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LTTextLineHorizontals in order to select table_area, columns.
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(optional, default: False)
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"""
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def __init__(self, table_area=None, columns=None, ytol=[2], mtol=[0],
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margins=(1.0, 0.5, 0.1), split_text=False, flag_size=True,
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debug=False):
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self.method = 'stream'
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self.table_area = table_area
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self.columns = columns
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self.ytol = ytol
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self.mtol = mtol
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self.char_margin, self.line_margin, self.word_margin = margins
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self.split_text = split_text
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self.flag_size = flag_size
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self.debug = debug
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@staticmethod
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def _text_bbox(t_bbox):
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"""Returns bounding box for the text present on a page.
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Parameters
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----------
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t_bbox : dict
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Dict with two keys 'horizontal' and 'vertical' with lists of
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LTTextLineHorizontals and LTTextLineVerticals respectively.
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Returns
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-------
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text_bbox : tuple
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Tuple of the form (x0, y0, x1, y1) in PDFMiner's coordinate
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space.
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"""
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xmin = min([t.x0 for direction in t_bbox for t in t_bbox[direction]])
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ymin = min([t.y0 for direction in t_bbox for t in t_bbox[direction]])
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xmax = max([t.x1 for direction in t_bbox for t in t_bbox[direction]])
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ymax = max([t.y1 for direction in t_bbox for t in t_bbox[direction]])
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text_bbox = (xmin, ymin, xmax, ymax)
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return text_bbox
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@staticmethod
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def _group_rows(text, ytol=2):
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"""Groups PDFMiner text objects into rows using their
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y-coordinates taking into account some tolerance ytol.
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Parameters
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----------
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text : list
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List of PDFMiner text objects.
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ytol : int
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Tolerance parameter.
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(optional, default: 2)
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Returns
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-------
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rows : list
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Two-dimensional list of text objects grouped into rows.
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"""
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row_y = 0
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rows = []
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temp = []
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for t in text:
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# is checking for upright necessary?
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# if t.get_text().strip() and all([obj.upright for obj in t._objs if
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# type(obj) is LTChar]):
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if t.get_text().strip():
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if not np.isclose(row_y, t.y0, atol=ytol):
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rows.append(sorted(temp, key=lambda t: t.x0))
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temp = []
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row_y = t.y0
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temp.append(t)
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rows.append(sorted(temp, key=lambda t: t.x0))
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__ = rows.pop(0) # hacky
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return rows
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@staticmethod
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def _merge_columns(l, mtol=0):
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"""Merges column boundaries if they overlap or lie within some
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tolerance mtol.
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Parameters
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----------
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l : list
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List of column coordinate tuples.
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mtol : int
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TODO
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(optional, default: 0)
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Returns
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-------
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merged : list
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List of merged column coordinate tuples.
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"""
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merged = []
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for higher in l:
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if not merged:
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merged.append(higher)
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else:
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lower = merged[-1]
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if mtol >= 0:
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if (higher[0] <= lower[1] or
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np.isclose(higher[0], lower[1], atol=mtol)):
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upper_bound = max(lower[1], higher[1])
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lower_bound = min(lower[0], higher[0])
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merged[-1] = (lower_bound, upper_bound)
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else:
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merged.append(higher)
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elif mtol < 0:
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if higher[0] <= lower[1]:
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if np.isclose(higher[0], lower[1], atol=abs(mtol)):
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merged.append(higher)
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else:
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upper_bound = max(lower[1], higher[1])
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lower_bound = min(lower[0], higher[0])
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merged[-1] = (lower_bound, upper_bound)
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else:
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merged.append(higher)
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return merged
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@staticmethod
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def _join_rows(rows_grouped, text_y_max, text_y_min):
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"""Makes row coordinates continuous.
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Parameters
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----------
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rows_grouped : list
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Two-dimensional list of text objects grouped into rows.
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text_y_max : int
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text_y_min : int
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Returns
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-------
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rows : list
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List of continuous row coordinate tuples.
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"""
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row_mids = [sum([(t.y0 + t.y1) / 2 for t in r]) / len(r)
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if len(r) > 0 else 0 for r in rows_grouped]
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rows = [(row_mids[i] + row_mids[i - 1]) / 2 for i in range(1, len(row_mids))]
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rows.insert(0, text_y_max)
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rows.append(text_y_min)
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rows = [(rows[i], rows[i + 1])
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for i in range(0, len(rows) - 1)]
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return rows
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@staticmethod
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def _add_columns(cols, text, ytol):
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"""Adds columns to existing list by taking into account
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the text that lies outside the current column coordinates.
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Parameters
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----------
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cols : list
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List of column coordinate tuples.
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text : list
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List of PDFMiner text objects.
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ytol : int
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Tolerance parameter.
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Returns
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-------
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cols : list
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Updated list of column coordinate tuples.
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"""
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if text:
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text = Stream._group_rows(text, ytol=ytol)
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elements = [len(r) for r in text]
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new_cols = [(t.x0, t.x1)
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for r in text if len(r) == max(elements) for t in r]
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cols.extend(Stream._merge_columns(sorted(new_cols)))
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return cols
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@staticmethod
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def _join_columns(cols, text_x_min, text_x_max):
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"""Makes column coordinates continuous.
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Parameters
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----------
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cols : list
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List of column coordinate tuples.
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text_x_min : int
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text_y_max : int
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Returns
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-------
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cols : list
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Updated list of column coordinate tuples.
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"""
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cols = sorted(cols)
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cols = [(cols[i][0] + cols[i - 1][1]) / 2 for i in range(1, len(cols))]
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cols.insert(0, text_x_min)
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cols.append(text_x_max)
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cols = [(cols[i], cols[i + 1])
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for i in range(0, len(cols) - 1)]
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return cols
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def extract_tables(self, pdfname):
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"""Expects a single page pdf as input with rotation corrected.
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Parameters
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---------
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pdfname : string
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Path to single page pdf file.
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Returns
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-------
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page : dict
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"""
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layout, dim = get_page_layout(pdfname, char_margin=self.char_margin,
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line_margin=self.line_margin, word_margin=self.word_margin)
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lttextlh = get_text_objects(layout, ltype="lh")
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lttextlv = get_text_objects(layout, ltype="lv")
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ltchar = get_text_objects(layout, ltype="char")
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width, height = dim
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bname, __ = os.path.splitext(pdfname)
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logger.info('Processing {0}.'.format(os.path.basename(bname)))
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if not lttextlh:
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warnings.warn("{0}: Page contains no text.".format(
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os.path.basename(bname)))
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return {os.path.basename(bname): None}
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g = Geometry()
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if self.debug:
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text = []
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text.extend([(t.x0, t.y0, t.x1, t.y1) for t in lttextlh])
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text.extend([(t.x0, t.y0, t.x1, t.y1) for t in lttextlv])
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g.text = text
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return [None], [g]
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if self.table_area is not None:
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if self.columns is not None:
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if len(self.table_area) != len(self.columns):
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raise ValueError("{0}: Length of table area and columns"
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" should be equal.".format(os.path.basename(bname)))
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table_bbox = {}
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for area in self.table_area:
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x1, y1, x2, y2 = area.split(",")
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x1 = float(x1)
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y1 = float(y1)
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x2 = float(x2)
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y2 = float(y2)
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table_bbox[(x1, y2, x2, y1)] = None
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else:
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table_bbox = {(0, 0, width, height): None}
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if len(self.ytol) == 1 and self.ytol[0] == 2:
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ytolerance = copy.deepcopy(self.ytol) * len(table_bbox)
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else:
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ytolerance = copy.deepcopy(self.ytol)
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if len(self.mtol) == 1 and self.mtol[0] == 0:
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mtolerance = copy.deepcopy(self.mtol) * len(table_bbox)
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else:
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mtolerance = copy.deepcopy(self.mtol)
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page = {}
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tables = {}
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# sort tables based on y-coord
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for table_no, k in enumerate(sorted(table_bbox.keys(), key=lambda x: x[1], reverse=True)):
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# select elements which lie within table_bbox
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table_data = {}
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t_bbox = {}
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t_bbox['horizontal'] = text_in_bbox(k, lttextlh)
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t_bbox['vertical'] = text_in_bbox(k, lttextlv)
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char_bbox = text_in_bbox(k, ltchar)
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table_data['text_p'] = 100 * (1 - (len(char_bbox) / len(ltchar)))
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for direction in t_bbox:
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t_bbox[direction].sort(key=lambda x: (-x.y0, x.x0))
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text_x_min, text_y_min, text_x_max, text_y_max = self._text_bbox(t_bbox)
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rows_grouped = self._group_rows(t_bbox['horizontal'], ytol=ytolerance[table_no])
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rows = self._join_rows(rows_grouped, text_y_max, text_y_min)
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elements = [len(r) for r in rows_grouped]
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guess = False
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if self.columns is not None and self.columns[table_no] != "":
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# user has to input boundary columns too
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# take (0, width) by default
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# similar to else condition
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# len can't be 1
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cols = self.columns[table_no].split(',')
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cols = [float(c) for c in cols]
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cols.insert(0, text_x_min)
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cols.append(text_x_max)
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cols = [(cols[i], cols[i + 1]) for i in range(0, len(cols) - 1)]
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else:
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guess = True
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ncols = max(set(elements), key=elements.count)
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len_non_mode = len(filter(lambda x: x != ncols, elements))
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if ncols == 1:
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# no tables detected
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warnings.warn("{0}: Page contains no tables.".format(
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os.path.basename(bname)))
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cols = [(t.x0, t.x1)
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for r in rows_grouped if len(r) == ncols for t in r]
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cols = self._merge_columns(sorted(cols), mtol=mtolerance[table_no])
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inner_text = []
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for i in range(1, len(cols)):
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left = cols[i - 1][1]
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right = cols[i][0]
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inner_text.extend([t for direction in t_bbox
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for t in t_bbox[direction]
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if t.x0 > left and t.x1 < right])
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outer_text = [t for direction in t_bbox
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for t in t_bbox[direction]
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if t.x0 > cols[-1][1] or t.x1 < cols[0][0]]
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inner_text.extend(outer_text)
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cols = self._add_columns(cols, inner_text, ytolerance[table_no])
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cols = self._join_columns(cols, text_x_min, text_x_max)
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table = Table(cols, rows)
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table = table.set_all_edges()
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assignment_errors = []
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table_data['split_text'] = []
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table_data['superscript'] = []
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for direction in t_bbox:
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for t in t_bbox[direction]:
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indices, error = get_table_index(
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table, t, direction, split_text=self.split_text,
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flag_size=self.flag_size)
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assignment_errors.append(error)
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if len(indices) > 1:
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table_data['split_text'].append(indices)
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for r_idx, c_idx, text in indices:
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if all(s in text for s in ['<s>', '</s>']):
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table_data['superscript'].append((r_idx, c_idx, text))
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table.cells[r_idx][c_idx].add_text(text)
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if guess:
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score = get_score([[66, assignment_errors], [34, [len_non_mode / len(elements)]]])
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else:
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score = get_score([[100, assignment_errors]])
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table_data['score'] = score
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ar = table.get_list()
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ar = encode_list(ar)
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table_data['data'] = ar
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empty_p, r_nempty_cells, c_nempty_cells = count_empty(ar)
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table_data['empty_p'] = empty_p
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table_data['r_nempty_cells'] = r_nempty_cells
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table_data['c_nempty_cells'] = c_nempty_cells
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table_data['nrows'] = len(ar)
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table_data['ncols'] = len(ar[0])
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tables['table-{0}'.format(table_no + 1)] = table_data
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page[os.path.basename(bname)] = tables
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return page
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class Lattice:
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"""Lattice looks for lines in the pdf to form a table.
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|
|
If you want to give fill and mtol for each table when specifying
|
|
multiple table areas, make sure that the length of fill and mtol
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|
is equal to the length of table_area. Mapping between them is based
|
|
on index.
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|
|
|
Parameters
|
|
----------
|
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table_area : list
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List of strings of the form x1,y1,x2,y2 where
|
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(x1, y1) -> left-top and (x2, y2) -> right-bottom in PDFMiner's
|
|
coordinate space, denoting table areas to analyze.
|
|
(optional, default: None)
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|
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fill : list
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List of strings specifying directions to fill spanning cells.
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{'h', 'v'} to fill spanning cells in horizontal or vertical
|
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direction.
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(optional, default: None)
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|
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mtol : list
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List of ints specifying m-tolerance parameters.
|
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(optional, default: [2])
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|
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jtol : list
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List of ints specifying j-tolerance parameters.
|
|
(optional, default: [2])
|
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|
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blocksize : int
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|
Size of a pixel neighborhood that is used to calculate a
|
|
threshold value for the pixel: 3, 5, 7, and so on.
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(optional, default: 15)
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|
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threshold_constant : float
|
|
Constant subtracted from the mean or weighted mean
|
|
(see the details below). Normally, it is positive but may be
|
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zero or negative as well.
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(optional, default: -2)
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|
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scale : int
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|
Used to divide the height/width of a pdf to get a structuring
|
|
element for image processing.
|
|
(optional, default: 15)
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|
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iterations : int
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Number of iterations for dilation.
|
|
(optional, default: 0)
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|
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invert : bool
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|
Whether or not to invert the image. Useful when pdfs have
|
|
tables with lines in background.
|
|
(optional, default: False)
|
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|
|
margins : tuple
|
|
PDFMiner margins. (char_margin, line_margin, word_margin)
|
|
(optional, default: (1.0, 0.5, 0.1))
|
|
|
|
split_text : bool
|
|
Whether or not to split a text line if it spans across
|
|
different cells.
|
|
(optional, default: False)
|
|
|
|
flag_size : bool
|
|
Whether or not to highlight a substring using <s></s>
|
|
if its size is different from rest of the string, useful for
|
|
super and subscripts.
|
|
(optional, default: True)
|
|
|
|
shift_text : list
|
|
{'l', 'r', 't', 'b'}
|
|
Select one or more from above and pass them as a list to
|
|
specify where the text in a spanning cell should flow.
|
|
(optional, default: ['l', 't'])
|
|
|
|
debug : string
|
|
{'contour', 'line', 'joint', 'table'}
|
|
Set to one of the above values to generate a matplotlib plot
|
|
of detected contours, lines, joints and the table generated.
|
|
(optional, default: None)
|
|
"""
|
|
def __init__(self, table_area=None, fill=None, mtol=[2], jtol=[2],
|
|
blocksize=15, threshold_constant=-2, scale=15, iterations=0,
|
|
invert=False, margins=(1.0, 0.5, 0.1), split_text=False,
|
|
flag_size=True, shift_text=['l', 't'], debug=None):
|
|
|
|
self.method = 'lattice'
|
|
self.table_area = table_area
|
|
self.fill = fill
|
|
self.mtol = mtol
|
|
self.jtol = jtol
|
|
self.blocksize = blocksize
|
|
self.threshold_constant = threshold_constant
|
|
self.scale = scale
|
|
self.iterations = iterations
|
|
self.invert = invert
|
|
self.char_margin, self.line_margin, self.word_margin = margins
|
|
self.split_text = split_text
|
|
self.flag_size = flag_size
|
|
self.shift_text = shift_text
|
|
self.debug = debug
|
|
|
|
@staticmethod
|
|
def _reduce_index(t, idx, shift_text):
|
|
"""Reduces index of a text object if it lies within a spanning
|
|
cell.
|
|
|
|
Parameters
|
|
----------
|
|
table : object
|
|
camelot.table.Table
|
|
|
|
idx : list
|
|
List of tuples of the form (r_idx, c_idx, text).
|
|
|
|
shift_text : list
|
|
{'l', 'r', 't', 'b'}
|
|
Select one or more from above and pass them as a list to
|
|
specify where the text in a spanning cell should flow.
|
|
|
|
Returns
|
|
-------
|
|
indices : list
|
|
List of tuples of the form (idx, text) where idx is the reduced
|
|
index of row/column and text is the an lttextline substring.
|
|
"""
|
|
indices = []
|
|
for r_idx, c_idx, text in idx:
|
|
for d in shift_text:
|
|
if d == 'l':
|
|
if t.cells[r_idx][c_idx].spanning_h:
|
|
while not t.cells[r_idx][c_idx].left:
|
|
c_idx -= 1
|
|
if d == 'r':
|
|
if t.cells[r_idx][c_idx].spanning_h:
|
|
while not t.cells[r_idx][c_idx].right:
|
|
c_idx += 1
|
|
if d == 't':
|
|
if t.cells[r_idx][c_idx].spanning_v:
|
|
while not t.cells[r_idx][c_idx].top:
|
|
r_idx -= 1
|
|
if d == 'b':
|
|
if t.cells[r_idx][c_idx].spanning_v:
|
|
while not t.cells[r_idx][c_idx].bottom:
|
|
r_idx += 1
|
|
indices.append((r_idx, c_idx, text))
|
|
return indices
|
|
|
|
|
|
def _fill_spanning(t, fill=None):
|
|
"""Fills spanning cells.
|
|
|
|
Parameters
|
|
----------
|
|
t : object
|
|
camelot.table.Table
|
|
|
|
fill : list
|
|
{'h', 'v'}
|
|
Specify to fill spanning cells in horizontal or vertical
|
|
direction.
|
|
(optional, default: None)
|
|
|
|
Returns
|
|
-------
|
|
t : object
|
|
camelot.table.Table
|
|
"""
|
|
for f in fill:
|
|
if f == "h":
|
|
for i in range(len(t.cells)):
|
|
for j in range(len(t.cells[i])):
|
|
if t.cells[i][j].get_text().strip() == '':
|
|
if t.cells[i][j].spanning_h and not t.cells[i][j].left:
|
|
t.cells[i][j].add_text(t.cells[i][j - 1].get_text())
|
|
elif f == "v":
|
|
for i in range(len(t.cells)):
|
|
for j in range(len(t.cells[i])):
|
|
if t.cells[i][j].get_text().strip() == '':
|
|
if t.cells[i][j].spanning_v and not t.cells[i][j].top:
|
|
t.cells[i][j].add_text(t.cells[i - 1][j].get_text())
|
|
return t
|
|
|
|
def extract_tables(self, pdfname):
|
|
"""Expects a single page pdf as input with rotation corrected.
|
|
|
|
Parameters
|
|
----------
|
|
pdfname : string
|
|
Path to single page pdf file.
|
|
|
|
Returns
|
|
-------
|
|
page : dict
|
|
"""
|
|
layout, dim = get_page_layout(pdfname, char_margin=self.char_margin,
|
|
line_margin=self.line_margin, word_margin=self.word_margin)
|
|
lttextlh = get_text_objects(layout, ltype="lh")
|
|
lttextlv = get_text_objects(layout, ltype="lv")
|
|
ltchar = get_text_objects(layout, ltype="char")
|
|
width, height = dim
|
|
bname, __ = os.path.splitext(pdfname)
|
|
logger.info('Processing {0}.'.format(os.path.basename(bname)))
|
|
if not ltchar:
|
|
warnings.warn("{0}: Page contains no text.".format(
|
|
os.path.basename(bname)))
|
|
return {os.path.basename(bname): None}
|
|
|
|
imagename = ''.join([bname, '.png'])
|
|
gs_call = [
|
|
"-q", "-sDEVICE=png16m", "-o", imagename, "-r600", pdfname
|
|
]
|
|
if "ghostscript" in subprocess.check_output(["gs", "-version"]).lower():
|
|
gs_call.insert(0, "gs")
|
|
else:
|
|
gs_call.insert(0, "gsc")
|
|
subprocess.call(gs_call, stdout=open(os.devnull, 'w'),
|
|
stderr=subprocess.STDOUT)
|
|
|
|
img, threshold = adaptive_threshold(imagename, invert=self.invert,
|
|
blocksize=self.blocksize, c=self.threshold_constant)
|
|
pdf_x = width
|
|
pdf_y = height
|
|
img_x = img.shape[1]
|
|
img_y = img.shape[0]
|
|
sc_x_image = img_x / float(pdf_x)
|
|
sc_y_image = img_y / float(pdf_y)
|
|
sc_x_pdf = pdf_x / float(img_x)
|
|
sc_y_pdf = pdf_y / float(img_y)
|
|
factors_image = (sc_x_image, sc_y_image, pdf_y)
|
|
factors_pdf = (sc_x_pdf, sc_y_pdf, img_y)
|
|
|
|
vmask, v_segments = find_lines(threshold, direction='vertical',
|
|
scale=self.scale, iterations=self.iterations)
|
|
hmask, h_segments = find_lines(threshold, direction='horizontal',
|
|
scale=self.scale, iterations=self.iterations)
|
|
|
|
if self.table_area is not None:
|
|
areas = []
|
|
for area in self.table_area:
|
|
x1, y1, x2, y2 = area.split(",")
|
|
x1 = float(x1)
|
|
y1 = float(y1)
|
|
x2 = float(x2)
|
|
y2 = float(y2)
|
|
x1, y1, x2, y2 = scale_to_image((x1, y1, x2, y2), factors_image)
|
|
areas.append((x1, y1, abs(x2 - x1), abs(y2 - y1)))
|
|
table_bbox = find_table_joints(areas, vmask, hmask)
|
|
else:
|
|
contours = find_table_contours(vmask, hmask)
|
|
table_bbox = find_table_joints(contours, vmask, hmask)
|
|
|
|
if len(self.mtol) == 1 and self.mtol[0] == 2:
|
|
mtolerance = copy.deepcopy(self.mtol) * len(table_bbox)
|
|
else:
|
|
mtolerance = copy.deepcopy(self.mtol)
|
|
|
|
if len(self.jtol) == 1 and self.jtol[0] == 2:
|
|
jtolerance = copy.deepcopy(self.jtol) * len(table_bbox)
|
|
else:
|
|
jtolerance = copy.deepcopy(self.jtol)
|
|
|
|
g = Geometry()
|
|
if self.debug:
|
|
g.images = [(img, table_bbox)]
|
|
|
|
table_bbox, v_segments, h_segments = scale_to_pdf(table_bbox, v_segments,
|
|
h_segments, factors_pdf)
|
|
|
|
if self.debug:
|
|
g.segments = [(v_segments, h_segments)]
|
|
_tables = []
|
|
|
|
page = {}
|
|
tables = {}
|
|
# sort tables based on y-coord
|
|
for table_no, k in enumerate(sorted(table_bbox.keys(), key=lambda x: x[1], reverse=True)):
|
|
# select elements which lie within table_bbox
|
|
table_data = {}
|
|
t_bbox = {}
|
|
v_s, h_s = segments_bbox(k, v_segments, h_segments)
|
|
t_bbox['horizontal'] = text_in_bbox(k, lttextlh)
|
|
t_bbox['vertical'] = text_in_bbox(k, lttextlv)
|
|
char_bbox = text_in_bbox(k, ltchar)
|
|
table_data['text_p'] = 100 * (1 - (len(char_bbox) / len(ltchar)))
|
|
for direction in t_bbox:
|
|
t_bbox[direction].sort(key=lambda x: (-x.y0, x.x0))
|
|
cols, rows = zip(*table_bbox[k])
|
|
cols, rows = list(cols), list(rows)
|
|
cols.extend([k[0], k[2]])
|
|
rows.extend([k[1], k[3]])
|
|
# sort horizontal and vertical segments
|
|
cols = merge_close_values(sorted(cols), mtol=mtolerance[table_no])
|
|
rows = merge_close_values(
|
|
sorted(rows, reverse=True), mtol=mtolerance[table_no])
|
|
# make grid using x and y coord of shortlisted rows and cols
|
|
cols = [(cols[i], cols[i + 1])
|
|
for i in range(0, len(cols) - 1)]
|
|
rows = [(rows[i], rows[i + 1])
|
|
for i in range(0, len(rows) - 1)]
|
|
|
|
table = Table(cols, rows)
|
|
# set table edges to True using ver+hor lines
|
|
table = table.set_edges(v_s, h_s, jtol=jtolerance[table_no])
|
|
# set spanning cells to True
|
|
table = table.set_spanning()
|
|
# set table border edges to True
|
|
table = table.set_border_edges()
|
|
|
|
if self.debug:
|
|
_tables.append(table)
|
|
|
|
assignment_errors = []
|
|
table_data['split_text'] = []
|
|
table_data['superscript'] = []
|
|
for direction in ['vertical', 'horizontal']:
|
|
for t in t_bbox[direction]:
|
|
indices, error = get_table_index(
|
|
table, t, direction, split_text=self.split_text,
|
|
flag_size=self.flag_size)
|
|
if indices[:2] != (-1, -1):
|
|
assignment_errors.append(error)
|
|
indices = self._reduce_index(table, indices, shift_text=self.shift_text)
|
|
if len(indices) > 1:
|
|
table_data['split_text'].append(indices)
|
|
for r_idx, c_idx, text in indices:
|
|
if all(s in text for s in ['<s>', '</s>']):
|
|
table_data['superscript'].append((r_idx, c_idx, text))
|
|
table.cells[r_idx][c_idx].add_text(text)
|
|
score = get_score([[100, assignment_errors]])
|
|
table_data['score'] = score
|
|
|
|
if self.fill is not None:
|
|
table = self._fill_spanning(table, fill=self.fill)
|
|
ar = table.get_list()
|
|
ar = encode_list(ar)
|
|
table_data['data'] = ar
|
|
empty_p, r_nempty_cells, c_nempty_cells = count_empty(ar)
|
|
table_data['empty_p'] = empty_p
|
|
table_data['r_nempty_cells'] = r_nempty_cells
|
|
table_data['c_nempty_cells'] = c_nempty_cells
|
|
table_data['nrows'] = len(ar)
|
|
table_data['ncols'] = len(ar[0])
|
|
tables['table-{0}'.format(table_no + 1)] = table_data
|
|
page[os.path.basename(bname)] = tables
|
|
|
|
if self.debug:
|
|
g.tables = _tables
|
|
return [None], [g]
|
|
|
|
return page |