para_split.py 20 KB

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  1. from sklearn.cluster import DBSCAN
  2. import numpy as np
  3. from loguru import logger
  4. from magic_pdf.libs.boxbase import _is_in_or_part_overlap
  5. from magic_pdf.libs.ocr_content_type import ContentType
  6. LINE_STOP_FLAG = ['.', '!', '?', '。', '!', '?',":", ":", ")", ")", ";"]
  7. INLINE_EQUATION = ContentType.InlineEquation
  8. INTERLINE_EQUATION = ContentType.InterlineEquation
  9. TEXT = "text"
  10. def __get_span_text(span):
  11. c = span.get('content', '')
  12. if len(c)==0:
  13. c = span.get('image_path', '')
  14. return c
  15. def __add_line_period(blocks, layout_bboxes):
  16. """
  17. 为每行添加句号
  18. 如果这个行
  19. 1. 以行内公式结尾,但没有任何标点符号,此时加个句号,认为他就是段落结尾。
  20. """
  21. for block in blocks:
  22. for line in block['lines']:
  23. last_span = line['spans'][-1]
  24. span_type = last_span['type']
  25. if span_type in [INLINE_EQUATION]:
  26. span_content = last_span['content'].strip()
  27. if span_type==INLINE_EQUATION and span_content[-1] not in LINE_STOP_FLAG:
  28. if span_type in [INLINE_EQUATION, INTERLINE_EQUATION]:
  29. last_span['content'] = span_content + '.'
  30. def __detect_line_align_direction(line, new_layout_bboxes):
  31. """
  32. 探测line是左对齐,还是右对齐,还是居中。
  33. """
  34. lbox = line['bbox']
  35. x0, x1 = lbox[0], lbox[2]
  36. layout_x0, layout_x1 = new_layout_bboxes[0], new_layout_bboxes[2]
  37. if x0 <= layout_x0 and x1 < layout_x1:
  38. return "left"
  39. elif x0 > layout_x0 and x1 >= layout_x1:
  40. return "right"
  41. else:
  42. return "center"
  43. def __detect_line_group_align_direction(lines, new_layout_bboxes):
  44. """
  45. 首先把lines按照行距离分成几部分。针对每一部分分别探测。
  46. 最后返回[(dir, lines), (dir, lines), ...]
  47. """
  48. pass
  49. def __detect_list_lines(lines, new_layout_bboxes, lang='en'):
  50. """
  51. 探测是否包含了列表,并且把列表的行分开.
  52. 这样的段落特点是,顶格字母大写/数字,紧跟着几行缩进的。缩进的行首字母含小写的。
  53. """
  54. def find_repeating_patterns(lst):
  55. indices = []
  56. ones_indices = []
  57. i = 0
  58. while i < len(lst) - 1: # 确保余下元素至少有2个
  59. if lst[i] == 1 and lst[i+1] in [2, 3]: # 额外检查以防止连续出现的1
  60. start = i
  61. ones_in_this_interval = [i]
  62. i += 1
  63. while i < len(lst) and lst[i] in [2, 3]:
  64. i += 1
  65. # 验证下一个序列是否符合条件
  66. if i < len(lst) - 1 and lst[i] == 1 and lst[i+1] in [2, 3] and lst[i-1] in [2, 3]:
  67. while i < len(lst) and lst[i] in [1, 2, 3]:
  68. if lst[i] == 1:
  69. ones_in_this_interval.append(i)
  70. i += 1
  71. indices.append((start, i - 1))
  72. ones_indices.append(ones_in_this_interval)
  73. else:
  74. i += 1
  75. else:
  76. i += 1
  77. return indices, ones_indices
  78. """===================="""
  79. def split_indices(slen, index_array):
  80. result = []
  81. last_end = 0
  82. for start, end in sorted(index_array):
  83. if start > last_end:
  84. # 前一个区间结束到下一个区间开始之间的部分标记为"text"
  85. result.append(('text', last_end, start - 1))
  86. # 区间内标记为"list"
  87. result.append(('list', start, end))
  88. last_end = end + 1
  89. if last_end < slen:
  90. # 如果最后一个区间结束后还有剩余的字符串,将其标记为"text"
  91. result.append(('text', last_end, slen - 1))
  92. return result
  93. """===================="""
  94. if lang!='en':
  95. return lines, None
  96. else:
  97. total_lines = len(lines)
  98. line_fea_encode = []
  99. """
  100. 对每一行进行特征编码,编码规则如下:
  101. 1. 如果行顶格,且大写字母开头或者数字开头,编码为1
  102. 2. 如果顶格,其他非大写开头编码为4
  103. 3. 如果非顶格,首字符大写,编码为2
  104. 4. 如果非顶格,首字符非大写编码为3
  105. """
  106. for l in lines:
  107. first_char = __get_span_text(l['spans'][0])[0]
  108. layout_left = __find_layout_bbox_by_line(l['bbox'], new_layout_bboxes)[0]
  109. if l['bbox'][0] == layout_left:
  110. if first_char.isupper() or first_char.isdigit():
  111. line_fea_encode.append(1)
  112. else:
  113. line_fea_encode.append(4)
  114. else:
  115. if first_char.isupper():
  116. line_fea_encode.append(2)
  117. else:
  118. line_fea_encode.append(3)
  119. # 然后根据编码进行分段, 选出来 1,2,3连续出现至少2次的行,认为是列表。
  120. list_indice, list_start_idx = find_repeating_patterns(line_fea_encode)
  121. if len(list_indice)>0:
  122. logger.info(f"发现了列表,列表行数:{list_indice}, {list_start_idx}")
  123. # TODO check一下这个特列表里缩进的行左侧是不是对齐的。
  124. segments = []
  125. for start, end in list_indice:
  126. for i in range(start, end+1):
  127. if i>0:
  128. if line_fea_encode[i] == 4:
  129. logger.info(f"列表行的第{i}行不是顶格的")
  130. break
  131. else:
  132. logger.info(f"列表行的第{start}到第{end}行是列表")
  133. return split_indices(total_lines, list_indice), list_start_idx
  134. def __valign_lines(blocks, layout_bboxes):
  135. """
  136. 在一个layoutbox内对齐行的左侧和右侧。
  137. 扫描行的左侧和右侧,如果x0, x1差距不超过一个阈值,就强行对齐到所处layout的左右两侧(和layout有一段距离)。
  138. 3是个经验值,TODO,计算得来,可以设置为1.5个正文字符。
  139. """
  140. min_distance = 3
  141. min_sample = 2
  142. new_layout_bboxes = []
  143. for layout_box in layout_bboxes:
  144. blocks_in_layoutbox = [b for b in blocks if _is_in_or_part_overlap(b['bbox'], layout_box['layout_bbox'])]
  145. if len(blocks_in_layoutbox)==0:
  146. continue
  147. x0_lst = np.array([[line['bbox'][0], 0] for block in blocks_in_layoutbox for line in block['lines']])
  148. x1_lst = np.array([[line['bbox'][2], 0] for block in blocks_in_layoutbox for line in block['lines']])
  149. x0_clusters = DBSCAN(eps=min_distance, min_samples=min_sample).fit(x0_lst)
  150. x1_clusters = DBSCAN(eps=min_distance, min_samples=min_sample).fit(x1_lst)
  151. x0_uniq_label = np.unique(x0_clusters.labels_)
  152. x1_uniq_label = np.unique(x1_clusters.labels_)
  153. x0_2_new_val = {} # 存储旧值对应的新值映射
  154. x1_2_new_val = {}
  155. for label in x0_uniq_label:
  156. if label==-1:
  157. continue
  158. x0_index_of_label = np.where(x0_clusters.labels_==label)
  159. x0_raw_val = x0_lst[x0_index_of_label][:,0]
  160. x0_new_val = np.min(x0_lst[x0_index_of_label][:,0])
  161. x0_2_new_val.update({idx: x0_new_val for idx in x0_raw_val})
  162. for label in x1_uniq_label:
  163. if label==-1:
  164. continue
  165. x1_index_of_label = np.where(x1_clusters.labels_==label)
  166. x1_raw_val = x1_lst[x1_index_of_label][:,0]
  167. x1_new_val = np.max(x1_lst[x1_index_of_label][:,0])
  168. x1_2_new_val.update({idx: x1_new_val for idx in x1_raw_val})
  169. for block in blocks_in_layoutbox:
  170. for line in block['lines']:
  171. x0, x1 = line['bbox'][0], line['bbox'][2]
  172. if x0 in x0_2_new_val:
  173. line['bbox'][0] = int(x0_2_new_val[x0])
  174. if x1 in x1_2_new_val:
  175. line['bbox'][2] = int(x1_2_new_val[x1])
  176. # 其余对不齐的保持不动
  177. # 由于修改了block里的line长度,现在需要重新计算block的bbox
  178. for block in blocks_in_layoutbox:
  179. block['bbox'] = [min([line['bbox'][0] for line in block['lines']]),
  180. min([line['bbox'][1] for line in block['lines']]),
  181. max([line['bbox'][2] for line in block['lines']]),
  182. max([line['bbox'][3] for line in block['lines']])]
  183. """新计算layout的bbox,因为block的bbox变了。"""
  184. layout_x0 = min([block['bbox'][0] for block in blocks_in_layoutbox])
  185. layout_y0 = min([block['bbox'][1] for block in blocks_in_layoutbox])
  186. layout_x1 = max([block['bbox'][2] for block in blocks_in_layoutbox])
  187. layout_y1 = max([block['bbox'][3] for block in blocks_in_layoutbox])
  188. new_layout_bboxes.append([layout_x0, layout_y0, layout_x1, layout_y1])
  189. return new_layout_bboxes
  190. def __common_pre_proc(blocks, layout_bboxes):
  191. """
  192. 不分语言的,对文本进行预处理
  193. """
  194. #__add_line_period(blocks, layout_bboxes)
  195. aligned_layout_bboxes = __valign_lines(blocks, layout_bboxes)
  196. return aligned_layout_bboxes
  197. def __pre_proc_zh_blocks(blocks, layout_bboxes):
  198. """
  199. 对中文文本进行分段预处理
  200. """
  201. pass
  202. def __pre_proc_en_blocks(blocks, layout_bboxes):
  203. """
  204. 对英文文本进行分段预处理
  205. """
  206. pass
  207. def __group_line_by_layout(blocks, layout_bboxes, lang="en"):
  208. """
  209. 每个layout内的行进行聚合
  210. """
  211. # 因为只是一个block一行目前, 一个block就是一个段落
  212. lines_group = []
  213. for lyout in layout_bboxes:
  214. lines = [line for block in blocks if _is_in_or_part_overlap(block['bbox'], lyout['layout_bbox']) for line in block['lines']]
  215. lines_group.append(lines)
  216. return lines_group
  217. def __split_para_in_layoutbox(lines_group, new_layout_bbox, lang="en", char_avg_len=10):
  218. """
  219. lines_group 进行行分段——layout内部进行分段。lines_group内每个元素是一个Layoutbox内的所有行。
  220. 1. 先计算每个group的左右边界。
  221. 2. 然后根据行末尾特征进行分段。
  222. 末尾特征:以句号等结束符结尾。并且距离右侧边界有一定距离。
  223. 且下一行开头不留空白。
  224. """
  225. paras = []
  226. right_tail_distance = 1.5 * char_avg_len
  227. for lines in lines_group:
  228. total_lines = len(lines)
  229. if total_lines<=1: # 0行无需处理。1行无法分段。
  230. continue
  231. """在进入到真正的分段之前,要对文字块从统计维度进行对齐方式的探测,
  232. 对齐方式分为以下:
  233. 1. 左对齐的文本块(特点是左侧顶格,或者左侧不顶格但是右侧顶格的行数大于非顶格的行数,顶格的首字母有大写也有小写)
  234. 1) 右侧对齐的行,单独成一段
  235. 2) 中间对齐的行,按照字体/行高聚合成一段
  236. 2. 左对齐的列表块(其特点是左侧顶格的行数小于等于非顶格的行数,非定格首字母会有小写,顶格90%是大写。并且左侧顶格行数大于1,大于1是为了这种模式连续出现才能称之为列表)
  237. 这样的文本块,顶格的为一个段落开头,紧随其后非顶格的行属于这个段落。
  238. """
  239. text_segments, list_start_line = __detect_list_lines(lines, new_layout_bbox, lang)
  240. """根据list_range,把lines分成几个部分
  241. """
  242. layout_right = __find_layout_bbox_by_line(lines[0]['bbox'], new_layout_bbox)[2]
  243. layout_left = __find_layout_bbox_by_line(lines[0]['bbox'], new_layout_bbox)[0]
  244. para = [] # 元素是line
  245. for content_type, start, end in text_segments:
  246. if content_type == 'list':
  247. for i, line in enumerate(lines[start:end+1]):
  248. line_x0 = line['bbox'][0]
  249. if line_x0 == layout_left: # 列表开头
  250. if len(para)>0:
  251. paras.append(para)
  252. para = []
  253. para.append(line)
  254. else:
  255. para.append(line)
  256. if len(para)>0:
  257. paras.append(para)
  258. para = []
  259. else:
  260. for i, line in enumerate(lines[start:end+1]):
  261. # 如果i有下一行,那么就要根据下一行位置综合判断是否要分段。如果i之后没有行,那么只需要判断一下行结尾特征。
  262. cur_line_type = line['spans'][-1]['type']
  263. next_line = lines[i+1] if i<total_lines-1 else None
  264. if cur_line_type in [TEXT, INLINE_EQUATION]:
  265. if line['bbox'][2] < layout_right - right_tail_distance:
  266. para.append(line)
  267. paras.append(para)
  268. para = []
  269. elif line['bbox'][2] >= layout_right - right_tail_distance and next_line and next_line['bbox'][0] == layout_left: # 现在这行到了行尾沾满,下一行存在且顶格。
  270. para.append(line)
  271. else:
  272. para.append(line)
  273. paras.append(para)
  274. para = []
  275. else: # 其他,图片、表格、行间公式,各自占一段
  276. if len(para)>0: # 先把之前的段落加入到结果中
  277. paras.append(para)
  278. para = []
  279. paras.append([line]) # 再把当前行加入到结果中。当前行为行间公式、图、表等。
  280. para = []
  281. if len(para)>0:
  282. paras.append(para)
  283. para = []
  284. return paras
  285. def __find_layout_bbox_by_line(line_bbox, layout_bboxes):
  286. """
  287. 根据line找到所在的layout
  288. """
  289. for layout in layout_bboxes:
  290. if _is_in_or_part_overlap(line_bbox, layout):
  291. return layout
  292. return None
  293. def __connect_para_inter_layoutbox(layout_paras, new_layout_bbox, lang="en"):
  294. """
  295. layout之间进行分段。
  296. 主要是计算前一个layOut的最后一行和后一个layout的第一行是否可以连接。
  297. 连接的条件需要同时满足:
  298. 1. 上一个layout的最后一行沾满整个行。并且没有结尾符号。
  299. 2. 下一行开头不留空白。
  300. """
  301. connected_layout_paras = []
  302. for i, para in enumerate(layout_paras):
  303. if i==0:
  304. connected_layout_paras.append(para)
  305. continue
  306. pre_last_line = layout_paras[i-1][-1]
  307. next_first_line = layout_paras[i][0]
  308. pre_last_line_text = ''.join([__get_span_text(span) for span in pre_last_line['spans']])
  309. pre_last_line_type = pre_last_line['spans'][-1]['type']
  310. next_first_line_text = ''.join([__get_span_text(span) for span in next_first_line['spans']])
  311. next_first_line_type = next_first_line['spans'][0]['type']
  312. if pre_last_line_type not in [TEXT, INLINE_EQUATION] or next_first_line_type not in [TEXT, INLINE_EQUATION]: # TODO,真的要做好,要考虑跨table, image, 行间的情况
  313. connected_layout_paras.append(para)
  314. continue
  315. pre_x2_max = __find_layout_bbox_by_line(pre_last_line['bbox'], new_layout_bbox)[2]
  316. next_x0_min = __find_layout_bbox_by_line(next_first_line['bbox'], new_layout_bbox)[0]
  317. pre_last_line_text = pre_last_line_text.strip()
  318. next_first_line_text = next_first_line_text.strip()
  319. if pre_last_line['bbox'][2] == pre_x2_max and pre_last_line_text[-1] not in LINE_STOP_FLAG and next_first_line['bbox'][0]==next_x0_min: # 前面一行沾满了整个行,并且没有结尾符号.下一行没有空白开头。
  320. """连接段落条件成立,将前一个layout的段落和后一个layout的段落连接。"""
  321. connected_layout_paras[-1].extend(para)
  322. else:
  323. """连接段落条件不成立,将前一个layout的段落加入到结果中。"""
  324. connected_layout_paras.append(para)
  325. return connected_layout_paras
  326. def __connect_para_inter_page(pre_page_paras, next_page_paras, pre_page_layout_bbox, next_page_layout_bbox, lang):
  327. """
  328. 连接起来相邻两个页面的段落——前一个页面最后一个段落和后一个页面的第一个段落。
  329. 是否可以连接的条件:
  330. 1. 前一个页面的最后一个段落最后一行沾满整个行。并且没有结尾符号。
  331. 2. 后一个页面的第一个段落第一行没有空白开头。
  332. """
  333. pre_last_para = pre_page_paras[-1]
  334. next_first_para = next_page_paras[0]
  335. pre_last_line = pre_last_para[-1]
  336. next_first_line = next_first_para[0]
  337. pre_last_line_text = ''.join([__get_span_text(span) for span in pre_last_line['spans']])
  338. pre_last_line_type = pre_last_line['spans'][-1]['type']
  339. next_first_line_text = ''.join([__get_span_text(span) for span in next_first_line['spans']])
  340. next_first_line_type = next_first_line['spans'][0]['type']
  341. if pre_last_line_type not in [TEXT, INLINE_EQUATION] or next_first_line_type not in [TEXT, INLINE_EQUATION]: # TODO,真的要做好,要考虑跨table, image, 行间的情况
  342. # 不是文本,不连接
  343. return False
  344. pre_x2_max = __find_layout_bbox_by_line(pre_last_line['bbox'], pre_page_layout_bbox)[2]
  345. next_x0_min = __find_layout_bbox_by_line(next_first_line['bbox'], next_page_layout_bbox)[0]
  346. pre_last_line_text = pre_last_line_text.strip()
  347. next_first_line_text = next_first_line_text.strip()
  348. if pre_last_line['bbox'][2] == pre_x2_max and pre_last_line_text[-1] not in LINE_STOP_FLAG and next_first_line['bbox'][0]==next_x0_min: # 前面一行沾满了整个行,并且没有结尾符号.下一行没有空白开头。
  349. """连接段落条件成立,将前一个layout的段落和后一个layout的段落连接。"""
  350. pre_page_paras[-1].extend(next_first_para)
  351. next_page_paras.pop(0) # 删除后一个页面的第一个段落, 因为他已经被合并到前一个页面的最后一个段落了。
  352. return True
  353. else:
  354. return False
  355. def __do_split(blocks, layout_bboxes, new_layout_bbox, lang="en"):
  356. """
  357. 根据line和layout情况进行分段
  358. 先实现一个根据行末尾特征分段的简单方法。
  359. """
  360. """
  361. 算法思路:
  362. 1. 扫描layout里每一行,找出来行尾距离layout有边界有一定距离的行。
  363. 2. 从上述行中找到末尾是句号等可作为断行标志的行。
  364. 3. 参照上述行尾特征进行分段。
  365. 4. 图、表,目前独占一行,不考虑分段。
  366. """
  367. lines_group = __group_line_by_layout(blocks, layout_bboxes, lang) # block内分段
  368. layout_paras = __split_para_in_layoutbox(lines_group, new_layout_bbox, lang) # layout内分段
  369. connected_layout_paras = __connect_para_inter_layoutbox(layout_paras, new_layout_bbox, lang) # layout间链接段落
  370. return connected_layout_paras
  371. def para_split(pdf_info_dict, lang="en"):
  372. """
  373. 根据line和layout情况进行分段
  374. """
  375. new_layout_of_pages = [] # 数组的数组,每个元素是一个页面的layoutS
  376. for _, page in pdf_info_dict.items():
  377. blocks = page['preproc_blocks']
  378. layout_bboxes = page['layout_bboxes']
  379. new_layout_bbox = __common_pre_proc(blocks, layout_bboxes)
  380. new_layout_of_pages.append(new_layout_bbox)
  381. splited_blocks = __do_split(blocks, layout_bboxes, new_layout_bbox, lang)
  382. page['para_blocks'] = splited_blocks
  383. """连接页面与页面之间的可能合并的段落"""
  384. pdf_infos = list(pdf_info_dict.values())
  385. for i, page in enumerate(pdf_info_dict.values()):
  386. if i==0:
  387. continue
  388. pre_page_paras = pdf_infos[i-1]['para_blocks']
  389. next_page_paras = pdf_infos[i]['para_blocks']
  390. pre_page_layout_bbox = new_layout_of_pages[i-1]
  391. next_page_layout_bbox = new_layout_of_pages[i]
  392. is_conn= __connect_para_inter_page(pre_page_paras, next_page_paras, pre_page_layout_bbox, next_page_layout_bbox, lang)
  393. if is_conn:
  394. logger.info(f"连接了第{i-1}页和第{i}页的段落")