| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322 |
- from sklearn.cluster import DBSCAN
- import numpy as np
- from loguru import logger
- from magic_pdf.libs.boxbase import _is_in
- from magic_pdf.libs.ocr_content_type import ContentType
- LINE_STOP_FLAG = ['.', '!', '?', '。', '!', '?',":", ":", ")", ")", ";"]
- INLINE_EQUATION = ContentType.InlineEquation
- INTERLINE_EQUATION = ContentType.InterlineEquation
- TEXT = "text"
- def __get_span_text(span):
- c = span.get('content', '')
- if len(c)==0:
- c = span.get('image_path', '')
-
- return c
-
-
- def __add_line_period(blocks, layout_bboxes):
- """
- 为每行添加句号
- 如果这个行
- 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。
- """
- for block in blocks:
- for line in block['lines']:
- last_span = line['spans'][-1]
- span_type = last_span['type']
- if span_type in [INLINE_EQUATION]:
- span_content = last_span['content'].strip()
- if span_type==INLINE_EQUATION and span_content[-1] not in LINE_STOP_FLAG:
- if span_type in [INLINE_EQUATION, INTERLINE_EQUATION]:
- last_span['content'] = span_content + '.'
- def __valign_lines(blocks, layout_bboxes):
- """
- 在一个layoutbox内对齐行的左侧和右侧。
- 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)。
- 3是个经验值,TODO,计算得来,可以设置为1.5个正文字符。
- """
-
- min_distance = 3
- min_sample = 2
- new_layout_bboxes = []
-
- for layout_box in layout_bboxes:
- blocks_in_layoutbox = [b for b in blocks if _is_in(b['bbox'], layout_box['layout_bbox'])]
- if len(blocks_in_layoutbox)==0:
- continue
-
- x0_lst = np.array([[line['bbox'][0], 0] for block in blocks_in_layoutbox for line in block['lines']])
- x1_lst = np.array([[line['bbox'][2], 0] for block in blocks_in_layoutbox for line in block['lines']])
- x0_clusters = DBSCAN(eps=min_distance, min_samples=min_sample).fit(x0_lst)
- x1_clusters = DBSCAN(eps=min_distance, min_samples=min_sample).fit(x1_lst)
- x0_uniq_label = np.unique(x0_clusters.labels_)
- x1_uniq_label = np.unique(x1_clusters.labels_)
-
- x0_2_new_val = {} # 存储旧值对应的新值映射
- x1_2_new_val = {}
- for label in x0_uniq_label:
- if label==-1:
- continue
- x0_index_of_label = np.where(x0_clusters.labels_==label)
- x0_raw_val = x0_lst[x0_index_of_label][:,0]
- x0_new_val = np.min(x0_lst[x0_index_of_label][:,0])
- x0_2_new_val.update({idx: x0_new_val for idx in x0_raw_val})
- for label in x1_uniq_label:
- if label==-1:
- continue
- x1_index_of_label = np.where(x1_clusters.labels_==label)
- x1_raw_val = x1_lst[x1_index_of_label][:,0]
- x1_new_val = np.max(x1_lst[x1_index_of_label][:,0])
- x1_2_new_val.update({idx: x1_new_val for idx in x1_raw_val})
-
- for block in blocks_in_layoutbox:
- for line in block['lines']:
- x0, x1 = line['bbox'][0], line['bbox'][2]
- if x0 in x0_2_new_val:
- line['bbox'][0] = int(x0_2_new_val[x0])
- if x1 in x1_2_new_val:
- line['bbox'][2] = int(x1_2_new_val[x1])
- # 其余对不齐的保持不动
-
- # 由于修改了block里的line长度,现在需要重新计算block的bbox
- for block in blocks_in_layoutbox:
- block['bbox'] = [min([line['bbox'][0] for line in block['lines']]),
- min([line['bbox'][1] for line in block['lines']]),
- max([line['bbox'][2] for line in block['lines']]),
- max([line['bbox'][3] for line in block['lines']])]
-
- """新计算layout的bbox,因为block的bbox变了。"""
- layout_x0 = min([block['bbox'][0] for block in blocks_in_layoutbox])
- layout_y0 = min([block['bbox'][1] for block in blocks_in_layoutbox])
- layout_x1 = max([block['bbox'][2] for block in blocks_in_layoutbox])
- layout_y1 = max([block['bbox'][3] for block in blocks_in_layoutbox])
- new_layout_bboxes.append([layout_x0, layout_y0, layout_x1, layout_y1])
-
- return new_layout_bboxes
- def __common_pre_proc(blocks, layout_bboxes):
- """
- 不分语言的,对文本进行预处理
- """
- #__add_line_period(blocks, layout_bboxes)
- aligned_layout_bboxes = __valign_lines(blocks, layout_bboxes)
-
- return aligned_layout_bboxes
- def __pre_proc_zh_blocks(blocks, layout_bboxes):
- """
- 对中文文本进行分段预处理
- """
- pass
- def __pre_proc_en_blocks(blocks, layout_bboxes):
- """
- 对英文文本进行分段预处理
- """
- pass
- def __group_line_by_layout(blocks, layout_bboxes, lang="en"):
- """
- 每个layout内的行进行聚合
- """
- # 因为只是一个block一行目前, 一个block就是一个段落
- lines_group = []
-
- for lyout in layout_bboxes:
- lines = [line for block in blocks if _is_in(block['bbox'], lyout['layout_bbox']) for line in block['lines']]
- lines_group.append(lines)
- return lines_group
-
- def __split_para_in_layoutbox(lines_group, new_layout_bbox, lang="en", char_avg_len=10):
- """
- 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。
- 1. 先计算每个group的左右边界。
- 2. 然后根据行末尾特征进行分段。
- 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。
- 且下一行开头不留空白。
-
- """
- paras = []
- right_tail_distance = 1.5 * char_avg_len
- for lines in lines_group:
- total_lines = len(lines)
- if total_lines<=1: # 0行无需处理。1行无法分段。
- continue
- #layout_right = max([line['bbox'][2] for line in lines])
- layout_right = __find_layout_bbox_by_line(lines[0]['bbox'], new_layout_bbox)[2]
- para = [] # 元素是line
-
- for i, line in enumerate(lines):
- # 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。
-
- cur_line_type = line['spans'][-1]['type']
- #cur_line_last_char = line['spans'][-1]['content'][-1]
- next_line = lines[i+1] if i<total_lines-1 else None
-
- if cur_line_type in [TEXT, INLINE_EQUATION]:
- if line['bbox'][2] < layout_right - right_tail_distance:
- para.append(line)
- paras.append(para)
- para = []
- elif line['bbox'][2] >= layout_right - right_tail_distance and next_line and next_line['bbox'][0] == layout_right: # 现在这行到了行尾沾满,下一行存在且顶格。
- para.append(line)
- else:
- para.append(line)
- paras.append(para)
- para = []
- else: # 其他,图片、表格、行间公式,各自占一段
- if len(para)>0: # 先把之前的段落加入到结果中
- paras.append(para)
- para = []
- 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。
- para = []
- if len(para)>0:
- paras.append(para)
- para = []
-
- return paras
- def __find_layout_bbox_by_line(line_bbox, layout_bboxes):
- """
- 根据line找到所在的layout
- """
- for layout in layout_bboxes:
- if _is_in(line_bbox, layout):
- return layout
- return None
- def __connect_para_inter_layoutbox(layout_paras, new_layout_bbox, lang="en"):
- """
- layout之间进行分段。
- 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。
- 连接的条件需要同时满足:
- 1. 上一个layout的最后一行沾满整个行。并且没有结尾符号。
- 2. 下一行开头不留空白。
- """
- connected_layout_paras = []
- for i, para in enumerate(layout_paras):
- if i==0:
- connected_layout_paras.append(para)
- continue
- pre_last_line = layout_paras[i-1][-1]
- next_first_line = layout_paras[i][0]
- pre_last_line_text = ''.join([__get_span_text(span) for span in pre_last_line['spans']])
- pre_last_line_type = pre_last_line['spans'][-1]['type']
- next_first_line_text = ''.join([__get_span_text(span) for span in next_first_line['spans']])
- next_first_line_type = next_first_line['spans'][0]['type']
- 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
- connected_layout_paras.append(para)
- continue
-
-
- pre_x2_max = __find_layout_bbox_by_line(pre_last_line['bbox'], new_layout_bbox)[2]
- next_x0_min = __find_layout_bbox_by_line(next_first_line['bbox'], new_layout_bbox)[0]
-
- pre_last_line_text = pre_last_line_text.strip()
- next_first_line_text = next_first_line_text.strip()
- 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。
- """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。"""
- connected_layout_paras[-1].extend(para)
- else:
- """连接段落条件不成立,将前一个layout的段落加入到结果中。"""
- connected_layout_paras.append(para)
-
- return connected_layout_paras
- def __connect_para_inter_page(pre_page_paras, next_page_paras, pre_page_layout_bbox, next_page_layout_bbox, lang):
- """
- 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。
- 是否可以连接的条件:
- 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。
- 2. 后一个页面的第一个段落第一行没有空白开头。
- """
- pre_last_para = pre_page_paras[-1]
- next_first_para = next_page_paras[0]
- pre_last_line = pre_last_para[-1]
- next_first_line = next_first_para[0]
- pre_last_line_text = ''.join([__get_span_text(span) for span in pre_last_line['spans']])
- pre_last_line_type = pre_last_line['spans'][-1]['type']
- next_first_line_text = ''.join([__get_span_text(span) for span in next_first_line['spans']])
- next_first_line_type = next_first_line['spans'][0]['type']
-
- 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
- # 不是文本,不连接
- return False
-
- pre_x2_max = __find_layout_bbox_by_line(pre_last_line['bbox'], pre_page_layout_bbox)[2]
- next_x0_min = __find_layout_bbox_by_line(next_first_line['bbox'], next_page_layout_bbox)[0]
-
- pre_last_line_text = pre_last_line_text.strip()
- next_first_line_text = next_first_line_text.strip()
- 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。
- """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。"""
- pre_page_paras[-1].extend(next_first_para)
- 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。
- return True
- else:
- return False
- def __do_split(blocks, layout_bboxes, new_layout_bbox, lang="en"):
- """
- 根据line和layout情况进行分段
- 先实现一个根据行末尾特征分段的简单方法。
- """
- """
- 算法思路:
- 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。
- 2. 从上述行中找到末尾是句号等可作为断行标志的行。
- 3. 参照上述行尾特征进行分段。
- 4. 图、表,目前独占一行,不考虑分段。
- """
- lines_group = __group_line_by_layout(blocks, layout_bboxes, lang) # block内分段
- layout_paras = __split_para_in_layoutbox(lines_group, new_layout_bbox, lang) # layout内分段
- connected_layout_paras = __connect_para_inter_layoutbox(layout_paras, new_layout_bbox, lang) # layout间链接段落
- return connected_layout_paras
-
-
- def para_split(pdf_info_dict, lang="en"):
- """
- 根据line和layout情况进行分段
- """
- new_layout_of_pages = [] # 数组的数组,每个元素是一个页面的layoutS
- for _, page in pdf_info_dict.items():
- blocks = page['preproc_blocks']
- layout_bboxes = page['layout_bboxes']
- new_layout_bbox = __common_pre_proc(blocks, layout_bboxes)
- new_layout_of_pages.append(new_layout_bbox)
- splited_blocks = __do_split(blocks, layout_bboxes, new_layout_bbox, lang)
- page['para_blocks'] = splited_blocks
-
- """连接页面与页面之间的可能合并的段落"""
- pdf_infos = list(pdf_info_dict.values())
- for i, page in enumerate(pdf_info_dict.values()):
- if i==0:
- continue
- pre_page_paras = pdf_infos[i-1]['para_blocks']
- next_page_paras = pdf_infos[i]['para_blocks']
- pre_page_layout_bbox = new_layout_of_pages[i-1]
- next_page_layout_bbox = new_layout_of_pages[i]
-
- is_conn= __connect_para_inter_page(pre_page_paras, next_page_paras, pre_page_layout_bbox, next_page_layout_bbox, lang)
- if is_conn:
- logger.info(f"连接了第{i-1}页和第{i}页的段落")
|