pdf_parse_by_txt_v2.py 7.5 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222
  1. import time
  2. from loguru import logger
  3. from magic_pdf.layout.layout_sort import get_bboxes_layout
  4. from magic_pdf.libs.convert_utils import dict_to_list
  5. from magic_pdf.libs.hash_utils import compute_md5
  6. from magic_pdf.libs.commons import fitz, get_delta_time
  7. from magic_pdf.model.magic_model import MagicModel
  8. from magic_pdf.pre_proc.construct_page_dict import ocr_construct_page_component_v2
  9. from magic_pdf.pre_proc.cut_image import ocr_cut_image_and_table
  10. from magic_pdf.pre_proc.ocr_detect_all_bboxes import ocr_prepare_bboxes_for_layout_split
  11. from magic_pdf.pre_proc.ocr_dict_merge import (
  12. sort_blocks_by_layout,
  13. fill_spans_in_blocks,
  14. fix_block_spans,
  15. )
  16. from magic_pdf.libs.ocr_content_type import ContentType
  17. from magic_pdf.pre_proc.ocr_span_list_modify import (
  18. remove_overlaps_min_spans,
  19. get_qa_need_list_v2,
  20. )
  21. from magic_pdf.pre_proc.equations_replace import (
  22. combine_chars_to_pymudict,
  23. remove_chars_in_text_blocks,
  24. replace_equations_in_textblock,
  25. )
  26. from magic_pdf.pre_proc.equations_replace import (
  27. combine_chars_to_pymudict,
  28. remove_chars_in_text_blocks,
  29. replace_equations_in_textblock,
  30. )
  31. from magic_pdf.pre_proc.citationmarker_remove import remove_citation_marker
  32. from magic_pdf.libs.math import float_equal
  33. from magic_pdf.para.para_split_v2 import para_split
  34. def txt_spans_extract(pdf_page, inline_equations, interline_equations):
  35. text_raw_blocks = pdf_page.get_text("dict", flags=fitz.TEXTFLAGS_TEXT)["blocks"]
  36. char_level_text_blocks = pdf_page.get_text("rawdict", flags=fitz.TEXTFLAGS_TEXT)[
  37. "blocks"
  38. ]
  39. text_blocks = combine_chars_to_pymudict(text_raw_blocks, char_level_text_blocks)
  40. text_blocks = replace_equations_in_textblock(
  41. text_blocks, inline_equations, interline_equations
  42. )
  43. text_blocks = remove_citation_marker(text_blocks)
  44. text_blocks = remove_chars_in_text_blocks(text_blocks)
  45. spans = []
  46. for v in text_blocks:
  47. for line in v["lines"]:
  48. for span in line["spans"]:
  49. bbox = span["bbox"]
  50. if float_equal(bbox[0], bbox[2]) or float_equal(bbox[1], bbox[3]):
  51. continue
  52. spans.append(
  53. {
  54. "bbox": list(span["bbox"]),
  55. "content": span["text"],
  56. "type": ContentType.Text,
  57. }
  58. )
  59. return spans
  60. def replace_text_span(pymu_spans, ocr_spans):
  61. return list(filter(lambda x: x["type"] != ContentType.Text, ocr_spans)) + pymu_spans
  62. def parse_pdf_by_txt(
  63. pdf_bytes,
  64. model_list,
  65. imageWriter,
  66. start_page_id=0,
  67. end_page_id=None,
  68. debug_mode=False,
  69. ):
  70. pdf_bytes_md5 = compute_md5(pdf_bytes)
  71. pdf_docs = fitz.open("pdf", pdf_bytes)
  72. """初始化空的pdf_info_dict"""
  73. pdf_info_dict = {}
  74. """用model_list和docs对象初始化magic_model"""
  75. magic_model = MagicModel(model_list, pdf_docs)
  76. """根据输入的起始范围解析pdf"""
  77. end_page_id = end_page_id if end_page_id else len(pdf_docs) - 1
  78. """初始化启动时间"""
  79. start_time = time.time()
  80. for page_id in range(start_page_id, end_page_id + 1):
  81. """debug时输出每页解析的耗时"""
  82. if debug_mode:
  83. time_now = time.time()
  84. logger.info(
  85. f"page_id: {page_id}, last_page_cost_time: {get_delta_time(start_time)}"
  86. )
  87. start_time = time_now
  88. """从magic_model对象中获取后面会用到的区块信息"""
  89. img_blocks = magic_model.get_imgs(page_id)
  90. table_blocks = magic_model.get_tables(page_id)
  91. discarded_blocks = magic_model.get_discarded(page_id)
  92. text_blocks = magic_model.get_text_blocks(page_id)
  93. title_blocks = magic_model.get_title_blocks(page_id)
  94. inline_equations, interline_equations, interline_equation_blocks = (
  95. magic_model.get_equations(page_id)
  96. )
  97. page_w, page_h = magic_model.get_page_size(page_id)
  98. """将所有区块的bbox整理到一起"""
  99. all_bboxes = ocr_prepare_bboxes_for_layout_split(
  100. img_blocks,
  101. table_blocks,
  102. discarded_blocks,
  103. text_blocks,
  104. title_blocks,
  105. interline_equation_blocks,
  106. page_w,
  107. page_h,
  108. )
  109. """根据区块信息计算layout"""
  110. page_boundry = [0, 0, page_w, page_h]
  111. layout_bboxes, layout_tree = get_bboxes_layout(
  112. all_bboxes, page_boundry, page_id
  113. )
  114. """根据layout顺序,对当前页面所有需要留下的block进行排序"""
  115. sorted_blocks = sort_blocks_by_layout(all_bboxes, layout_bboxes)
  116. """ocr 中文本类的 span 用 pymu spans 替换!"""
  117. ocr_spans = magic_model.get_all_spans(page_id)
  118. pymu_spans = txt_spans_extract(
  119. pdf_docs[page_id], inline_equations, interline_equations
  120. )
  121. spans = replace_text_span(pymu_spans, ocr_spans)
  122. """删除重叠spans中较小的那些"""
  123. spans, dropped_spans_by_span_overlap = remove_overlaps_min_spans(spans)
  124. """对image和table截图"""
  125. spans = ocr_cut_image_and_table(
  126. spans, pdf_docs[page_id], page_id, pdf_bytes_md5, imageWriter
  127. )
  128. """将span填入排好序的blocks中"""
  129. block_with_spans = fill_spans_in_blocks(sorted_blocks, spans)
  130. """对block进行fix操作"""
  131. fix_blocks = fix_block_spans(block_with_spans, img_blocks, table_blocks)
  132. """获取QA需要外置的list"""
  133. images, tables, interline_equations = get_qa_need_list_v2(fix_blocks)
  134. """构造pdf_info_dict"""
  135. page_info = ocr_construct_page_component_v2(
  136. fix_blocks,
  137. layout_bboxes,
  138. page_id,
  139. page_w,
  140. page_h,
  141. layout_tree,
  142. images,
  143. tables,
  144. interline_equations,
  145. discarded_blocks,
  146. )
  147. pdf_info_dict[f"page_{page_id}"] = page_info
  148. """分段"""
  149. try:
  150. para_split(pdf_info_dict, debug_mode=debug_mode)
  151. except Exception as e:
  152. logger.exception(e)
  153. raise e
  154. """dict转list"""
  155. pdf_info_list = dict_to_list(pdf_info_dict)
  156. new_pdf_info_dict = {
  157. "pdf_info": pdf_info_list,
  158. }
  159. return new_pdf_info_dict
  160. if __name__ == "__main__":
  161. if 1:
  162. import fitz
  163. import json
  164. with open("/opt/data/pdf/20240418/25536-00.pdf", "rb") as f:
  165. pdf_bytes = f.read()
  166. pdf_docs = fitz.open("pdf", pdf_bytes)
  167. with open("/opt/data/pdf/20240418/25536-00.json") as f:
  168. model_list = json.loads(f.readline())
  169. magic_model = MagicModel(model_list, pdf_docs)
  170. for i in range(7):
  171. print(magic_model.get_imgs(i))
  172. for page_no, page in enumerate(pdf_docs):
  173. inline_equations, interline_equations, interline_equation_blocks = (
  174. magic_model.get_equations(page_no)
  175. )
  176. text_raw_blocks = page.get_text("dict", flags=fitz.TEXTFLAGS_TEXT)["blocks"]
  177. char_level_text_blocks = page.get_text(
  178. "rawdict", flags=fitz.TEXTFLAGS_TEXT
  179. )["blocks"]
  180. text_blocks = combine_chars_to_pymudict(
  181. text_raw_blocks, char_level_text_blocks
  182. )
  183. text_blocks = replace_equations_in_textblock(
  184. text_blocks, inline_equations, interline_equations
  185. )
  186. text_blocks = remove_citation_marker(text_blocks)
  187. text_blocks = remove_chars_in_text_blocks(text_blocks)