magic_pdf_parse_main_zhch.py 5.6 KB

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  1. import copy
  2. import json
  3. import os
  4. from loguru import logger
  5. from magic_pdf.data.data_reader_writer import FileBasedDataWriter
  6. from magic_pdf.libs.draw_bbox import draw_layout_bbox, draw_span_bbox
  7. from magic_pdf.pipe.OCRPipe import OCRPipe
  8. from magic_pdf.pipe.TXTPipe import TXTPipe
  9. from magic_pdf.pipe.UNIPipe import UNIPipe
  10. # todo: 设备类型选择 (?)
  11. from dotenv import load_dotenv; load_dotenv()
  12. print(f"os.environ['CUDA_VISIBLE_DEVICES']: {os.environ['CUDA_VISIBLE_DEVICES']}")
  13. print(f"os.environ['MINERU_TOOLS_CONFIG_JSON']: {os.environ['MINERU_TOOLS_CONFIG_JSON']}")
  14. def json_md_dump(
  15. pipe,
  16. md_writer,
  17. pdf_name,
  18. content_list,
  19. md_content,
  20. orig_model_list,
  21. ):
  22. # 写入模型结果到 model.json
  23. md_writer.write_string(
  24. f'{pdf_name}_model.json',
  25. json.dumps(orig_model_list, ensure_ascii=False, indent=4)
  26. )
  27. # 写入中间结果到 middle.json
  28. md_writer.write_string(
  29. f'{pdf_name}_middle.json',
  30. json.dumps(pipe.pdf_mid_data, ensure_ascii=False, indent=4)
  31. )
  32. # text文本结果写入到 conent_list.json
  33. md_writer.write_string(
  34. f'{pdf_name}_content_list.json',
  35. json.dumps(content_list, ensure_ascii=False, indent=4)
  36. )
  37. # 写入结果到 .md 文件中
  38. md_writer.write_string(
  39. f'{pdf_name}.md',
  40. md_content,
  41. )
  42. # 可视化
  43. def draw_visualization_bbox(pdf_info, pdf_bytes, local_md_dir, pdf_file_name):
  44. # 画布局框,附带排序结果
  45. draw_layout_bbox(pdf_info, pdf_bytes, local_md_dir, pdf_file_name)
  46. # 画 span 框
  47. draw_span_bbox(pdf_info, pdf_bytes, local_md_dir, pdf_file_name)
  48. def pdf_parse_main(
  49. pdf_path: str,
  50. parse_method: str = 'auto',
  51. model_json_path: str = None,
  52. is_json_md_dump: bool = True,
  53. is_draw_visualization_bbox: bool = True,
  54. output_dir: str = None
  55. ):
  56. """执行从 pdf 转换到 json、md 的过程,输出 md 和 json 文件到 pdf 文件所在的目录.
  57. :param pdf_path: .pdf 文件的路径,可以是相对路径,也可以是绝对路径
  58. :param parse_method: 解析方法, 共 auto、ocr、txt 三种,默认 auto,如果效果不好,可以尝试 ocr
  59. :param model_json_path: 已经存在的模型数据文件,如果为空则使用内置模型,pdf 和 model_json 务必对应
  60. :param is_json_md_dump: 是否将解析后的数据写入到 .json 和 .md 文件中,默认 True,会将不同阶段的数据写入到不同的 .json 文件中(共3个.json文件),md内容会保存到 .md 文件中
  61. :param is_draw_visualization_bbox: 是否绘制可视化边界框,默认 True,会生成布局框和 span 框的图像
  62. :param output_dir: 输出结果的目录地址,会生成一个以 pdf 文件名命名的文件夹并保存所有结果
  63. """
  64. try:
  65. pdf_name = os.path.basename(pdf_path).split('.')[0]
  66. pdf_path_parent = os.path.dirname(pdf_path)
  67. if output_dir:
  68. output_path = os.path.join(output_dir, pdf_name)
  69. else:
  70. output_path = os.path.join(pdf_path_parent, pdf_name)
  71. output_image_path = os.path.join(output_path, 'images')
  72. # 获取图片的父路径,为的是以相对路径保存到 .md 和 conent_list.json 文件中
  73. image_path_parent = os.path.basename(output_image_path)
  74. pdf_bytes = open(pdf_path, 'rb').read() # 读取 pdf 文件的二进制数据
  75. orig_model_list = []
  76. if model_json_path:
  77. # 读取已经被模型解析后的pdf文件的 json 原始数据,list 类型
  78. model_json = json.loads(open(model_json_path, 'r', encoding='utf-8').read())
  79. orig_model_list = copy.deepcopy(model_json)
  80. else:
  81. model_json = []
  82. # 执行解析步骤
  83. image_writer, md_writer = FileBasedDataWriter(output_image_path), FileBasedDataWriter(output_path)
  84. # 选择解析方式
  85. if parse_method == 'auto':
  86. jso_useful_key = {'_pdf_type': '', 'model_list': model_json}
  87. pipe = UNIPipe(pdf_bytes, jso_useful_key, image_writer)
  88. elif parse_method == 'txt':
  89. pipe = TXTPipe(pdf_bytes, model_json, image_writer)
  90. elif parse_method == 'ocr':
  91. pipe = OCRPipe(pdf_bytes, model_json, image_writer)
  92. else:
  93. logger.error('unknown parse method, only auto, ocr, txt allowed')
  94. exit(1)
  95. # 执行分类
  96. pipe.pipe_classify()
  97. # 如果没有传入模型数据,则使用内置模型解析
  98. if len(model_json) == 0:
  99. pipe.pipe_analyze() # 解析
  100. orig_model_list = copy.deepcopy(pipe.model_list)
  101. # 执行解析
  102. pipe.pipe_parse()
  103. # 保存 text 和 md 格式的结果
  104. content_list = pipe.pipe_mk_uni_format(image_path_parent, drop_mode='none')
  105. md_content = pipe.pipe_mk_markdown(image_path_parent, drop_mode='none')
  106. if is_json_md_dump:
  107. json_md_dump(pipe, md_writer, pdf_name, content_list, md_content, orig_model_list)
  108. if is_draw_visualization_bbox:
  109. draw_visualization_bbox(pipe.pdf_mid_data['pdf_info'], pdf_bytes, output_path, pdf_name)
  110. except Exception as e:
  111. logger.exception(e)
  112. # 测试
  113. if __name__ == '__main__':
  114. current_script_dir = os.path.dirname(os.path.abspath(__file__))
  115. demo_names = ['demo1', 'demo2', 'small_ocr']
  116. for name in demo_names:
  117. file_path = os.path.join(current_script_dir, f'{name}.pdf')
  118. # pdf_parse_main(file_path, model_json_path='./magic-pdf-0.json', output_dir='./output.demo')
  119. pdf_parse_main(file_path, output_dir='./output.demo')