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+import copy
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+import json
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+import os
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+
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+from loguru import logger
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+
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+from magic_pdf.data.data_reader_writer import FileBasedDataWriter
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+from magic_pdf.data.dataset import PymuDocDataset
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+from magic_pdf.libs.draw_bbox import draw_layout_bbox, draw_span_bbox
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+from magic_pdf.pipe.OCRPipe import OCRPipe
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+from magic_pdf.pipe.TXTPipe import TXTPipe
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+from magic_pdf.pipe.UNIPipe import UNIPipe
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+
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+# todo: 设备类型选择 （？）
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+
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+
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+def json_md_dump(
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+ pipe,
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+ md_writer,
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+ pdf_name,
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+ content_list,
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+ md_content,
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+ orig_model_list,
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+):
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+ # 写入模型结果到 model.json
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+
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+ md_writer.write_string(
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+ f'{pdf_name}_model.json',
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+ json.dumps(orig_model_list, ensure_ascii=False, indent=4)
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+ )
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+
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+ # 写入中间结果到 middle.json
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+ md_writer.write_string(
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+ f'{pdf_name}_middle.json',
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+ json.dumps(pipe.pdf_mid_data, ensure_ascii=False, indent=4)
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+ )
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+
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+ # text文本结果写入到 conent_list.json
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+ md_writer.write_string(
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+ f'{pdf_name}_content_list.json',
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+ json.dumps(content_list, ensure_ascii=False, indent=4)
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+ )
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+
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+ # 写入结果到 .md 文件中
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+ md_writer.write_string(
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+ f'{pdf_name}.md',
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+ md_content,
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+ )
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+
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+
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+# 可视化
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+def draw_visualization_bbox(pdf_info, pdf_bytes, local_md_dir, pdf_file_name):
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+ # 画布局框，附带排序结果
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+ draw_layout_bbox(pdf_info, pdf_bytes, local_md_dir, pdf_file_name)
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+ # 画 span 框
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+ draw_span_bbox(pdf_info, pdf_bytes, local_md_dir, pdf_file_name)
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+
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+
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+def pdf_parse_main(
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+ pdf_path: str,
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+ parse_method: str = 'auto',
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+ model_json_path: str = None,
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+ is_json_md_dump: bool = True,
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+ is_draw_visualization_bbox: bool = True,
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+ output_dir: str = None
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+):
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+ """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.
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+
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+ :param pdf_path: .pdf 文件的路径，可以是相对路径，也可以是绝对路径
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+ :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
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+ :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
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+ :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
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+ :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
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+ :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
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+ """
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+ try:
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+ pdf_name = os.path.basename(pdf_path).split('.')[0]
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+ pdf_path_parent = os.path.dirname(pdf_path)
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+
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+ if output_dir:
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+ output_path = os.path.join(output_dir, pdf_name)
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+ else:
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+ output_path = os.path.join(pdf_path_parent, pdf_name)
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+
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+ output_image_path = os.path.join(output_path, 'images')
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+
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+ # 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
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+ image_path_parent = os.path.basename(output_image_path)
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+
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+ pdf_bytes = open(pdf_path, 'rb').read() # 读取 pdf 文件的二进制数据
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+
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+ orig_model_list = []
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+
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+ if model_json_path:
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+ # 读取已经被模型解析后的pdf文件的 json 原始数据，list 类型
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+ model_json = json.loads(open(model_json_path, 'r', encoding='utf-8').read())
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+ orig_model_list = copy.deepcopy(model_json)
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+ else:
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+ model_json = []
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+
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+ # 执行解析步骤
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+ image_writer, md_writer = FileBasedDataWriter(output_image_path), FileBasedDataWriter(output_path)
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+
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+ # 选择解析方式
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+ if parse_method == 'auto':
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+ jso_useful_key = {'_pdf_type': '', 'model_list': model_json}
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+ pipe = UNIPipe(PymuDocDataset(pdf_bytes), jso_useful_key, image_writer)
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+ elif parse_method == 'txt':
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+ pipe = TXTPipe(PymuDocDataset(pdf_bytes), model_json, image_writer)
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+ elif parse_method == 'ocr':
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+ pipe = OCRPipe(PymuDocDataset(pdf_bytes), model_json, image_writer)
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+ else:
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+ logger.error('unknown parse method, only auto, ocr, txt allowed')
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+ exit(1)
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+
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+ # 执行分类
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+ pipe.pipe_classify()
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+
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+ # 如果没有传入模型数据，则使用内置模型解析
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+ if len(model_json) == 0:
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+ pipe.pipe_analyze() # 解析
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+ orig_model_list = copy.deepcopy(pipe.model_list)
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+
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+ # 执行解析
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+ pipe.pipe_parse()
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+
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+ # 保存 text 和 md 格式的结果
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+ content_list = pipe.pipe_mk_uni_format(image_path_parent, drop_mode='none')
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+ md_content = pipe.pipe_mk_markdown(image_path_parent, drop_mode='none')
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+
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+ if is_json_md_dump:
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+ json_md_dump(pipe, md_writer, pdf_name, content_list, md_content, orig_model_list)
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+
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+ if is_draw_visualization_bbox:
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+ draw_visualization_bbox(pipe.pdf_mid_data['pdf_info'], pdf_bytes, output_path, pdf_name)
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+
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+ except Exception as e:
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+ logger.exception(e)
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+
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+
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+# 测试
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+if __name__ == '__main__':
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+ current_script_dir = os.path.dirname(os.path.abspath(__file__))
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+ demo_names = ['demo1', 'demo2', 'small_ocr']
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+ for name in demo_names:
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+ file_path = os.path.join(current_script_dir, f'{name}.pdf')
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+ pdf_parse_main(file_path)
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xu rui