# Copyright (c) Opendatalab. All rights reserved. import io import json import os import copy from multiprocessing import Pool from pathlib import Path import pypdfium2 as pdfium from loguru import logger from mineru.data.data_reader_writer import FileBasedDataWriter from mineru.utils.draw_bbox import draw_layout_bbox, draw_span_bbox, draw_line_sort_bbox from mineru.utils.enum_class import MakeMode from mineru.utils.guess_suffix_or_lang import guess_suffix_by_bytes from mineru.utils.pdf_image_tools import images_bytes_to_pdf_bytes from mineru.backend.vlm.vlm_middle_json_mkcontent import union_make as vlm_union_make from mineru.backend.vlm.vlm_analyze import doc_analyze as vlm_doc_analyze from mineru.backend.vlm.vlm_analyze import aio_doc_analyze as aio_vlm_doc_analyze from mineru.utils.pdf_page_id import get_end_page_id pdf_suffixes = ["pdf"] image_suffixes = ["png", "jpeg", "jp2", "webp", "gif", "bmp", "jpg", "tiff"] os.environ["TOKENIZERS_PARALLELISM"] = "false" def read_fn(path): if not isinstance(path, Path): path = Path(path) with open(str(path), "rb") as input_file: file_bytes = input_file.read() file_suffix = guess_suffix_by_bytes(file_bytes, path) if file_suffix in image_suffixes: return images_bytes_to_pdf_bytes(file_bytes) elif file_suffix in pdf_suffixes: return file_bytes else: raise Exception(f"Unknown file suffix: {file_suffix}") def prepare_env(output_dir, pdf_file_name, parse_method): local_md_dir = str(os.path.join(output_dir, pdf_file_name, parse_method)) local_image_dir = os.path.join(str(local_md_dir), "images") os.makedirs(local_image_dir, exist_ok=True) os.makedirs(local_md_dir, exist_ok=True) return local_image_dir, local_md_dir def convert_pdf_bytes_to_bytes_by_pypdfium2(pdf_bytes, start_page_id=0, end_page_id=None): try: # 从字节数据加载PDF pdf = pdfium.PdfDocument(pdf_bytes) end_page_id = get_end_page_id(end_page_id, len(pdf)) # 创建一个新的PDF文档 output_pdf = pdfium.PdfDocument.new() # 选择要导入的页面索引 page_indices = list(range(start_page_id, end_page_id + 1)) # 从原PDF导入页面到新PDF output_pdf.import_pages(pdf, page_indices) # 将新PDF保存到内存缓冲区 output_buffer = io.BytesIO() output_pdf.save(output_buffer) # 获取字节数据 output_bytes = output_buffer.getvalue() pdf.close() # 关闭原PDF文档以释放资源 output_pdf.close() # 关闭新PDF文档以释放资源 except Exception as e: logger.warning(f"Error in converting PDF bytes: {e}, Using original PDF bytes.") output_bytes = pdf_bytes return output_bytes def _convert_pdf_in_process(args): """在独立进程中执行PDF转换""" pdf_bytes, start_page_id, end_page_id = args return convert_pdf_bytes_to_bytes_by_pypdfium2(pdf_bytes, start_page_id, end_page_id) def _prepare_pdf_bytes(pdf_bytes_list, start_page_id, end_page_id): """准备处理PDF字节数据""" # 准备参数列表 args_list = [(pdf_bytes, start_page_id, end_page_id) for pdf_bytes in pdf_bytes_list] # 使用进程池执行转换 with Pool(processes=min(len(pdf_bytes_list), min(os.cpu_count() or 1, 4))) as pool: result = pool.map(_convert_pdf_in_process, args_list) return result def _process_output( pdf_info, pdf_bytes, pdf_file_name, local_md_dir, local_image_dir, md_writer, f_draw_layout_bbox, f_draw_span_bbox, f_dump_orig_pdf, f_dump_md, f_dump_content_list, f_dump_middle_json, f_dump_model_output, f_make_md_mode, middle_json, model_output=None, is_pipeline=True ): f_draw_line_sort_bbox = False from mineru.backend.pipeline.pipeline_middle_json_mkcontent import union_make as pipeline_union_make """处理输出文件""" if f_draw_layout_bbox: draw_layout_bbox(pdf_info, pdf_bytes, local_md_dir, f"{pdf_file_name}_layout.pdf") if f_draw_span_bbox: draw_span_bbox(pdf_info, pdf_bytes, local_md_dir, f"{pdf_file_name}_span.pdf") if f_dump_orig_pdf: md_writer.write( f"{pdf_file_name}_origin.pdf", pdf_bytes, ) if f_draw_line_sort_bbox: draw_line_sort_bbox(pdf_info, pdf_bytes, local_md_dir, f"{pdf_file_name}_line_sort.pdf") image_dir = str(os.path.basename(local_image_dir)) if f_dump_md: make_func = pipeline_union_make if is_pipeline else vlm_union_make md_content_str = make_func(pdf_info, f_make_md_mode, image_dir) md_writer.write_string( f"{pdf_file_name}.md", md_content_str, ) if f_dump_content_list: make_func = pipeline_union_make if is_pipeline else vlm_union_make content_list = make_func(pdf_info, MakeMode.CONTENT_LIST, image_dir) md_writer.write_string( f"{pdf_file_name}_content_list.json", json.dumps(content_list, ensure_ascii=False, indent=4), ) if f_dump_middle_json: md_writer.write_string( f"{pdf_file_name}_middle.json", json.dumps(middle_json, ensure_ascii=False, indent=4), ) if f_dump_model_output: md_writer.write_string( f"{pdf_file_name}_model.json", json.dumps(model_output, ensure_ascii=False, indent=4), ) logger.info(f"local output dir is {local_md_dir}") def _process_pipeline( output_dir, pdf_file_names, pdf_bytes_list, p_lang_list, parse_method, p_formula_enable, p_table_enable, f_draw_layout_bbox, f_draw_span_bbox, f_dump_md, f_dump_middle_json, f_dump_model_output, f_dump_orig_pdf, f_dump_content_list, f_make_md_mode, ): """处理pipeline后端逻辑""" from mineru.backend.pipeline.model_json_to_middle_json import result_to_middle_json as pipeline_result_to_middle_json from mineru.backend.pipeline.pipeline_analyze import doc_analyze as pipeline_doc_analyze infer_results, all_image_lists, all_pdf_docs, lang_list, ocr_enabled_list = ( pipeline_doc_analyze( pdf_bytes_list, p_lang_list, parse_method=parse_method, formula_enable=p_formula_enable, table_enable=p_table_enable ) ) for idx, model_list in enumerate(infer_results): model_json = copy.deepcopy(model_list) pdf_file_name = pdf_file_names[idx] local_image_dir, local_md_dir = prepare_env(output_dir, pdf_file_name, parse_method) image_writer, md_writer = FileBasedDataWriter(local_image_dir), FileBasedDataWriter(local_md_dir) images_list = all_image_lists[idx] pdf_doc = all_pdf_docs[idx] _lang = lang_list[idx] _ocr_enable = ocr_enabled_list[idx] middle_json = pipeline_result_to_middle_json( model_list, images_list, pdf_doc, image_writer, _lang, _ocr_enable, p_formula_enable ) pdf_info = middle_json["pdf_info"] pdf_bytes = pdf_bytes_list[idx] _process_output( pdf_info, pdf_bytes, pdf_file_name, local_md_dir, local_image_dir, md_writer, f_draw_layout_bbox, f_draw_span_bbox, f_dump_orig_pdf, f_dump_md, f_dump_content_list, f_dump_middle_json, f_dump_model_output, f_make_md_mode, middle_json, model_json, is_pipeline=True ) async def _async_process_vlm( output_dir, pdf_file_names, pdf_bytes_list, backend, f_draw_layout_bbox, f_draw_span_bbox, f_dump_md, f_dump_middle_json, f_dump_model_output, f_dump_orig_pdf, f_dump_content_list, f_make_md_mode, server_url=None, **kwargs, ): """异步处理VLM后端逻辑""" parse_method = "vlm" f_draw_span_bbox = False if not backend.endswith("client"): server_url = None for idx, pdf_bytes in enumerate(pdf_bytes_list): pdf_file_name = pdf_file_names[idx] local_image_dir, local_md_dir = prepare_env(output_dir, pdf_file_name, parse_method) image_writer, md_writer = FileBasedDataWriter(local_image_dir), FileBasedDataWriter(local_md_dir) middle_json, infer_result = await aio_vlm_doc_analyze( pdf_bytes, image_writer=image_writer, backend=backend, server_url=server_url, **kwargs, ) pdf_info = middle_json["pdf_info"] _process_output( pdf_info, pdf_bytes, pdf_file_name, local_md_dir, local_image_dir, md_writer, f_draw_layout_bbox, f_draw_span_bbox, f_dump_orig_pdf, f_dump_md, f_dump_content_list, f_dump_middle_json, f_dump_model_output, f_make_md_mode, middle_json, infer_result, is_pipeline=False ) def _process_vlm( output_dir, pdf_file_names, pdf_bytes_list, backend, f_draw_layout_bbox, f_draw_span_bbox, f_dump_md, f_dump_middle_json, f_dump_model_output, f_dump_orig_pdf, f_dump_content_list, f_make_md_mode, server_url=None, **kwargs, ): """同步处理VLM后端逻辑""" parse_method = "vlm" f_draw_span_bbox = False if not backend.endswith("client"): server_url = None for idx, pdf_bytes in enumerate(pdf_bytes_list): pdf_file_name = pdf_file_names[idx] local_image_dir, local_md_dir = prepare_env(output_dir, pdf_file_name, parse_method) image_writer, md_writer = FileBasedDataWriter(local_image_dir), FileBasedDataWriter(local_md_dir) middle_json, infer_result = vlm_doc_analyze( pdf_bytes, image_writer=image_writer, backend=backend, server_url=server_url, **kwargs, ) pdf_info = middle_json["pdf_info"] _process_output( pdf_info, pdf_bytes, pdf_file_name, local_md_dir, local_image_dir, md_writer, f_draw_layout_bbox, f_draw_span_bbox, f_dump_orig_pdf, f_dump_md, f_dump_content_list, f_dump_middle_json, f_dump_model_output, f_make_md_mode, middle_json, infer_result, is_pipeline=False ) def do_parse( output_dir, pdf_file_names: list[str], pdf_bytes_list: list[bytes], p_lang_list: list[str], backend="pipeline", parse_method="auto", formula_enable=True, table_enable=True, server_url=None, f_draw_layout_bbox=True, f_draw_span_bbox=True, f_dump_md=True, f_dump_middle_json=True, f_dump_model_output=True, f_dump_orig_pdf=True, f_dump_content_list=True, f_make_md_mode=MakeMode.MM_MD, start_page_id=0, end_page_id=None, **kwargs, ): # 预处理PDF字节数据 pdf_bytes_list = _prepare_pdf_bytes(pdf_bytes_list, start_page_id, end_page_id) if backend == "pipeline": _process_pipeline( output_dir, pdf_file_names, pdf_bytes_list, p_lang_list, parse_method, formula_enable, table_enable, f_draw_layout_bbox, f_draw_span_bbox, f_dump_md, f_dump_middle_json, f_dump_model_output, f_dump_orig_pdf, f_dump_content_list, f_make_md_mode ) else: if backend.startswith("vlm-"): backend = backend[4:] if backend == "vllm-async-engine": raise Exception("vlm-vllm-async-engine backend is not supported in sync mode, please use vlm-vllm-engine backend") os.environ['MINERU_VLM_FORMULA_ENABLE'] = str(formula_enable) os.environ['MINERU_VLM_TABLE_ENABLE'] = str(table_enable) _process_vlm( output_dir, pdf_file_names, pdf_bytes_list, backend, f_draw_layout_bbox, f_draw_span_bbox, f_dump_md, f_dump_middle_json, f_dump_model_output, f_dump_orig_pdf, f_dump_content_list, f_make_md_mode, server_url, **kwargs, ) async def aio_do_parse( output_dir, pdf_file_names: list[str], pdf_bytes_list: list[bytes], p_lang_list: list[str], backend="pipeline", parse_method="auto", formula_enable=True, table_enable=True, server_url=None, f_draw_layout_bbox=True, f_draw_span_bbox=True, f_dump_md=True, f_dump_middle_json=True, f_dump_model_output=True, f_dump_orig_pdf=True, f_dump_content_list=True, f_make_md_mode=MakeMode.MM_MD, start_page_id=0, end_page_id=None, **kwargs, ): # 预处理PDF字节数据 pdf_bytes_list = _prepare_pdf_bytes(pdf_bytes_list, start_page_id, end_page_id) if backend == "pipeline": # pipeline模式暂不支持异步,使用同步处理方式 _process_pipeline( output_dir, pdf_file_names, pdf_bytes_list, p_lang_list, parse_method, formula_enable, table_enable, f_draw_layout_bbox, f_draw_span_bbox, f_dump_md, f_dump_middle_json, f_dump_model_output, f_dump_orig_pdf, f_dump_content_list, f_make_md_mode ) else: if backend.startswith("vlm-"): backend = backend[4:] if backend == "vllm-engine": raise Exception("vlm-vllm-engine backend is not supported in async mode, please use vlm-vllm-async-engine backend") os.environ['MINERU_VLM_FORMULA_ENABLE'] = str(formula_enable) os.environ['MINERU_VLM_TABLE_ENABLE'] = str(table_enable) await _async_process_vlm( output_dir, pdf_file_names, pdf_bytes_list, backend, f_draw_layout_bbox, f_draw_span_bbox, f_dump_md, f_dump_middle_json, f_dump_model_output, f_dump_orig_pdf, f_dump_content_list, f_make_md_mode, server_url, **kwargs, ) if __name__ == "__main__": # pdf_path = "../../demo/pdfs/demo3.pdf" pdf_path = "C:/Users/zhaoxiaomeng/Downloads/4546d0e2-ba60-40a5-a17e-b68555cec741.pdf" try: do_parse("./output", [Path(pdf_path).stem], [read_fn(Path(pdf_path))],["ch"], end_page_id=10, backend='vlm-huggingface' # backend = 'pipeline' ) except Exception as e: logger.exception(e)