# Copyright (c) Opendatalab. All rights reserved. import base64 import os import time import zipfile from pathlib import Path import re # os.system('pip install -U magic-pdf==0.8.1') os.system('pip install git+https://github.com/opendatalab/MinerU.git@dev') os.system('wget https://github.com/opendatalab/MinerU/raw/master/docs/download_models_hf.py -O download_models_hf.py') os.system('python download_models_hf.py') os.system("sed -i 's|cpu|cuda|g' /home/user/magic-pdf.json") os.system('cp -r paddleocr /home/user/.paddleocr') os.system("pip install gradio-pdf==0.0.17") from gradio_pdf import PDF import gradio as gr from loguru import logger from magic_pdf.libs.hash_utils import compute_sha256 from magic_pdf.rw.AbsReaderWriter import AbsReaderWriter from magic_pdf.rw.DiskReaderWriter import DiskReaderWriter from magic_pdf.tools.common import do_parse, prepare_env def read_fn(path): disk_rw = DiskReaderWriter(os.path.dirname(path)) return disk_rw.read(os.path.basename(path), AbsReaderWriter.MODE_BIN) # @spaces.GPU def parse_pdf(doc_path, output_dir, end_page_id, ocr): os.makedirs(output_dir, exist_ok=True) try: file_name = f"{str(Path(doc_path).stem)}_{time.time()}" pdf_data = read_fn(doc_path) if ocr: parse_method = "ocr" else: parse_method = "auto" local_image_dir, local_md_dir = prepare_env(output_dir, file_name, parse_method) do_parse( output_dir, file_name, pdf_data, [], parse_method, False, end_page_id=end_page_id, ) return local_md_dir, file_name except Exception as e: logger.exception(e) def compress_directory_to_zip(directory_path, output_zip_path): """ 压缩指定目录到一个 ZIP 文件。 :param directory_path: 要压缩的目录路径 :param output_zip_path: 输出的 ZIP 文件路径 """ try: with zipfile.ZipFile(output_zip_path, 'w', zipfile.ZIP_DEFLATED) as zipf: # 遍历目录中的所有文件和子目录 for root, dirs, files in os.walk(directory_path): for file in files: # 构建完整的文件路径 file_path = os.path.join(root, file) # 计算相对路径 arcname = os.path.relpath(file_path, directory_path) # 添加文件到 ZIP 文件 zipf.write(file_path, arcname) return 0 except Exception as e: logger.exception(e) return -1 def image_to_base64(image_path): with open(image_path, "rb") as image_file: return base64.b64encode(image_file.read()).decode('utf-8') def replace_image_with_base64(markdown_text, image_dir_path): # 匹配Markdown中的图片标签 pattern = r'\!\[(?:[^\]]*)\]\(([^)]+)\)' # 替换图片链接 def replace(match): relative_path = match.group(1) full_path = os.path.join(image_dir_path, relative_path) base64_image = image_to_base64(full_path) return f"![{relative_path}](data:image/jpeg;base64,{base64_image})" # 应用替换 return re.sub(pattern, replace, markdown_text) def to_markdown(file_path, end_pages, ocr): # 获取识别的md文件以及压缩包文件路径 local_md_dir, file_name = parse_pdf(file_path, './output', end_pages - 1, ocr) archive_zip_path = os.path.join("./output", compute_sha256(local_md_dir) + ".zip") zip_archive_success = compress_directory_to_zip(local_md_dir, archive_zip_path) if zip_archive_success == 0: logger.info("压缩成功") else: logger.error("压缩失败") md_path = os.path.join(local_md_dir, file_name + ".md") with open(md_path, 'r', encoding='utf-8') as f: txt_content = f.read() md_content = replace_image_with_base64(txt_content, local_md_dir) # 返回转换后的PDF路径 new_pdf_path = os.path.join(local_md_dir, file_name + "_layout.pdf") return md_content, txt_content, archive_zip_path, new_pdf_path latex_delimiters = [{"left": "$$", "right": "$$", "display": True}, {"left": '$', "right": '$', "display": False}] def init_model(): from magic_pdf.model.doc_analyze_by_custom_model import ModelSingleton try: model_manager = ModelSingleton() txt_model = model_manager.get_model(False, False) logger.info(f"txt_model init final") ocr_model = model_manager.get_model(True, False) logger.info(f"ocr_model init final") return 0 except Exception as e: logger.exception(e) return -1 model_init = init_model() logger.info(f"model_init: {model_init}") with open("header.html", "r") as file: header = file.read() if __name__ == "__main__": with gr.Blocks() as demo: gr.HTML(header) with gr.Row(): with gr.Column(variant='panel', scale=5): pdf_show = gr.Markdown() max_pages = gr.Slider(1, 10, 5, step=1, label="Max convert pages") with gr.Row() as bu_flow: is_ocr = gr.Checkbox(label="Force enable OCR") change_bu = gr.Button("Convert") clear_bu = gr.ClearButton([pdf_show], value="Clear") pdf_show = PDF(label="Please upload pdf", interactive=True, height=800) with gr.Accordion("Examples:"): example_root = os.path.join(os.path.dirname(__file__), "examples") gr.Examples( examples=[os.path.join(example_root, _) for _ in os.listdir(example_root) if _.endswith("pdf")], inputs=pdf_show, ) with gr.Column(variant='panel', scale=5): output_file = gr.File(label="convert result", interactive=False) with gr.Tabs(): with gr.Tab("Markdown rendering"): md = gr.Markdown(label="Markdown rendering", height=900, show_copy_button=True, latex_delimiters=latex_delimiters, line_breaks=True) with gr.Tab("Markdown text"): md_text = gr.TextArea(lines=45, show_copy_button=True) change_bu.click(fn=to_markdown, inputs=[pdf_show, max_pages, is_ocr], outputs=[md, md_text, output_file, pdf_show]) clear_bu.add([md, pdf_show, md_text, output_file, is_ocr]) demo.launch()