转换为 Markdown 文件 ======================== 本地文件示例 ^^^^^^^^^^^^^^^^^^ .. code:: python import os from magic_pdf.data.data_reader_writer import FileBasedDataWriter, FileBasedDataReader from magic_pdf.data.dataset import PymuDocDataset from magic_pdf.model.doc_analyze_by_custom_model import doc_analyze from magic_pdf.config.enums import SupportedPdfParseMethod # args pdf_file_name = "abc.pdf" # replace with the real pdf path name_without_suff = pdf_file_name.split(".")[0] # prepare env local_image_dir, local_md_dir = "output/images", "output" image_dir = str(os.path.basename(local_image_dir)) os.makedirs(local_image_dir, exist_ok=True) image_writer, md_writer = FileBasedDataWriter(local_image_dir), FileBasedDataWriter( local_md_dir ) image_dir = str(os.path.basename(local_image_dir)) # read bytes reader1 = FileBasedDataReader("") pdf_bytes = reader1.read(pdf_file_name) # read the pdf content # proc ## Create Dataset Instance ds = PymuDocDataset(pdf_bytes) ## inference if ds.classify() == SupportedPdfParseMethod.OCR: infer_result = ds.apply(doc_analyze, ocr=True) ## pipeline pipe_result = infer_result.pipe_ocr_mode(image_writer) else: infer_result = ds.apply(doc_analyze, ocr=False) ## pipeline pipe_result = infer_result.pipe_txt_mode(image_writer) ### draw model result on each page infer_result.draw_model(os.path.join(local_md_dir, f"{name_without_suff}_model.pdf")) ### draw layout result on each page pipe_result.draw_layout(os.path.join(local_md_dir, f"{name_without_suff}_layout.pdf")) ### draw spans result on each page pipe_result.draw_span(os.path.join(local_md_dir, f"{name_without_suff}_spans.pdf")) ### dump markdown pipe_result.dump_md(md_writer, f"{name_without_suff}.md", image_dir) ### dump content list pipe_result.dump_content_list(md_writer, f"{name_without_suff}_content_list.json", image_dir) 对象存储文件示例 ^^^^^^^^^^^^^^^^ .. code:: python import os from magic_pdf.data.data_reader_writer import S3DataReader, S3DataWriter from magic_pdf.data.dataset import PymuDocDataset from magic_pdf.model.doc_analyze_by_custom_model import doc_analyze bucket_name = "{Your S3 Bucket Name}" # replace with real bucket name ak = "{Your S3 access key}" # replace with real s3 access key sk = "{Your S3 secret key}" # replace with real s3 secret key endpoint_url = "{Your S3 endpoint_url}" # replace with real s3 endpoint_url reader = S3DataReader('unittest/tmp/', bucket_name, ak, sk, endpoint_url) # replace `unittest/tmp` with the real s3 prefix writer = S3DataWriter('unittest/tmp', bucket_name, ak, sk, endpoint_url) image_writer = S3DataWriter('unittest/tmp/images', bucket_name, ak, sk, endpoint_url) # args pdf_file_name = ( "s3://llm-pdf-text-1/unittest/tmp/bug5-11.pdf" # replace with the real s3 path ) # prepare env local_dir = "output" name_without_suff = os.path.basename(pdf_file_name).split(".")[0] # read bytes pdf_bytes = reader.read(pdf_file_name) # read the pdf content # proc ## Create Dataset Instance ds = PymuDocDataset(pdf_bytes) ## inference if ds.classify() == SupportedPdfParseMethod.OCR: infer_result = ds.apply(doc_analyze, ocr=True) ## pipeline pipe_result = infer_result.pipe_ocr_mode(image_writer) else: infer_result = ds.apply(doc_analyze, ocr=False) ## pipeline pipe_result = infer_result.pipe_txt_mode(image_writer) ### draw model result on each page infer_result.draw_model(os.path.join(local_dir, f'{name_without_suff}_model.pdf')) # dump to local ### draw layout result on each page pipe_result.draw_layout(os.path.join(local_dir, f'{name_without_suff}_layout.pdf')) # dump to local ### draw spans result on each page pipe_result.draw_span(os.path.join(local_dir, f'{name_without_suff}_spans.pdf')) # dump to local ### dump markdown pipe_result.dump_md(writer, f'{name_without_suff}.md', "unittest/tmp/images") # dump to remote s3 ### dump content list pipe_result.dump_content_list(md_writer, f"{name_without_suff}_content_list.json", image_dir) 前去 :doc:`../data/data_reader_writer` 获取更多有关 **读写** 示例