import os from typing import List import datasets import pdf2image logger = datasets.logging.get_logger(__name__) _DESCRIPTION = "A generic pdf folder" _CLASSES = ["categoryA", "categoryB"] # define in advance _URL = "https://huggingface.co/datasets/jordyvl/unit-test_PDFfolder/resolve/main/data/data.tar.gz" # folder # train # categoryA # file1 # test # ... class PdfFolder(datasets.GeneratorBasedBuilder): def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "file": datasets.Sequence(datasets.Image()), "labels": datasets.features.ClassLabel(names=_CLASSES), } ), task_templates=None, ) def _split_generators( self, dl_manager: datasets.DownloadManager ) -> List[datasets.SplitGenerator]: archive_path = dl_manager.download(_URL) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "archive_iterator": dl_manager.iter_archive(archive_path), "supposed_labelset": "train", }, ), datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "archive_iterator": dl_manager.iter_archive(archive_path), "supposed_labelset": "test", }, ), datasets.SplitGenerator( name=datasets.Split.VALIDATION, gen_kwargs={ "archive_iterator": dl_manager.iter_archive(archive_path), "supposed_labelset": "val", }, ), ] def _generate_examples(self, archive_iterator, supposed_labelset): extensions = {"pdf", "PDF"} for file_path, file_obj in archive_iterator: if file_path.split(".")[-1] not in extensions: # metadata.jsonlines continue folder, labelset, label, filename = file_path.split("/") if labelset != supposed_labelset: continue images = pdf2image.convert_from_bytes(file_obj.read()) yield file_path, {"file": images, "labels": label}