| import os |
| from typing import List |
|
|
| import datasets |
| import pdf2image |
|
|
| logger = datasets.logging.get_logger(__name__) |
|
|
| _DESCRIPTION = "A generic pdf folder" |
|
|
| _CLASSES = ["categoryA", "categoryB"] |
|
|
| _URL = "https://huggingface.co/datasets/jordyvl/unit-test_PDFfolder/resolve/main/data/data.tar.gz" |
|
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| |
| |
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| |
| |
| |
|
|
|
|
| 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: |
| 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} |
|
|