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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}
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