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from pathlib import Path
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_dir.tar.gz"
#folder
# train
# categoryA
# file1
# test
#...
class PdfFolder(datasets.GeneratorBasedBuilder):
def _info(self):
"""
folder = None
elif isinstance(self.config.data_files, str):
folder = self.config.data_files
elif isinstance(self.config.data_files, dict):
folder = self.config.data_files.get("train", None)
if folder is None:
raise RuntimeError()
"""
#classes = sorted([x.name.lower() for x in Path(_URL).glob("*/**")])
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)
import pdb; pdb.set_trace() # breakpoint aef4d417 //
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"archive_iterator": dl_manager.iter_archive(archive_path),
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"archive_iterator": dl_manager.iter_archive(archive_path),
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"archive_iterator": dl_manager.iter_archive(archive_path),
},
),
]
# if isinstance(self.config.data_files, str):
# return [
# datasets.SplitGenerator(
# name=datasets.Split.TRAIN, gen_kwargs={"archive_path": self.config.data_files}
# )
# ]
# splits = []
# for split_name, folder in self.config.data_files.items():
# splits.append(
# datasets.SplitGenerator(name=split_name, gen_kwargs={"archive_path": folder})
# )
# return splits
def _generate_examples(self, archive_path):
labels = self.info.features["labels"]
logger.info("generating examples from = %s", archive_path)
extensions = {".pdf"}
for i, path in enumerate(Path(archive_path).glob("**/*")):
if path.suffix in extensions:
images = pdf2image.convert_from_bytes(path.posix()) #alternatively https://huggingface.co/docs/datasets/v2.8.0/en/package_reference/main_classes#datasets.Dataset.set_transform
# convert PDF to list of images
yield i, {"file": images, "labels": labels.encode_example(path.parent.name.lower())}
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