Datasets:
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import datasets
import tarfile
import os
_CITATION = """\
@InProceedings{huggingface:dataset,
title = {Bee-wings-large},
author={Slawek Maciura},
year={2023}
}
"""
_DESCRIPTION = """\
Random Small
"""
_HOMEPAGE = ""
_LICENSE = ""
_REPO = "https://huggingface.co/datasets/smaciu/bee-wings-large"
class ImageSet(datasets.GeneratorBasedBuilder):
"""Small sample of image-text pairs"""
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
'file_name': datasets.Value('string'),
'image': datasets.Image(),
'label': datasets.Value("string"),
}
),
supervised_keys=None,
homepage=_HOMEPAGE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
images_archive = dl_manager.download(f"{_REPO}/resolve/main/bee-wings-large.tar")
image_iters = dl_manager.iter_archive(images_archive)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN,gen_kwargs={"images": image_iters}),
]
def _generate_examples(self, images):
""" This function returns the examples in the raw (text) form."""
for idx, (filepath, image) in enumerate(images):
filename = os.path.basename(filepath) # Get the file name from the path
description = filename[:2]
yield idx, {
"file_name": filename,
"image": {"path": filepath, "bytes": image.read()},
"label": description,
}
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