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import datasets
_CITATION = """\
@InProceedings{huggingface:dataset,
title = {Klee},
author={Kevin Li},
year={2022}
}
"""
_DESCRIPTION = """\
128x128 PNG images of kanjis from the Klee font
"""
_HOMEPAGE = "https://huggingface.co/datasets/AlienKevin/klee"
_LICENSE = "CC0"
_REPO = "https://huggingface.co/datasets/AlienKevin/klee"
class ImageSet(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
'character': datasets.Value("string"),
'image': datasets.Image(),
}
),
supervised_keys=None,
homepage=_HOMEPAGE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
images_archive = dl_manager.download(f"{_REPO}/resolve/main/images.tgz")
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):
idx = 0
for filepath, image in images:
character = filepath.split('/')[-1][:-4]
yield idx, {
"image": {"path": filepath, "bytes": image.read()},
"character": character,
}
idx += 1 |