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import datasets
_TAR_FILES=[
"part0.tar.gz",
"part1.tar.gz",
"part2.tar.gz",
"part3.tar.gz",
"part4.tar.gz",
"part5.tar.gz",
"part6.tar.gz",
]
_TAR_FILES_DICT={
"1024.512": "1024-512-merged1.tar.gz",
"1152.512": "1152-512-merged1.tar.gz",
"384.1152": "384-1152-merged1.tar.gz",
"512.1024": "512-1024-merged1.tar.gz",
"512.1152": "512-1152-merged1.tar.gz",
"512.896": "512-896-merged1.tar.gz",
"640.640": "640-640-merged1.tar.gz",
"640.768": "640-768-merged1.tar.gz",
"640.896": "640-896-merged1.tar.gz",
"768.640": "768-640-merged1.tar.gz",
"768.768": "768-768-merged1.tar.gz",
"896.512": "896-512-merged1.tar.gz",
"896.640": "896-640-merged1.tar.gz",
"1152.384": "1152-384-merged1.tar.gz",
}
class Food101(datasets.GeneratorBasedBuilder):
"""Food-101 Images dataset."""
def _info(self):
return datasets.DatasetInfo(
description="TMP description",
homepage="google it",
citation="lmao",
license="dunno, tbh, assume the worst, k thx."
)
def _split_generators(self, dl_manager):
l=[]
for k in _TAR_FILES_DICT.keys():
archive_path = dl_manager.download(_TAR_FILES_DICT[k])
l.append(
datasets.SplitGenerator(
name=k,
gen_kwargs={
"images": dl_manager.iter_archive(archive_path),
},)
)
return l
def _generate_examples(self, images):
"""Generate images and labels for splits."""
for file_path, file_obj in images:
yield file_path, {
"image": {"path": file_path, "bytes": file_obj.read()},
}
#https://huggingface.co/datasets/oscar-corpus/OSCAR-2201/blob/main/OSCAR-2201.py
#https://huggingface.co/datasets/food101 |