Datasets:
Size Categories:
10K<n<100K
Language Creators:
expert-generated
Annotations Creators:
no-annotation
Source Datasets:
original
License:
| import datasets | |
| logger = datasets.logging.get_logger(__name__) | |
| _HOMEPAGE = 'https://brain-development.org/ixi-dataset/' | |
| _DESCRIPTION = ( | |
| "This dataset contains around 28000 2D slices extracted from 600 MRI images of healthy subjects." | |
| " Each MRI volume was skull-stripped, white matter normalized and registered to the 'fsaverage' template using affine transformation. " | |
| ) | |
| _URLS = { | |
| 'train': 'data/train.zip', | |
| 'valid': 'data/valid.zip' | |
| } | |
| _LICENSE = """\ | |
| LICENSE AGREEMENT | |
| ================= | |
| - The IXI-2D dataset consists of images from IXI Dataset [1] which are | |
| property of the Biomedical Image Analysis Group, Imperial College London. Any use beyond | |
| scientific fair use must be negotiated with the respective picture owners | |
| according to the Creative Commons license [2]. | |
| [1] https://brain-development.org/ixi-dataset/ | |
| [2] https://creativecommons.org/licenses/by-sa/3.0/legalcode | |
| """ | |
| class IXI2D(datasets.GeneratorBasedBuilder): | |
| """Food-101 Images dataset""" | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| features=datasets.Features( | |
| { | |
| "image": datasets.Image(), | |
| } | |
| ), | |
| homepage=_HOMEPAGE, | |
| description=_DESCRIPTION, | |
| license=_LICENSE | |
| ) | |
| def _split_generators(self, dl_manager): | |
| archive_path = dl_manager.download(_URLS) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "images": dl_manager.iter_archive(archive_path['train']), | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.VALIDATION, | |
| gen_kwargs={ | |
| "images": dl_manager.iter_archive(archive_path['valid']), | |
| }, | |
| ), | |
| ] | |
| def _generate_examples(self, images): | |
| for file_path, file_obj in images: | |
| yield file_path, { | |
| "image": {"path": file_path, "bytes": file_obj.read()}, | |
| } | |