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import datasets |
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from description import description |
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_DESCRIPTION ="""Fetus Brain Abnormalities Images dataset""" |
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_CITATION = """ |
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@misc{ |
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fetal-brain-abnormalities-ultrasound_dataset, |
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title = { Fetal Brain Abnormalities Ultrasound Dataset }, |
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type = { Open Source Dataset }, |
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author = { Hritwik Trivedi }, |
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howpublished = { \url{ https://universe.roboflow.com/hritwik-trivedi-gkgrv/fetal-brain-abnormalities-ultrasound } }, |
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url = { https://universe.roboflow.com/hritwik-trivedi-gkgrv/fetal-brain-abnormalities-ultrasound }, |
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journal = { Roboflow Universe }, |
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publisher = { Roboflow }, |
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year = { 2023 }, |
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month = { oct }, |
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note = { visited on 2024-03-12 }, |
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} |
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""" |
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_URL = "https://huggingface.co/datasets/KBayoud/roboflow-fetus-head-abnormalities/resolve/main/images.tar.gz" |
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class FetusBrain(datasets.GeneratorBasedBuilder): |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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'text': datasets.Value('string'), |
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'image': datasets.Image(), |
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} |
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), |
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supervised_keys=None, |
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homepage='https://huggingface.co/datasets/KBayoud/roboflow-fetus-head-abnormalities', |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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path = dl_manager.download_and_extract(_URL) |
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image_iters = dl_manager.iter_archive(path) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"images": image_iters |
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} |
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), |
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] |
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def _generate_examples(self, images): |
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idx = 0 |
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for filepath, image in images: |
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yield idx, { |
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'image': {'path': filepath, 'bytes': image.read()}, |
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'text': description[idx] |
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} |
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idx += 1 |
