import os import datasets from datasets.tasks import ImageClassification _HOMEPAGE = "https://nihcc.app.box.com/v/ChestXray-NIHCC" _CITATION = """\ @ONLINE {beansdata, author="Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, Mohammadhadi Bagheri, Ronald Summer", title="ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases", month="January", year="2017", url="https://nihcc.app.box.com/v/ChestXray-NIHCC" } """ _DESCRIPTION = """\ The NIH Chest X-ray dataset consists of 100,000 de-identified images of chest x-rays. The images are in PNG format. The data is provided by the NIH Clinical Center and is available through the NIH download site: https://nihcc.app.box.com/v/ChestXray-NIHCC """ _URLS = [ 'https://nihcc.box.com/shared/static/vfk49d74nhbxq3nqjg0900w5nvkorp5c.gz', 'https://nihcc.box.com/shared/static/i28rlmbvmfjbl8p2n3ril0pptcmcu9d1.gz', 'https://nihcc.box.com/shared/static/f1t00wrtdk94satdfb9olcolqx20z2jp.gz', 'https://nihcc.box.com/shared/static/0aowwzs5lhjrceb3qp67ahp0rd1l1etg.gz', 'https://nihcc.box.com/shared/static/v5e3goj22zr6h8tzualxfsqlqaygfbsn.gz', 'https://nihcc.box.com/shared/static/asi7ikud9jwnkrnkj99jnpfkjdes7l6l.gz', 'https://nihcc.box.com/shared/static/jn1b4mw4n6lnh74ovmcjb8y48h8xj07n.gz', 'https://nihcc.box.com/shared/static/tvpxmn7qyrgl0w8wfh9kqfjskv6nmm1j.gz', 'https://nihcc.box.com/shared/static/upyy3ml7qdumlgk2rfcvlb9k6gvqq2pj.gz', 'https://nihcc.box.com/shared/static/l6nilvfa9cg3s28tqv1qc1olm3gnz54p.gz', 'https://nihcc.box.com/shared/static/hhq8fkdgvcari67vfhs7ppg2w6ni4jze.gz', 'https://nihcc.box.com/shared/static/ioqwiy20ihqwyr8pf4c24eazhh281pbu.gz' ] LABEL2IDX = {'No Finding': 0, 'Atelactasis': 1, 'Cardiomegaly': 2, 'Effusion': 3, 'Infiltration': 4, 'Mass': 5, 'Nodule': 6, 'Pneumonia': 7, 'Pneumothorax': 8, 'Consolidation': 9, 'Edema': 10, 'Emphysema': 11, 'Fibrosis': 12, 'Pleural_Thickening': 13, 'Hernia': 14} class XChest(datasets.GeneratorBasedBuilder): """NIH Image Chest X-ray dataset.""" def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "image_file_path": datasets.Value("string"), "image": datasets.Image(), "labels": datasets.features.ClassLabel(names=list(LABEL2IDX.keys())), } ), supervised_keys=("image", "labels"), homepage=_HOMEPAGE, citation=_CITATION, task_templates=[ImageClassification(image_column="image", label_column="labels")], )