Datasets:
Tasks:
Image Classification
Sub-tasks:
multi-class-image-classification
Languages:
English
Size:
10K<n<100K
ArXiv:
License:
from pathlib import Path | |
from typing import List | |
import datasets | |
import pickle | |
logger = datasets.logging.get_logger(__name__) | |
class Fairface(datasets.GeneratorBasedBuilder): | |
_HOMEPAGE = "https://huggingface.co/datasets/nateraw/fairface/" | |
_URL = "https://huggingface.co/datasets/nateraw/fairface/resolve/main/" | |
_URLS = { | |
"train": _URL + "train.pt", | |
"dev": _URL + "val.pt", | |
} | |
_DESCRIPTION = "The Fairface dataset" | |
_CITATION = None | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=self._DESCRIPTION, | |
features=datasets.Features( | |
{ | |
'img_bytes': datasets.Value('binary'), | |
'age': datasets.features.ClassLabel(names=['0-2', '3-9', '10-19', '20-29', '30-39', '40-49', '50-59', '60-69', 'more than 70']), | |
"gender": datasets.features.ClassLabel(names=['Female', 'Male']), | |
'race': datasets.features.ClassLabel(names=['Black', 'East Asian', 'Indian', 'Latino_Hispanic', 'Middle Eastern', 'Southeast Asian', 'White']) | |
} | |
), | |
supervised_keys=('img_bytes', 'age'), | |
homepage=self._HOMEPAGE, | |
citation=self._CITATION, | |
) | |
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: | |
downloaded_files = dl_manager.download_and_extract(self._URLS) | |
return [ | |
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), | |
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}) | |
] | |
def _generate_examples(self, filepath): | |
"""This function returns the examples in the raw (text) form.""" | |
logger.info("generating examples from = %s", filepath) | |
with Path(filepath).open('rb') as f: | |
examples = pickle.load(f) | |
for i, ex in enumerate(examples): | |
_id = ex.pop('_id') | |
yield _id, ex | |