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2.06 kB
| import pickle | |
| from pathlib import Path | |
| from typing import List | |
| import datasets | |
| logger = datasets.logging.get_logger(__name__) | |
| _HOMEPAGE = "https://www.kaggle.com/datasets/msambare/fer2013" | |
| _URL = "https://huggingface.co/datasets/Jeneral/fer-2013/resolve/main/" | |
| _URLS = { | |
| "train": _URL + "train.pt", | |
| "test": _URL + "test.pt", | |
| } | |
| _DESCRIPTION = "A large set of images of faces with seven emotional classes" | |
| _CITATION = """\ | |
| @TECHREPORT{FER2013 dataset, | |
| author = {Prince Awuah Baffour}, | |
| title = {Facial Emotion Detection}, | |
| institution = {}, | |
| year = {2022} | |
| } | |
| """ | |
| class fer2013(datasets.GeneratorBasedBuilder): | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features( | |
| { | |
| "img_bytes": datasets.Value("binary"), | |
| "labels": datasets.features.ClassLabel(names=["angry", "disgust", "fear", "happy", "neutral", "sad", "surprise"]), | |
| } | |
| ), | |
| supervised_keys=("img_bytes", "labels"), | |
| homepage=_HOMEPAGE, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: | |
| downloaded_files = dl_manager.download_and_extract(_URLS) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={"filepath": downloaded_files["train"] | |
| } | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| gen_kwargs={ | |
| "filepath": downloaded_files["test"], | |
| }, | |
| ), | |
| ] | |
| 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): | |
| yield str(i), ex | |