auto-cats-and-dogs / auto-cats-and-dogs.py
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import requests
from pathlib import Path
from typing import List
import datasets
logger = datasets.logging.get_logger(__name__)
_URLS = {'train': 'https://huggingface.co/datasets/auto-cats-and-dogs/resolve/main/train.tar.gz'}
_NAMES = ['cat', 'dog']
class ImageFolder(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(
features=datasets.Features(
dict(
file=datasets.Value("string"),
labels=datasets.features.ClassLabel(names=_NAMES)
)
),
)
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
data_files = dl_manager.download_and_extract(_URLS)
if isinstance(data_files, str):
return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs=dict(archive_path=data_files))]
splits = []
for split_name, folder in data_files.items():
splits.append(datasets.SplitGenerator(name=split_name, gen_kwargs=dict(archive_path=folder)))
return splits
def _generate_examples(self, archive_path):
labels = self.info.features['labels']
extensions = set(('.jpg', '.jpeg', '.png', '.ppm', '.bmp', '.pgm', '.tif', '.tiff', '.webp'))
for i, path in enumerate(Path(archive_path).glob('**/*')):
if path.suffix in extensions:
yield i, dict(file=path.as_posix(), labels=labels.encode_example(path.parent.name.lower()))