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from pathlib import Path
from typing import List
import datasets
logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = "A generic image folder"
class ImageFolder(datasets.GeneratorBasedBuilder):
def _info(self):
folder=None
if isinstance(self.config.data_files, str):
folder = self.config.data_files
elif isinstance(self.config.data_files, dict):
folder = self.config.data_files.get('train', None)
if folder is None:
raise RuntimeError()
classes = sorted([x.name.lower() for x in Path(folder).glob('*/**')])
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"file": datasets.Value("string"),
"labels": datasets.features.ClassLabel(names=classes)
}
),
)
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
data_files = self.config.data_files
if isinstance(data_files, str):
return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'archive_path': data_files})]
splits = []
for split_name, folder in data_files.items():
splits.append(datasets.SplitGenerator(name=split_name, gen_kwargs={'archive_path': folder}))
return splits
def _generate_examples(self, archive_path):
labels = self.info.features['labels']
logger.info("generating examples from = %s", archive_path)
extensions = {'.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, {'file': path.as_posix(), 'labels': labels.encode_example(path.parent.name.lower())}
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