| 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())} | |