| 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())} |
|
|