import os import datasets from huggingface_hub import HfApi from datasets import DownloadManager, DatasetInfo from datasets.data_files import DataFilesDict _EXTENSION = [".png", ".jpg", ".jpeg"] _DESCRIPTION = "" _NAME = "animelover/princess-connect-images" _REVISION = "main" class DanbooruDataset(datasets.GeneratorBasedBuilder): def _info(self) -> DatasetInfo: return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "image": datasets.Image(), "tags": datasets.Value("string") } ), supervised_keys=None, citation="", ) def _split_generators(self, dl_manager: DownloadManager): hfh_dataset_info = HfApi().dataset_info(_NAME, revision=_REVISION, timeout=100.0) data_files = DataFilesDict.from_hf_repo( {datasets.Split.TRAIN: ["**"]}, dataset_info=hfh_dataset_info, allowed_extensions=["zip"], ) gs = [] for split, files in data_files.items(): downloaded_files = dl_manager.download_and_extract(files) gs.append(datasets.SplitGenerator(name=split, gen_kwargs={"filepath": downloaded_files})) return gs def _generate_examples(self, filepath): for path in filepath: all_fnames = {os.path.relpath(os.path.join(root, fname), start=path) for root, _dirs, files in os.walk(path) for fname in files} image_fnames = sorted(fname for fname in all_fnames if os.path.splitext(fname)[1].lower() in _EXTENSION) for image_fname in image_fnames: image_path = os.path.join(path, image_fname) tags_path = os.path.join(path, os.path.splitext(image_fname)[0] + ".txt") with open(tags_path, "r", encoding="utf-8") as f: tags = f.read() yield image_fname, {"image": image_path, "tags": tags}