import datasets import os import json _DESCRIPTION = """\ Contains Kanji images with corresponding radicals ids from WaniKani or https://api.robanohashi.org/docs/index.html """ _METADATA_URL = "https://huggingface.co/datasets/martingrzzler/kanjis2radicals/raw/main/kanji_metadata.jsonl" _IMAGES_URL = "https://huggingface.co/datasets/martingrzzler/kanjis2radicals/resolve/main/kanji.tar.gz" class Kanji2Radicals(datasets.GeneratorBasedBuilder): """Kanji to radicals dataset.""" def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "kanji_image": datasets.Image(), "radicals": { "id": datasets.Value("int32"), "characters": datasets.Value("string"), "meanings": datasets.Value("string"), "radicals": datasets.Sequence( { "characters": datasets.Value("string"), "id": datasets.Value("int32"), "slug": datasets.Value("string"), } ), }, } ), supervised_keys=None, homepage="https://robanohashi.org/", ) def _split_generators(self, dl_manager): metadata_path = dl_manager.download_and_extract(_METADATA_URL) images_path = dl_manager.download_and_extract(_IMAGES_URL) images_iter = dl_manager.iter_archive(images_path) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "metadata_path": metadata_path, "images_iter": images_iter, }, ), ] def _generate_examples(self, metadata_path, images_iter): radicals = [] print(os.listdir(images_iter)) with open(metadata_path, encoding="utf-8") as f: for line in f: metadata = json.loads(line) radicals.append(metadata) for idx, (image_path, image) in enumerate(images_iter): yield image_path, { "radicals": radicals[idx], "kanji_image": image.read(), }