from io import BytesIO from PIL import Image from pathlib import Path import datasets import json RAW_METADATA_URL = r'https://huggingface.co/datasets/OleehyO/latex-formulas/resolve/main/raw_formulas.jsonl' # DIR_URL = r'https://huggingface.co/datasets/OleehyO/latex-formulas/resolve/main/data.tar.gz' DIR_URL = r'https://huggingface.co/datasets/OleehyO/latex-formulas/resolve/main/data1.tar.gz' class LatexFormulasConfig(datasets.BuilderConfig): def __init__(self, data_url, **kwargs): super().__init__(**kwargs) self.data_url = data_url class LatexFormulas(datasets.GeneratorBasedBuilder): BUILDER_CONFIGS = [ LatexFormulasConfig( name="raw_formulas", data_url=RAW_METADATA_URL ), LatexFormulasConfig( name="tokenized_formulas", data_url=DIR_URL ) ] def _info(self): if self.config.name == "raw_formulas": return datasets.DatasetInfo( features=datasets.Features({ "latex_formula": datasets.Value("string") }) ) if self.config.name == "tokenized_formulas": return datasets.DatasetInfo( features=datasets.Features({ "image": datasets.Image(), "latex_formula": datasets.Value("string") }) ) def _split_generators(self, dl_manager: datasets.DownloadManager): if self.config.name == 'raw_formulas': data_path = dl_manager.download(self.config.data_url) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "data_path": data_path } ) ] if self.config.name == "tokenized_formulas": # dir_path = Path(data_path) # dir_path = Path(dl_manager.download_and_extract(data_path)) dir_path = Path(dl_manager.download_and_extract(self.config.data_url)) / 'common_formulas' assert dir_path.is_dir() return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ 'dir_path': dir_path, 'dl_manager': dl_manager } ) ] def _generate_examples(self, data_path=None, dir_path: Path=None, dl_manager=None): if self.config.name == 'tokenized_formulas': idx = 0 for directory in dir_path.iterdir(): if not directory.is_dir(): continue if not directory.name.startswith('process'): continue image_path = str(directory / "compressed_img.tar.gz") metadata_path = str(directory / "tokenized_finally.jsonl") images = dl_manager.iter_archive(image_path) img_formula_pair = {} with open(metadata_path, 'r', encoding='utf-8') as f: for line in f: single_json = json.loads(line) img_formula_pair[single_json['id']] = single_json['formula'] for img_path, img_obj in images: img_name = img_path.split('/')[-1] if img_name in img_formula_pair: idx += 1 # yield idx, { yield str(directory) + img_path, { "image": {"path": img_path, "bytes": img_obj.read()}, "latex_formula": img_formula_pair[img_name] } if self.config.name == 'raw_formulas': assert data_path is not None with open(data_path, 'r', encoding="utf-8") as f: for idx, line in enumerate(f): yield idx, { "latex_formula": json.loads(line)["formula"] }