import os import datasets import urllib.request import csv _CITATION = """\ @InProceedings{huggingface:dataset, title = {diffusion train set}, } """ _DESCRIPTION = """\ This is a dataset that image data and caption txt """ _HOMEPAGE = "" _LICENSE = "" _VERSION = "0.0.1" _URL = "data/" _URLS = { "train": _URL + 'train1_dataset.csv', "reg": _URL + 'reg1_dataset.csv', } task_list = [ "train", "reg", ] class taskConfig(datasets.BuilderConfig): def __init__(self, **kwargs): super().__init__(version=datasets.Version("1.0.0"), **kwargs) class imgdataset(datasets.GeneratorBasedBuilder): BUILDER_CONFIGS = [ taskConfig( name=task_name, ) for task_name in task_list ] def _info(self): features = datasets.Features( { "folder_name" : datasets.Value("string"), "Class_name": datasets.Value("string"), "file_name": datasets.Value("string"), "file_id": datasets.Value("string") } ) return datasets.DatasetInfo( description=_DESCRIPTION, features=features, supervised_keys=None, version=_VERSION, citation=_CITATION, ) def _split_generators(self, dl_manager: datasets.DownloadManager): downloaded_files = dl_manager.download_and_extract(_URLS) task_name = self.config.name return [ datasets.SplitGenerator(datasets.Split.TRAIN, { "filepath": downloaded_files[task_name] }), ] def _generate_examples(self, filepath): """This function returns the examples in the raw (text) form.""" with open(filepath, encoding="utf-8") as f: data = csv.DictReader(f) key = 0 for row in data: yield key, { "folder_name" : row['folder_name'], "Class_name": row['Class_name'], "file_name": row['file_name'], "file_id": row['file_id'] } folder_name = row['folder_name'] class_name =row['Class_name'] file_name = row['file_name'] url =row['file_id'] path = os.path.join('./',folder_name,class_name,file_name) folder = os.path.join('./',folder_name,class_name) if not os.path.isdir(folder): #폴더가 존재하지 않는다면 폴더 생성 os.makedirs(folder) urllib.request.urlretrieve(url, path) key += 1