Datasets:

mickylan2367
/

ParquetPractice


	import datasets
	from huggingface_hub import HfApi
	from datasets import DownloadManager, DatasetInfo
	from datasets.data_files import DataFilesDict
	import os
	import json

	# memo
	# train-00000-of-00001.parquet

	# ここに設定を記入
	_NAME = "mickylan2367/spectrogram_musicCaps"
	_EXTENSION = [".png"]
	_REVISION = "main"

	# _HOMEPAGE = "https://github.com/fastai/imagenette"
	# プログラムを置く場所が決まったら、ここにホームページURLつける
	_HOMEPAGE = "https://huggingface.co/datasets/mickylan2367/spectrogram_musicCaps"

	_DESCRIPTION = f"""\
	{_NAME} Datasets including spectrogram.png file from Google MusicCaps Datasets!
	Using for Project Learning...
	"""

	# え...なにこれ(;´･ω･)
	_IMAGES_DIR = "mickylan2367/images/data/"
	# _REPO = "https://huggingface.co/datasets/frgfm/imagenette/resolve/main/metadata"

	# 参考になりそうなURL集
	# https://huggingface.co/docs/datasets/v1.1.1/_modules/datasets/utils/download_manager.html
	# https://huggingface.co/datasets/animelover/danbooru2022/blob/main/danbooru2022.py
	# https://huggingface.co/datasets/food101/blob/main/food101.py
	# https://huggingface.co/docs/datasets/about_dataset_load


	class spectrogram_musicCapsConfig(datasets.BuilderConfig):
	"""Builder Config for spectrogram_MusicCaps"""

	def __init__(self, metadata_urls, **kwargs):
	"""BuilderConfig
	Args:
	data_url: `string`, url to download the zip file from.
	metadata_urls: dictionary with keys 'train' and 'validation' containing the archive metadata URLs
	**kwargs: keyword arguments forwarded to super.
	"""
	super(spectrogram_musicCapsConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs)
	# self.data_url = data_url
	self.metadata_urls = metadata_urls

	class spectrogram_musicCaps(datasets.GeneratorBasedBuilder):

	# データのサブセットはここで用意
	BUILDER_CONFIGS = [
	spectrogram_musicCapsConfig(
	name="MusicCaps data 0_10",
	description="Datasets from MusicCaps by Mikan",
	# data_url="https://huggingface.co/datasets/mickylan2367/spectrogram_musicCaps/blob/main/data/data0_10.zip",
	metadata_urls = {
	"train":"https://huggingface.co/datasets/mickylan2367/spectrogram_musicCaps/blob/main/data/metadata0_10.jsonl"
	}
	),

	spectrogram_musicCapsConfig(
	name="MusicCpas data 10_100",
	description="Datasets second action by Mikan",
	# data_url="https://huggingface.co/datasets/mickylan2367/spectrogram_musicCaps/blob/main/data/data10_200.zip",
	metadata_urls = {
	"train" : "https://huggingface.co/datasets/mickylan2367/spectrogram_musicCaps/blob/main/data/metadata10_200.jsonl"
	}
	)
	]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"image": datasets.Image(),
	"caption": datasets.Value("string")
	}
	),
	supervised_keys=("image", "caption"),
	homepage=_HOMEPAGE,
	# citation=_CITATION,
	# license=_LICENSE,
	# task_templates=[ImageClassification(image_column="image", label_column="label")],
	)

	# def _split_generators(self, dl_manager):
	# archive_path = dl_manager.download(self.config.data_url)
	# split_metadata_paths = dl_manager.download(self.config.metadata_urls)
	# return [
	# datasets.SplitGenerator(
	# name=datasets.Split.TRAIN,
	# gen_kwargs={
	# "images": dl_manager.iter_archive(archive_path),
	# "metadata_path": split_metadata_paths["train"],
	# }
	# )
	# ]

	def _split_generators(self, dl_manager: DownloadManager):
	# huggingfaceのディレクトリからデータを取ってくる
	hfh_dataset_info = HfApi().dataset_info(_NAME, revision=_REVISION, timeout=100.0)
	# archive_path = dl_manager.download(self.config.data_url)
	split_metadata_paths = dl_manager.download(self.config.metadata_urls)

	# **.zipのファイル名をDict型として取得？
	data_files = DataFilesDict.from_hf_repo(
	{datasets.Split.TRAIN: ["**"]},
	dataset_info=hfh_dataset_info,
	allowed_extensions=["zip", ".zip"],
	)

	gs = []
	for split, files in data_files.items():
	downloaded_files = dl_manager.download_and_extract(files) # zipファイルを解凍してファイル名リストにする。
	# 元のコードではzipファイルの中身を"filepath"としてそのまま_generate_exampleに引き渡している？
	gs.append(
	datasets.SplitGenerator(
	name = split,
	gen_kwargs={
	"images" : downloaded_files,
	"metadata_path": split_metadata_paths["train"]
	}
	)
	)
	return gs

	def _generate_examples(self, images, metadata_path):
	"""Generate images and captions for splits."""
	# with open(metadata_path, encoding="utf-8") as f:
	# files_to_keep = set(f.read().split("\n"))
	with open(metadata_path) as fin:
	for idx, line in enumerate(fin):
	data = json.loads(line)
	# file_path = os.path.join(data["file_name"])
	yield data["file_name"], {
	"image": data["file_name"],
	"caption":data["caption"]
	}