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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} |