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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", ".webp", ".bmp"]
_NAME = "nyanko7/danbooru2023"
_REVISION = "main"
class DanbooruDataset(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
# add number before name for sorting
datasets.BuilderConfig(name="full"),
]
def _info(self) -> DatasetInfo:
features = {
"image": datasets.Image(),
"post_id": datasets.Value("int64")
}
info = datasets.DatasetInfo(
features=datasets.Features(features),
supervised_keys=None,
citation="",
)
return info
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=["tar", ".tar"],
)
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], reverse=True)
for image_fname in image_fnames:
image_path = os.path.join(path, image_fname)
post_id = int(os.path.splitext(os.path.basename(image_fname))[0])
yield image_fname, {"post_id": post_id}
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