Datasets:

Languages:
English
Size Categories:
1M<n<10M
Tags:
art
DOI:
License:
danbooru2022 / danbooru2022.py
animelover's picture
Update danbooru2022.py
38d1ff9
import os
import datasets
from huggingface_hub import HfApi
from datasets import DownloadManager, DatasetInfo
from datasets.data_files import DataFilesDict
_EXTENSION = [".png", ".jpg", ".jpeg"]
_NAME = "animelover/danbooru2022"
_REVISION = "main"
class DanbooruDataset(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
# add number before name for sorting
datasets.BuilderConfig(
name="0-sfw",
description="sfw subset",
),
datasets.BuilderConfig(
name="1-full",
description="full dataset",
),
datasets.BuilderConfig(
name="2-tags",
description="only tags of dataset",
),
]
def _info(self) -> DatasetInfo:
if self.config.name == "2-tags":
features = {
"tags": datasets.Value("string"),
"post_id": datasets.Value("int64")
}
else:
features = {
"image": datasets.Image(),
"tags": datasets.Value("string"),
"post_id": datasets.Value("int64")
}
return datasets.DatasetInfo(
description=self.config.description,
features=datasets.Features(features),
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", ".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],
reverse=True)
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()
if self.config.name == "0-sfw" and any(tag.strip() in nsfw_tags for tag in tags.split(",")):
continue
post_id = int(os.path.splitext(os.path.basename(image_fname))[0])
if self.config.name == "2-tags":
yield image_fname, {"tags": tags, "post_id": post_id}
else:
yield image_fname, {"image": image_path, "tags": tags, "post_id": post_id}
nsfw_tags = ["nude", "completely nude", "topless", "bottomless", "sex", "oral", "fellatio gesture", "tentacle sex",
"nipples", "pussy", "vaginal", "pubic hair", "anus", "ass focus", "penis", "cum", "condom", "sex toy"]