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import io
import zipfile
from collections.abc import Sequence
from dataclasses import dataclass
from typing import TYPE_CHECKING, Union
import datasets
from datasets.data_files import DataFilesDict
from datasets.packaged_modules.imagefolder import imagefolder
if TYPE_CHECKING:
import numpy as np
import PIL.Image
logger = datasets.utils.logging.get_logger(__name__)
@dataclass
class Comic(datasets.Image):
"""Comic feature that extends Image feature for CBZ files."""
def encode_example(
self, value: Sequence[Union[str, bytes, dict, "np.ndarray", "PIL.Image.Image"]]
) -> dict:
"""Encode example into a format for Arrow.
Args:
value (`Sequence` of `str`, `bytes`, `dict`, `np.ndarray`, or
`PIL.Image.Image`):
Sequence of data passed as input to Comic feature. Each element can be:
- A path to a local image file
- Raw bytes of an image file
- A dictionary containing image data
- A numpy array representing an image
- A PIL Image object
Returns:
`dict` with "path" and "bytes" fields for each image in the sequence
"""
return [super().encode_example(img) for img in value]
def decode_example(
self, value: dict, token_per_repo_id=None
) -> list["PIL.Image.Image"]:
"""Decode example CBZ file into image data.
Args:
value (`str` or `dict`):
Either a string with absolute path to CBZ file, or a dictionary
with keys:
- `path`: String with absolute path to CBZ file.
- `bytes`: The bytes of the CBZ file.
token_per_repo_id (`dict`, *optional*):
To access and decode files from private repositories on the Hub.
Returns:
`List[PIL.Image.Image]`: List of images from CBZ
"""
if isinstance(value, str):
zip_file = value
else:
zip_file = (
io.BytesIO(value["bytes"]) if value.get("bytes") else value["path"]
)
with zipfile.ZipFile(zip_file, "r") as zip_ref:
return [
super().decode_example(img_file)
for img_file in sorted(zip_ref.namelist())
]
class NhentaiConfig(imagefolder.ImageFolderConfig):
"""BuilderConfig for NhentaiFolder."""
class Nhentai(imagefolder.ImageFolder):
BASE_COLUMN_NAME = "comic"
BASE_FEATURE = Comic
BUILDER_CONFIG_CLASS = NhentaiConfig
BUILDER_CONFIGS = [
NhentaiConfig(
name="nhentai",
description="Default configuration for nhentai dataset",
data_dir="data"
)
]
DEFAULT_CONFIG_NAME = "nhentai"
EXTENSIONS: list[str] = [".cbz"]
VERSION = datasets.Version("1.0.0")
def _info(self):
"""Returns the dataset metadata."""
return datasets.DatasetInfo(
description="Dataset of comic books in CBZ format",
features=datasets.Features(
{
"comic": Comic(),
"title": datasets.Value("string"),
"media_id": datasets.Value("int64"),
"num_favorites": datasets.Value("int64"),
"tag": datasets.Sequence(datasets.Value("string")),
"language": datasets.Sequence(datasets.Value("string")),
"artist": datasets.Sequence(datasets.Value("string")),
"category": datasets.Sequence(datasets.Value("string")),
"num_pages": datasets.Value("int64"),
"scanlator": datasets.Value("string"),
"group": datasets.Sequence(datasets.Value("string")),
"parody": datasets.Sequence(datasets.Value("string")),
"character": datasets.Sequence(datasets.Value("string")),
"epos": datasets.Value("int64"),
"file_name": datasets.Value("string"),
}
),
supervised_keys=None,
homepage="https://nhentai.net/",
)
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