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from dataclasses import dataclass
from pathlib import Path
from typing import Optional
import pyarrow as pa
import datasets
logger = datasets.utils.logging.get_logger(__name__)
@dataclass
class ImageFolderConfig(datasets.BuilderConfig):
"""BuilderConfig for ImageFolder."""
features: Optional[datasets.Features] = None
@property
def schema(self):
return pa.schema(self.features.type) if self.features is not None else None
class ImageFolder(datasets.GeneratorBasedBuilder):
BUILDER_CONFIG_CLASS = ImageFolderConfig
def _info(self):
folder=None
if isinstance(self.config.data_files, str):
folder = self.config.data_files
elif isinstance(self.config.data_files, dict):
folder = self.config.data_files.get('train', None)
if folder is None:
raise RuntimeError()
classes = sorted([x.name.lower() for x in Path(folder).glob('*/**')])
return datasets.DatasetInfo(
features=datasets.Features(
{"image_file_path": datasets.Value("string"), "labels": datasets.Value("string")}
),
)
def _split_generators(self, dl_manager):
if not self.config.data_files:
raise ValueError(f"At least one data file must be specified, but got data_files={self.config.data_files}")
data_files = self.config.data_files
if isinstance(data_files, str):
folder = data_files
return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"archive_path": folder})]
splits = []
for split_name, folder in data_files.items():
splits.append(datasets.SplitGenerator(name=split_name, gen_kwargs={"archive_path": folder}))
return splits
def _generate_examples(self, archive_path):
logger.info("generating examples from = %s", archive_path)
extensions = {".jpg", ".jpeg", ".png", ".ppm", ".bmp", ".pgm", ".tif", ".tiff", ".webp"}
for i, path in enumerate(Path(archive_path).glob("**/*")):
if path.suffix in extensions:
yield i, {"image_file_path": path.as_posix(), "labels": path.parent.name.lower()} |