folder.py

# ---------------------------------------
# Modified from torchvision by QIU Tian
# ---------------------------------------

__all__ = ['ImageFolder']

import os
import os.path
from typing import Any, Callable, cast, Dict, List, Optional, Tuple
from typing import Union

from ._base_ import BaseDataset

IMG_EXTENSIONS = ('.jpg', '.jpeg', '.png', '.ppm', '.bmp', '.pgm', '.tif', '.tiff', '.webp')


def has_file_allowed_extension(filename: str, extensions: Union[str, Tuple[str, ...]]) -> bool:
    return filename.lower().endswith(extensions if isinstance(extensions, str) else tuple(extensions))


def is_image_file(filename: str) -> bool:
    return has_file_allowed_extension(filename, IMG_EXTENSIONS)


def find_classes(directory: str) -> Tuple[List[str], Dict[str, int]]:
    classes = sorted(entry.name for entry in os.scandir(directory) if entry.is_dir())
    if not classes:
        raise FileNotFoundError(f"Couldn't find any class folder in {directory}.")

    class_to_idx = {cls_name: i for i, cls_name in enumerate(classes)}
    return classes, class_to_idx


def make_dataset(
        directory: str,
        class_to_idx: Optional[Dict[str, int]] = None,
        extensions: Optional[Union[str, Tuple[str, ...]]] = None,
        is_valid_file: Optional[Callable[[str], bool]] = None,
) -> List[Tuple[str, int]]:
    """Generates a list of samples of a form (path_to_sample, class).
    Note: The class_to_idx parameter is here optional and will use the logic of the ``find_classes`` function
    by default.
    """
    directory = os.path.expanduser(directory)

    if class_to_idx is None:
        _, class_to_idx = find_classes(directory)

    elif not class_to_idx:
        raise ValueError("'class_to_index' must have at least one entry to collect any samples.")

    both_none = extensions is None and is_valid_file is None
    both_something = extensions is not None and is_valid_file is not None
    if both_none or both_something:
        raise ValueError("Both extensions and is_valid_file cannot be None or not None at the same time")

    if extensions is not None:
        def is_valid_file(x: str) -> bool:
            return has_file_allowed_extension(x, extensions)  # type: ignore[arg-type]

    is_valid_file = cast(Callable[[str], bool], is_valid_file)

    instances = []
    available_classes = set()
    for target_class in sorted(class_to_idx.keys()):
        class_index = class_to_idx[target_class]
        target_dir = os.path.join(directory, target_class)
        if not os.path.isdir(target_dir):
            continue
        for root, _, fnames in sorted(os.walk(target_dir, followlinks=True)):
            for fname in sorted(fnames):
                path = os.path.join(root, fname)
                if is_valid_file(path):
                    item = path, class_index
                    instances.append(item)

                    if target_class not in available_classes:
                        available_classes.add(target_class)

    empty_classes = set(class_to_idx.keys()) - available_classes
    if empty_classes:
        msg = f"Found no valid file for the classes {', '.join(sorted(empty_classes))}. "
        if extensions is not None:
            msg += f"Supported extensions are: {extensions if isinstance(extensions, str) else ', '.join(extensions)}"
        raise FileNotFoundError(msg)

    return instances


class ImageFolder(BaseDataset):
    def __init__(self, root, split, transform=None, target_transform=None, batch_transform=None, loader=None,
                 is_valid_file=None):
        super().__init__(root, split, transform, target_transform, batch_transform, loader)
        extensions = IMG_EXTENSIONS if is_valid_file is None else None
        split_folder = os.path.join(self.root, split)
        classes, class_to_idx = self.find_classes(split_folder)
        samples = self.make_dataset(split_folder, class_to_idx, extensions, is_valid_file)

        self.classes = classes
        self.class_to_idx = class_to_idx
        self.samples = samples
        self.targets = [s[1] for s in samples]

    @staticmethod
    def make_dataset(
            directory: str,
            class_to_idx: Dict[str, int],
            extensions: Optional[Tuple[str, ...]] = None,
            is_valid_file: Optional[Callable[[str], bool]] = None,
    ) -> List[Tuple[str, int]]:
        if class_to_idx is None:
            # prevent potential bug since make_dataset() would use the class_to_idx logic of the
            # find_classes() function, instead of using that of the find_classes() method, which
            # is potentially overridden and thus could have a different logic.
            raise ValueError("The class_to_idx parameter cannot be None.")
        return make_dataset(directory, class_to_idx, extensions=extensions, is_valid_file=is_valid_file)

    def find_classes(self, directory: str) -> Tuple[List[str], Dict[str, int]]:
        return find_classes(directory)

    def __getitem__(self, index: int) -> Tuple[Any, Any]:
        """
        Args:
            index (int): Index

        Returns:
            tuple: (image, target) where target is class_index of the target class.
        """
        path, target = self.samples[index]
        image = self.loader(path, format="RGB")

        if self.transform is not None:
            image = self.transform(image)

        if self.target_transform is not None:
            target = self.target_transform(target)

        return image, target

    def __len__(self) -> int:
        return len(self.samples)