Source code for compressai.datasets.image

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from pathlib import Path

from PIL import Image
from torch.utils.data import Dataset

from compressai.registry import register_dataset


[docs] @register_dataset("ImageFolder") class ImageFolder(Dataset): """Load an image folder database. Training and testing image samples are respectively stored in separate directories: .. code-block:: - rootdir/ - train/ - img000.png - img001.png - test/ - img000.png - img001.png Args: root (string): root directory of the dataset transform (callable, optional): a function or transform that takes in a PIL image and returns a transformed version split (string): split mode ('train' or 'val') """ def __init__(self, root, transform=None, split="train"): splitdir = Path(root) / split if not splitdir.is_dir(): raise RuntimeError(f'Missing directory "{splitdir}"') self.samples = sorted(f for f in splitdir.iterdir() if f.is_file()) self.transform = transform def __getitem__(self, index): """ Args: index (int): Index Returns: img: `PIL.Image.Image` or transformed `PIL.Image.Image`. """ img = Image.open(self.samples[index]).convert("RGB") if self.transform: return self.transform(img) return img def __len__(self): return len(self.samples)