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)