dataloader.py

import torch.utils.data as data

from PIL import Image
import os

IMG_EXTENSIONS = [
    '.jpg', '.JPG', '.jpeg', '.JPEG',
    '.png', '.PNG', '.ppm', '.PPM', '.bmp', '.BMP',
    '.tif', '.TIF', '.tiff', '.TIFF',
]


def is_image_file(filename):
    return any(filename.endswith(extension) for extension in IMG_EXTENSIONS)


def make_dataset(dir, max_dataset_size=float("inf")):
    images = []
    assert os.path.isdir(dir), '%s is not a valid directory' % dir

    for root, _, fnames in sorted(os.walk(dir)):
        for fname in fnames:
            if is_image_file(fname):
                path = os.path.join(root, fname)
                images.append(path)
    return images[:min(max_dataset_size, len(images))]


class ImageFolder(data.Dataset):

    def __init__(self, root, transform=None):
        imgs = make_dataset(root)
        self.root = root
        self.imgs = imgs
        self.transform = transform

    def __getitem__(self, index):
        path = self.imgs[index]
        img = Image.open(path).convert('RGB')
        img = self.transform(img)
        return img

    def __len__(self):
        return len(self.imgs)