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| """A modified image folder class | |
| We modify the official PyTorch image folder (https://github.com/pytorch/vision/blob/master/torchvision/datasets/folder.py) | |
| so that this class can load images from both current directory and its subdirectories. | |
| """ | |
| import numpy as np | |
| import torch.utils.data as data | |
| from PIL import Image | |
| import os | |
| import os.path | |
| 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) or os.path.islink(dir), '%s is not a valid directory' % dir | |
| for root, _, fnames in sorted(os.walk(dir, followlinks=True)): | |
| 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))] | |
| def default_loader(path): | |
| return Image.open(path).convert('RGB') | |
| class ImageFolder(data.Dataset): | |
| def __init__(self, root, transform=None, return_paths=False, | |
| loader=default_loader): | |
| imgs = make_dataset(root) | |
| if len(imgs) == 0: | |
| raise(RuntimeError("Found 0 images in: " + root + "\n" | |
| "Supported image extensions are: " + ",".join(IMG_EXTENSIONS))) | |
| self.root = root | |
| self.imgs = imgs | |
| self.transform = transform | |
| self.return_paths = return_paths | |
| self.loader = loader | |
| def __getitem__(self, index): | |
| path = self.imgs[index] | |
| img = self.loader(path) | |
| if self.transform is not None: | |
| img = self.transform(img) | |
| if self.return_paths: | |
| return img, path | |
| else: | |
| return img | |
| def __len__(self): | |
| return len(self.imgs) | |