141 lines
4.7 KiB
Python
141 lines
4.7 KiB
Python
### Modify the ImageFolder function to get the image path in the data loader
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import torch.utils.data as data
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from PIL import Image
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import os
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import os.path
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from PIL import ImageFile
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ImageFile.LOAD_TRUNCATED_IMAGES = True ## used to handle some error when loading the special images.
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print('the data loader file has been modified')
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IMG_EXTENSIONS = ['.jpg', '.jpeg', '.png', '.ppm', '.bmp', '.pgm']
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def is_image_file(filename):
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"""Checks if a file is an image.
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Args:
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filename (string): path to a file
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Returns:
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bool: True if the filename ends with a known image extension
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"""
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filename_lower = filename.lower()
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return any(filename_lower.endswith(ext) for ext in IMG_EXTENSIONS)
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def find_classes(dir):
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classes = [d for d in os.listdir(dir) if os.path.isdir(os.path.join(dir, d))]
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classes.sort()
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class_to_idx = {classes[i]: i for i in range(len(classes))}
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return classes, class_to_idx
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def make_dataset(dir, class_to_idx):
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images = []
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dir = os.path.expanduser(dir)
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for target in sorted(os.listdir(dir)):
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d = os.path.join(dir, target)
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if not os.path.isdir(d):
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continue
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for root, _, fnames in sorted(os.walk(d)): # os.walk()是一种遍历目录数的函数
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for fname in sorted(fnames):
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if is_image_file(fname):
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path = os.path.join(root, fname)
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item = (path, class_to_idx[target])
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images.append(item)
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return images
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def pil_loader(path):
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# open path as file to avoid ResourceWarning (https://github.com/python-pillow/Pillow/issues/835)
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with open(path, 'rb') as f:
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img = Image.open(f)
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return img.convert('RGB')
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def accimage_loader(path):
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import accimage
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try:
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return accimage.Image(path)
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except IOError:
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# Potentially a decoding problem, fall back to PIL.Image
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return pil_loader(path)
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def default_loader(path):
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from torchvision import get_image_backend
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if get_image_backend() == 'accimage':
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return accimage_loader(path)
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else:
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return pil_loader(path)
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class ImageFolder_new(data.Dataset):
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"""A generic data loader where the images are arranged in this way: ::
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root/dog/xxx.png
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root/dog/xxy.png
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root/dog/xxz.png
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root/cat/123.png
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root/cat/nsdf3.png
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root/cat/asd932_.png
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Args:
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root (string): Root directory path.
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transform (callable, optional): A function/transform that takes in an PIL image
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and returns a transformed version. E.g, ``transforms.RandomCrop``
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target_transform (callable, optional): A function/transform that takes in the
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target and transforms it.
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loader (callable, optional): A function to load an image given its path.
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Attributes:
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classes (list): List of the class names.
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class_to_idx (dict): Dict with items (class_name, class_index).
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imgs (list): List of (image path, class_index) tuples
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"""
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def __init__(self, root, transform=None, target_transform=None,
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loader=default_loader):
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classes, class_to_idx = find_classes(root)
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imgs = make_dataset(root, class_to_idx)
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if len(imgs) == 0:
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raise (RuntimeError("Found 0 images in subfolders of: " + root + "\n"
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"Supported image extensions are: " + ",".join(
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IMG_EXTENSIONS)))
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self.root = root
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self.imgs = imgs
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self.classes = classes
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self.class_to_idx = class_to_idx
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self.transform = transform
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self.target_transform = target_transform
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self.loader = loader
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def __getitem__(self, index):
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"""
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Args:
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index (int): Index
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Returns:
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tuple: (image, target) where target is class_index of the target class.
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"""
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path, target = self.imgs[index]
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img = self.loader(path)
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if self.transform is not None:
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img = self.transform(img)
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if self.target_transform is not None:
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target = self.target_transform(target)
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return img, target, path
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def __len__(self):
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return len(self.imgs)
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def __repr__(self):
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fmt_str = 'Dataset ' + self.__class__.__name__ + '\n'
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fmt_str += ' Number of datapoints: {}\n'.format(self.__len__())
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fmt_str += ' Root Location: {}\n'.format(self.root)
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tmp = ' Transforms (if any): '
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fmt_str += '{0}{1}\n'.format(tmp, self.transform.__repr__().replace('\n', '\n' + ' ' * len(tmp)))
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tmp = ' Target Transforms (if any): '
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fmt_str += '{0}{1}'.format(tmp, self.target_transform.__repr__().replace('\n', '\n' + ' ' * len(tmp)))
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return fmt_str
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