enable ~ expression in datasets

torchvision/datasets/cifar.py

@@ -50,7 +50,7 @@ class CIFAR10(data.Dataset):
     def __init__(self, root, train=True,
                  transform=None, target_transform=None,
                  download=False):
-        self.root = root
+        self.root = os.path.expanduser(root)
         self.transform = transform
         self.target_transform = target_transform
         self.train = train  # training set or test set

torchvision/datasets/coco.py

@@ -44,7 +44,7 @@ class CocoCaptions(data.Dataset):
     """
     def __init__(self, root, annFile, transform=None, target_transform=None):
         from pycocotools.coco import COCO
-        self.root = root
+        self.root = os.path.expanduser(root)
         self.coco = COCO(annFile)
         self.ids = list(self.coco.imgs.keys())
         self.transform = transform

torchvision/datasets/folder.py

@@ -23,6 +23,7 @@ def find_classes(dir):
 
 def make_dataset(dir, class_to_idx):
     images = []
+    dir = os.path.expanduser(dir)
     for target in os.listdir(dir):
         d = os.path.join(dir, target)
         if not os.path.isdir(d):

torchvision/datasets/mnist.py

@@ -36,7 +36,7 @@ class MNIST(data.Dataset):
     test_file = 'test.pt'
 
     def __init__(self, root, train=True, transform=None, target_transform=None, download=False):
-        self.root = root
+        self.root = os.path.expanduser(root)
         self.transform = transform
         self.target_transform = target_transform
         self.train = train  # training set or test set

torchvision/datasets/phototour.py

@@ -49,7 +49,7 @@ class PhotoTour(data.Dataset):
     matches_files = 'm50_100000_100000_0.txt'
 
     def __init__(self, root, name, train=True, transform=None, download=False):
-        self.root = root
+        self.root = os.path.expanduser(root)
         self.name = name
         self.data_dir = os.path.join(root, name)
         self.data_down = os.path.join(root, '{}.zip'.format(name))

torchvision/datasets/stl10.py

@@ -44,7 +44,7 @@ class STL10(CIFAR10):
 
     def __init__(self, root, split='train',
                  transform=None, target_transform=None, download=False):
-        self.root = root
+        self.root = os.path.expanduser(root)
         self.transform = transform
         self.target_transform = target_transform
         self.split = split  # train/test/unlabeled set

torchvision/datasets/svhn.py

@@ -38,7 +38,7 @@ class SVHN(data.Dataset):
 
     def __init__(self, root, split='train',
                  transform=None, target_transform=None, download=False):
-        self.root = root
+        self.root = os.path.expanduser(root)
         self.transform = transform
         self.target_transform = target_transform
         self.split = split  # training set or test set or extra set

torchvision/datasets/utils.py

@@ -21,6 +21,7 @@ def check_integrity(fpath, md5):
 def download_url(url, root, filename, md5):
     from six.moves import urllib
 
+    root = os.path.expanduser(root)
     fpath = os.path.join(root, filename)
 
     try: