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Use https for dataset download URLs where the host supports TLS #9631

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2 changes: 1 addition & 1 deletion torchvision/datasets/food101.py
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Expand Up @@ -32,7 +32,7 @@ class Food101(VisionDataset):
``torchvision.io.decode_image`` for decoding image data into tensors directly.
"""

_URL = "http://data.vision.ee.ethz.ch/cvl/food-101.tar.gz"
_URL = "https://data.vision.ee.ethz.ch/cvl/food-101.tar.gz"
_MD5 = "85eeb15f3717b99a5da872d97d918f87"

def __init__(
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7 changes: 5 additions & 2 deletions torchvision/datasets/mnist.py
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Expand Up @@ -36,6 +36,9 @@ class MNIST(VisionDataset):

mirrors = [
"https://ossci-datasets.s3.amazonaws.com/mnist/",
# yann.lecun.com has no TLS listener (connections to port 443 are refused), so this
# fallback mirror cannot be moved to https. It currently 404s for these files anyway;
# the checksummed https mirror above is the working source.
"http://yann.lecun.com/exdb/mnist/",
]

Expand Down Expand Up @@ -218,7 +221,7 @@ class FashionMNIST(MNIST):
downloaded again.
"""

mirrors = ["http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/"]
mirrors = ["https://fashion-mnist.s3.eu-central-1.amazonaws.com/"]

resources = [
("train-images-idx3-ubyte.gz", "8d4fb7e6c68d591d4c3dfef9ec88bf0d"),
Expand Down Expand Up @@ -246,7 +249,7 @@ class KMNIST(MNIST):
downloaded again.
"""

mirrors = ["http://codh.rois.ac.jp/kmnist/dataset/kmnist/"]
mirrors = ["https://codh.rois.ac.jp/kmnist/dataset/kmnist/"]

resources = [
("train-images-idx3-ubyte.gz", "bdb82020997e1d708af4cf47b453dcf7"),
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2 changes: 1 addition & 1 deletion torchvision/datasets/moving_mnist.py
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Expand Up @@ -25,7 +25,7 @@ class MovingMNIST(VisionDataset):
and returns a transformed version. E.g, ``transforms.RandomCrop``
"""

_URL = "http://www.cs.toronto.edu/~nitish/unsupervised_video/mnist_test_seq.npy"
_URL = "https://www.cs.toronto.edu/~nitish/unsupervised_video/mnist_test_seq.npy"

def __init__(
self,
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2 changes: 1 addition & 1 deletion torchvision/datasets/places365.py
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Expand Up @@ -38,7 +38,7 @@ class Places365(VisionDataset):
"""

_SPLITS = ("train-standard", "train-challenge", "val", "test")
_BASE_URL = "http://data.csail.mit.edu/places/places365/"
_BASE_URL = "https://data.csail.mit.edu/places/places365/"
# {variant: (archive, md5)}
_DEVKIT_META = {
"standard": ("filelist_places365-standard.tar", "35a0585fee1fa656440f3ab298f8479c"),
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2 changes: 1 addition & 1 deletion torchvision/datasets/semeion.py
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Expand Up @@ -25,7 +25,7 @@ class SEMEION(VisionDataset):

"""

url = "http://archive.ics.uci.edu/ml/machine-learning-databases/semeion/semeion.data"
url = "https://archive.ics.uci.edu/ml/machine-learning-databases/semeion/semeion.data"
filename = "semeion.data"
md5_checksum = "cb545d371d2ce14ec121470795a77432"

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2 changes: 1 addition & 1 deletion torchvision/datasets/stl10.py
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Expand Up @@ -30,7 +30,7 @@ class STL10(VisionDataset):
"""

base_folder = "stl10_binary"
url = "http://ai.stanford.edu/~acoates/stl10/stl10_binary.tar.gz"
url = "https://ai.stanford.edu/~acoates/stl10/stl10_binary.tar.gz"
filename = "stl10_binary.tar.gz"
tgz_md5 = "91f7769df0f17e558f3565bffb0c7dfb"
class_names_file = "class_names.txt"
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2 changes: 2 additions & 0 deletions torchvision/datasets/svhn.py
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Expand Up @@ -33,6 +33,8 @@ class SVHN(VisionDataset):

"""

# ufldl.stanford.edu serves a certificate valid only for ai.stanford.edu, so https
# fails hostname verification. Contents are checksummed below.
split_list = {
"train": [
"http://ufldl.stanford.edu/housenumbers/train_32x32.mat",
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2 changes: 2 additions & 0 deletions torchvision/datasets/widerface.py
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Expand Up @@ -49,6 +49,8 @@ class WIDERFace(VisionDataset):
("1GUCogbp16PMGa39thoMMeWxp7Rp5oM8Q", "dfa7d7e790efa35df3788964cf0bbaea", "WIDER_val.zip"),
("1HIfDbVEWKmsYKJZm4lchTBDLW5N7dY5T", "e5d8f4248ed24c334bbd12f49c29dd40", "WIDER_test.zip"),
]
# shuoyang1213.me serves a certificate for *.github.com, so https fails hostname
# verification. Contents are checksummed below.
ANNOTATIONS_FILE = (
"http://shuoyang1213.me/WIDERFACE/support/bbx_annotation/wider_face_split.zip",
"0e3767bcf0e326556d407bf5bff5d27c",
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