def download_file(url, binary=True):
if sys.version_info < (3, ):
from urlparse import urlsplit
import urllib2
request = urllib2
error = urllib2
else:
from urllib.parse import urlsplit
from urllib import request, error
filename = os.path.basename(urlsplit(url)[2])
data_dir = get_writable_path(
os.path.join(os.path.dirname(__file__), 'data'))
path = os.path.join(data_dir, filename)
if os.path.exists(path):
return path
try:
data = request.urlopen(url, timeout=15).read()
with open(path, 'wb' if binary else 'w') as f:
f.write(data)
return path
except error.URLError:
msg = "could not download test file '{}'".format(url)
warnings.warn(msg, RuntimeWarning)
raise unittest.SkipTest(msg)
def download_file(url, binary=True):
if sys.version_info < (3,):
from urlparse import urlsplit
import urllib2
request = urllib2
error = urllib2
else:
from urllib.parse import urlsplit
from urllib import request, error
filename = os.path.basename(urlsplit(url)[2])
data_dir = get_writable_path(os.path.join(os.path.dirname(__file__), 'data'))
path = os.path.join(data_dir, filename)
if os.path.exists(path):
return path
try:
data = request.urlopen(url, timeout=15).read()
with open(path, 'wb' if binary else 'w') as f:
f.write(data)
return path
except error.URLError:
msg = "could not download test file '{}'".format(url)
warnings.warn(msg, RuntimeWarning)
raise unittest.SkipTest(msg)
def get_image_from_url(self, url, size=(300, 200)):
import os
from urllib.parse import urlsplit
from urllib import request
from PIL import Image
from torchvision import transforms
from torch._utils_internal import get_writable_path
filename = os.path.basename(urlsplit(url)[2])
data_dir = get_writable_path(os.path.join(os.path.dirname(__file__)))
path = os.path.join(data_dir, filename)
data = request.urlopen(url, timeout=15).read()
with open(path, 'wb') as f:
f.write(data)
image = Image.open(path).convert("RGB")
image = image.resize(size, Image.BILINEAR)
to_tensor = transforms.ToTensor()
return to_tensor(image)