from vergeml.utils import download_files
from vergeml.utils import Error
import shutil
import os.path
import zipfile
import tarfile
def download(env):
"""The Street View House Numbers (SVHN) Dataset.
SVHN is a real-world image dataset for developing machine
learning and object recognition algorithms with minimal
requirement on data preprocessing and formatting. It can be
seen as similar in flavor to MNIST (e.g., the images are of
small cropped digits), but incorporates an order of magnitude
more labeled data (over 600,000 digit images) and comes from a
significantly harder, unsolved, real world problem
(recognizing digits and numbers in natural scene images). SVHN
is obtained from house numbers in Google Street View images.
Authors:
Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco,
Bo Wu, Andrew Y. Ng
Reading Digits in Natural Images with Unsupervised Feature
Learning NIPS Workshop on Deep Learning and Unsupervised
Feature Learning 2011.
http://ufldl.stanford.edu/housenumbers/nips2011_housenumbers.pdf
For more information visit: http://ufldl.stanford.edu/housenumbers/"""
urls = ["http://ufldl.stanford.edu/housenumbers/train_32x32.mat",
"http://ufldl.stanford.edu/housenumbers/test_32x32.mat"]
samples_dir = env.get('base.samples_dir')
print("Downloading SVHN to {}.".format(samples_dir))
src_dir = download_files(urls, dir=env.get('base.cache_dir'))
for file in ("train_32x32.mat", "test_32x32.mat", ):
shutil.copy(os.path.join(src_dir, file), samples_dir)
shutil.rmtree(src_dir)
print("Finished downloading SVHN.")
download.__info__ = [
('Samples', '73K'),
('Test Samples', '26K'),
('Type', 'Labeled Images'),
('Resolution', '32x32 rgb'),
('Size', '235.3 MB')
]
