"""Utils for loading common datasets.
"""
"""
Copyright 2017 Parag K. Mital. See also NOTICE.md.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
import tensorflow.examples.tutorials.mnist.input_data as input_data
import os
import numpy as np
from cadl.dataset_utils import \
Dataset, cifar10_load, tiny_imagenet_load, gtzan_music_speech_load
[docs]def MNIST(one_hot=True, split=[1.0, 0.0, 0.0]):
"""Returns the MNIST dataset.
Returns
-------
mnist : DataSet
DataSet object w/ convenienve props for accessing
train/validation/test sets and batches.
Parameters
----------
one_hot : bool, optional
Description
split : list, optional
Description
"""
ds = input_data.read_data_sets('MNIST_data/', one_hot=one_hot)
return Dataset(
np.r_[ds.train.images, ds.validation.images, ds.test.images],
np.r_[ds.train.labels, ds.validation.labels, ds.test.labels],
split=split)
[docs]def CIFAR10(flatten=True, split=[1.0, 0.0, 0.0]):
"""Returns the CIFAR10 dataset.
Parameters
----------
flatten : bool, optional
Convert the 3 x 32 x 32 pixels to a single vector
split : list, optional
Description
Returns
-------
cifar : Dataset
Description
"""
# plt.imshow(np.transpose(np.reshape(
# cifar.train.images[10], (3, 32, 32)), [1, 2, 0]))
Xs, ys = cifar10_load()
if flatten:
Xs = Xs.reshape((Xs.shape[0], -1))
return Dataset(Xs, ys, split=split)
[docs]def CELEB(path='./img_align_celeba/'):
"""Attempt to load the files of the CELEB dataset.
Requires the files already be downloaded and placed in the `dst` directory.
The first 100 files can be downloaded from the cadl.utils function get_celeb_files
http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html
Parameters
----------
path : str, optional
Directory where the aligned/cropped celeb dataset can be found.
Returns
-------
files : list
List of file paths to the dataset.
"""
if not os.path.exists(path):
print('Could not find celeb dataset under {}.'.format(path))
print('Try downloading the dataset from the "Aligned and Cropped" '
'link located here (imgs/img_align_celeba.zip [1.34 GB]): '
'http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html '
'Or you can download the first 100 files using the '
'utils.get_celeb_files function.')
return None
else:
fs = [
os.path.join(path, f) for f in os.listdir(path)
if f.endswith('.jpg')
]
if len(fs) < 202598:
print(
'WARNING: Loaded only a small subset of the CELEB dataset. '
'If you want to use the entire 1.3 GB dataset, try downloading '
'the dataset from the "Aligned and Cropped" '
'link located here (imgs/img_align_celeba.zip [1.34 GB]): '
'http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html')
return fs
[docs]def TINYIMAGENET(path='./tiny_imagenet/'):
"""Attempt to load the files of the Tiny ImageNet dataset.
http://cs231n.stanford.edu/tiny-imagenet-200.zip
https://tiny-imagenet.herokuapp.com/
Parameters
----------
path : str, optional
Directory where the dataset can be found or else will be placed.
Returns
-------
files : list
List of file paths to the dataset.
labels : list
List of labels for each file (only training files have labels)
"""
files, labels = tiny_imagenet_load(path)
return files, labels
[docs]def GTZAN(path='./gtzan_music_speech'):
"""Load the GTZAN Music and Speech dataset.
Downloads the dataset if it does not exist into the dst directory.
Parameters
----------
path : str, optional
Description
Returns
-------
ds : Dataset
Dataset object with array of data in X and array of labels in Y
Deleted Parameters
------------------
dst : str, optional
Location of GTZAN Music and Speech dataset.
"""
return Dataset(*gtzan_music_speech_load())