mxnet.gluon.data.vision.datasets¶

Dataset container.

Classes

`CIFAR10`([root, train, transform])	CIFAR10 image classification dataset from https://www.cs.toronto.edu/~kriz/cifar.html
`CIFAR100`([root, fine_label, train, transform])	CIFAR100 image classification dataset from https://www.cs.toronto.edu/~kriz/cifar.html
`FashionMNIST`([root, train, transform])	A dataset of Zalando's article images consisting of fashion products, a drop-in replacement of the original MNIST dataset from https://github.com/zalandoresearch/fashion-mnist
`ImageFolderDataset`(root[, flag, transform, ...])	A dataset for loading image files stored in a folder structure.
`ImageListDataset`([root, imglist, flag])	A dataset for loading image files specified by a list of entries.
`ImageRecordDataset`(filename[, flag, transform])	A dataset wrapping over a RecordIO file containing images.
`MNIST`([root, train, transform])	MNIST handwritten digits dataset from http://yann.lecun.com/exdb/mnist

class mxnet.gluon.data.vision.datasets.CIFAR10(root=None, train=True, transform=None)[source]¶

Bases: _DownloadedDataset

CIFAR10 image classification dataset from https://www.cs.toronto.edu/~kriz/cifar.html

Each sample is an image (in 3D NDArray) with shape (32, 32, 3).

Parameters:

root (str, default $MXNET_HOME/datasets/cifar10) – Path to temp folder for storing data.
train (bool, default True) – Whether to load the training or testing set.
transform (function, default None) –
DEPRECATED FUNCTION ARGUMENTS. A user defined callback that transforms each sample. For example:
```
transform=lambda data, label: (data.astype(np.float32)/255, label)
```

class mxnet.gluon.data.vision.datasets.CIFAR100(root=None, fine_label=False, train=True, transform=None)[source]¶

Bases: CIFAR10

CIFAR100 image classification dataset from https://www.cs.toronto.edu/~kriz/cifar.html

Each sample is an image (in 3D NDArray) with shape (32, 32, 3).

Parameters:

root (str, default $MXNET_HOME/datasets/cifar100) – Path to temp folder for storing data.
fine_label (bool, default False) – Whether to load the fine-grained (100 classes) or coarse-grained (20 super-classes) labels.
train (bool, default True) – Whether to load the training or testing set.
transform (function, default None) –
DEPRECATED FUNCTION ARGUMENTS. A user defined callback that transforms each sample. For example:
```
transform=lambda data, label: (data.astype(np.float32)/255, label)
```

class mxnet.gluon.data.vision.datasets.FashionMNIST(root=None, train=True, transform=None)[source]¶

Bases: MNIST

A dataset of Zalando’s article images consisting of fashion products, a drop-in replacement of the original MNIST dataset from https://github.com/zalandoresearch/fashion-mnist

Each sample is an image (in 3D NDArray) with shape (28, 28, 1).

Parameters:

root (str, default $MXNET_HOME/datasets/fashion-mnist') – Path to temp folder for storing data.
train (bool, default True) – Whether to load the training or testing set.
transform (function, default None) –
DEPRECATED FUNCTION ARGUMENTS. A user defined callback that transforms each sample. For example:
```
transform=lambda data, label: (data.astype(np.float32)/255, label)
```

class mxnet.gluon.data.vision.datasets.ImageFolderDataset(root, flag=1, transform=None, classes=None)[source]¶

Bases: Dataset

A dataset for loading image files stored in a folder structure.

like:

root/car/0001.jpg
root/car/xxxa.jpg
root/car/yyyb.jpg
root/bus/123.jpg
root/bus/023.jpg
root/bus/wwww.jpg

Parameters:

root (str) – Path to root directory.
flag ({0, 1}, default 1) – If 0, always convert loaded images to greyscale (1 channel). If 1, always convert loaded images to colored (3 channels).
transform (callable, default None) –
DEPRECATED FUNCTION ARGUMENTS. A function that takes data and label and transforms them:
```
transform = lambda data, label: (data.astype(np.float32)/255, label)
```
classes (sequence of str, optional) – Explicit class folder names. When provided, labels follow this order instead of the alphabetical order of folders found under root.

synsets¶

List of class names. synsets[i] is the name for the integer label i

Type:: list

items¶

List of all images in (filename, label) pairs.

Type:: list of tuples

class mxnet.gluon.data.vision.datasets.ImageListDataset(root='.', imglist=None, flag=1)[source]¶

Bases: Dataset

A dataset for loading image files specified by a list of entries.

like:

# if written to text file *.lst
0       0       root/car/0001.jpg
1       0       root/car/xxxa.jpg
2       0       root/car/yyyb.jpg
3       1       root/bus/123.jpg
4       1       root/bus/023.jpg
5       1       root/bus/wwww.jpg

# if as a pure list, each item is a list [imagelabel: float or list of float, imgpath]
[[0, root/car/0001.jpg]
 [0, root/car/xxxa.jpg]
 [0, root/car/yyyb.jpg]
 [1, root/bus/123.jpg]
 [1, root/bus/023.jpg]
 [1, root/bus/wwww.jpg]]

Parameters:

root (str) – Path to root directory.
imglist (str or list) – Specify the path of imglist file or a list directly
flag ({0, 1}, default 1) – If 0, always convert loaded images to greyscale (1 channel). If 1, always convert loaded images to colored (3 channels).

items¶

List of all images in (filename, label) pairs.

Type:: list of tuples

class mxnet.gluon.data.vision.datasets.ImageRecordDataset(filename, flag=1, transform=None)[source]¶

Bases: RecordFileDataset

A dataset wrapping over a RecordIO file containing images.

Each sample is an image and its corresponding label.

Parameters:

filename (str) – Path to rec file.
flag ({0, 1}, default 1) – If 0, always convert images to greyscale. If 1, always convert images to colored (RGB).
transform (function, default None) –
DEPRECATED FUNCTION ARGUMENTS. A user defined callback that transforms each sample. For example:
```
transform=lambda data, label: (data.astype(np.float32)/255, label)
```

class mxnet.gluon.data.vision.datasets.MNIST(root=None, train=True, transform=None)[source]¶

Bases: _DownloadedDataset

MNIST handwritten digits dataset from http://yann.lecun.com/exdb/mnist

Each sample is an image (in 3D NDArray) with shape (28, 28, 1).

Parameters:

root (str, default $MXNET_HOME/datasets/mnist) – Path to temp folder for storing data.
train (bool, default True) – Whether to load the training or testing set.
transform (function, default None) –
DEPRECATED FUNCTION ARGUMENTS. A user defined callback that transforms each sample. For example:
```
transform=lambda data, label: (data.astype(np.float32)/255, label)
```