vision.datasets¶
Gluon provides pre-defined vision datasets functions in the mxnet.gluon.data.vision.datasets
module.
Dataset container.
Classes
|
MNIST handwritten digits dataset from http://yann.lecun.com/exdb/mnist |
|
A dataset of Zalando’s article images consisting of fashion products, |
|
CIFAR10 image classification dataset from https://www.cs.toronto.edu/~kriz/cifar.html |
|
CIFAR100 image classification dataset from https://www.cs.toronto.edu/~kriz/cifar.html |
|
A dataset wrapping over a RecordIO file containing images. |
|
A dataset for loading image files stored in a folder structure. |
-
class
mxnet.gluon.data.vision.datasets.
MNIST
(root='/home/jenkins_slave/.mxnet/datasets/mnist', train=True, transform=None)[source]¶ Bases:
mxnet.gluon.data.dataset._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) –
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='/home/jenkins_slave/.mxnet/datasets/fashion-mnist', train=True, transform=None)[source]¶ Bases:
mxnet.gluon.data.vision.datasets.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) –
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.
CIFAR10
(root='/home/jenkins_slave/.mxnet/datasets/cifar10', train=True, transform=None)[source]¶ Bases:
mxnet.gluon.data.dataset._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) –
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='/home/jenkins_slave/.mxnet/datasets/cifar100', fine_label=False, train=True, transform=None)[source]¶ Bases:
mxnet.gluon.data.vision.datasets.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) –
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.
ImageRecordDataset
(filename, flag=1, transform=None)[source]¶ Bases:
mxnet.gluon.data.dataset.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) –
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)[source]¶ Bases:
mxnet.gluon.data.dataset.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) –
A function that takes data and label and transforms them:
transform = lambda data, label: (data.astype(np.float32)/255, label)
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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