- chainer.datasets.get_cifar100(withlabel=True, ndim=3, scale=1.0, dtype=None)¶
Gets the CIFAR-100 dataset.
CIFAR-100 is a set of small natural images. Each example is an RGB color image of size 32x32, classified into 100 groups. In the original images, each component pixels is represented by one-byte unsigned integer. This function scales the components to floating point values in the interval
This function returns the training set and the test set of the official CIFAR-100 dataset. If
True, each dataset consists of tuples of images and labels, otherwise it only consists of images.
withlabel (bool) – If
True, it returns datasets with labels. In this case, each example is a tuple of an image and a label. Otherwise, the datasets only contain images.
ndim (int) –
Number of dimensions of each image. The shape of each image is determined depending on ndim as follows:
ndim == 1: the shape is
ndim == 3: the shape is
(3, 32, 32)
scale (float) – Pixel value scale. If it is 1 (default), pixels are scaled to the interval
dtype – Data type of resulting image arrays.
chainer.config.dtypeis used by default (see Configuring Chainer).
A tuple of two datasets. If
True, both are
TupleDatasetinstances. Otherwise, both datasets are arrays of images.