chainer.datasets.get_cifar100(withlabel=True, ndim=3, scale=1.0, dtype=None)[source]

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 [0, scale].

This function returns the training set and the test set of the official CIFAR-100 dataset. If withlabel is 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 (3072,)

    • ndim == 3: the shape is (3, 32, 32)

  • scale (float) – Pixel value scale. If it is 1 (default), pixels are scaled to the interval [0, 1].

  • dtype – Data type of resulting image arrays. chainer.config.dtype is used by default (see Configuring Chainer).


A tuple of two datasets. If withlabel is True, both are TupleDataset instances. Otherwise, both datasets are arrays of images.