CIFAR100 small images classification dataset
- 원본 링크 : https://keras.io/api/datasets/cifar100/
- 최종 확인 : 2024-11-25
load_data
function
keras.datasets.cifar100.load_data(label_mode="fine")
Loads the CIFAR100 dataset.
This is a dataset of 50,000 32x32 color training images and 10,000 test images, labeled over 100 fine-grained classes that are grouped into 20 coarse-grained classes. See more info at the CIFAR homepage.
Arguments
- label_mode: one of
"fine"
,"coarse"
. If it is"fine"
, the category labels are the fine-grained labels, and if it is"coarse"
, the output labels are the coarse-grained superclasses.
Returns
- Tuple of NumPy arrays:
(x_train, y_train), (x_test, y_test)
.
x_train
: uint8
NumPy array of grayscale image data with shapes
(50000, 32, 32, 3)
, containing the training data. Pixel values range
from 0 to 255.
y_train
: uint8
NumPy array of labels (integers in range 0-99)
with shape (50000, 1)
for the training data.
x_test
: uint8
NumPy array of grayscale image data with shapes
(10000, 32, 32, 3)
, containing the test data. Pixel values range
from 0 to 255.
y_test
: uint8
NumPy array of labels (integers in range 0-99)
with shape (10000, 1)
for the test data.
Example
(x_train, y_train), (x_test, y_test) = keras.datasets.cifar100.load_data()
assert x_train.shape == (50000, 32, 32, 3)
assert x_test.shape == (10000, 32, 32, 3)
assert y_train.shape == (50000, 1)
assert y_test.shape == (10000, 1)