| View source on GitHub | 
Loads the CIFAR10 dataset.
tf.keras.datasets.cifar10.load_data()
This is a dataset of 50,000 32x32 color training images and 10,000 test images, labeled over 10 categories. See more info at the CIFAR homepage.
| Label | Description | 
|---|---|
| 0 | airplane | 
| 1 | automobile | 
| 2 | bird | 
| 3 | cat | 
| 4 | deer | 
| 5 | dog | 
| 6 | frog | 
| 7 | horse | 
| 8 | ship | 
| 9 | truck | 
| 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 0-9) 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 0-9) with shape (10000, 1) for the test data.
(x_train, y_train), (x_test, y_test) = keras.datasets.cifar10.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)
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Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
    https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/keras/datasets/cifar10/load_data