CIFAR10
Published: 15 March 2024| Version 1 | DOI: 10.17632/kfjcsbhhss.1
Contributor:
Arpit RaiDescription
The CIFAR-10 and CIFAR-100 are labeled subsets of the 80 million tiny images dataset. They were collected by Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton. The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images. The dataset can be used in tensorflow and is available in tensorflow.keras.datasets.
Files
Steps to reproduce
1) Import tensorflow. 2) Run the statement in python: from tensorflow.keras.datasets import cifar10,cifar100 3) Run: (train_images, train_labels), (test_images, test_labels) = cifar10.load_data() to import cifar10 dataset and their corresponding labels in numpy format.
Categories
Image Classification