Datasetpublic

rajnandinib/CIFAR10

🖼️ CIFAR10 (Extracted from PyTorch Vision) 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. ℹ️ Dataset Details 📖 Dataset Description 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 classes are completely mutually exclusive. There… See the full description on the dataset page: https://huggingface.co/datasets/rajnandinib/CIFAR10.

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Dataset Card

🖼️ CIFAR10 (Extracted from PyTorch Vision)

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.

ℹ️ Dataset Details

📖 Dataset Description

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 classes are completely mutually exclusive. There is no overlap between automobiles and trucks. "Automobile" includes sedans, SUVs, things of that sort. "Truck" includes only big trucks. Neither includes pickup trucks.

📂 Dataset Structure

Each data point is a pair:

—image: A visual captured (stored as a PIL Image).
—label: The corresponding label (an integer representing the class).

🚀 How to Use this Dataset

python

from datasets import load_dataset

dataset = load_dataset('p2pfl/CIFAR10')

🗄️ Source Data

Auto-generated from PyTorch Vision, please check the original CIFAR10 for more info.

📜 License

mit