Datasets:
cifar10

Task Categories: other
Size Categories: 10K<n<100K
Licenses: unknown
Language Creators: found
Annotations Creators: crowdsourced
Dataset Preview Go to dataset viewer
img (image)label (class label)
airplane
frog
airplane
bird
horse
bird
automobile
bird
deer
automobile
dog
frog
frog
cat
automobile
cat
dog
dog
ship
automobile
deer
bird
cat
bird
automobile
bird
ship
truck
dog
airplane
horse
frog
horse
frog
ship
ship
horse
deer
truck
automobile
bird
frog
dog
truck
deer
bird
dog
automobile
airplane
automobile
automobile
truck
airplane
horse
dog
cat
truck
frog
cat
cat
cat
deer
automobile
dog
truck
horse
horse
bird
truck
airplane
bird
ship
dog
truck
frog
horse
ship
deer
airplane
deer
truck
bird
horse
automobile
airplane
dog
automobile
ship
automobile
frog
dog
truck
horse
airplane
deer
dog
bird
cat
dog
dog

Dataset Card for CIFAR-10

Dataset Summary

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 is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the remaining images in random order, but some training batches may contain more images from one class than another. Between them, the training batches contain exactly 5000 images from each class.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

English

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

  • img: 32x32x3 image
  • label: 0-9 with the following correspondence
        0 airplane 
        1 automobile 
        2 bird 
        3 cat 
        4 deer
        5 dog
        6 frog
        7 horse
        8 ship
        9 truck
    

Data Splits

Train and Test

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

@TECHREPORT{Krizhevsky09learningmultiple,
    author = {Alex Krizhevsky},
    title = {Learning multiple layers of features from tiny images},
    institution = {},
    year = {2009}
}

Contributions

Thanks to @czabo for adding this dataset.

Models trained or fine-tuned on cifar10