---
license: gpl-2.0
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Butterfly
          '1': Cat
          '2': Chicken
          '3': Cow
          '4': Dog
          '5': Elephant
          '6': Horse
          '7': Sheep
          '8': Spider
          '9': Squirrel
  splits:
  - name: train
    num_bytes: 300304734.49
    num_examples: 23554
  download_size: 318523927
  dataset_size: 300304734.49
---

# Rapidata Animals-10

We took this existing Animals-10 dataset from [kaggle](https://www.kaggle.com/datasets/alessiocorrado99/animals10) and cleaned it using Rapidata's crowd, as detailed in this [blog post](https://rapidata.ai/blog/animal-classification).

If you get value from this dataset and would like to see more in the future, please consider liking it.

## Dataset Details

10 classes: Butterfly, Cat, Chicken, Cow, Dog, Elephant, Horse, Sheep Spider, Squirrel
23554 Images

In total, 124k labels were collected by human annotators, so each image is cross-validated on average by 5 independent annotators.

- **Curated by:** @canwiper
- **Funded by:** [Rapidata](https://rapidata.ai)
- **License:** gpl-2.0

### Dataset Sources

[Blog post](https://rapidata.ai/blog/animal-classification) describing the setup and results of cleaning the original dataset.

## Dataset Structure

Structured by folders named after each of the 10 different animals.

### Source Data

https://www.kaggle.com/datasets/alessiocorrado99/animals10

## Dataset Contact

marian@rapidata.ai