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---
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 |