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ANIMAL (ANIMAL10N) Dataset

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Visualization of the Animal10n dataset in the Deep Lake UI

ANIMAL10N dataset

What is ANIMAL10N Dataset?

ANIMAL10N dataset contains ten classes of animals with a total of 50,000 training and testing pictures. The following animals are included in the dataset: lynx, guinea pig, jaguar, cat, hamster, cheetah, coyote, chimpanzee, wolf, and orangutan. Noisy labels were introduced spontaneously by human error. The estimated noise rate is 8%.

Download ANIMAL10N Dataset in Python

Instead of downloading the ANIMAL10N dataset in Python, you can effortlessly load it in Python via our Deep Lake open-source with just one line of code.

Load ANIMAL10N Dataset Training Subset in Python

				
					import deeplake
ds = deeplake.load("hub://activeloop/animal10n-train")

Load ANIMAL10N Dataset Testing Subset in Python

				
					import deeplake
ds = deeplake.load("hub://activeloop/animal10n-test")

ANIMAL10N Dataset Structure

ANIMAL10N Data Fields
  • images: tensor containing the image.
  • labels: tensor to represent the category of animal in the image.
ANIMAL10N Data Splits

How to use Animal10n Dataset with PyTorch and TensorFlow in Python

Train a model on ANIMAL10N dataset with PyTorch in Python

Let’s use Deep Lake built-in PyTorch one-line dataloader to connect the data to the compute:

				
					dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False)
Train a model on Animal10n dataset with TensorFlow in Python
				
					dataloader = ds.tensorflow()

Additional Information about ANIMAL10N Dataset

ANIMAL10N Dataset Description

  • Homepage: https://dm.kaist.ac.kr/datasets/animal-10n/
  • Repository: N/A
  • Paper: Introduced by Song, Hwanjun and Kim, Minseok and Lee, Jae-Gil. in {SELFIE}: Refurbishing Unclean Samples for Robust Deep Learning
  • Point of Contact: N/A
Animal10n Dataset Curators

Song, Hwanjun and Kim,Minseok and Lee, Jae-Gil.

ANIMAL10N Dataset Licensing Information
Deep Lake users may have access to a variety of publicly available datasets. We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have a license to use the datasets. It is your responsibility to determine whether you have permission to use the datasets under their license.
 
If you’re a dataset owner and do not want your dataset to be included in this library, please get in touch through a GitHub issue. Thank you for your contribution to the ML community!
ANIMAL10N Dataset Citation Information
				
					@inproceedings{song2019selfie,
title={{SELFIE}: Refurbishing Unclean Samples for Robust Deep Learning},
author={Song, Hwanjun and Kim, Minseok and Lee, Jae-Gil},
booktitle={ICML},
year={2019} }

ANIMAL10N Dataset FAQs

What classes does ANIMAL10N dataset contain?
  • lynx
  • guinea pig
  • jaguar
  • cat
  • hamster
  • cheetah
  • coyote
  • chimpanzee
  • wolf
  • orangutan
What is the ANIMAL10N dataset for Python?

There are ten classes with a total of 50,000 training and testing pictures. Please note that in ANIMAL10N, noisy labels were introduced spontaneously by human error, with an estimated noise rate of 8%.

How to download the ANIMAL10N dataset in Python?

You can load the ANIMAL10N dataset fast with one line of code using the open-source package Activeloop Deep Lake in Python. See detailed instructions on how to load the ANIMAL10N dataset training subset and Animal10N testing subset in Python.

How can I use the ANIMAL10N dataset in PyTorch or TensorFlow?

You can stream the ANIMAL10N dataset while training a model in PyTorch or TensorFlow with one line of code using the open-source package Activeloop Deep Lake in Python. See detailed instructions on how to train a model on the ANIMAL10N dataset with PyTorch in Python or train a model on the ANIMAL10N dataset with TensorFlow in Python.

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