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ANIMAL (ANIMAL10N) Dataset
Load ANIMAL10N with one line of code. ANIMAL10N has 10 classes of animals for classification. Stream ANIMAL10N while training models in PyTorch & TensorFlow.
Visualization of the Animal10n dataset on the Activeloop Platform

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 a 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 open-source package Hub with just one line of code.

Load ANIMAL10N Dataset Training Subset in Python

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import hub
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ds = hub.load("hub://activeloop/animal10-train")
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Load ANIMAL10N Dataset Testing Subset in Python

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import hub
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ds = hub.load("hub://activeloop/animal10-test")
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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 Hub's built-in PyTorch one-line dataloader to connect the data to the compute:
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dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False)
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Train a model on Animal10n dataset with TensorFlow in Python

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dataloader = ds.tensorflow()
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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

Hub 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

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@inproceedings{song2019selfie,
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title={{SELFIE}: Refurbishing Unclean Samples for Robust Deep Learning},
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author={Song, Hwanjun and Kim, Minseok and Lee, Jae-Gil},
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booktitle={ICML},
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year={2019} }
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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 ANIMAL10N dataset fast with one line of code using the open-source package Activeloop Hub in Python. See detailed instructions on how to load ANIMAL10N dataset training subset and Animal10N testing subset in Python.

How can I use 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 Hub in Python. See detailed instructions on how to train a model on ANIMAL10N dataset with PyTorch in Python or train a model on ANIMAL10N dataset with TensorFlow in Python.