Datasets:
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- apache-2.0
multilinguality: []
size_categories:
- 1K<n<10K
source_datasets:
- extended
task_categories:
- image-classification
task_ids: []
paperswithcode_id: imagewoof
pretty_name: Imagewoof
Dataset Card for Imagewoof
Table of Contents
- Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://github.com/fastai/imagenette#imagewoof
- Repository: https://github.com/fastai/imagenette
- Leaderboard: https://paperswithcode.com/sota/image-classification-on-imagewoof
Dataset Summary
A smaller subset of 10 classes from Imagenet that aren't so easy to classify, since they're all dog breeds. This dataset was created by Jeremy Howard, and this repository is only there to share his work on this platform. The repository owner takes no credit of any kind in the creation, curation or packaging of the dataset.
Supported Tasks and Leaderboards
image-classification
: The dataset can be used to train a model for Image Classification.
Languages
The class labels in the dataset are in English.
Dataset Structure
Data Instances
A data point comprises an image URL and its classification label.
{
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=320x320 at 0x19FA12186D8>,
'label': 'Beagle',
}
Data Fields
image
: APIL.Image.Image
object containing the image.label
: the expected class label of the image.
Data Splits
train | validation | |
---|---|---|
imagewoof | 9025 | 3929 |
Dataset Creation
Curation Rationale
cf. https://huggingface.co/datasets/imagenet-1k#curation-rationale
Source Data
Initial Data Collection and Normalization
Imagewoof is a subset of ImageNet. Information about data collection of the source data can be found here.
Annotations
Annotation process
cf. https://huggingface.co/datasets/imagenet-1k#annotation-process
Who are the annotators?
cf. https://huggingface.co/datasets/imagenet-1k#who-are-the-annotators
Personal and Sensitive Information
cf. https://huggingface.co/datasets/imagenet-1k#personal-and-sensitive-information
Considerations for Using the Data
Social Impact of Dataset
cf. https://huggingface.co/datasets/imagenet-1k#social-impact-of-dataset
Discussion of Biases
cf. https://huggingface.co/datasets/imagenet-1k#discussion-of-biases
Other Known Limitations
cf. https://huggingface.co/datasets/imagenet-1k#other-known-limitations
Additional Information
Dataset Curators
cf. https://huggingface.co/datasets/imagenet-1k#dataset-curators and Jeremy Howard
Licensing Information
Citation Information
@software{Howard_Imagewoof_2019,
title={Imagewoof: a subset of 10 classes from Imagenet that aren't so easy to classify},
author={Jeremy Howard},
year={2019},
month={March},
publisher = {GitHub},
url = {https://github.com/fastai/imagenette#imagewoof}
}
Contributions
This dataset was created by Jeremy Howard and published on Github. It was then only integrated into HuggingFace Datasets by @frgfm.