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--- |
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pretty_name: Ecoset |
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license: cc |
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source_datasets: |
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- original |
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task_categories: |
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- image-classification |
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- image |
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task_ids: |
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- multi-class-image-classification |
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- other-other-image-classification |
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- image-classification |
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- other-image-classification |
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paperswithcode_id: ecoset |
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--- |
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In order to work with ecoset, please make sure to install the s3 compatible version of huggingface datasets, which should include the 's3fs', `botocore` and 'boto3' modules: |
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```pip install datasets[s3]``` |
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## Table of Contents |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Dataset Creation](#dataset-creation) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Social Impact of Dataset](#social-impact-of-dataset) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Other Known Limitations](#other-known-limitations) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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- [Contributions](#contributions) |
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## Dataset Description |
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- **Homepage:** [https://www.kietzmannlab.org/ecoset](https://www.kietzmannlab.org/ecoset/) |
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- **Repository:** [https://codeocean.com/capsule/9570390/tree/v1](https://codeocean.com/capsule/9570390/tree/v1) |
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- **Paper:** [https://doi.org/10.1073/pnas.2011417118](https://doi.org/10.1073/pnas.2011417118) |
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- **Point of Contact:** [support@codeocean.com](support@codeocean.com.) |
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### Dataset Summary |
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Tired of all the dogs in ImageNet (ILSVRC)? Then ecoset is here for you. 1.5m images |
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from 565 basic level categories, chosen to be both (i) frequent in linguistic usage, |
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and (ii) rated by human observers as concrete (e.g. ‘table’ is concrete, ‘romance’ |
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is not). Here we collect resources associated with ecoset. This includes the dataset, |
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trained deep neural network models, code to interact with them, and published papers |
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using it. |
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### Supported Tasks and Leaderboards |
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Ecoset is a large multi-class single-label object recognition image dataset (similar to ImageNet). |
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## Dataset Structure |
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We show detailed information for all the configurations of the dataset. Currently, there is only one setting (`Full`) available, containing all data. |
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### Data Instances |
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<details> |
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<summary>Click to expand the Data/size information for each language (deduplicated)</summary> |
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#### Full |
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- **Size of downloaded dataset files:** 155 GB |
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- **Total amount of disk used:** 311 GB |
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## Dataset Creation |
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### Personal and Sensitive Information |
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# TODO |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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# TODO |
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### Discussion of Biases |
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# TODO |
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### Other Known Limitations |
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# TODO |
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## Additional Information |
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### Dataset Curators |
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The corpus was put together by # TODO. |
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### Licensing Information |
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Ecoset is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 license (cc-by-nc-sa-2.0). |
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### Citation Information |
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``` |
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@article{mehrer2021ecologically, |
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title={An ecologically motivated image dataset for deep learning yields better models of human vision}, |
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author={Mehrer, Johannes and Spoerer, Courtney J and Jones, Emer C and Kriegeskorte, Nikolaus and Kietzmann, Tim C}, |
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journal={Proceedings of the National Academy of Sciences}, |
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volume={118}, |
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number={8}, |
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pages={e2011417118}, |
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year={2021}, |
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publisher={National Acad Sciences} |
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} |
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``` |
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### Contributions |
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Thanks to #TODO |
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