Update README.md

README.md

@@ -1,9 +1,132 @@
 ---
+pretty_name: Ecoset
 license: cc
+source_datasets:
+- original
+task_categories:
+- image-classification
+- image
+task_ids:
+- multi-class-image-classification
+- other-other-image-classification
+- image-classification
+- other-image-classification
+paperswithcode_id: ecoset
+
 ---
 Ecoset is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 license (cc-by-nc-sa-2.0).
 
 
 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:
 
-```pip install datasets[s3]```
+```pip install datasets[s3]```
+
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+  
+  
+## Dataset Description
+
+- **Homepage:** [https://www.kietzmannlab.org/ecoset](https://www.kietzmannlab.org/ecoset/)
+- **Repository:** [https://codeocean.com/capsule/9570390/tree/v1](https://codeocean.com/capsule/9570390/tree/v1)
+- **Paper:** [https://doi.org/10.1073/pnas.2011417118](https://doi.org/10.1073/pnas.2011417118)
+- **Point of Contact:** [support@codeocean.com](support@codeocean.com.)
+
+
+### Dataset Summary
+
+Tired of all the dogs in ImageNet (ILSVRC)? Then ecoset is here for you. 1.5m images 
+from 565 basic level categories, chosen to be both (i) frequent in linguistic usage, 
+and (ii) rated by human observers as concrete (e.g. ‘table’ is concrete, ‘romance’ 
+is not). Here we collect resources associated with ecoset. This includes the dataset,
+trained deep neural network models, code to interact with them, and published papers 
+using it.
+
+
+### Supported Tasks and Leaderboards
+
+Ecoset is a large multi-class single-label object recognition image dataset (similar to ImageNet).
+
+
+## Dataset Structure
+
+
+We show detailed information for all the configurations of the dataset. Currently, there is only one setting (`Full`) available, containing all data.
+
+
+### Data Instances
+
+<details>
+  <summary>Click to expand the Data/size information for each language (deduplicated)</summary>
+
+#### Full
+
+- **Size of downloaded dataset files:** 155 GB
+- **Total amount of disk used:** 311 GB
+
+## Dataset Creation
+
+### Personal and Sensitive Information
+
+  # TODO
+  
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+  
+  # TODO
+
+### Discussion of Biases
+
+  # TODO
+
+### Other Known Limitations
+
+  # TODO
+
+## Additional Information
+
+### Dataset Curators
+
+The corpus was put together by # TODO.
+
+### Licensing Information
+
+    #TODO
+
+### Citation Information
+
+```
+@article{mehrer2021ecologically,
+  title={An ecologically motivated image dataset for deep learning yields better models of human vision},
+  author={Mehrer, Johannes and Spoerer, Courtney J and Jones, Emer C and Kriegeskorte, Nikolaus and Kietzmann, Tim C},
+  journal={Proceedings of the National Academy of Sciences},
+  volume={118},
+  number={8},
+  pages={e2011417118},
+  year={2021},
+  publisher={National Acad Sciences}
+}
+```
+
+### Contributions
+
+Thanks to  #TODO