DEVELOPMENT...      {
    "data_id": "44305",
    "name": "Meta_Album_AWA_Mini",
    "exact_name": "Meta_Album_AWA_Mini",
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    "description": "## **Meta-Album Animals with Attributes Dataset (Mini)**\n***\nThe original Animals with Attributes 2 (AWA) dataset (https:\/\/cvml.ist.ac.at\/AwA2\/) was designed to benchmark transfer-learning algorithms, in particular attribute base classification and zero-shot learning. It has more than 37 000 images from 50 animals, where each animal corresponds to a class. The images of this dataset were collected from public sources, such as Flickr, in 2016, considering only images licensed for free use and redistribution. Each class can have 100 to 1 645 images with a resolution from 100x100 to 1 893x1 920 px. To preprocess this dataset, we cropped the images from either side to make them square. In case an image has a resolution lower than 128 px, the squared images are done by either duplicating the top and bottom-most 3 rows or the left and right most 3 columns based on the orientation of the original image. Lastly, the square images are resized into 128x128 px using an anti-aliasing filter.  \n\n\n\n### **Dataset Details**\n![](https:\/\/meta-album.github.io\/assets\/img\/samples\/AWA.png)\n\n**Meta Album ID**: LR_AM.AWA  \n**Meta Album URL**: [https:\/\/meta-album.github.io\/datasets\/AWA.html](https:\/\/meta-album.github.io\/datasets\/AWA.html)  \n**Domain ID**: LR_AM  \n**Domain Name**: Large Aninamls  \n**Dataset ID**: AWA  \n**Dataset Name**: Animals with Attributes  \n**Short Description**: Mamals dataset for image classification  \n**\\# Classes**: 50  \n**\\# Images**: 2000  \n**Keywords**: mammals, animals,  \n**Data Format**: images  \n**Image size**: 128x128  \n\n**License (original data release)**: Creative Commons  \n**License URL(original data release)**: https:\/\/cvml.ist.ac.at\/AwA2\/\n \n**License (Meta-Album data release)**: Creative Commons  \n**License URL (Meta-Album data release)**: [https:\/\/cvml.ist.ac.at\/AwA2\/](https:\/\/cvml.ist.ac.at\/AwA2\/)  \n\n**Source**: Animals with attributes 2  \n**Source URL**: https:\/\/cvml.ist.ac.at\/AwA2\/  \n  \n**Original Author**: Christoph H. Lampert, Bernt Schiele, Zeynep Akata  \n**Original contact**: chl@ist.ac.at  \n\n**Meta Album author**: Dustin Carrion  \n**Created Date**: 01 March 2022  \n**Contact Name**: Ihsan Ullah  \n**Contact Email**: meta-album@chalearn.org  \n**Contact URL**: [https:\/\/meta-album.github.io\/](https:\/\/meta-album.github.io\/)  \n\n\n\n### **Cite this dataset**\n```\n@ARTICLE{8413121,\n  author={Xian, Yongqin and Lampert, Christoph H. and Schiele, Bernt and Akata, Zeynep},\n  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, \n  title={Zero-Shot Learning - A Comprehensive Evaluation of the Good, the Bad and the Ugly}, \n  year={2019},\n  volume={41},\n  number={9},\n  pages={2251-2265},\n  doi={10.1109\/TPAMI.2018.2857768}\n}\n\n```\n\n\n### **Cite Meta-Album**\n```\n@inproceedings{meta-album-2022,\n        title={Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification},\n        author={Ullah, Ihsan and Carrion, Dustin and Escalera, Sergio and Guyon, Isabelle M and Huisman, Mike and Mohr, Felix and van Rijn, Jan N and Sun, Haozhe and Vanschoren, Joaquin and Vu, Phan Anh},\n        booktitle={Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track},\n        url = {https:\/\/meta-album.github.io\/},\n        year = {2022}\n    }\n```\n\n\n### **More**\nFor more information on the Meta-Album dataset, please see the [[NeurIPS 2022 paper]](https:\/\/meta-album.github.io\/paper\/Meta-Album.pdf)  \nFor details on the dataset preprocessing, please see the [[supplementary materials]](https:\/\/openreview.net\/attachment?id=70_Wx-dON3q&name=supplementary_material)  \nSupporting code can be found on our [[GitHub repo]](https:\/\/github.com\/ihsaan-ullah\/meta-album)  \nMeta-Album on Papers with Code [[Meta-Album]](https:\/\/paperswithcode.com\/dataset\/meta-album)  \n\n\n\n### **Other versions of this dataset**\n[[Micro]](https:\/\/www.openml.org\/d\/44275)  [[Extended]](https:\/\/www.openml.org\/d\/44338)  ",
    "format": "arff",
    "uploader": "Amber ",
    "uploader_id": 30980,
    "visibility": "public",
    "creator": "\"Ihsan Ullah\"",
    "contributor": null,
    "date": "2022-10-28 16:27:37",
    "update_comment": null,
    "last_update": "2022-10-28 16:27:37",
    "licence": "CC BY-NC 4.0",
    "status": "active",
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    "url": "https:\/\/api.openml.org\/data\/download\/22111005\/dataset",
    "default_target_attribute": "CATEGORY",
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            "## **Meta-Album Animals with Attributes Dataset (Mini)** The original Animals with Attributes 2 (AWA) dataset (https:\/\/cvml.ist.ac.at\/AwA2\/) was designed to benchmark transfer-learning algorithms, in particular attribute base classification and zero-shot learning. It has more than 37 000 images from 50 animals, where each animal corresponds to a class. The images of this dataset were collected from public sources, such as Flickr, in 2016, considering only images licensed for free use and redistr "
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