{ "data_id": "44305", "name": "Meta_Album_AWA_Mini", "exact_name": "Meta_Album_AWA_Mini", "version": 1, "version_label": null, "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": "Meta Album", "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", "error_message": null, "url": "https:\/\/api.openml.org\/data\/download\/22111005\/dataset", "kaggle_url": null, "default_target_attribute": "CATEGORY", "row_id_attribute": null, "ignore_attribute": null, "runs": 0, "suggest": { "input": [ "Meta_Album_AWA_Mini", "## **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 " ], "weight": 5 }, "qualities": { "NumberOfInstances": 2000, "NumberOfFeatures": 3, "NumberOfClasses": 50, "NumberOfMissingValues": 2000, "NumberOfInstancesWithMissingValues": 2000, "NumberOfNumericFeatures": 1, "NumberOfSymbolicFeatures": 0, "PercentageOfBinaryFeatures": 0, "PercentageOfInstancesWithMissingValues": 100, "PercentageOfMissingValues": 33.33333333333333, "AutoCorrelation": 1, "PercentageOfNumericFeatures": 33.33333333333333, "Dimensionality": 0.0015, "PercentageOfSymbolicFeatures": 0, "MajorityClassPercentage": 2, "MajorityClassSize": 40, "MinorityClassPercentage": 2, "MinorityClassSize": 40, "NumberOfBinaryFeatures": 0 }, "tags": [], "features": [ { "name": "CATEGORY", "index": "1", "type": "string", "distinct": "50", "missing": "0", "target": "1" }, { "name": "FILE_NAME", "index": "0", "type": "string", "distinct": "2000", "missing": "0" }, { "name": "SUPER_CATEGORY", "index": "2", "type": "numeric", "distinct": "0", "missing": "2000", "min": "2147483647", "max": "0", "mean": "0", "stdev": "0" } ], "nr_of_issues": 0, "nr_of_downvotes": 0, "nr_of_likes": 0, "nr_of_downloads": 0, "total_downloads": 0, "reach": 0, "reuse": 0, "impact_of_reuse": 0, "reach_of_reuse": 0, "impact": 0 }