Data
Meta_Album_SPT_Micro

Meta_Album_SPT_Micro

active ARFF CC BY-NC 4.0 Visibility: public Uploaded 11-10-2022 by Meta Album
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## Meta-Album Sports Actions Dataset (Micro) * The 100-Sports dataset(https://www.kaggle.com/datasets/gpiosenka/sports-classification) is a collection of sports images covering 73 different sports. Images are 224x224x3 in size and in .jpg format. Images were gathered from internet searches. The images were scanned with a duplicate image detector program and all duplicate images were removed. For Meta-Album, the dataset is preprocessed and images are resized into 128x128 pixels using Open-CV. ### Dataset Details ![](https://meta-album.github.io/assets/img/samples/SPT.png) Meta Album ID: HUM_ACT.SPT Meta Album URL: [https://meta-album.github.io/datasets/SPT.html](https://meta-album.github.io/datasets/SPT.html) Domain ID: HUM_ACT Domain Name: Human Actions Dataset ID: SPT Dataset Name: Sports Actions Short Description: 100 Sports Dataset \# Classes: 20 \# Images: 800 Keywords: human actions, sports Data Format: images Image size: 128x128 License (original data release): CC0 1.0 Public Domain License URL(original data release): https://www.kaggle.com/gpiosenka/sports-classification https://creativecommons.org/publicdomain/zero/1.0/ License (Meta-Album data release): CC0 1.0 Public Domain License URL (Meta-Album data release): [https://creativecommons.org/publicdomain/zero/1.0/](https://creativecommons.org/publicdomain/zero/1.0/) Source: 100 Sports Image Classification Source URL: https://www.kaggle.com/gpiosenka/sports-classification Original Author: Gerald Piosenka Original contact: https://www.kaggle.com/gpiosenka/contact Meta Album author: Jilin He Created Date: 01 March 2022 Contact Name: Ihsan Ullah Contact Email: meta-album@chalearn.org Contact URL: [https://meta-album.github.io/](https://meta-album.github.io/) ### Cite this dataset ``` @article{100-sports, title={100 Sports Image Classification}, author={Gerald Piosenka}, url={https://www.kaggle.com/datasets/gpiosenka/sports-classification}, publisher= {Kaggle} } ``` ### Cite Meta-Album ``` @inproceedings{meta-album-2022, title={Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification}, 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}, booktitle={Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track}, url = {https://meta-album.github.io/}, year = {2022} } ``` ### More For more information on the Meta-Album dataset, please see the [[NeurIPS 2022 paper]](https://meta-album.github.io/paper/Meta-Album.pdf) For details on the dataset preprocessing, please see the [[supplementary materials]](https://openreview.net/attachment?id=70_Wx-dON3q&name=supplementary_material) Supporting code can be found on our [[GitHub repo]](https://github.com/ihsaan-ullah/meta-album) Meta-Album on Papers with Code [[Meta-Album]](https://paperswithcode.com/dataset/meta-album) ### Other versions of this dataset [[Mini]](https://www.openml.org/d/44284) [[Extended]](https://www.openml.org/d/44319)

3 features

CATEGORY (target)string20 unique values
0 missing
FILE_NAMEstring800 unique values
0 missing
SUPER_CATEGORYnumeric0 unique values
800 missing

19 properties

800
Number of instances (rows) of the dataset.
3
Number of attributes (columns) of the dataset.
20
Number of distinct values of the target attribute (if it is nominal).
800
Number of missing values in the dataset.
800
Number of instances with at least one value missing.
1
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
100
Percentage of instances having missing values.
1
Average class difference between consecutive instances.
33.33
Percentage of missing values.
0
Number of attributes divided by the number of instances.
33.33
Percentage of numeric attributes.
5
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
40
Number of instances belonging to the most frequent class.
5
Percentage of instances belonging to the least frequent class.
40
Number of instances belonging to the least frequent class.
0
Number of binary attributes.

1 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: CATEGORY
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