Data
Meta_Album_BRD_Extended

Meta_Album_BRD_Extended

active ARFF CC BY-NC 4.0 Visibility: public Uploaded 08-11-2022 by Meta Album
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
## Meta-Album Birds Dataset (Extended) * When Meta-Album was created, the Birds dataset(https://www.kaggle.com/datasets/gpiosenka/100-bird-species) contained images of 315 bird species, but now it has increased the number of species to 450. It has more than 49 000 images, each with a resolution of 224x224 px. All the images have their natural background, which can lead to bias since, for example, some birds are frequently found in water backgrounds. Additionally, the dataset is imbalanced regarding the ratio of male species images to female species images. The preprocessed version distributed in Meta-Album is made from the original dataset by resizing all the images to a resolution of 128x128 px using an anti-aliasing filter. ### Dataset Details ![](https://meta-album.github.io/assets/img/samples/BRD.png) Meta Album ID: LR_AM.BRD Meta Album URL: [https://meta-album.github.io/datasets/BRD.html](https://meta-album.github.io/datasets/BRD.html) Domain ID: LR_AM Domain Name: Large Animals Dataset ID: BRD Dataset Name: Birds Short Description: Birds dataset for image classification \# Classes: 315 \# Images: 49054 Keywords: birds, animals Data Format: images Image size: 128x128 License (original data release): CC0 Public Domain License URL(original data release): https://www.kaggle.com/gpiosenka/100-bird-species https://creativecommons.org/publicdomain/zero/1.0/ License (Meta-Album data release): CC0 Public Domain License URL (Meta-Album data release): [https://creativecommons.org/publicdomain/zero/1.0/](https://creativecommons.org/publicdomain/zero/1.0/) Source: BIRDS 400 - SPECIES IMAGE CLASSIFICATION Source URL: https://www.kaggle.com/gpiosenka/100-bird-species Original Author: Gerald Piosenka Original contact: https://www.kaggle.com/gpiosenka/contact Meta Album author: Dustin Carrion 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{birds, title={BIRDS 400 - SPECIES IMAGE CLASSIFICATION}, author={Gerald Piosenka}, url={https://www.kaggle.com/datasets/gpiosenka/100-bird-species}, 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 [[Micro]](https://www.openml.org/d/44241) [[Mini]](https://www.openml.org/d/44285)

3 features

CATEGORY (target)string315 unique values
0 missing
FILE_NAMEstring49054 unique values
0 missing
SUPER_CATEGORYnumeric0 unique values
49054 missing

19 properties

49054
Number of instances (rows) of the dataset.
3
Number of attributes (columns) of the dataset.
315
Number of distinct values of the target attribute (if it is nominal).
49054
Number of missing values in the dataset.
49054
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.
0.53
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
259
Number of instances belonging to the most frequent class.
0.25
Percentage of instances belonging to the least frequent class.
124
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
Define a new task