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## Meta-Album Cars Dataset (Extended) * The original Cars dataset ( was collected in 2013, and it contains more than 16 000 images from 196 classes of cars. Most images are on the road, but some have different backgrounds, and each image has only one car. Each class can have 48 to 136 images of variable resolutions. The preprocess version for this dataset was obtained by creating square images 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. In this case, cropping was not applied to create the square images since following this technique results in losing too much information from the cars. Then, the square images were resized into 128x128 px using an anti-aliasing filter. ### Dataset Details ![]( Meta Album ID: VCL.CRS Meta Album URL: []( Domain ID: VCL Domain Name: Vehicles Dataset ID: CRS Dataset Name: Cars Short Description: Dataset with images of different car models \# Classes: 196 \# Images: 16185 Keywords: vehicles, cars Data Format: images Image size: 128x128 License (original data release): ImageNet License License URL(original data release): License (Meta-Album data release): ImageNet License License URL (Meta-Album data release): []( Source: Stanford Cars Dataset Source URL: Original Author: Jonathan Krause, Michael Stark, Jia Deng, Li Fei-Fei Original contact: Meta Album author: Philip Boser Created Date: 01 March 2022 Contact Name: Ihsan Ullah Contact Email: Contact URL: []( ### Cite this dataset ``` @inproceedings{KrauseStarkDengFei-Fei_3DRR2013, title = {3D Object Representations for Fine-Grained Categorization}, booktitle = {4th International IEEE Workshop on 3D Representation and Recognition (3dRR-13)}, year = {2013}, address = {Sydney, Australia}, author = {Jonathan Krause and Michael Stark and Jia Deng and Li Fei-Fei} } ``` ### 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 = {}, year = {2022} } ``` ### More For more information on the Meta-Album dataset, please see the [[NeurIPS 2022 paper]]( For details on the dataset preprocessing, please see the [[supplementary materials]]( Supporting code can be found on our [[GitHub repo]]( Meta-Album on Papers with Code [[Meta-Album]]( ### Other versions of this dataset [[Micro]]( [[Mini]](

3 features

CATEGORY (target)string196 unique values
0 missing
FILE_NAMEstring16185 unique values
0 missing
SUPER_CATEGORYnumeric0 unique values
16185 missing

19 properties

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

1 tasks

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