## Meta-Album Plant Village Dataset (Micro)
*
The Plant Village dataset(https://data.mendeley.com/datasets/tywbtsjrjv/1) contains camera photos of 17 crop leaves. The original image resolution is 256x256 px. This collection covers 26 plant diseases and 12 healthy plants. The leaves are removed from the plant and placed on gray or black background, in various lighting conditions. All images are captured on a variety of gray backgrounds, except Corn Common rust which has a black background. For the curated version, we exclude the irrelevant Background and Corn Common Rust classes from the original collection. Plant Village has a 2-level label hierarchy, the supercategory is the crop type and the category is the disease type. We have preprocessed Plant Village for Meta-Album by resizing a subset from the original dataset to 128x128 image size.
### Dataset Details
Meta Album ID: PLT_DIS.PLT_VIL
Meta Album URL: [https://meta-album.github.io/datasets/PLT_VIL.html](https://meta-album.github.io/datasets/PLT_VIL.html)
Domain ID: PLT_DIS
Domain Name: Plant Diseases
Dataset ID: PLT_VIL
Dataset Name: Plant Village
Short Description: Plant disease dataset
\# Classes: 20
\# Images: 800
Keywords: plants, plant diseases
Data Format: images
Image size: 128x128
License (original data release): CC0 1.0
License URL(original data release): https://data.mendeley.com/datasets/tywbtsjrjv/1
https://creativecommons.org/publicdomain/zero/1.0/
License (Meta-Album data release): CC0 1.0
License URL (Meta-Album data release): [https://creativecommons.org/publicdomain/zero/1.0/](https://creativecommons.org/publicdomain/zero/1.0/)
Source: Plant Village Dataset
Source URL: https://github.com/spMohanty/PlantVillage-Dataset
Original Author: Sharada Mohanty, David Hughes, and Marcel Salathe
Original contact: arunpandian@mamcet.com
Meta Album author: Phan Anh VU
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{G2019323,
title = {Identification of plant leaf diseases using a nine-layer deep convolutional neural network},
journal = {Computers & Electrical Engineering},
volume = {76},
pages = {323-338},
year = {2019},
issn = {0045-7906},
doi = {https://doi.org/10.1016/j.compeleceng.2019.04.011},
url = {https://www.sciencedirect.com/science/article/pii/S0045790619300023},
author = {Geetharamani G. and Arun Pandian J.},
keywords = {Artificial intelligence, Deep convolutional neural networks, Deep learning, Dropout, Image augmentation, Leaf diseases identification, Machine learning, Mini batch, Training epoch, Transfer learning},
}
```
### 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/44286) [[Extended]](https://www.openml.org/d/44321)