Plant Village Dataset

Dataset details

Last updated: 15 Dec 2022
Meta Album ID PLT_DIS.PLT_VIL
Domain ID PLT_DIS
Domain Name Plant Diseases
Set Number 0
Dataset ID PLT_VIL
Dataset Name Plant Village
Short Description Plant disease dataset
Long Description 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.
# Classes 38
# Images 54305
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/
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/

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Dataset Info Datasheet

Download Dataset from OpenML

Dataset Version OpenML ID
Micro 44242 Download
Mini 44286 Download
Extended 44321 Download

Code to download dataset using OpenML API

      # import openml
      import openml
  
      # download dataset with DATASET_ID. DATASET_ID is OpenML ID
      dataset = openml.datasets.get_dataset(DATASET_ID)
  
      # display dataset info
      print(dataset.name)

Sample Images

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},
}
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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}
  }
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