Datasets:

Project-AgML
/

soybean_leaf_disease_classification

dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': Bacterial leaf Blight
            '1': Dry_leaf
            '2': Healthy
            '3': Root_images
            '4': Septoria_Brown_Spot
            '5': Vein Necrosis
  splits:
    - name: train
      num_bytes: 2839590431
      num_examples: 1176
  download_size: 2848562521
  dataset_size: 2839590431
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - image-classification
size_categories:
  - 1K<n<10K

Soybean Leaf Disease Classification

A dataset for disease classification of soybean leaves. The dataset contains 1,176 images across 6 classes: Bacterial leaf Blight, Dry_leaf, Healthy, Root_images, Septoria_Brown_Spot, Vein Necrosis.
Images per class:

Bacterial leaf Blight: 226
Dry_leaf: 230
Healthy: 288
Root_images: 10
Septoria_Brown_Spot: 284
Vein Necrosis: 138

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

Citation

@article{kotwal2024india,
  title={An India soyabean dataset for identification and classification of diseases using computer-vision algorithms},
  author={Kotwal, Jameer and Kashyap, Ramgopal and Pathan, Mohd Shafi},
  journal={Data in Brief},
  volume={53},
  pages={110216},
  year={2024}
}

Kotwal, Jameer ; kashyap, Ramgopal (2023), “ An India soyabean leaf dataset”, Mendeley Data, V1, doi: 10.17632/bshkvgbzpt.1