Datasets:

Project-AgML
/

groundnut_leaf_disease_classification_2

dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': early_leaf_spot
            '1': healthy leaf
            '2': late leaf spot
            '3': nutrition deficiency
            '4': rust
  splits:
    - name: train
      num_bytes: 801090792
      num_examples: 3058
  download_size: 809834020
  dataset_size: 801090792
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

Groundnut Leaf Disease Classification 2

A dataset for disease classification of groundnut leaves. The dataset contains 3,058 images across 5 classes: early_leaf_spot, healthy leaf, late leaf spot, nutrition deficiency, rust.
Images per class:

early_leaf_spot: 885
healthy leaf: 929
late leaf spot: 689
nutrition deficiency: 329
rust: 226

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

Citation

@article{aishwarya2023dataset,
  title={Dataset of groundnut plant leaf images for classification and detection},
  author={Aishwarya, MP and Reddy, A Padmanabha},
  journal={Data in Brief},
  volume={48},
  pages={109185},
  year={2023},
  publisher={Elsevier}
}

Manvikar, Aishwarya; Reddy, Padmanabha (2023), “Dataset of groundnut plant leaf images for classification and detection”, Mendeley Data, V3, doi: 10.17632/22p2vcbxfk.3