---
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

```bibtex
@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