---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Bud_Root_Dropping
          '1': Bud_Rot
          '2': Gray_Leaf_Spot
          '3': Leaf_Rot
          '4': Stem_Bleeding
  splits:
  - name: train
    num_bytes: 1096196081
    num_examples: 5798
  download_size: 1022205386
  dataset_size: 1096196081
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---


# Coconut Tree Disease Classification

A dataset for disease classification of coconut trees. The dataset contains 5,798 images across 5 classes: Bud_Root_Dropping, Bud_Rot, Gray_Leaf_Spot, Leaf_Rot, Stem_Bleeding.  
Images per class:
- Bud_Root_Dropping: 514
- Bud_Rot: 470
- Gray_Leaf_Spot: 2,135
- Leaf_Rot: 1,673
- Stem_Bleeding: 1,006

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

## Citation

```bibtex
@article{thite2023coconut,
  title={Coconut (Cocos nucifera) tree disease dataset: A dataset for disease detection and classification for machine learning applications},
  author={Thite, Sandip and Suryawanshi, Yogesh and Patil, Kailas and Chumchu, Prawit},
  journal={Data in Brief},
  volume={51},
  pages={109690},
  year={2023},
  publisher={Elsevier}
}
```

PATIL, Kailas; Thite, Sandip; Suryawanshi, Yogesh; chumchu, prawit (2023), “Coconut Tree Disease Dataset”, Mendeley Data, V1, doi: 10.17632/gh56wbsnj5.1