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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 |