metadata
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': citrus_canker
'1': citrus_greening
'2': citrus_mealybugs
'3': die_back
'4': foliage_damaged
'5': healthy_leaf
'6': powdery_mildew
'7': shot_hole
'8': spiny_whitefly
'9': yellow_dragon
'10': yellow_leaves
splits:
- name: train
num_bytes: 2923333962
num_examples: 5813
download_size: 3681067331
dataset_size: 2923333962
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
Orange Leaf Disease Classification
A dataset for disease classification of orange leaves. The dataset contains 5,813 images across 11 classes: citrus_canker, citrus_greening, citrus_mealybugs, die_back, foliage_damaged, healthy_leaf, powdery_mildew, shot_hole, spiny_whitefly, yellow_dragon, yellow_leaves.
Images per class:
- citrus_canker: 588
- citrus_greening: 254
- citrus_mealybugs: 603
- die_back: 642
- foliage_damaged: 632
- healthy_leaf: 547
- powdery_mildew: 598
- shot_hole: 560
- spiny_whitefly: 672
- yellow_dragon: 407
- yellow_leaves: 310
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{emon2024multi,
title={Multi-format open-source sweet orange leaf dataset for disease detection, classification, and analysis},
author={Emon, Yousuf Rayhan and Ahad, Md Taimur and Rabbany, Golam},
journal={Data in Brief},
volume={55},
pages={110713},
year={2024},
publisher={Elsevier}
}
Emon, Yousuf Rayhan; Ahad, Md Taimur; Khan, Shahrin ; Mustofa, Sumaya (2025), “Multi-format open-source sweet orange leaf dataset for disease detection, classification, and analysis.”, Mendeley Data, V2, doi: 10.17632/f7cr74mwpj.2