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---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Anthracnose
'1': Black spots
'2': Brown clumps
'3': Brown spots
'4': Downy mildew
'5': Flea Beetles
'6': Healthy
'7': Mealy bugs
'8': Mosaic Viruses
'9': Powdery mildew
'10': Scale insect
'11': Sooty mold
'12': Spiders
'13': Translucent lesion
splits:
- name: train
num_bytes: 27269465966
num_examples: 5472
download_size: 26001048140
dataset_size: 27269465966
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
---
# Agarwood Leaf Disease Classification
A dataset for disease classification of agarwood leaves. The dataset contains 5,472 images across 14 classes: Anthracnose, Black spots, Brown clumps, Brown spots, Downy mildew, Flea Beetles, Healthy, Mealy bugs, Mosaic Viruses, Powdery mildew, Scale insect, Sooty mold, Spiders, Translucent lesion.
Images per class:
- Anthracnose: 232
- Black spots: 674
- Brown clumps: 118
- Brown spots: 1,055
- Downy mildew: 674
- Flea Beetles: 115
- Healthy: 415
- Mealy bugs: 391
- Mosaic Viruses: 398
- Powdery mildew: 478
- Scale insect: 37
- Sooty mold: 41
- Spiders: 410
- Translucent lesion: 434
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{shafik2025comprehensive,
title={A comprehensive dataset of agarwood tree (Aquilaria Malaccensis) leaf images for disease analysis in Brunei Darussalam},
author={Shafik, Wasswa and Sukri, Rahayu Sukmaria and Liyanage, Chandratilak De Silva and Zaini, Nurul Hazlina and Yu, Soon Boon and Ruslan, Mohammad Amiruddin and Apong, Rosyzie Anna Awg Haji Mohd and Tufail, Ali},
journal={Data in Brief},
pages={112227},
year={2025},
publisher={Elsevier}
}
```
Wasswa, S., Rahayu, S. binti H. S., Liyanage, C. D. S., Nurul Hazlina, H. Z., Soon Boon, Y., Mohammad Amiruddin, R., Rosyzie Anna Awg, H. M. A.& Ali, T. (2025). Agarwood Leaf Image Dataset for Pest and Disease Analysis in Real-World Environment [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.14842100