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dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Anthracnose
'1': Bacterial_Canker
'2': Cutting_Weevil
'3': Die_Back
'4': Gall_Midge
'5': Healthy
'6': Powdery_Mildew
'7': Sooty_Mold
splits:
- name: train
num_bytes: 144381309
num_examples: 4000
download_size: 140834790
dataset_size: 144381309
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Mango Leaf Disease Classification
A dataset for image classification of Mango Leaf Disease Classification. The dataset contains 4,000 images across 8 classes: Anthracnose, Bacterial_Canker, Cutting_Weevil, Die_Back, Gall_Midge, Healthy, Powdery_Mildew, Sooty_Mold.
Images per class:
- Anthracnose: 500
- Bacterial_Canker: 500
- Cutting_Weevil: 500
- Die_Back: 500
- Gall_Midge: 500
- Healthy: 500
- Powdery_Mildew: 500
- Sooty_Mold: 500
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{ahmed2023mangoleafbd,
title={MangoLeafBD: A comprehensive image dataset to classify diseased and healthy mango leaves},
author={Ahmed, Sarder Iftekhar and Ibrahim, Muhammad and Nadim, Md and Rahman, Md Mizanur and Shejunti, Maria Mehjabin and Jabid, Taskeed and Ali, Md Sawkat},
journal={Data in Brief},
volume={47},
pages={108941},
year={2023},
publisher={Elsevier}
}
```
Ali, Sawkat; Ibrahim, Muhammad ; Ahmed, Sarder Iftekhar ; Nadim, Md. ; Mizanur, Mizanur Rahman; Shejunti, Maria Mehjabin ; Jabid, Taskeed (2022), “MangoLeafBD Dataset”, Mendeley Data, V1, doi: 10.17632/hxsnvwty3r.1
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