---
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