| --- |
| 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 |
|
|
