MangoLeafBD Dataset

Published: 30 August 2022| Version 1 | DOI: 10.17632/hxsnvwty3r.1
Sawkat Ali,


Type of data: 240x320 mango leaf images. Data format: JPG. Number of images: 4000 images. Of these, around 1800 are of distinct leaves, and the rest are prepared by zooming and rotating where deemed necessary. Diseases considered: Seven diseases, namely Anthracnose, Bacterial Canker, Cutting Weevil, Die Back, Gall Midge, Powdery Mildew, and Sooty Mould. Number of classes: Eight (including the healthy category). Distribution of instances: Each of the eight categories contains 500 images. How data are acquired: Captured from mango trees through the mobile phone camera. Data source locations: Four mango orchards of Bangladesh, namely Sher-e-Bangla Agricultural University orchard, Jahangir Nagar University orchard, Udaypur village mango orchard, and Itakhola village mango orchard. Where applicable: Suitable for distinguishing healthy and diseases leaves (two-class prediction) as well as for differentiating among various diseases (multi-class prediction).



Dhaka University, East West University


Machine Learning, Image Classification, Plant Diseases