Datasets:
Dataset Viewer
The dataset viewer is not available for this dataset.
Unexpected token '<', "<html>
<h"... is not valid JSON
Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Plant Leaf Disease Classification
A dataset for disease classification of leaves from Bitter Gourd, Bottle Gourd, Tomato, Eggplant, Cauliflower, and Cucumber. The dataset contains 12,786 images across 16 classes:
Images per class:
- Anthracnose: 601
- Anthracnose lesions: 535
- Black Rot: 560
- Downey mildew: 1,254
- Downy mildew: 1,076
- Eggplant Cercopora leaf spot: 723
- Eggplant begomovirus: 720
- Eggplant fresh leaf: 771
- Eggplant verticillium wilt: 730
- Fresh leaf: 2,122
- Fusarium wilt: 502
- Mosaic virus: 600
- Tomato Bacterial spot: 589
- Tomato Fresh leaf: 594
- Tomato leaf curl virus: 755
- Tomato spotted wilt: 654
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{hasan2024comprehensive,
title={Comprehensive smart smartphone image dataset for plant leaf disease detection and freshness assessment from Bangladesh vegetable fields},
author={Hasan, Mahamudul and Gani, Raiyan and Rashid, Mohammad Rifat Ahmmad and Tarin, Taslima Khan and Kamara, Raka and Mou, Mahbuba Yasmin and Rabbi, Sheikh Fajlay},
journal={Data in Brief},
volume={56},
pages={110775},
year={2024},
publisher={Elsevier}
}
Rashid, Mohammad Rifat Ahmmad; Tarin, Taslima Khan ; Kamara, Raka ; Mou, Mahbuba Yasmin ; Rabbi, Sheikh Fajlay ; Hasan, Mahamudul (2024), “Plant Leaf Freshness and Disease Detection Dataset From Bangladesh”, Mendeley Data, V3, doi: 10.17632/n67gctmjyj.3
- Downloads last month
- 25