Datasets:
File size: 1,275 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Healthy
'1': MLN
'2': MSV
splits:
- name: train
num_bytes: 7911968327
num_examples: 9356
download_size: 7528242288
dataset_size: 7911968327
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 10K<n<100K
---
# Maize Disease Classification
A dataset for disease classification of Maize leaves. The dataset contains 9,356 images across 3 classes: Healthy, MLN, MSV.
Images per class:
- Healthy: 3,073
- MLN: 3,231
- MSV: 3,052
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{mduma2024updating,
title={Updating “machine learning imagery dataset for maize crop: A case of Tanzania” with expanded data to cover the new farming season},
author={Mduma, Neema and Mayo, Flavia},
journal={Data in Brief},
volume={54},
pages={110359},
year={2024},
publisher={Elsevier}
}
```
Mduma, Neema; Mayo, Flavia (2023), “Maize Imagery Dataset - Tanzania”, Mendeley Data, V1, doi: 10.17632/fkw49mz3xs.1 |