Datasets:
File size: 1,539 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Bacterial leaf Blight
'1': Dry_leaf
'2': Healthy
'3': Root_images
'4': Septoria_Brown_Spot
'5': Vein Necrosis
splits:
- name: train
num_bytes: 2839590431
num_examples: 1176
download_size: 2848562521
dataset_size: 2839590431
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
---
# Soybean Leaf Disease Classification
A dataset for disease classification of soybean leaves. The dataset contains 1,176 images across 6 classes: Bacterial leaf Blight, Dry_leaf, Healthy, Root_images, Septoria_Brown_Spot, Vein Necrosis.
Images per class:
- Bacterial leaf Blight: 226
- Dry_leaf: 230
- Healthy: 288
- Root_images: 10
- Septoria_Brown_Spot: 284
- Vein Necrosis: 138
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{kotwal2024india,
title={An India soyabean dataset for identification and classification of diseases using computer-vision algorithms},
author={Kotwal, Jameer and Kashyap, Ramgopal and Pathan, Mohd Shafi},
journal={Data in Brief},
volume={53},
pages={110216},
year={2024}
}
```
Kotwal, Jameer ; kashyap, Ramgopal (2023), “ An India soyabean leaf dataset”, Mendeley Data, V1, doi: 10.17632/bshkvgbzpt.1 |