Datasets:
File size: 1,488 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': early_leaf_spot
'1': healthy leaf
'2': late leaf spot
'3': nutrition deficiency
'4': rust
splits:
- name: train
num_bytes: 801090792
num_examples: 3058
download_size: 809834020
dataset_size: 801090792
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
---
# Groundnut Leaf Disease Classification 2
A dataset for disease classification of groundnut leaves. The dataset contains 3,058 images across 5 classes: early_leaf_spot, healthy leaf, late leaf spot, nutrition deficiency, rust.
Images per class:
- early_leaf_spot: 885
- healthy leaf: 929
- late leaf spot: 689
- nutrition deficiency: 329
- rust: 226
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{aishwarya2023dataset,
title={Dataset of groundnut plant leaf images for classification and detection},
author={Aishwarya, MP and Reddy, A Padmanabha},
journal={Data in Brief},
volume={48},
pages={109185},
year={2023},
publisher={Elsevier}
}
```
Manvikar, Aishwarya; Reddy, Padmanabha (2023), “Dataset of groundnut plant leaf images for classification and detection”, Mendeley Data, V3, doi: 10.17632/22p2vcbxfk.3 |