Datasets:
File size: 1,441 Bytes
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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
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Black Rot
'1': Healthy
'2': Insect Hole
splits:
- name: train
num_bytes: 5068797196
num_examples: 2661
download_size: 5260015832
dataset_size: 5068797196
---
# Cauliflower Leaf Disease Classification
A dataset for disease classification of Cauliflower leaves. The dataset contains 2,661 images across 3 classes: Black Rot, Healthy, Insect Hole.
Images per class:
- Black Rot: 1,088
- Healthy: 934
- Insect Hole: 639
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{durjoy2025cauliflower,
title={Cauliflower leaf diseases: A computer vision dataset for smart agriculture},
author={Durjoy, Sabbir Hossain and Shikder, Md Emon and Shoib, Md Mehedi Hasan and Bijoy, Md Hasan Imam},
journal={Data in Brief},
volume={60},
pages={111594},
year={2025},
publisher={Elsevier}
}
```
Durjoy, Sabbir Hossain; Shikder, Md Emon; Shoib, Md Mehedi Hasan; Bijoy, Md Hasan Imam (2025), “Cauliflower Leaf Diseases: A Computer Vision Dataset for Smart Agriculture”, Mendeley Data, V1, doi: 10.17632/x995snz7p3.1 |