| --- |
| 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 |
