| --- |
| dataset_info: |
| - config_name: augmented |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': Black Spot |
| '1': Downy mildew |
| '2': Fresh Leaf |
| splits: |
| - name: train |
| num_bytes: 1988446946 |
| num_examples: 4342 |
| download_size: 1884098252 |
| dataset_size: 1988446946 |
| - config_name: raw |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': Black Spot |
| '1': Downy Mildew |
| '2': Fresh Leaf |
| splits: |
| - name: train |
| num_bytes: 530370256 |
| num_examples: 917 |
| download_size: 530409292 |
| dataset_size: 530370256 |
| configs: |
| - config_name: augmented |
| data_files: |
| - split: train |
| path: augmented/train-* |
| - config_name: raw |
| default: true |
| data_files: |
| - split: train |
| path: raw/train-* |
| license: cc-by-4.0 |
| task_categories: |
| - image-classification |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # RoseNet Leaf Disease Classification |
|
|
| A dataset for disease classification of rose leaves. The dataset contains raw and augmented versions. |
| The raw dataset contains 917 images. |
| Images per class: |
| - Black Spot: 313 |
| - Downy Mildew: 200 |
| - Fresh Leaf: 404 |
|
|
| The augmented dataset contains 4,342 images. |
| Images per class: |
| - Black Spot: 1,434 |
| - Downy mildew: 1,478 |
| - Fresh Leaf: 1,430 |
|
|
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{sazzad2022rosenet, |
| title={RoseNet: Rose leave dataset for the development of an automation system to recognize the diseases of rose}, |
| author={Sazzad, Sadia and Rajbongshi, Aditya and Shakil, Rashiduzzaman and Akter, Bonna and Kaiser, M Shamim}, |
| journal={Data in Brief}, |
| volume={44}, |
| pages={108497}, |
| year={2022}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Rajbongshi, Aditya; Sazzad, Sadia ; Shakil, Rashiduzzaman ; Akter, Bonna ; Kaiser, M Shamim (2022), “FlowerNet: An extensive rose leaves dataset for disease recognition applying machine learning and deep learning models”, Mendeley Data, V2, doi: 10.17632/7z67nyc57w.2 |
