| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': Citrus_leafminer |
| '1': Fe |
| '2': Greasy_spot |
| '3': HLB |
| '4': Healthy |
| '5': Mg |
| '6': Mn |
| '7': 'N' |
| '8': Red_scale |
| '9': Red_scale_sequelae |
| '10': Texas_mite |
| '11': Zn |
| splits: |
| - name: train |
| num_bytes: 1884058990 |
| num_examples: 953 |
| download_size: 1884130526 |
| dataset_size: 1884058990 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| task_categories: |
| - image-classification |
| license: cc-by-4.0 |
| size_categories: |
| - n<1K |
| --- |
| |
| # CitrusUAT Disease Classification |
|
|
| A dataset for disease classification of orange leaves. The dataset contains 953 images across 12 classes: Citrus_leafminer, Fe, Greasy_spot, HLB, Healthy, Mg, Mn, N, Red_scale, Red_scale_sequelae, Texas_mite, Zn. |
| Images per class: |
| - Citrus_leafminer: 100 |
| - Fe: 100 |
| - Greasy_spot: 100 |
| - HLB: 43 |
| - Healthy: 100 |
| - Mg: 100 |
| - Mn: 30 |
| - N: 50 |
| - Red_scale: 30 |
| - Red_scale_sequelae: 100 |
| - Texas_mite: 100 |
| - Zn: 100 |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{gomez2024citrusuat, |
| title={CitrusUAT: A dataset of orange Citrus sinensis leaves for abnormality detection using image analysis techniques}, |
| author={G{\'o}mez-Flores, Wilfrido and Garza-Salda{\~n}a, Juan Jos{\'e} and Varela-Fuentes, S{\'o}stenes Edmundo}, |
| journal={Data in brief}, |
| volume={52}, |
| pages={109908}, |
| year={2024}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Wilfrido Gómez Flores. (2023). CitrusUAT: A Dataset of Orange Citrus sinensis Leaves for Abnormality Detection Using Image Analysis Techniques [Data set]. In CitrusUAT: A dataset of orange Citrus sinensis leaves for abnormality detection using image analysis techniques (1.0, Vol. 52, p. 109908). Zenodo. https://doi.org/10.5281/zenodo.8294078 |
