Datasets:
| dataset_info: | |
| features: | |
| - name: image | |
| dtype: image | |
| - name: label | |
| dtype: | |
| class_label: | |
| names: | |
| '0': diseased | |
| '1': healthy | |
| - name: species | |
| dtype: string | |
| - name: cultivar | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 7312118052 | |
| num_examples: 4502 | |
| download_size: 7312376792 | |
| dataset_size: 7312118052 | |
| 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 | |
| # Leafnet Plant Disease Classification | |
| This dataset comprises real-world RGB images of plant leaves, capturing both diseased and healthy specimens for disease detection tasks. Collected under typical agricultural imaging conditions, it provides a practical resource for developing computer vision models in plant pathology applications. The dataset contains 4,502 images across 2 classes: diseased, healthy. | |
| Images per class: | |
| - diseased: 2,225 | |
| - healthy: 2,277 | |
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. | |
| ## Citation | |
| ```bibtex | |
| <!-- TODO: add BibTeX citation --> | |
| ``` | |
| <!-- TODO: add plain text citation --> | |
| The dataset itself can be cited as: | |
| Siddharth Singh Chouhan. (2022). *A Database of Leaf Images: Practice towards Plant Conservation with Plant Pathology* [Dataset]. Mendeley. https://doi.org/10.17632/HB74YNKJCN.5 | |
| *This dataset was reformatted from its original format to match HuggingFace standards.* | |