Datasets:
| configs: | |
| - config_name: raw | |
| default: true | |
| license: cc-by-4.0 | |
| task_categories: | |
| - image-classification | |
| size_categories: | |
| - n<1K | |
| dataset_info: | |
| config_name: raw | |
| features: | |
| - name: image | |
| dtype: image | |
| - name: label | |
| dtype: | |
| class_label: | |
| names: | |
| '0': Mature | |
| '1': Over-mature | |
| '2': Under-mature | |
| splits: | |
| - name: train | |
| num_bytes: 62584172 | |
| num_examples: 364 | |
| download_size: 62604394 | |
| dataset_size: 62584172 | |
| # Okra Maturity Classification | |
| A dataset for maturity classification of okra. | |
| The dataset contains 364 images. | |
| Images per class: | |
| - Mature: 132 | |
| - Over-mature: 100 | |
| - Under-mature: 132 | |
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. | |
| ## Citation | |
| ```bibtex | |
| @article{bharathi2025rgb, | |
| title={RGB image dataset for okra maturity classification to enhance agricultural quality and market readiness}, | |
| author={Bharathi, Nikhilesh Kumar and Fj, Ferbin and others}, | |
| journal={Data in Brief}, | |
| pages={111982}, | |
| year={2025}, | |
| publisher={Elsevier} | |
| } | |
| ``` | |
| Bharathi, Nikhilesh Kumar; FJ, Ferbin ; Sivapatham, Shoba (2025), “Okra Image Dataset”, Mendeley Data, V1, doi: 10.17632/jmhz4826f2.1 |