| --- |
| configs: |
| - config_name: default |
| default: true |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': bruised |
| '1': cracked |
| '2': rotten |
| '3': spotted |
| '4': unaffected |
| '5': unripe |
| license: cc-by-4.0 |
| task_categories: |
| - image-classification |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # African Plum Grading Classification |
|
|
| A dataset for grade classification of plums. The dataset contains 4,507 images across 6 classes: bruised, cracked, rotten, spotted, unaffected, unripe. |
| Images per class: |
| - bruised: 319 |
| - cracked: 162 |
| - rotten: 720 |
| - spotted: 759 |
| - unaffected: 1,721 |
| - unripe: 826 |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{fadja2025dataset, |
| title={A dataset of annotated African plum images from Cameroon for AI-based quality assessment}, |
| author={Fadja, Arnaud Nguembang and Tagni, Armel Gabin Fameni and Che, Sain Rigobert and Atemkeng, Marcellin}, |
| journal={Data in Brief}, |
| volume={59}, |
| pages={111351}, |
| year={2025}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Arnaud Nguembang Fadja, and Armel Gabin Fameni Tagni. (2024). African Plums Dataset [Dataset]. Kaggle. https://doi.org/10.34740/KAGGLE/DSV/9694239 |
