| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': Large |
| '1': Medium |
| '2': Small |
| '3': Spoiled |
| splits: |
| - name: train |
| num_bytes: 16876341 |
| num_examples: 6010 |
| download_size: 15845938 |
| dataset_size: 16876341 |
| 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 |
| --- |
| # Sapota Fruit Size Classification |
|
|
| A dataset for classification of Sapota Fruit Size. The dataset contains 6,010 images across 4 classes: Large, Medium, Small, Spoiled. |
| Images per class: |
| - Large: 1,451 |
| - Medium: 1,416 |
| - Small: 1,443 |
| - Spoiled: 1,700 |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{bhatt2025dedicated, |
| title={Dedicated dataset of Sapota (Manilkara zapota) fruit for machine vision applications}, |
| author={Bhatt, Anita and Joshi, Maulin}, |
| journal={Data in Brief}, |
| pages={111896}, |
| year={2025}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Bhatt, Anita; Joshi, Maulin (2025), “Sapota Fruit Datasets”, Mendeley Data, V2, doi: 10.17632/jgtb95x6kf.2 |
|
|
| *This dataset was reformatted from its original format to match HuggingFace standards.* |
