| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': grade-1 |
| '1': grade-2 |
| '2': grade-3 |
| - name: quality |
| dtype: |
| class_label: |
| names: |
| '0': quality-1 |
| '1': quality-2 |
| '2': quality-3 |
| '3': quality-4 |
| splits: |
| - name: train |
| num_bytes: 129205249 |
| num_examples: 1080 |
| download_size: 127371587 |
| dataset_size: 129205249 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: cc0-1.0 |
| task_categories: |
| - image-classification |
| size_categories: |
| - 1K<n<10K |
| --- |
| # Pomegranate Quality Classification |
|
|
| A dataset for classification of Pomegranate quality. The dataset contains 1,080 images across 3 classes: G1_Q1, G2_Q1, G3_Q1. |
| Images per class: |
| - G1_Q1: 360 |
| - G2_Q1: 360 |
| - G3_Q1: 360 |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{kumar2021image, |
| title={Image dataset of pomegranate fruits (Punica granatum) for various machine vision applications}, |
| author={Kumar, Arun and Rajpurohit, Vijay S and Gaikwad, Nilesh N}, |
| journal={data in Brief}, |
| volume={37}, |
| pages={107249}, |
| year={2021}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Dr. Vijay S Rajpurohit, and Kshitijarun Y Bidari. (2020). Pomegranate Fruit Dataset [Dataset]. Kaggle. https://doi.org/10.34740/KAGGLE/DS/551234 |
|
|
| *This dataset was reformatted from its original format to match HuggingFace standards.* |
