| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': Bad |
| '1': Good |
| '2': Mixed |
| - name: crop |
| dtype: |
| class_label: |
| names: |
| '0': Apple |
| '1': Banana |
| '2': Guava |
| '3': Lemon |
| '4': Lime |
| '5': Orange |
| '6': Pomegranate |
| splits: |
| - name: train |
| num_bytes: 4009003647 |
| num_examples: 19526 |
| download_size: 3291544075 |
| dataset_size: 4009003647 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: cc-by-4.0 |
| task_categories: |
| - image-classification |
| size_categories: |
| - 10K<n<100K |
| --- |
| # Fruitnet Quality Classification |
|
|
| A dataset for image classification of Fruitnet Quality Classification. The dataset contains 19,526 images across 3 classes: Bad, Good, Mixed. |
| Images per class: |
| - Bad: 6,788 |
| - Good: 11,664 |
| - Mixed: 1,074 |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{meshram2022fruitnet, |
| title={FruitNet: Indian fruits image dataset with quality for machine learning applications}, |
| author={Meshram, Vishal and Patil, Kailas}, |
| journal={Data in Brief}, |
| volume={40}, |
| pages={107686}, |
| year={2022}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| PATIL, Kailas; MESHRAM, Vishal (2022), “FruitNet: Indian Fruits Dataset with quality (Good, Bad & Mixed quality)”, Mendeley Data, V3, doi: 10.17632/b6fftwbr2v.3 |
|
|
| *This dataset was reformatted from its original format to match HuggingFace standards.* |
