| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': Major Defect |
| '1': Minor Defect |
| '2': No Defect |
| splits: |
| - name: train |
| num_bytes: 741149609 |
| num_examples: 982 |
| download_size: 741179545 |
| dataset_size: 741149609 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: cc-by-4.0 |
| task_categories: |
| - image-classification |
| size_categories: |
| - n<1K |
| --- |
| # Pomegranate Thermal Defect Classification |
|
|
| A dataset for classification of Pomegranate defects using thermal imagery. The dataset contains 982 images across 3 classes: Major Defect, Minor Defect, No Defect. |
| Images per class: |
| - Major Defect: 303 |
| - Minor Defect: 340 |
| - No Defect: 339 |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{gaikwad2025dataset, |
| title={Dataset creation of thermal images of pomegranate for internal defect detection}, |
| author={Gaikwad, Ashvini and Deshpande, Manoj and Bhole, Varsha}, |
| journal={Data in brief}, |
| volume={60}, |
| pages={111538}, |
| year={2025}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| gaikwad, ashvini (2024), “Pomegranate Thermal Images”, Mendeley Data, V1, doi: 10.17632/djcgvgtcfm.1 |
|
|
| *This dataset was reformatted from its original format to match HuggingFace standards.* |
