Datasets:
| configs: | |
| - config_name: raw | |
| default: true | |
| license: cc-by-4.0 | |
| task_categories: | |
| - image-classification | |
| size_categories: | |
| - 1K<n<10K | |
| dataset_info: | |
| config_name: raw | |
| features: | |
| - name: image | |
| dtype: image | |
| - name: label | |
| dtype: | |
| class_label: | |
| names: | |
| '0': Colletotrichum spp | |
| '1': Ectomyelois ceratoniae | |
| '2': Healthy | |
| '3': Sunburn | |
| splits: | |
| - name: train | |
| num_bytes: 751472790 | |
| num_examples: 2178 | |
| download_size: 778518065 | |
| dataset_size: 751472790 | |
| # Pomegranate Disease Classification | |
| A dataset for disease classification of pomegranate. | |
| The dataset contains 2,178 images. | |
| Images per class: | |
| - Colletotrichum spp: 571 | |
| - Ectomyelois ceratoniae: 555 | |
| - Healthy: 661 | |
| - Sunburn: 391 | |
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. | |
| ## Citation | |
| ```bibtex | |
| @article{mohammed2025pomegranate, | |
| title={Pomegranate disease detection and classification dataset for deep learning applications: A case study from Halabja city}, | |
| author={Mohammed, Bashdar Abdalrahman and Abdalla, Peshraw Ahmed and Aziz, Sirwan M and Hassan, Hiwa Omer}, | |
| journal={Data in Brief}, | |
| pages={112298}, | |
| year={2025}, | |
| publisher={Elsevier} | |
| } | |
| ``` | |
| Mohammed, B. A., Abdalla, P. A., & Hassan, H. O. (2025). Halabja Pomegranate Fruit Disease Image Dataset. Zenodo. https://doi.org/10.5281/zenodo.15856012 |