---
configs:
- config_name: default
  default: true
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Black Scorch
          '1': Fusarium Wilt
          '2': Healthy sample
          '3': Leaf Spots
          '4': Magnesium Deficiency
          '5': Manganese Deficiency
          '6': Parlatoria Blanchardi
          '7': Potassium Deficiency
          '8': Rachis Blight
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
---

# Date Palm Leaf Disease Classification

A dataset for image classification of Date Palm Leaf Disease Classification.  The dataset contains 3,089 images across 9 classes: Black Scorch, Fusarium Wilt, Healthy sample, Leaf Spots, Magnesium Deficiency, Manganese Deficiency, Parlatoria Blanchardi, Potassium Deficiency, Rachis Blight.
Images per class:
- Black Scorch: 106
- Fusarium Wilt: 210
- Healthy sample: 389
- Leaf Spots: 69
- Magnesium Deficiency: 566
- Manganese Deficiency: 415
- Parlatoria Blanchardi: 101
- Potassium Deficiency: 831
- Rachis Blight: 402

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

## Citation

```bibtex
@article{namoun2024dataset,
  title={Dataset of infected date palm leaves for palm tree disease detection and classification},
  author={Namoun, Abdallah and Alkhodre, Ahmad B and Abi Sen, Adnan Ahmad and Alsaawy, Yazed and Almoamari, Hani},
  journal={Data in brief},
  volume={57},
  pages={110933},
  year={2024},
  publisher={Elsevier}
}
```

Namoun, Abdallah; Alkhodre, Ahmad B.; Abi Sen, Adnan Ahmad ; Alsaawy, Yazed; Almoamari, Hani (2024), “Diseases of date palm leaves dataset”, Mendeley Data, V2, doi: 10.17632/g684ghfxvg.2