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---
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Aegle marmelos
          '1': Black plum
          '2': Custard Apple
          '3': Guava
          '4': Jackfruit
          '5': Lotkon
          '6': Lychee
          '7': Mango
          '8': Plum
          '9': Star Fruit
  splits:
  - name: train
    num_bytes: 13373984193
    num_examples: 3173
  download_size: 10452397888
  dataset_size: 13373984193
---

# Fruit Leaf Variety Classification

A dataset for variety classification of fruit leaves. The dataset contains 3,173 images across 10 classes: Aegle marmelos, Black plum, Custard Apple, Guava, Jackfruit, Lotkon, Lychee, Mango, Plum, Star Fruit.  
Images per class:
- Aegle marmelos: 336
- Black plum: 304
- Custard Apple: 304
- Guava: 325
- Jackfruit: 311
- Lotkon: 306
- Lychee: 312
- Mango: 330
- Plum: 302
- Star Fruit: 343

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

## Citation

```bibtex
@article{abedin2025comprehensive,
  title={Comprehensive data of 10 fruit leaf classes captured for agricultural AI applications},
  author={Abedin, Minhajul and Islam, Sujon and Sultana, Naznin},
  journal={Data in Brief},
  pages={111879},
  year={2025},
  publisher={Elsevier}
}
```

Abedin, Minhajul ; Islam, Md. Sujon ; Sultana, Dr. Naznin  (2025), “Multi-Class Fruit Leaf Classification Dataset (10 Classes)”, Mendeley Data, V2, doi: 10.17632/4gxzx6h7gv.2