Datasets:
File size: 1,690 Bytes
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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 |