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---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Bacterial_Leaf_Disease
          '1': Dried_Leaf
          '2': Fungal_Brown_Spot_Disease
          '3': Healthy_Leaf
  splits:
  - name: train
    num_bytes: 6476375318
    num_examples: 3589
  download_size: 6067102967
  dataset_size: 6476375318
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
---
# Betel Leaf Disease Classification

A dataset for image classification of Betel Leaf Disease Classification. The dataset contains 3,589 images across 4 classes: Bacterial_Leaf_Disease, Dried_Leaf, Fungal_Brown_Spot_Disease, Healthy_Leaf.  
Images per class:
- Bacterial_Leaf_Disease: 906
- Dried_Leaf: 898
- Fungal_Brown_Spot_Disease: 892
- Healthy_Leaf: 893

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

## Citation  
Rashid, Mohammad Rifat Ahmmad; Hossain, Md. Miskat ; Biswas,  Joy ; Majumder, Hredoy  (2024), “Betel Leaf Image Dataset from Bangladesh”, Mendeley Data, V2, doi: 10.17632/g7fpgj57wc.2