README.md

---
configs:
- config_name: augmented
  data_files:
  - split: train
    path: augmented/train-*
- config_name: raw
  data_dir: raw
  default: true
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
dataset_info:
- config_name: augmented
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': anthracnose_leaf_spot
          '1': healthy
          '2': straw_mite
  splits:
  - name: train
    num_bytes: 7866314601
    num_examples: 5868
  download_size: 7868310409
  dataset_size: 7866314601
- config_name: raw
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': anthracnose_leaf_spot
          '1': healthy
          '2': straw_mite
  splits:
  - name: train
    num_bytes: 709284060
    num_examples: 603
  download_size: 709322795
  dataset_size: 709284060
---

# Malabar Spinach Disease Classification

A dataset for disease classification of Malabar Spinach leaves. The dataset contains raw and augmented versions.  
The raw dataset contains 603 images.  
Images per class:
- anthracnose_leaf_spot: 214
- healthy: 150
- straw_mite: 239

The augmented dataset contains 5,868 images.  
Images per class:
- anthracnose_leaf_spot: 2,140
- healthy: 1,500
- straw_mite: 2,228


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

## Citation

```bibtex
@article{rahman2025comprehensive,
  title={A comprehensive Malabar Spinach dataset for diseases classification},
  author={Rahman, Mushfiqur and Al Mamun, Md},
  journal={Data in Brief},
  volume={60},
  pages={111532},
  year={2025},
  publisher={Elsevier}
}
```

Rahman, Mushfiqur; Mukherjee, Anirban ; Shanto , Md Hasibul Hasan  (2023), “Malabar Spinach dataset for diseases classification using deep learning approach”, Mendeley Data, V2, doi: 10.17632/n56pn9fncw.2