---
configs:
- config_name: default
  default: true
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Abutilon Indicum
          '1': Aloe barbadensis miller
          '2': Calotropis gigantea
          '3': Canna indica
          '4': Cissus quadrangularis
          '5': Curcuma longa
          '6': Eclipta prostrate
          '7': Eichhornia Crassipes
          '8': Hibiscus Rosasinensis
          '9': Ixora coccinea
          '10': Justica adhatoda
          '11': Murraya koenigii
          '12': Ocimum tenuiflorum
          '13': Ouretlanata
          '14': Phyllanthus amarus
          '15': Ricinus communis
          '16': Senna Atriculata
          '17': Sesbania grandiflora
          '18': Trifolium Repens
          '19': Ziziphus mauritiana
license: cc-by-nc-3.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
---

# SIMPDV1 Plant Classification

A dataset for classification of medicinal plants in South India. The dataset contains 2,513 images across 20 classes: Abutilon Indicum, Aloe barbadensis miller, Calotropis gigantea, Canna indica, Cissus quadrangularis, Curcuma longa, Eclipta prostrate, Eichhornia Crassipes, Hibiscus Rosasinensis, Ixora coccinea, Justica adhatoda, Murraya koenigii, Ocimum tenuiflorum, Ouretlanata, Phyllanthus amarus, Ricinus communis, Senna Atriculata, Sesbania grandiflora, Trifolium Repens, Ziziphus mauritiana.  
Images per class:
- Abutilon Indicum: 165
- Aloe barbadensis miller: 145
- Calotropis gigantea: 106
- Canna indica: 149
- Cissus quadrangularis: 134
- Curcuma longa: 110
- Eclipta prostrate: 208
- Eichhornia Crassipes: 202
- Hibiscus Rosasinensis: 113
- Ixora coccinea: 114
- Justica adhatoda: 100
- Murraya koenigii: 118
- Ocimum tenuiflorum: 102
- Ouretlanata: 119
- Phyllanthus amarus: 111
- Ricinus communis: 109
- Senna Atriculata: 125
- Sesbania grandiflora: 91
- Trifolium Repens: 100
- Ziziphus mauritiana: 92

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

## Citation

```bibtex
@article{arunachalam2025medicinal,
  title={Medicinal plants of South India: A comprehensive dataset for species identification},
  author={Arunachalam, Muthukumar and Gopu, T and Uma, K and Nathan, Sabari},
  journal={Data in Brief},
  volume={61},
  pages={111660},
  year={2025},
  publisher={Elsevier}
}```

T, gopu; k, uma (2025), “SIMPD V1: South Indian Medicinal Plants dataset (Version 1)”, Mendeley Data, V2, doi: 10.17632/9d89vjcghv.2