Project-AgML/BDMediLeaves_variety_classification

BDMediLeaves Variety Classification

A dataset for variety classification of common medicinal plants. The dataset contains raw and augmented versions.
The raw dataset contains 2,048 images.
Images per class:

• azadirachta-indica: 205
• calotropis-gigantea: 233
• centella-asiatica: 201
• hibiscus-rosa-sinensis: 214
• justicia-adhatoda: 200
• kalanchoe-pinnata: 229
• mikania-micrantha: 201
• ocimum-tenuiflorum: 151
• phyllanthus-emblica: 200
• terminalia-arjuna: 214

The augmented dataset contains 38,606 images.
Images per class:

• azadirachta-indica: 3,957
• calotropis-gigantea: 3,795
• centella-asiatica: 3,881
• hibiscus-rosa-sinensis: 3,861
• justicia-adhatoda: 3,863
• kalanchoe-pinnata: 3,837
• mikania-micrantha: 3,919
• ocimum-tenuiflorum: 3,789
• phyllanthus-emblica: 3,863
• terminalia-arjuna: 3,841

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

Citation

@article{islam2023bdmedileaves,
  title={BDMediLeaves: a leaf images dataset for Bangladeshi medicinal plants identification},
  author={Islam, Saiful and Ahmed, Md Rayhan and Islam, Siful and Rishad, Md Mahfuzul Alam and Ahmed, Sayem and Utshow, Toyabur Rahman and Siam, Minhajul Islam},
  journal={Data in Brief},
  volume={50},
  pages={109488},
  year={2023},
  publisher={Elsevier}
}

Islam, Saiful ; Ahmed, Rayhan; siful islam, siful islam; Rishad, Md Mahfuzul Alam; Ahmed, Sayem; Utshow, Toyabur Rahman; Siam, Minhajul Islam (2023), “BDMediLeaves: A leaf images dataset for Bangladeshi medicinal plants identification”, Mendeley Data, V1, doi: 10.17632/gk5x6k8xr5.1

This dataset was reformatted from its original format to match HuggingFace standards.