Project-AgML/DIMPSAR_medicinal_leaf_classification

DIMPSAR Medicinal Leaf Classification

A dataset for variety classification of medicinal plant leaves. The dataset contains 6,900 images across 80 classes: Images per class:

• Aloevera: 118
• Amla: 67
• Amruthaballi: 91
• Arali: 89
• Astma_weed: 82
• Badipala: 76
• Balloon_Vine: 61
• Bamboo: 118
• Beans: 97
• Betel: 114
• Bhrami: 104
• Bringaraja: 73
• Caricature: 76
• Castor: 129
• Catharanthus: 134
• Chakte: 68
• Chilly: 69
• Citron lime (herelikai): 99
• Coffee: 83
• Common rue(naagdalli): 67
• Coriender: 115
• Curry: 168
• Doddpathre: 142
• Drumstick: 56
• Ekka: 81
• Eucalyptus: 80
• Ganigale: 75
• Ganike: 63
• Gasagase: 79
• Ginger: 82
• Globe Amarnath: 81
• Guava: 128
• Henna: 80
• Hibiscus: 118
• Honge: 113
• Insulin: 89
• Jackfruit: 110
• Jasmine: 49
• Kambajala: 59
• Kasambruga: 48
• Kohlrabi: 73
• Lantana: 76
• Lemon: 123
• Lemongrass: 8
• Malabar_Nut: 51
• Malabar_Spinach: 79
• Mango: 103
• Marigold: 93
• Mint: 135
• Neem: 132
• Nelavembu: 90
• Nerale: 62
• Nooni: 72
• Onion: 92
• Padri: 73
• Palak(Spinach): 149
• Papaya: 135
• Parijatha: 66
• Pea: 47
• Pepper: 8
• Pomoegranate: 75
• Pumpkin: 92
• Raddish: 40
• Rose: 106
• Sampige: 61
• Sapota: 44
• Seethaashoka: 47
• Seethapala: 114
• Spinach1: 67
• Tamarind: 176
• Taro: 69
• Tecoma: 69
• Thumbe: 74
• Tomato: 62
• Tulsi: 177
• Turmeric: 39
• ashoka: 81
• camphor: 66
• kamakasturi: 67
• kepala: 76

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

Citation

@article{pushpa2023dimpsar,
  title={DIMPSAR: Dataset for Indian medicinal plant species analysis and recognition},
  author={Pushpa, BR and Rani, N Shobha},
  journal={Data in Brief},
  volume={49},
  pages={109388},
  year={2023},
  publisher={Elsevier}
}

B R, Pushpa; Rani, Shobha (2023), “Indian Medicinal Leaves Image Datasets”, Mendeley Data, V3, doi: 10.17632/748f8jkphb.3