| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': Aloevera |
| '1': Amla |
| '2': Amruthaballi |
| '3': Arali |
| '4': Astma_weed |
| '5': Badipala |
| '6': Balloon_Vine |
| '7': Bamboo |
| '8': Beans |
| '9': Betel |
| '10': Bhrami |
| '11': Bringaraja |
| '12': Caricature |
| '13': Castor |
| '14': Catharanthus |
| '15': Chakte |
| '16': Chilly |
| '17': Citron lime (herelikai) |
| '18': Coffee |
| '19': Common rue(naagdalli) |
| '20': Coriender |
| '21': Curry |
| '22': Doddpathre |
| '23': Drumstick |
| '24': Ekka |
| '25': Eucalyptus |
| '26': Ganigale |
| '27': Ganike |
| '28': Gasagase |
| '29': Ginger |
| '30': Globe Amarnath |
| '31': Guava |
| '32': Henna |
| '33': Hibiscus |
| '34': Honge |
| '35': Insulin |
| '36': Jackfruit |
| '37': Jasmine |
| '38': Kambajala |
| '39': Kasambruga |
| '40': Kohlrabi |
| '41': Lantana |
| '42': Lemon |
| '43': Lemongrass |
| '44': Malabar_Nut |
| '45': Malabar_Spinach |
| '46': Mango |
| '47': Marigold |
| '48': Mint |
| '49': Neem |
| '50': Nelavembu |
| '51': Nerale |
| '52': Nooni |
| '53': Onion |
| '54': Padri |
| '55': Palak(Spinach) |
| '56': Papaya |
| '57': Parijatha |
| '58': Pea |
| '59': Pepper |
| '60': Pomoegranate |
| '61': Pumpkin |
| '62': Raddish |
| '63': Rose |
| '64': Sampige |
| '65': Sapota |
| '66': Seethaashoka |
| '67': Seethapala |
| '68': Spinach1 |
| '69': Tamarind |
| '70': Taro |
| '71': Tecoma |
| '72': Thumbe |
| '73': Tomato |
| '74': Tulsi |
| '75': Turmeric |
| '76': ashoka |
| '77': camphor |
| '78': kamakasturi |
| '79': kepala |
| splits: |
| - name: train |
| num_bytes: 9989663974 |
| num_examples: 6900 |
| download_size: 9484082641 |
| dataset_size: 9989663974 |
| 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 |
| --- |
| |
| # 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 |
|
|
| ```bibtex |
| @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 |
