Datasets:

Project-AgML
/

plant_leaf_disease_classification

dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': Anthracnose
            '1': Anthracnose lesions
            '2': Black Rot
            '3': Downey mildew
            '4': Downy mildew
            '5': Eggplant Cercopora leaf spot
            '6': Eggplant begomovirus
            '7': Eggplant fresh leaf
            '8': Eggplant verticillium wilt
            '9': Fresh leaf
            '10': Fusarium wilt
            '11': Mosaic virus
            '12': Tomato Bacterial spot
            '13': Tomato Fresh leaf
            '14': Tomato leaf curl virus
            '15': Tomato spotted wilt
    - name: plant_type
      dtype:
        class_label:
          names:
            '0': Bitter Gourd
            '1': Bottle gourd
            '2': Cauliflower
            '3': Cucumber
            '4': Eggplant
            '5': Tomato
  splits:
    - name: train
      num_bytes: 812512223
      num_examples: 12786
  download_size: 958168710
  dataset_size: 812512223
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - image-classification
size_categories:
  - 10K<n<100K

Plant Leaf Disease Classification

A dataset for disease classification of leaves from Bitter Gourd, Bottle Gourd, Tomato, Eggplant, Cauliflower, and Cucumber. The dataset contains 12,786 images across 16 classes:
Images per class:

Anthracnose: 601
Anthracnose lesions: 535
Black Rot: 560
Downey mildew: 1,254
Downy mildew: 1,076
Eggplant Cercopora leaf spot: 723
Eggplant begomovirus: 720
Eggplant fresh leaf: 771
Eggplant verticillium wilt: 730
Fresh leaf: 2,122
Fusarium wilt: 502
Mosaic virus: 600
Tomato Bacterial spot: 589
Tomato Fresh leaf: 594
Tomato leaf curl virus: 755
Tomato spotted wilt: 654

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

Citation

@article{hasan2024comprehensive,
  title={Comprehensive smart smartphone image dataset for plant leaf disease detection and freshness assessment from Bangladesh vegetable fields},
  author={Hasan, Mahamudul and Gani, Raiyan and Rashid, Mohammad Rifat Ahmmad and Tarin, Taslima Khan and Kamara, Raka and Mou, Mahbuba Yasmin and Rabbi, Sheikh Fajlay},
  journal={Data in Brief},
  volume={56},
  pages={110775},
  year={2024},
  publisher={Elsevier}
}

Rashid, Mohammad Rifat Ahmmad; Tarin, Taslima Khan ; Kamara, Raka ; Mou, Mahbuba Yasmin ; Rabbi, Sheikh Fajlay ; Hasan, Mahamudul (2024), “Plant Leaf Freshness and Disease Detection Dataset From Bangladesh”, Mendeley Data, V3, doi: 10.17632/n67gctmjyj.3