Datasets:

Project-AgML
/

BPLD_leaf_disease_classification

dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': Anthracnose
            '1': Healthy
            '2': Leaf Crinckle
            '3': Powdery Mildew
            '4': Yellow Mosaic
  splits:
    - name: train
      num_bytes: 121482774
      num_examples: 1007
  download_size: 121530406
  dataset_size: 121482774
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

BPLD Leaf Disease Classification

A dataset for disease classification of Blackgram leaves. The dataset contains 1,007 images across 5 classes: Anthracnose, Healthy, Leaf Crinckle, Powdery Mildew, Yellow Mosaic.
Images per class:

Anthracnose: 230
Healthy: 221
Leaf Crinckle: 152
Powdery Mildew: 180
Yellow Mosaic: 224

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

Citation

@article{talasila2022black,
  title={Black gram Plant Leaf Disease (BPLD) dataset for recognition and classification of diseases using computer-vision algorithms},
  author={Talasila, Srinivas and Rawal, Kirti and Sethi, Gaurav and Mss, Sanjay and others},
  journal={Data in Brief},
  volume={45},
  pages={108725},
  year={2022},
  publisher={Elsevier}
}

Talasila, Srinivas; Rawal, Kirti; Sethi, Gaurav; MSS, Sanjay; M, Surya Prakash Reddy (2022), “Blackgram Plant Leaf Disease Dataset”, Mendeley Data, V3, doi: 10.17632/zfcv9fmrgv.3