---
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

```bibtex
@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