Datasets:
File size: 1,563 Bytes
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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 |