metadata
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': bacterial_leaf_blight
'1': bacterial_leaf_streak
'2': bacterial_panicle_blight
'3': blast
'4': brown_spot
'5': dead_heart
'6': downy_mildew
'7': hispa
'8': normal
'9': tungro
splits:
- name: train
num_bytes: 807799888
num_examples: 10407
download_size: 819745776
dataset_size: 807799888
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
Paddy Disease Classification
A dataset for disease classification of rice paddies. The dataset contains 10,407 images across 10 classes: bacterial_leaf_blight, bacterial_leaf_streak, bacterial_panicle_blight, blast, brown_spot, dead_heart, downy_mildew, hispa, normal, tungro.
Images per class:
- bacterial_leaf_blight: 479
- bacterial_leaf_streak: 380
- bacterial_panicle_blight: 337
- blast: 1,738
- brown_spot: 965
- dead_heart: 1,442
- downy_mildew: 620
- hispa: 1,594
- normal: 1,764
- tungro: 1,088
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
Petchiammal A, Briskline Kiruba S, Murugan D, Pandarasamy Arjunan. (2022). Paddy Doctor: A Visual Image Dataset for Automated Paddy Disease Classification and Benchmarking. IEEE Dataport. https://dx.doi.org/10.21227/hz4v-af08