Datasets:
File size: 2,993 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Apple Scab Leaf
'1': Apple leaf
'2': Apple rust leaf
'3': Bell_pepper leaf
'4': Bell_pepper leaf spot
'5': Blueberry leaf
'6': Cherry leaf
'7': Corn Gray leaf spot
'8': Corn leaf blight
'9': Corn rust leaf
'10': Peach leaf
'11': Potato leaf early blight
'12': Potato leaf late blight
'13': Raspberry leaf
'14': Soyabean leaf
'15': Squash Powdery mildew leaf
'16': Strawberry leaf
'17': Tomato Early blight leaf
'18': Tomato Septoria leaf spot
'19': Tomato leaf
'20': Tomato leaf bacterial spot
'21': Tomato leaf late blight
'22': Tomato leaf mosaic virus
'23': Tomato leaf yellow virus
'24': Tomato mold leaf
'25': Tomato two spotted spider mites leaf
'26': grape leaf
'27': grape leaf black rot
splits:
- name: train
num_bytes: 870747799
num_examples: 2569
download_size: 993536349
dataset_size: 870747799
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-sa-4.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
---
# Plant Doc Classification
A dataset for disease classification of various plants. The dataset contains 2,569 images across 28 classes:
Images per class:
- Apple Scab Leaf: 93
- Apple leaf: 91
- Apple rust leaf: 88
- Bell_pepper leaf: 61
- Bell_pepper leaf spot: 71
- Blueberry leaf: 114
- Cherry leaf: 57
- Corn Gray leaf spot: 68
- Corn leaf blight: 191
- Corn rust leaf: 116
- Peach leaf: 111
- Potato leaf early blight: 116
- Potato leaf late blight: 105
- Raspberry leaf: 119
- Soyabean leaf: 65
- Squash Powdery mildew leaf: 130
- Strawberry leaf: 96
- Tomato Early blight leaf: 88
- Tomato Septoria leaf spot: 150
- Tomato leaf: 63
- Tomato leaf bacterial spot: 110
- Tomato leaf late blight: 111
- Tomato leaf mosaic virus: 54
- Tomato leaf yellow virus: 75
- Tomato mold leaf: 91
- Tomato two spotted spider mites leaf: 2
- grape leaf: 69
- grape leaf black rot: 64
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@inproceedings{10.1145/3371158.3371196,
author = {Singh, Davinder and Jain, Naman and Jain, Pranjali and Kayal, Pratik and Kumawat, Sudhakar and Batra, Nipun},
title = {PlantDoc: A Dataset for Visual Plant Disease Detection},
year = {2020},
isbn = {9781450377386},
publisher = {Association for Computing Machinery},
url = {https://doi.org/10.1145/3371158.3371196},
doi = {10.1145/3371158.3371196},
booktitle = {Proceedings of the 7th ACM IKDD CoDS and 25th COMAD},
pages = {249–253},
numpages = {5},
series = {CoDS COMAD 2020}
}
```
https://github.com/pratikkayal/PlantDoc-Dataset |